diff --git a/OpenCV/Form1.cs b/OpenCV/Form1.cs index 8de4261..d804f64 100644 --- a/OpenCV/Form1.cs +++ b/OpenCV/Form1.cs @@ -1,5 +1,6 @@ using System; using System.Windows.Forms; +using OpenCV.OpenCV; using OpenCvSharp; namespace OpenCV diff --git a/OpenCV/Forms/CVDialog.Designer.cs b/OpenCV/Forms/CVDialog.Designer.cs new file mode 100644 index 0000000..dbd9192 --- /dev/null +++ b/OpenCV/Forms/CVDialog.Designer.cs @@ -0,0 +1,95 @@ +namespace OpenCV.Forms +{ + partial class CVDialog + { + /// + /// Required designer variable. + /// + private System.ComponentModel.IContainer components = null; + + /// + /// Clean up any resources being used. + /// + /// true if managed resources should be disposed; otherwise, false. + protected override void Dispose(bool disposing) + { + if (disposing && (components != null)) + { + components.Dispose(); + } + base.Dispose(disposing); + } + + #region Windows Form Designer generated code + + /// + /// Required method for Designer support - do not modify + /// the contents of this method with the code editor. + /// + private void InitializeComponent() + { + this.picSource = new OpenCvSharp.UserInterface.PictureBoxIpl(); + this.tableLayoutPanel1 = new System.Windows.Forms.TableLayoutPanel(); + this.picConverted = new OpenCvSharp.UserInterface.PictureBoxIpl(); + ((System.ComponentModel.ISupportInitialize)(this.picSource)).BeginInit(); + this.tableLayoutPanel1.SuspendLayout(); + ((System.ComponentModel.ISupportInitialize)(this.picConverted)).BeginInit(); + this.SuspendLayout(); + // + // picSource + // + this.picSource.Dock = System.Windows.Forms.DockStyle.Fill; + this.picSource.Location = new System.Drawing.Point(3, 3); + this.picSource.Name = "picSource"; + this.picSource.Size = new System.Drawing.Size(381, 419); + this.picSource.SizeMode = System.Windows.Forms.PictureBoxSizeMode.Zoom; + this.picSource.TabIndex = 0; + this.picSource.TabStop = false; + // + // tableLayoutPanel1 + // + this.tableLayoutPanel1.ColumnCount = 2; + this.tableLayoutPanel1.ColumnStyles.Add(new System.Windows.Forms.ColumnStyle(System.Windows.Forms.SizeType.Percent, 50F)); + this.tableLayoutPanel1.ColumnStyles.Add(new System.Windows.Forms.ColumnStyle(System.Windows.Forms.SizeType.Percent, 50F)); + this.tableLayoutPanel1.Controls.Add(this.picSource, 0, 0); + this.tableLayoutPanel1.Controls.Add(this.picConverted, 1, 0); + this.tableLayoutPanel1.Dock = System.Windows.Forms.DockStyle.Fill; + this.tableLayoutPanel1.Location = new System.Drawing.Point(0, 0); + this.tableLayoutPanel1.Name = "tableLayoutPanel1"; + this.tableLayoutPanel1.RowCount = 1; + this.tableLayoutPanel1.RowStyles.Add(new System.Windows.Forms.RowStyle(System.Windows.Forms.SizeType.Percent, 50F)); + this.tableLayoutPanel1.Size = new System.Drawing.Size(774, 425); + this.tableLayoutPanel1.TabIndex = 1; + // + // picConverted + // + this.picConverted.Dock = System.Windows.Forms.DockStyle.Fill; + this.picConverted.Location = new System.Drawing.Point(390, 3); + this.picConverted.Name = "picConverted"; + this.picConverted.Size = new System.Drawing.Size(381, 419); + this.picConverted.SizeMode = System.Windows.Forms.PictureBoxSizeMode.Zoom; + this.picConverted.TabIndex = 0; + this.picConverted.TabStop = false; + // + // CVDialog + // + this.AutoScaleDimensions = new System.Drawing.SizeF(7F, 12F); + this.AutoScaleMode = System.Windows.Forms.AutoScaleMode.Font; + this.ClientSize = new System.Drawing.Size(774, 425); + this.Controls.Add(this.tableLayoutPanel1); + this.Name = "CVDialog"; + this.Text = "CVDialog"; + ((System.ComponentModel.ISupportInitialize)(this.picSource)).EndInit(); + this.tableLayoutPanel1.ResumeLayout(false); + ((System.ComponentModel.ISupportInitialize)(this.picConverted)).EndInit(); + this.ResumeLayout(false); + + } + + #endregion + + private OpenCvSharp.UserInterface.PictureBoxIpl picSource; + private System.Windows.Forms.TableLayoutPanel tableLayoutPanel1; + private OpenCvSharp.UserInterface.PictureBoxIpl picConverted; + } +} \ No newline at end of file diff --git a/OpenCV/Forms/CVDialog.cs b/OpenCV/Forms/CVDialog.cs new file mode 100644 index 0000000..985f931 --- /dev/null +++ b/OpenCV/Forms/CVDialog.cs @@ -0,0 +1,34 @@ +using OpenCvSharp; +using OpenCvSharp.UserInterface; +using System; +using System.Collections.Generic; +using System.ComponentModel; +using System.Data; +using System.Drawing; +using System.Linq; +using System.Text; +using System.Threading.Tasks; +using System.Windows.Forms; + +namespace OpenCV.Forms +{ + public partial class CVDialog : Form + { + public IplImage Source + { + get { return picSource.ImageIpl; } + set { picSource.ImageIpl = value; } + } + + public IplImage Converted + { + get { return picConverted.ImageIpl; } + set { picConverted.ImageIpl = value; } + } + + public CVDialog() + { + InitializeComponent(); + } + } +} diff --git a/OpenCV/Forms/CVDialog.resx b/OpenCV/Forms/CVDialog.resx new file mode 100644 index 0000000..1af7de1 --- /dev/null +++ b/OpenCV/Forms/CVDialog.resx @@ -0,0 +1,120 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + text/microsoft-resx + + + 2.0 + + + System.Resources.ResXResourceReader, System.Windows.Forms, Version=4.0.0.0, Culture=neutral, PublicKeyToken=b77a5c561934e089 + + + System.Resources.ResXResourceWriter, System.Windows.Forms, Version=4.0.0.0, Culture=neutral, PublicKeyToken=b77a5c561934e089 + + \ No newline at end of file diff --git a/OpenCV/Forms/MainForm.Designer.cs b/OpenCV/Forms/MainForm.Designer.cs new file mode 100644 index 0000000..a5afd4d --- /dev/null +++ b/OpenCV/Forms/MainForm.Designer.cs @@ -0,0 +1,60 @@ +namespace OpenCV.Forms +{ + partial class MainForm + { + /// + /// Required designer variable. + /// + private System.ComponentModel.IContainer components = null; + + /// + /// Clean up any resources being used. + /// + /// true if managed resources should be disposed; otherwise, false. + protected override void Dispose(bool disposing) + { + if (disposing && (components != null)) + { + components.Dispose(); + } + base.Dispose(disposing); + } + + #region Windows Form Designer generated code + + /// + /// Required method for Designer support - do not modify + /// the contents of this method with the code editor. + /// + private void InitializeComponent() + { + this.btnCanny = new System.Windows.Forms.Button(); + this.SuspendLayout(); + // + // btnCanny + // + this.btnCanny.Location = new System.Drawing.Point(13, 13); + this.btnCanny.Name = "btnCanny"; + this.btnCanny.Size = new System.Drawing.Size(75, 23); + this.btnCanny.TabIndex = 0; + this.btnCanny.Text = "Canny"; + this.btnCanny.UseVisualStyleBackColor = true; + this.btnCanny.Click += new System.EventHandler(this.btnCanny_Click); + // + // MainForm + // + this.AutoScaleDimensions = new System.Drawing.SizeF(7F, 12F); + this.AutoScaleMode = System.Windows.Forms.AutoScaleMode.Font; + this.ClientSize = new System.Drawing.Size(470, 365); + this.Controls.Add(this.btnCanny); + this.Name = "MainForm"; + this.Text = "MainForm"; + this.ResumeLayout(false); + + } + + #endregion + + private System.Windows.Forms.Button btnCanny; + } +} \ No newline at end of file diff --git a/OpenCV/Forms/MainForm.cs b/OpenCV/Forms/MainForm.cs new file mode 100644 index 0000000..cce9f84 --- /dev/null +++ b/OpenCV/Forms/MainForm.cs @@ -0,0 +1,48 @@ +using OpenCV.OpenCV; +using OpenCvSharp; +using System; +using System.Collections.Generic; +using System.ComponentModel; +using System.Data; +using System.Drawing; +using System.Linq; +using System.Text; +using System.Threading.Tasks; +using System.Windows.Forms; + +namespace OpenCV.Forms +{ + public partial class MainForm : Form + { + public MainForm() + { + InitializeComponent(); + } + + private IplImage GetImage() + { + OpenFileDialog dlg = new OpenFileDialog(); + if (dlg.ShowDialog() != DialogResult.OK) + return null; + + return new IplImage(dlg.FileName); + } + + private void btnCanny_Click(object sender, EventArgs e) + { + IplImage src = GetImage(); + if (src == null) + return; + + OpenCVClass converter = new OpenCVClass(); + IplImage converted = converter.CannyEdge(src); + + CVDialog dlg = new CVDialog(); + dlg.Source = src; + dlg.Converted = converted; + dlg.ShowDialog(); + + converter.Dispose(); + } + } +} diff --git a/OpenCV/Forms/MainForm.resx b/OpenCV/Forms/MainForm.resx new file mode 100644 index 0000000..1af7de1 --- /dev/null +++ b/OpenCV/Forms/MainForm.resx @@ -0,0 +1,120 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + text/microsoft-resx + + + 2.0 + + + System.Resources.ResXResourceReader, System.Windows.Forms, Version=4.0.0.0, Culture=neutral, PublicKeyToken=b77a5c561934e089 + + + System.Resources.ResXResourceWriter, System.Windows.Forms, Version=4.0.0.0, Culture=neutral, PublicKeyToken=b77a5c561934e089 + + \ No newline at end of file diff --git a/OpenCV/Libs/OpenCvSharp.Blob.dll b/OpenCV/Libs/OpenCvSharp.Blob.dll new file mode 100644 index 0000000..4d89e5d Binary files /dev/null and b/OpenCV/Libs/OpenCvSharp.Blob.dll differ diff --git a/OpenCV/Libs/OpenCvSharp.Blob.dll.config b/OpenCV/Libs/OpenCvSharp.Blob.dll.config new file mode 100644 index 0000000..095f0d9 --- /dev/null +++ b/OpenCV/Libs/OpenCvSharp.Blob.dll.config @@ -0,0 +1,4 @@ + + + + \ No newline at end of file diff --git a/OpenCV/Libs/OpenCvSharp.Blob.xml b/OpenCV/Libs/OpenCvSharp.Blob.xml new file mode 100644 index 0000000..8331d6c --- /dev/null +++ b/OpenCV/Libs/OpenCvSharp.Blob.xml @@ -0,0 +1,1285 @@ + + + + OpenCvSharp.Blob + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Struct that contain information about one blob. + + + + + Constructor + + + + + + + + + + + + + Label assigned to the blob + + + + + Area (moment 00) + + + + + Area (moment 00) + + + + + X min + + + + + X max + + + + + Y min + + + + + Y max + + + + + CvRect(MinX, MinY, MaxX - MinX, MaxY - MinY) + + + + + Centroid + + + + + Moment 10 + + + + + Moment 01 + + + + + Moment 11 + + + + + Moment 20 + + + + + Moment 02 + + + + + True if central moments are being calculated + + + + + Central moment 11 + + + + + Central moment 20 + + + + + Central moment 02 + + + + + Normalized central moment 11. + + + + + Normalized central moment 20. + + + + + Normalized central moment 02. + + + + + Hu moment 1. + + + + + Hu moment 2. + + + + + Contour + + + + + Internal contours + + + + + Calculates angle orientation of a blob. + This function uses central moments so cvCentralMoments should have been called before for this blob. (cvAngle) + + Angle orientation in radians. + + + + Calculates centroid. + Centroid will be returned and stored in the blob structure. (cvCentroid) + + Centroid. + + + + Save the image of a blob to a file. + The function uses an image (that can be the original pre-processed image or a processed one, or even the result of cvRenderBlobs, for example) and a blob structure. + Then the function saves a copy of the part of the image where the blob is. + + Name of the file. + Image. + + + + Set the ROI of an image to the bounding box of a blob. + + Image. + + + + Set central/hu moments and centroid value from moment values (M**) + + + + + + + + + + + Functions of cvblob library + + + + + Size of a label in bits. + + + + + Calculates angle orientation of a blob. + This function uses central moments so cvCentralMoments should have been called before for this blob. (cvAngle) + + Blob. + Angle orientation in radians. + + + + Calculates centroid. + Centroid will be returned and stored in the blob structure. (cvCentroid) + + Blob whose centroid will be calculated. + Centroid. + + + + Calculates area of a polygonal contour. + + Contour (polygon type). + Area of the contour. + + + + Calculates the circularity of a polygon (compactness measure). + + Contour (polygon type). + Circularity: a non-negative value, where 0 correspond with a circumference. + + + + Calculates perimeter of a chain code contour. + + Contour (polygon type). + Perimeter of the contour. + + + + Calculates perimeter of a chain code contour. + + Contour (chain code type). + Perimeter of the contour. + + + + Convert a chain code contour to a polygon. + + Chain code contour. + A polygon. + + + + Filter blobs by area. + Those blobs whose areas are not in range will be erased from the input list of blobs. (cvFilterByArea) + + List of blobs. + Minimun area. + Maximun area. + + + + Filter blobs by label. + Delete all blobs except those with label l. + + List of blobs. + Label to leave. + + + + Draw a binary image with the blobs that have been given. (cvFilterLabels) + + List of blobs to be drawn. + Output binary image (depth=IPL_DEPTH_8U and nchannels=1). + + + + Get the label value from a labeled image. + + Blob data. + X coordenate. + Y coordenate. + Label value. + + + + Find greater blob. (cvGreaterBlob) + + List of blobs. + The greater blob. + + + + Find the largest blob. (cvLargestBlob) + + List of blobs. + The largest blob. + + + + Label the connected parts of a binary image. (cvLabel) + + Input binary image (depth=IPL_DEPTH_8U and num. channels=1). + List of blobs. + Number of pixels that has been labeled. + + + + Calculates mean color of a blob in an image. + + Blob list + The target blob + Original image. + Average color. + + + + Calculates convex hull of a contour. + Uses the Melkman Algorithm. Code based on the version in http://w3.impa.br/~rdcastan/Cgeometry/. + + Contour (polygon type). + Convex hull. + + + + Draws or prints information about a blob. + + Label data. + Blob. + Input image (depth=IPL_DEPTH_8U and num. channels=3). + Output image (depth=IPL_DEPTH_8U and num. channels=3). + + + + Draws or prints information about a blob. + + Label data. + Blob. + Input image (depth=IPL_DEPTH_8U and num. channels=3). + Output image (depth=IPL_DEPTH_8U and num. channels=3). + Render mode. By default is CV_BLOB_RENDER_COLOR|CV_BLOB_RENDER_CENTROID|CV_BLOB_RENDER_BOUNDING_BOX|CV_BLOB_RENDER_ANGLE. + + + + Draws or prints information about a blob. + + Label data. + Blob. + Input image (depth=IPL_DEPTH_8U and num. channels=3). + Output image (depth=IPL_DEPTH_8U and num. channels=3). + Render mode. By default is CV_BLOB_RENDER_COLOR|CV_BLOB_RENDER_CENTROID|CV_BLOB_RENDER_BOUNDING_BOX|CV_BLOB_RENDER_ANGLE. + Color to render (if CV_BLOB_RENDER_COLOR is used). + + + + Draws or prints information about a blob. + + Label data. + Blob. + Input image (depth=IPL_DEPTH_8U and num. channels=3). + Output image (depth=IPL_DEPTH_8U and num. channels=3). + Render mode. By default is CV_BLOB_RENDER_COLOR|CV_BLOB_RENDER_CENTROID|CV_BLOB_RENDER_BOUNDING_BOX|CV_BLOB_RENDER_ANGLE. + Color to render (if CV_BLOB_RENDER_COLOR is used). + If mode CV_BLOB_RENDER_COLOR is used. 1.0 indicates opaque and 0.0 translucent (1.0 by default). + + + + Draws or prints information about blobs. (cvRenderBlobs) + + List of blobs. + Input image (depth=IPL_DEPTH_8U and num. channels=3). + Output image (depth=IPL_DEPTH_8U and num. channels=3). + + + + Draws or prints information about blobs. (cvRenderBlobs) + + List of blobs. + Input image (depth=IPL_DEPTH_8U and num. channels=3). + Output image (depth=IPL_DEPTH_8U and num. channels=3). + Render mode. By default is CV_BLOB_RENDER_COLOR|CV_BLOB_RENDER_CENTROID|CV_BLOB_RENDER_BOUNDING_BOX|CV_BLOB_RENDER_ANGLE. + + + + Draws or prints information about blobs. (cvRenderBlobs) + + List of blobs. + Input image (depth=IPL_DEPTH_8U and num. channels=3). + Output image (depth=IPL_DEPTH_8U and num. channels=3). + Render mode. By default is CV_BLOB_RENDER_COLOR|CV_BLOB_RENDER_CENTROID|CV_BLOB_RENDER_BOUNDING_BOX|CV_BLOB_RENDER_ANGLE. + If mode CV_BLOB_RENDER_COLOR is used. 1.0 indicates opaque and 0.0 translucent (1.0 by default). + + + + Draw a contour. + + Chain code contour. + Image to draw on. + + + + Draw a contour. + + Chain code contour. + Image to draw on. + Color to draw (default, white). + + + + Draw a polygon. + + Polygon contour. + Image to draw on. + + + + Draw a polygon. + + Polygon contour. + Image to draw on. + Color to draw (default, white). + + + + Prints tracks information. + + List of tracks. + Input image (depth=IPL_DEPTH_8U and num. channels=3). + Output image (depth=IPL_DEPTH_8U and num. channels=3). + + + + Prints tracks information. + + List of tracks. + Input image (depth=IPL_DEPTH_8U and num. channels=3). + Output image (depth=IPL_DEPTH_8U and num. channels=3). + Render mode. By default is CV_TRACK_RENDER_ID. + + + + Prints tracks information. + + List of tracks. + Input image (depth=IPL_DEPTH_8U and num. channels=3). + Output image (depth=IPL_DEPTH_8U and num. channels=3). + Render mode. By default is CV_TRACK_RENDER_ID. + OpenCV font for print on the image. + + + + Save the image of a blob to a file. + The function uses an image (that can be the original pre-processed image or a processed one, or even the result of cvRenderBlobs, for example) and a blob structure. + Then the function saves a copy of the part of the image where the blob is. + + Name of the file. + Image. + Blob. + + + + Set the ROI of an image to the bounding box of a blob. + + Image. + Blob. + + + + Simplify a polygon reducing the number of vertex according the distance "delta". + Uses a version of the Ramer-Douglas-Peucker algorithm (http://en.wikipedia.org/wiki/Ramer-Douglas-Peucker_algorithm). + + Contour (polygon type). + A simplify version of the original polygon. + + + + Simplify a polygon reducing the number of vertex according the distance "delta". + Uses a version of the Ramer-Douglas-Peucker algorithm (http://en.wikipedia.org/wiki/Ramer-Douglas-Peucker_algorithm). + + Contour (polygon type). + Minimun distance. + A simplify version of the original polygon. + + + + Updates list of tracks based on current blobs. + + List of blobs. + List of tracks. + Max distance to determine when a track and a blob match. + Max number of frames a track can be inactive. + + + + Updates list of tracks based on current blobs. + + List of blobs. + List of tracks. + Max distance to determine when a track and a blob match. + Max number of frames a track can be inactive. + If a track becomes inactive but it has been active less than thActive frames, the track will be deleted. + + Tracking based on: + A. Senior, A. Hampapur, Y-L Tian, L. Brown, S. Pankanti, R. Bolle. Appearance Models for + Occlusion Handling. Second International workshop on Performance Evaluation of Tracking and + Surveillance Systems & CVPR'01. December, 2001. + (http://www.research.ibm.com/peoplevision/PETS2001.pdf) + + + + + Write a contour to a CSV (Comma-separated values) file. + + Polygon contour. + File name. + + + + Write a contour to a SVG file. + + Polygon contour. + File name. + + + + Write a contour to a SVG file. + + Polygon contour. + File name. + Stroke color (black by default). + Fill color (white by default). + + + + Blob set + + + + + Label values + + + + + Constructor (init only) + + + + + Constructor (copy) + + + + + Constructor (copy) + + + + + Constructor (init and cvLabel) + + Input binary image (depth=IPL_DEPTH_8U and nchannels=1). + + + + Calculates mean color of a blob in an image. (cvBlobMeanColor) + + The target blob + Original image. + + + + Filter blobs by area. + Those blobs whose areas are not in range will be erased from the input list of blobs. (cvFilterByArea) + + Minimun area. + Maximun area. + + + + Filter blobs by label. + Delete all blobs except those with label l. + + Label to leave. + + + + Draw a binary image with the blobs that have been given. (cvFilterLabels) + + Output binary image (depth=IPL_DEPTH_8U and nchannels=1). + + + + Find greater blob. (cvGreaterBlob) + + The greater blob. + + + + Find the largest blob. (cvGreaterBlob) + + The largest blob. + + + + Label the connected parts of a binary image. (cvLabel) + + + + Number of pixels that has been labeled. + + + + Label the connected parts of a binary image. (cvLabel) + + Input binary image (depth=IPL_DEPTH_8U and num. channels=1). + Number of pixels that has been labeled. + + + + Draws or prints information about blobs. (cvRenderBlobs) + + Input image (depth=IPL_DEPTH_8U and num. channels=3). + Output image (depth=IPL_DEPTH_8U and num. channels=3). + + + + Draws or prints information about blobs. (cvRenderBlobs) + + Input image (depth=IPL_DEPTH_8U and num. channels=3). + Output image (depth=IPL_DEPTH_8U and num. channels=3). + Render mode. By default is CV_BLOB_RENDER_COLOR|CV_BLOB_RENDER_CENTROID|CV_BLOB_RENDER_BOUNDING_BOX|CV_BLOB_RENDER_ANGLE. + + + + Draws or prints information about blobs. (cvRenderBlobs) + + Input image (depth=IPL_DEPTH_8U and num. channels=3). + Output image (depth=IPL_DEPTH_8U and num. channels=3). + Render mode. By default is CV_BLOB_RENDER_COLOR|CV_BLOB_RENDER_CENTROID|CV_BLOB_RENDER_BOUNDING_BOX|CV_BLOB_RENDER_ANGLE. + If mode CV_BLOB_RENDER_COLOR is used. 1.0 indicates opaque and 0.0 translucent (1.0 by default). + + + + Updates list of tracks based on current blobs. + + List of tracks. + Max distance to determine when a track and a blob match. + Max number of frames a track can be inactive. + + Tracking based on: + A. Senior, A. Hampapur, Y-L Tian, L. Brown, S. Pankanti, R. Bolle. Appearance Models for + Occlusion Handling. Second International workshop on Performance Evaluation of Tracking and + Surveillance Systems & CVPR'01. December, 2001. + (http://www.research.ibm.com/peoplevision/PETS2001.pdf) + + + + + Updates list of tracks based on current blobs. + + List of tracks. + Max distance to determine when a track and a blob match. + Max number of frames a track can be inactive. + If a track becomes inactive but it has been active less than thActive frames, the track will be deleted. + + Tracking based on: + A. Senior, A. Hampapur, Y-L Tian, L. Brown, S. Pankanti, R. Bolle. Appearance Models for + Occlusion Handling. Second International workshop on Performance Evaluation of Tracking and + Surveillance Systems & CVPR'01. December, 2001. + (http://www.research.ibm.com/peoplevision/PETS2001.pdf) + + + + + + + + + + + Chain code (direction) + + + + + Up. + + + + + Up and right. + + + + + Right. + + + + + Down and right. + + + + + Down. + + + + + Down and left. + + + + + Left. + + + + + Up and left. + + + + + + + + + + Point where contour begin. + + + + + Polygon description based on chain codes. + + + + + + + + + + Convert a chain code contour to a polygon. + + A polygon. + + + + Calculates perimeter of a polygonal contour. + + Perimeter of the contour. + + + + Draw a contour. + + Image to draw on. + + + + Draw a contour. + + Image to draw on. + Color to draw (default, white). + + + + + + + + + + Polygon based contour. + + + + + + + + + + + + + + + + Converts this to CSV string + + + + + + Calculates area of a polygonal contour. + + Area of the contour. + + + + Calculates the circularity of a polygon (compactness measure). + + Circularity: a non-negative value, where 0 correspond with a circumference. + + + + Calculates convex hull of a contour. + Uses the Melkman Algorithm. Code based on the version in http://w3.impa.br/~rdcastan/Cgeometry/. + + Convex hull. + + + + Calculates perimeter of a chain code contour. + + Perimeter of the contour. + + + + Draw a polygon. + + Image to draw on. + + + + Draw a polygon. + + Image to draw on. + Color to draw (default, white). + + + + Simplify a polygon reducing the number of vertex according the distance "delta". + Uses a version of the Ramer-Douglas-Peucker algorithm (http://en.wikipedia.org/wiki/Ramer-Douglas-Peucker_algorithm). + + A simplify version of the original polygon. + + + + Simplify a polygon reducing the number of vertex according the distance "delta". + Uses a version of the Ramer-Douglas-Peucker algorithm (http://en.wikipedia.org/wiki/Ramer-Douglas-Peucker_algorithm). + + Minimun distance. + A simplify version of the original polygon. + + + + Write a contour to a CSV (Comma-separated values) file. + + File name. + + + + Write a contour to a SVG file. + + File name + + + + Write a contour to a SVG file. + + File name + Stroke color + Fill color + + + + Struct that contain information about one track. + + + + + Track identification number. + + + + + Label assigned to the blob related to this track. + + + + + X min. + + + + + X max. + + + + + Y min. + + + + + Y max. + + + + + Centroid. + + + + + Indicates how much frames the object has been in scene. + + + + + Indicates number of frames that has been active from last inactive period. + + + + + Indicates number of frames that has been missing. + + + + + + + + + + + + + + + Prints tracks information. + + Input image (depth=IPL_DEPTH_8U and num. channels=3). + Output image (depth=IPL_DEPTH_8U and num. channels=3). + + + + Prints tracks information. + + Input image (depth=IPL_DEPTH_8U and num. channels=3). + Output image (depth=IPL_DEPTH_8U and num. channels=3). + Render mode. By default is CV_TRACK_RENDER_ID. + + + + Prints tracks information. + + Input image (depth=IPL_DEPTH_8U and num. channels=3). + Output image (depth=IPL_DEPTH_8U and num. channels=3). + Render mode. By default is CV_TRACK_RENDER_ID. + OpenCV font for print on the image. + + + + + + + + + + Label values for each pixel + + + + + Label value + + + + + Region of interest + + + + + Row length + + + + + Column Length + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Returns deep copied instance of this + + + + + + + + + + + Value of invalid pixel. + -1 == uint.MaxValue + + + + + + + + + + + + + Constants which are defined by cvblob + + + + + Size of a label in bits. + + + + + Render each blog with a different color. + + + + + Render centroid. + + + + + Render bounding box. + + + + + Render angle. + + + + + Print blob data to log out. + + + + + Print blob data to std out. + + + + + Up. + + + + + Up and right. + + + + + Right. + + + + + Down and right. + + + + + Down. + + + + + Down and left. + + + + + Left. + + + + + Up and left. + + + + + Move vectors of chain codes. + + + + + Print the ID of each track in the image. + + + + + Draw bounding box of each track in the image. \see cvRenderTracks + + + + + Print track info to log out. + + + + + Print track info to log out. + + + + + Render mode of cvRenderBlobs + + + + + No flags (=0) + + + + + Render each blog with a different color. + [CV_BLOB_RENDER_COLOR] + + + + + Render centroid. + CV_BLOB_RENDER_CENTROID] + + + + + Render bounding box. + [CV_BLOB_RENDER_BOUNDING_BOX] + + + + + Render angle. + [CV_BLOB_RENDER_ANGLE] + + + + + Print blob data to log out. + [CV_BLOB_RENDER_TO_LOG] + + + + + Print blob data to std out. + [CV_BLOB_RENDER_TO_STD] + + + + + Render mode of cvRenderTracks + + + + + No flags + [0] + + + + + Print the ID of each track in the image. + [CV_TRACK_RENDER_ID] + + + + + Draw bounding box of each track in the image. \see cvRenderTracks + [CV_TRACK_RENDER_BOUNDING_BOX] + + + + diff --git a/OpenCV/Libs/OpenCvSharp.CPlusPlus.dll b/OpenCV/Libs/OpenCvSharp.CPlusPlus.dll new file mode 100644 index 0000000..75e1529 Binary files /dev/null and b/OpenCV/Libs/OpenCvSharp.CPlusPlus.dll differ diff --git a/OpenCV/Libs/OpenCvSharp.CPlusPlus.dll.config b/OpenCV/Libs/OpenCvSharp.CPlusPlus.dll.config new file mode 100644 index 0000000..095f0d9 --- /dev/null +++ b/OpenCV/Libs/OpenCvSharp.CPlusPlus.dll.config @@ -0,0 +1,4 @@ + + + + \ No newline at end of file diff --git a/OpenCV/Libs/OpenCvSharp.CPlusPlus.xml b/OpenCV/Libs/OpenCvSharp.CPlusPlus.xml new file mode 100644 index 0000000..83331d8 --- /dev/null +++ b/OpenCV/Libs/OpenCvSharp.CPlusPlus.xml @@ -0,0 +1,34282 @@ + + + + OpenCvSharp.CPlusPlus + + + + + OpenCV Functions of C++ I/F (cv::xxx) + + + + + 引数がnullの時はIntPtr.Zeroに変換する + + + + + + + Groups the object candidate rectangles. + + Input/output vector of rectangles. Output vector includes retained and grouped rectangles. + Minimum possible number of rectangles minus 1. The threshold is used in a group of rectangles to retain it. + + + + + Groups the object candidate rectangles. + + Input/output vector of rectangles. Output vector includes retained and grouped rectangles. + + Minimum possible number of rectangles minus 1. The threshold is used in a group of rectangles to retain it. + Relative difference between sides of the rectangles to merge them into a group. + + + + Groups the object candidate rectangles. + + + + + + + + + + Groups the object candidate rectangles. + + + + + + + + + + + + + + + + + + + + IListの要素にvaluesを設定する + + + + + + + + detects corners using FAST algorithm by E. Rosten + + + + + + + + + detects corners using FAST algorithm by E. Rosten + + + + + + + + + + Draw keypoints. + + + + + + + + + + Draws matches of keypints from two images on output image. + + + + + + + + + + + + + + + Draws matches of keypints from two images on output image. + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + restores the damaged image areas using one of the available intpainting algorithms + + + + + + + + + + Perform image denoising using Non-local Means Denoising algorithm + with several computational optimizations. Noise expected to be a gaussian white noise + + Input 8-bit 1-channel, 2-channel or 3-channel image. + Output image with the same size and type as src . + + Parameter regulating filter strength. Big h value perfectly removes noise but also removes image details, + smaller h value preserves details but also preserves some noise + + Size in pixels of the template patch that is used to compute weights. Should be odd. Recommended value 7 pixels + + Size in pixels of the window that is used to compute weighted average for given pixel. + Should be odd. Affect performance linearly: greater searchWindowsSize - greater denoising time. Recommended value 21 pixels + + + + Modification of fastNlMeansDenoising function for colored images + + Input 8-bit 3-channel image. + Output image with the same size and type as src. + Parameter regulating filter strength for luminance component. + Bigger h value perfectly removes noise but also removes image details, smaller h value preserves details but also preserves some noise + The same as h but for color components. For most images value equals 10 will be enought + to remove colored noise and do not distort colors + + Size in pixels of the template patch that is used to compute weights. Should be odd. Recommended value 7 pixels + + Size in pixels of the window that is used to compute weighted average for given pixel. Should be odd. + Affect performance linearly: greater searchWindowsSize - greater denoising time. Recommended value 21 pixels + + + + Modification of fastNlMeansDenoising function for images sequence where consequtive images have been captured + in small period of time. For example video. This version of the function is for grayscale images or for manual manipulation with colorspaces. + + Input 8-bit 1-channel, 2-channel or 3-channel images sequence. All images should have the same type and size. + Output image with the same size and type as srcImgs images. + Target image to denoise index in srcImgs sequence + Number of surrounding images to use for target image denoising. + Should be odd. Images from imgToDenoiseIndex - temporalWindowSize / 2 to imgToDenoiseIndex - temporalWindowSize / 2 + from srcImgs will be used to denoise srcImgs[imgToDenoiseIndex] image. + Parameter regulating filter strength for luminance component. Bigger h value perfectly removes noise but also removes image details, + smaller h value preserves details but also preserves some noise + Size in pixels of the template patch that is used to compute weights. Should be odd. Recommended value 7 pixels + Size in pixels of the window that is used to compute weighted average for given pixel. + Should be odd. Affect performance linearly: greater searchWindowsSize - greater denoising time. Recommended value 21 pixels + + + + Modification of fastNlMeansDenoising function for images sequence where consequtive images have been captured + in small period of time. For example video. This version of the function is for grayscale images or for manual manipulation with colorspaces. + + Input 8-bit 1-channel, 2-channel or 3-channel images sequence. All images should have the same type and size. + Output image with the same size and type as srcImgs images. + Target image to denoise index in srcImgs sequence + Number of surrounding images to use for target image denoising. + Should be odd. Images from imgToDenoiseIndex - temporalWindowSize / 2 to imgToDenoiseIndex - temporalWindowSize / 2 + from srcImgs will be used to denoise srcImgs[imgToDenoiseIndex] image. + Parameter regulating filter strength for luminance component. Bigger h value perfectly removes noise but also removes image details, + smaller h value preserves details but also preserves some noise + Size in pixels of the template patch that is used to compute weights. Should be odd. Recommended value 7 pixels + Size in pixels of the window that is used to compute weighted average for given pixel. + Should be odd. Affect performance linearly: greater searchWindowsSize - greater denoising time. Recommended value 21 pixels + + + + Modification of fastNlMeansDenoisingMulti function for colored images sequences + + Input 8-bit 3-channel images sequence. All images should have the same type and size. + Output image with the same size and type as srcImgs images. + Target image to denoise index in srcImgs sequence + Number of surrounding images to use for target image denoising. Should be odd. + Images from imgToDenoiseIndex - temporalWindowSize / 2 to imgToDenoiseIndex - temporalWindowSize / 2 from srcImgs + will be used to denoise srcImgs[imgToDenoiseIndex] image. + Parameter regulating filter strength for luminance component. Bigger h value perfectly removes noise + but also removes image details, smaller h value preserves details but also preserves some noise. + The same as h but for color components. + Size in pixels of the template patch that is used to compute weights. Should be odd. Recommended value 7 pixels + Size in pixels of the window that is used to compute weighted average for given pixel. + Should be odd. Affect performance linearly: greater searchWindowsSize - greater denoising time. Recommended value 21 pixels + + + + Modification of fastNlMeansDenoisingMulti function for colored images sequences + + Input 8-bit 3-channel images sequence. All images should have the same type and size. + Output image with the same size and type as srcImgs images. + Target image to denoise index in srcImgs sequence + Number of surrounding images to use for target image denoising. Should be odd. + Images from imgToDenoiseIndex - temporalWindowSize / 2 to imgToDenoiseIndex - temporalWindowSize / 2 from srcImgs + will be used to denoise srcImgs[imgToDenoiseIndex] image. + Parameter regulating filter strength for luminance component. Bigger h value perfectly removes noise + but also removes image details, smaller h value preserves details but also preserves some noise. + The same as h but for color components. + Size in pixels of the template patch that is used to compute weights. Should be odd. Recommended value 7 pixels + Size in pixels of the window that is used to compute weighted average for given pixel. + Should be odd. Affect performance linearly: greater searchWindowsSize - greater denoising time. Recommended value 21 pixels + + + + You need to call this method before using SIFT/SURF functions. + + + + + + + + + + + Updates motion history image using the current silhouette + + Silhouette mask that has non-zero pixels where the motion occurs. + Motion history image that is updated by the function (single-channel, 32-bit floating-point). + Current time in milliseconds or other units. + Maximal duration of the motion track in the same units as timestamp . + + + + Computes the motion gradient orientation image from the motion history image + + Motion history single-channel floating-point image. + Output mask image that has the type CV_8UC1 and the same size as mhi. + Its non-zero elements mark pixels where the motion gradient data is correct. + Output motion gradient orientation image that has the same type and the same size as mhi. + Each pixel of the image is a motion orientation, from 0 to 360 degrees. + Minimal (or maximal) allowed difference between mhi values within a pixel neighborhood. + Maximal (or minimal) allowed difference between mhi values within a pixel neighborhood. + That is, the function finds the minimum ( m(x,y) ) and maximum ( M(x,y) ) mhi values over 3x3 neighborhood of each pixel + and marks the motion orientation at (x, y) as valid only if: + min(delta1, delta2) <= M(x,y)-m(x,y) <= max(delta1, delta2). + + + + + Computes the global orientation of the selected motion history image part + + Motion gradient orientation image calculated by the function CalcMotionGradient() . + Mask image. It may be a conjunction of a valid gradient mask, also calculated by CalcMotionGradient() , + and the mask of a region whose direction needs to be calculated. + Motion history image calculated by UpdateMotionHistory() . + Timestamp passed to UpdateMotionHistory() . + Maximum duration of a motion track in milliseconds, passed to UpdateMotionHistory() . + + + + + Splits a motion history image into a few parts corresponding to separate independent motions + (for example, left hand, right hand). + + Motion history image. + Image where the found mask should be stored, single-channel, 32-bit floating-point. + Vector containing ROIs of motion connected components. + Current time in milliseconds or other units. + Segmentation threshold that is recommended to be equal to the interval between motion history “steps” or greater. + + + + Finds an object center, size, and orientation. + + Back projection of the object histogram. + Initial search window. + Stop criteria for the underlying MeanShift() . + + + + + Finds an object on a back projection image. + + Back projection of the object histogram. + Initial search window. + Stop criteria for the iterative search algorithm. + Number of iterations CAMSHIFT took to converge. + + + + Constructs a pyramid which can be used as input for calcOpticalFlowPyrLK + + 8-bit input image. + output pyramid. + window size of optical flow algorithm. + Must be not less than winSize argument of calcOpticalFlowPyrLK(). + It is needed to calculate required padding for pyramid levels. + 0-based maximal pyramid level number. + set to precompute gradients for the every pyramid level. + If pyramid is constructed without the gradients then calcOpticalFlowPyrLK() will + calculate them internally. + the border mode for pyramid layers. + the border mode for gradients. + put ROI of input image into the pyramid if possible. + You can pass false to force data copying. + number of levels in constructed pyramid. Can be less than maxLevel. + + + + Constructs a pyramid which can be used as input for calcOpticalFlowPyrLK + + 8-bit input image. + output pyramid. + window size of optical flow algorithm. + Must be not less than winSize argument of calcOpticalFlowPyrLK(). + It is needed to calculate required padding for pyramid levels. + 0-based maximal pyramid level number. + set to precompute gradients for the every pyramid level. + If pyramid is constructed without the gradients then calcOpticalFlowPyrLK() will + calculate them internally. + the border mode for pyramid layers. + the border mode for gradients. + put ROI of input image into the pyramid if possible. + You can pass false to force data copying. + number of levels in constructed pyramid. Can be less than maxLevel. + + + + computes sparse optical flow using multi-scale Lucas-Kanade algorithm + + + + + + + + + + + + + + + + computes sparse optical flow using multi-scale Lucas-Kanade algorithm + + + + + + + + + + + + + + + + Computes a dense optical flow using the Gunnar Farneback's algorithm. + + first 8-bit single-channel input image. + second input image of the same size and the same type as prev. + computed flow image that has the same size as prev and type CV_32FC2. + parameter, specifying the image scale (<1) to build pyramids for each image; + pyrScale=0.5 means a classical pyramid, where each next layer is twice smaller than the previous one. + number of pyramid layers including the initial image; + levels=1 means that no extra layers are created and only the original images are used. + averaging window size; larger values increase the algorithm robustness to + image noise and give more chances for fast motion detection, but yield more blurred motion field. + number of iterations the algorithm does at each pyramid level. + size of the pixel neighborhood used to find polynomial expansion in each pixel; + larger values mean that the image will be approximated with smoother surfaces, + yielding more robust algorithm and more blurred motion field, typically poly_n =5 or 7. + standard deviation of the Gaussian that is used to smooth derivatives used as + a basis for the polynomial expansion; for polyN=5, you can set polySigma=1.1, + for polyN=7, a good value would be polySigma=1.5. + operation flags that can be a combination of OPTFLOW_USE_INITIAL_FLOW and/or OPTFLOW_FARNEBACK_GAUSSIAN + + + + Estimates the best-fit Euqcidean, similarity, affine or perspective transformation + that maps one 2D point set to another or one image to another. + + First input 2D point set stored in std::vector or Mat, or an image stored in Mat. + Second input 2D point set of the same size and the same type as A, or another image. + If true, the function finds an optimal affine transformation with no additional restrictions (6 degrees of freedom). + Otherwise, the class of transformations to choose from is limited to combinations of translation, rotation, and uniform scaling (5 degrees of freedom). + + + + + computes dense optical flow using Simple Flow algorithm + + First 8-bit 3-channel image. + Second 8-bit 3-channel image + Estimated flow + Number of layers + Size of block through which we sum up when calculate cost function for pixel + maximal flow that we search at each level + + + + computes dense optical flow using Simple Flow algorithm + + First 8-bit 3-channel image. + Second 8-bit 3-channel image + Estimated flow + Number of layers + Size of block through which we sum up when calculate cost function for pixel + maximal flow that we search at each level + vector smooth spatial sigma parameter + vector smooth color sigma parameter + window size for postprocess cross bilateral filter + spatial sigma for postprocess cross bilateralf filter + color sigma for postprocess cross bilateral filter + threshold for detecting occlusions + window size for bilateral upscale operation + spatial sigma for bilateral upscale operation + color sigma for bilateral upscale operation + threshold to detect point with irregular flow - where flow should be recalculated after upscale + + + + Implementation of the Zach, Pock and Bischof Dual TV-L1 Optical Flow method + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Create Bilateral TV-L1 Super Resolution. + + + + + + Create Bilateral TV-L1 Super Resolution. + + + + + + Create Bilateral TV-L1 Super Resolution. + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + converts rotation vector to rotation matrix or vice versa using Rodrigues transformation + + Input rotation vector (3x1 or 1x3) or rotation matrix (3x3). + Output rotation matrix (3x3) or rotation vector (3x1 or 1x3), respectively. + Optional output Jacobian matrix, 3x9 or 9x3, which is a matrix of partial derivatives of the output array components with respect to the input array components. + + + + converts rotation vector to rotation matrix using Rodrigues transformation + + Input rotation vector (3x1). + Output rotation matrix (3x3). + Optional output Jacobian matrix, 3x9, which is a matrix of partial derivatives of the output array components with respect to the input array components. + + + + converts rotation vector to rotation matrix using Rodrigues transformation + + Input rotation vector (3x1). + Output rotation matrix (3x3). + + + + converts rotation matrix to rotation vector using Rodrigues transformation + + Input rotation matrix (3x3). + Output rotation vector (3x1). + Optional output Jacobian matrix, 3x9, which is a matrix of partial derivatives of the output array components with respect to the input array components. + + + + converts rotation matrix to rotation vector using Rodrigues transformation + + Input rotation matrix (3x3). + Output rotation vector (3x1). + + + + computes the best-fit perspective transformation mapping srcPoints to dstPoints. + + Coordinates of the points in the original plane, a matrix of the type CV_32FC2 + Coordinates of the points in the target plane, a matrix of the type CV_32FC2 + Method used to computed a homography matrix. + Maximum allowed reprojection error to treat a point pair as an inlier (used in the RANSAC method only) + Optional output mask set by a robust method ( CV_RANSAC or CV_LMEDS ). Note that the input mask values are ignored. + + + + + computes the best-fit perspective transformation mapping srcPoints to dstPoints. + + Coordinates of the points in the original plane + Coordinates of the points in the target plane + Method used to computed a homography matrix. + Maximum allowed reprojection error to treat a point pair as an inlier (used in the RANSAC method only) + Optional output mask set by a robust method ( CV_RANSAC or CV_LMEDS ). Note that the input mask values are ignored. + + + + + Computes RQ decomposition of 3x3 matrix + + 3x3 input matrix. + Output 3x3 upper-triangular matrix. + Output 3x3 orthogonal matrix. + Optional output 3x3 rotation matrix around x-axis. + Optional output 3x3 rotation matrix around y-axis. + Optional output 3x3 rotation matrix around z-axis. + + + + + Computes RQ decomposition of 3x3 matrix + + 3x3 input matrix. + Output 3x3 upper-triangular matrix. + Output 3x3 orthogonal matrix. + + + + + Computes RQ decomposition of 3x3 matrix + + 3x3 input matrix. + Output 3x3 upper-triangular matrix. + Output 3x3 orthogonal matrix. + Optional output 3x3 rotation matrix around x-axis. + Optional output 3x3 rotation matrix around y-axis. + Optional output 3x3 rotation matrix around z-axis. + + + + + Decomposes the projection matrix into camera matrix and the rotation martix and the translation vector + + 3x4 input projection matrix P. + Output 3x3 camera matrix K. + Output 3x3 external rotation matrix R. + Output 4x1 translation vector T. + Optional 3x3 rotation matrix around x-axis. + Optional 3x3 rotation matrix around y-axis. + Optional 3x3 rotation matrix around z-axis. + ptional three-element vector containing three Euler angles of rotation in degrees. + + + + Decomposes the projection matrix into camera matrix and the rotation martix and the translation vector + + 3x4 input projection matrix P. + Output 3x3 camera matrix K. + Output 3x3 external rotation matrix R. + Output 4x1 translation vector T. + Optional 3x3 rotation matrix around x-axis. + Optional 3x3 rotation matrix around y-axis. + Optional 3x3 rotation matrix around z-axis. + ptional three-element vector containing three Euler angles of rotation in degrees. + + + + Decomposes the projection matrix into camera matrix and the rotation martix and the translation vector + + 3x4 input projection matrix P. + Output 3x3 camera matrix K. + Output 3x3 external rotation matrix R. + Output 4x1 translation vector T. + + + + computes derivatives of the matrix product w.r.t each of the multiplied matrix coefficients + + First multiplied matrix. + Second multiplied matrix. + First output derivative matrix d(A*B)/dA of size A.rows*B.cols X A.rows*A.cols . + Second output derivative matrix d(A*B)/dB of size A.rows*B.cols X B.rows*B.cols . + + + + composes 2 [R|t] transformations together. Also computes the derivatives of the result w.r.t the arguments + + First rotation vector. + First translation vector. + Second rotation vector. + Second translation vector. + Output rotation vector of the superposition. + Output translation vector of the superposition. + Optional output derivatives of rvec3 or tvec3 with regard to rvec1, rvec2, tvec1 and tvec2, respectively. + Optional output derivatives of rvec3 or tvec3 with regard to rvec1, rvec2, tvec1 and tvec2, respectively. + Optional output derivatives of rvec3 or tvec3 with regard to rvec1, rvec2, tvec1 and tvec2, respectively. + Optional output derivatives of rvec3 or tvec3 with regard to rvec1, rvec2, tvec1 and tvec2, respectively. + Optional output derivatives of rvec3 or tvec3 with regard to rvec1, rvec2, tvec1 and tvec2, respectively. + Optional output derivatives of rvec3 or tvec3 with regard to rvec1, rvec2, tvec1 and tvec2, respectively. + Optional output derivatives of rvec3 or tvec3 with regard to rvec1, rvec2, tvec1 and tvec2, respectively. + Optional output derivatives of rvec3 or tvec3 with regard to rvec1, rvec2, tvec1 and tvec2, respectively. + + + + composes 2 [R|t] transformations together. Also computes the derivatives of the result w.r.t the arguments + + First rotation vector. + First translation vector. + Second rotation vector. + Second translation vector. + Output rotation vector of the superposition. + Output translation vector of the superposition. + Optional output derivatives of rvec3 or tvec3 with regard to rvec1, rvec2, tvec1 and tvec2, respectively. + Optional output derivatives of rvec3 or tvec3 with regard to rvec1, rvec2, tvec1 and tvec2, respectively. + Optional output derivatives of rvec3 or tvec3 with regard to rvec1, rvec2, tvec1 and tvec2, respectively. + Optional output derivatives of rvec3 or tvec3 with regard to rvec1, rvec2, tvec1 and tvec2, respectively. + Optional output derivatives of rvec3 or tvec3 with regard to rvec1, rvec2, tvec1 and tvec2, respectively. + Optional output derivatives of rvec3 or tvec3 with regard to rvec1, rvec2, tvec1 and tvec2, respectively. + Optional output derivatives of rvec3 or tvec3 with regard to rvec1, rvec2, tvec1 and tvec2, respectively. + Optional output derivatives of rvec3 or tvec3 with regard to rvec1, rvec2, tvec1 and tvec2, respectively. + + + + composes 2 [R|t] transformations together. Also computes the derivatives of the result w.r.t the arguments + + First rotation vector. + First translation vector. + Second rotation vector. + Second translation vector. + Output rotation vector of the superposition. + Output translation vector of the superposition. + + + + projects points from the model coordinate space to the image coordinates. + Also computes derivatives of the image coordinates w.r.t the intrinsic + and extrinsic camera parameters + + Array of object points, 3xN/Nx3 1-channel or + 1xN/Nx1 3-channel, where N is the number of points in the view. + Rotation vector (3x1). + Translation vector (3x1). + Camera matrix (3x3) + Input vector of distortion coefficients + (k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6]]) of 4, 5, or 8 elements. + If the vector is null, the zero distortion coefficients are assumed. + Output array of image points, 2xN/Nx2 1-channel + or 1xN/Nx1 2-channel + Optional output 2Nx(10 + numDistCoeffs) jacobian matrix + of derivatives of image points with respect to components of the rotation vector, + translation vector, focal lengths, coordinates of the principal point and + the distortion coefficients. In the old interface different components of + the jacobian are returned via different output parameters. + Optional “fixed aspect ratio” parameter. + If the parameter is not 0, the function assumes that the aspect ratio (fx/fy) + is fixed and correspondingly adjusts the jacobian matrix. + + + + projects points from the model coordinate space to the image coordinates. + Also computes derivatives of the image coordinates w.r.t the intrinsic + and extrinsic camera parameters + + Array of object points, 3xN/Nx3 1-channel or + 1xN/Nx1 3-channel, where N is the number of points in the view. + Rotation vector (3x1). + Translation vector (3x1). + Camera matrix (3x3) + Input vector of distortion coefficients + (k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6]]) of 4, 5, or 8 elements. + If the vector is null, the zero distortion coefficients are assumed. + Output array of image points, 2xN/Nx2 1-channel + or 1xN/Nx1 2-channel + Optional output 2Nx(10 + numDistCoeffs) jacobian matrix + of derivatives of image points with respect to components of the rotation vector, + translation vector, focal lengths, coordinates of the principal point and + the distortion coefficients. In the old interface different components of + the jacobian are returned via different output parameters. + Optional “fixed aspect ratio” parameter. + If the parameter is not 0, the function assumes that the aspect ratio (fx/fy) + is fixed and correspondingly adjusts the jacobian matrix. + + + + Finds an object pose from 3D-2D point correspondences. + + Array of object points in the object coordinate space, 3xN/Nx3 1-channel or 1xN/Nx1 3-channel, + where N is the number of points. vector<Point3f> can be also passed here. + Array of corresponding image points, 2xN/Nx2 1-channel or 1xN/Nx1 2-channel, + where N is the number of points. vector<Point2f> can be also passed here. + Input camera matrix + Input vector of distortion coefficients (k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6]]) of 4, 5, or 8 elements. + If the vector is null, the zero distortion coefficients are assumed. + Output rotation vector that, together with tvec , brings points from the model coordinate system to the + camera coordinate system. + Output translation vector. + If true, the function uses the provided rvec and tvec values as initial approximations of + the rotation and translation vectors, respectively, and further optimizes them. + Method for solving a PnP problem: + + + + Finds an object pose from 3D-2D point correspondences. + + Array of object points in the object coordinate space, 3xN/Nx3 1-channel or 1xN/Nx1 3-channel, + where N is the number of points. vector<Point3f> can be also passed here. + Array of corresponding image points, 2xN/Nx2 1-channel or 1xN/Nx1 2-channel, + where N is the number of points. vector<Point2f> can be also passed here. + Input camera matrix + Input vector of distortion coefficients (k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6]]) of 4, 5, or 8 elements. + If the vector is null, the zero distortion coefficients are assumed. + Output rotation vector that, together with tvec , brings points from the model coordinate system to the + camera coordinate system. + Output translation vector. + If true, the function uses the provided rvec and tvec values as initial approximations of + the rotation and translation vectors, respectively, and further optimizes them. + Method for solving a PnP problem: + + + + computes the camera pose from a few 3D points and the corresponding projections. The outliers are possible. + + Array of object points in the object coordinate space, 3xN/Nx3 1-channel or 1xN/Nx1 3-channel, + where N is the number of points. List<Point3f> can be also passed here. + Array of corresponding image points, 2xN/Nx2 1-channel or 1xN/Nx1 2-channel, where N is the number of points. + List<Point2f> can be also passed here. + Input 3x3 camera matrix + Input vector of distortion coefficients (k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6]]) of 4, 5, or 8 elements. + If the vector is null, the zero distortion coefficients are assumed. + Output rotation vector that, together with tvec , brings points from the model coordinate system + to the camera coordinate system. + Output translation vector. + If true, the function uses the provided rvec and tvec values as initial approximations + of the rotation and translation vectors, respectively, and further optimizes them. + Number of iterations. + Inlier threshold value used by the RANSAC procedure. + The parameter value is the maximum allowed distance between the observed and computed point projections to consider it an inlier. + Number of inliers. If the algorithm at some stage finds more inliers than minInliersCount , it finishes. + Output vector that contains indices of inliers in objectPoints and imagePoints . + Method for solving a PnP problem + + + + computes the camera pose from a few 3D points and the corresponding projections. The outliers are possible. + + Array of object points in the object coordinate space, 3xN/Nx3 1-channel or 1xN/Nx1 3-channel, + where N is the number of points. List<Point3f> can be also passed here. + Array of corresponding image points, 2xN/Nx2 1-channel or 1xN/Nx1 2-channel, where N is the number of points. + List<Point2f> can be also passed here. + Input 3x3 camera matrix + Input vector of distortion coefficients (k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6]]) of 4, 5, or 8 elements. + If the vector is null, the zero distortion coefficients are assumed. + Output rotation vector that, together with tvec , brings points from the model coordinate system + to the camera coordinate system. + Output translation vector. + + + + computes the camera pose from a few 3D points and the corresponding projections. The outliers are possible. + + Array of object points in the object coordinate space, 3xN/Nx3 1-channel or 1xN/Nx1 3-channel, + where N is the number of points. List<Point3f> can be also passed here. + Array of corresponding image points, 2xN/Nx2 1-channel or 1xN/Nx1 2-channel, where N is the number of points. + List<Point2f> can be also passed here. + Input 3x3 camera matrix + Input vector of distortion coefficients (k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6]]) of 4, 5, or 8 elements. + If the vector is null, the zero distortion coefficients are assumed. + Output rotation vector that, together with tvec , brings points from the model coordinate system + to the camera coordinate system. + Output translation vector. + If true, the function uses the provided rvec and tvec values as initial approximations + of the rotation and translation vectors, respectively, and further optimizes them. + Number of iterations. + Inlier threshold value used by the RANSAC procedure. + The parameter value is the maximum allowed distance between the observed and computed point projections to consider it an inlier. + Number of inliers. If the algorithm at some stage finds more inliers than minInliersCount , it finishes. + Output vector that contains indices of inliers in objectPoints and imagePoints . + Method for solving a PnP problem + + + + initializes camera matrix from a few 3D points and the corresponding projections. + + Vector of vectors (vector<vector<Point3d>>) of the calibration pattern points in the calibration pattern coordinate space. In the old interface all the per-view vectors are concatenated. + Vector of vectors (vector<vector<Point2d>>) of the projections of the calibration pattern points. In the old interface all the per-view vectors are concatenated. + Image size in pixels used to initialize the principal point. + If it is zero or negative, both f_x and f_y are estimated independently. Otherwise, f_x = f_y * aspectRatio . + + + + + initializes camera matrix from a few 3D points and the corresponding projections. + + Vector of vectors of the calibration pattern points in the calibration pattern coordinate space. In the old interface all the per-view vectors are concatenated. + Vector of vectors of the projections of the calibration pattern points. In the old interface all the per-view vectors are concatenated. + Image size in pixels used to initialize the principal point. + If it is zero or negative, both f_x and f_y are estimated independently. Otherwise, f_x = f_y * aspectRatio . + + + + + Finds the positions of internal corners of the chessboard. + + Source chessboard view. It must be an 8-bit grayscale or color image. + Number of inner corners per a chessboard row and column + ( patternSize = Size(points_per_row,points_per_colum) = Size(columns, rows) ). + Output array of detected corners. + Various operation flags that can be zero or a combination of the ChessboardFlag values + The function returns true if all of the corners are found and they are placed in a certain order (row by row, left to right in every row). + Otherwise, if the function fails to find all the corners or reorder them, it returns false. + + + + Finds the positions of internal corners of the chessboard. + + Source chessboard view. It must be an 8-bit grayscale or color image. + Number of inner corners per a chessboard row and column + ( patternSize = Size(points_per_row,points_per_colum) = Size(columns, rows) ). + Output array of detected corners. + Various operation flags that can be zero or a combination of the ChessboardFlag values + The function returns true if all of the corners are found and they are placed in a certain order (row by row, left to right in every row). + Otherwise, if the function fails to find all the corners or reorder them, it returns false. + + + + finds subpixel-accurate positions of the chessboard corners + + + + + + + + + finds subpixel-accurate positions of the chessboard corners + + + + + + + + + Renders the detected chessboard corners. + + Destination image. It must be an 8-bit color image. + Number of inner corners per a chessboard row and column (patternSize = cv::Size(points_per_row,points_per_column)). + Array of detected corners, the output of findChessboardCorners. + Parameter indicating whether the complete board was found or not. The return value of findChessboardCorners() should be passed here. + + + + Renders the detected chessboard corners. + + Destination image. It must be an 8-bit color image. + Number of inner corners per a chessboard row and column (patternSize = cv::Size(points_per_row,points_per_column)). + Array of detected corners, the output of findChessboardCorners. + Parameter indicating whether the complete board was found or not. The return value of findChessboardCorners() should be passed here. + + + + Finds centers in the grid of circles. + + grid view of input circles; it must be an 8-bit grayscale or color image. + number of circles per row and column ( patternSize = Size(points_per_row, points_per_colum) ). + output array of detected centers. + various operation flags that can be one of the FindCirclesGridFlag values + feature detector that finds blobs like dark circles on light background. + + + + + Finds centers in the grid of circles. + + grid view of input circles; it must be an 8-bit grayscale or color image. + number of circles per row and column ( patternSize = Size(points_per_row, points_per_colum) ). + output array of detected centers. + various operation flags that can be one of the FindCirclesGridFlag values + feature detector that finds blobs like dark circles on light background. + + + + + finds intrinsic and extrinsic camera parameters from several fews of a known calibration pattern. + + In the new interface it is a vector of vectors of calibration pattern points in the calibration pattern coordinate space. + The outer vector contains as many elements as the number of the pattern views. If the same calibration pattern is shown in each view and + it is fully visible, all the vectors will be the same. Although, it is possible to use partially occluded patterns, or even different patterns + in different views. Then, the vectors will be different. The points are 3D, but since they are in a pattern coordinate system, then, + if the rig is planar, it may make sense to put the model to a XY coordinate plane so that Z-coordinate of each input object point is 0. + In the old interface all the vectors of object points from different views are concatenated together. + In the new interface it is a vector of vectors of the projections of calibration pattern points. + imagePoints.Count() and objectPoints.Count() and imagePoints[i].Count() must be equal to objectPoints[i].Count() for each i. + Size of the image used only to initialize the intrinsic camera matrix. + Output 3x3 floating-point camera matrix. + If CV_CALIB_USE_INTRINSIC_GUESS and/or CV_CALIB_FIX_ASPECT_RATIO are specified, some or all of fx, fy, cx, cy must be + initialized before calling the function. + Output vector of distortion coefficients (k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6]]) of 4, 5, or 8 elements. + Output vector of rotation vectors (see Rodrigues() ) estimated for each pattern view. That is, each k-th rotation vector + together with the corresponding k-th translation vector (see the next output parameter description) brings the calibration pattern + from the model coordinate space (in which object points are specified) to the world coordinate space, that is, a real position of the + calibration pattern in the k-th pattern view (k=0.. M -1) + Output vector of translation vectors estimated for each pattern view. + Different flags that may be zero or a combination of the CalibrationFlag values + Termination criteria for the iterative optimization algorithm. + + + + + finds intrinsic and extrinsic camera parameters from several fews of a known calibration pattern. + + In the new interface it is a vector of vectors of calibration pattern points in the calibration pattern coordinate space. + The outer vector contains as many elements as the number of the pattern views. If the same calibration pattern is shown in each view and + it is fully visible, all the vectors will be the same. Although, it is possible to use partially occluded patterns, or even different patterns + in different views. Then, the vectors will be different. The points are 3D, but since they are in a pattern coordinate system, then, + if the rig is planar, it may make sense to put the model to a XY coordinate plane so that Z-coordinate of each input object point is 0. + In the old interface all the vectors of object points from different views are concatenated together. + In the new interface it is a vector of vectors of the projections of calibration pattern points. + imagePoints.Count() and objectPoints.Count() and imagePoints[i].Count() must be equal to objectPoints[i].Count() for each i. + Size of the image used only to initialize the intrinsic camera matrix. + Output 3x3 floating-point camera matrix. + If CV_CALIB_USE_INTRINSIC_GUESS and/or CV_CALIB_FIX_ASPECT_RATIO are specified, some or all of fx, fy, cx, cy must be + initialized before calling the function. + Output vector of distortion coefficients (k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6]]) of 4, 5, or 8 elements. + Output vector of rotation vectors (see Rodrigues() ) estimated for each pattern view. That is, each k-th rotation vector + together with the corresponding k-th translation vector (see the next output parameter description) brings the calibration pattern + from the model coordinate space (in which object points are specified) to the world coordinate space, that is, a real position of the + calibration pattern in the k-th pattern view (k=0.. M -1) + Output vector of translation vectors estimated for each pattern view. + Different flags that may be zero or a combination of the CalibrationFlag values + Termination criteria for the iterative optimization algorithm. + + + + + computes several useful camera characteristics from the camera matrix, camera frame resolution and the physical sensor size. + + Input camera matrix that can be estimated by calibrateCamera() or stereoCalibrate() . + Input image size in pixels. + Physical width of the sensor. + Physical height of the sensor. + Output field of view in degrees along the horizontal sensor axis. + Output field of view in degrees along the vertical sensor axis. + Focal length of the lens in mm. + Principal point in pixels. + fy / fx + + + + computes several useful camera characteristics from the camera matrix, camera frame resolution and the physical sensor size. + + Input camera matrix that can be estimated by calibrateCamera() or stereoCalibrate() . + Input image size in pixels. + Physical width of the sensor. + Physical height of the sensor. + Output field of view in degrees along the horizontal sensor axis. + Output field of view in degrees along the vertical sensor axis. + Focal length of the lens in mm. + Principal point in pixels. + fy / fx + + + + finds intrinsic and extrinsic parameters of a stereo camera + + Vector of vectors of the calibration pattern points. + Vector of vectors of the projections of the calibration pattern points, observed by the first camera. + Vector of vectors of the projections of the calibration pattern points, observed by the second camera. + Input/output first camera matrix + Input/output vector of distortion coefficients (k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6]]) of 4, 5, or 8 elements. + The output vector length depends on the flags. + Input/output second camera matrix. The parameter is similar to cameraMatrix1 . + Input/output lens distortion coefficients for the second camera. The parameter is similar to distCoeffs1 . + Size of the image used only to initialize intrinsic camera matrix. + Output rotation matrix between the 1st and the 2nd camera coordinate systems. + Output translation vector between the coordinate systems of the cameras. + Output essential matrix. + Output fundamental matrix. + Termination criteria for the iterative optimization algorithm. + Different flags that may be zero or a combination of the CalibrationFlag values + + + + + finds intrinsic and extrinsic parameters of a stereo camera + + Vector of vectors of the calibration pattern points. + Vector of vectors of the projections of the calibration pattern points, observed by the first camera. + Vector of vectors of the projections of the calibration pattern points, observed by the second camera. + Input/output first camera matrix + Input/output vector of distortion coefficients (k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6]]) of 4, 5, or 8 elements. + The output vector length depends on the flags. + Input/output second camera matrix. The parameter is similar to cameraMatrix1 . + Input/output lens distortion coefficients for the second camera. The parameter is similar to distCoeffs1 . + Size of the image used only to initialize intrinsic camera matrix. + Output rotation matrix between the 1st and the 2nd camera coordinate systems. + Output translation vector between the coordinate systems of the cameras. + Output essential matrix. + Output fundamental matrix. + Termination criteria for the iterative optimization algorithm. + Different flags that may be zero or a combination of the CalibrationFlag values + + + + + computes the rectification transformation for a stereo camera from its intrinsic and extrinsic parameters + + First camera matrix. + First camera distortion parameters. + Second camera matrix. + Second camera distortion parameters. + Size of the image used for stereo calibration. + Rotation matrix between the coordinate systems of the first and the second cameras. + Translation vector between coordinate systems of the cameras. + Output 3x3 rectification transform (rotation matrix) for the first camera. + Output 3x3 rectification transform (rotation matrix) for the second camera. + Output 3x4 projection matrix in the new (rectified) coordinate systems for the first camera. + Output 3x4 projection matrix in the new (rectified) coordinate systems for the second camera. + Output 4x4 disparity-to-depth mapping matrix (see reprojectImageTo3D() ). + Operation flags that may be zero or CV_CALIB_ZERO_DISPARITY. + If the flag is set, the function makes the principal points of each camera have the same pixel coordinates in the rectified views. + And if the flag is not set, the function may still shift the images in the horizontal or vertical direction (depending on the orientation of epipolar lines) to maximize the useful image area. + Free scaling parameter. + If it is -1 or absent, the function performs the default scaling. Otherwise, the parameter should be between 0 and 1. + alpha=0 means that the rectified images are zoomed and shifted so that only valid pixels are visible (no black areas after rectification). + alpha=1 means that the rectified image is decimated and shifted so that all the pixels from the original images from the cameras are retained + in the rectified images (no source image pixels are lost). Obviously, any intermediate value yields an intermediate result between those two extreme cases. + New image resolution after rectification. The same size should be passed to initUndistortRectifyMap(). When (0,0) is passed (default), it is set to the original imageSize . + Setting it to larger value can help you preserve details in the original image, especially when there is a big radial distortion. + + + + computes the rectification transformation for a stereo camera from its intrinsic and extrinsic parameters + + First camera matrix. + First camera distortion parameters. + Second camera matrix. + Second camera distortion parameters. + Size of the image used for stereo calibration. + Rotation matrix between the coordinate systems of the first and the second cameras. + Translation vector between coordinate systems of the cameras. + Output 3x3 rectification transform (rotation matrix) for the first camera. + Output 3x3 rectification transform (rotation matrix) for the second camera. + Output 3x4 projection matrix in the new (rectified) coordinate systems for the first camera. + Output 3x4 projection matrix in the new (rectified) coordinate systems for the second camera. + Output 4x4 disparity-to-depth mapping matrix (see reprojectImageTo3D() ). + Operation flags that may be zero or CV_CALIB_ZERO_DISPARITY. + If the flag is set, the function makes the principal points of each camera have the same pixel coordinates in the rectified views. + And if the flag is not set, the function may still shift the images in the horizontal or vertical direction (depending on the orientation of epipolar lines) to maximize the useful image area. + Free scaling parameter. + If it is -1 or absent, the function performs the default scaling. Otherwise, the parameter should be between 0 and 1. + alpha=0 means that the rectified images are zoomed and shifted so that only valid pixels are visible (no black areas after rectification). + alpha=1 means that the rectified image is decimated and shifted so that all the pixels from the original images from the cameras are retained + in the rectified images (no source image pixels are lost). Obviously, any intermediate value yields an intermediate result between those two extreme cases. + New image resolution after rectification. The same size should be passed to initUndistortRectifyMap(). When (0,0) is passed (default), it is set to the original imageSize . + Setting it to larger value can help you preserve details in the original image, especially when there is a big radial distortion. + Optional output rectangles inside the rectified images where all the pixels are valid. If alpha=0 , the ROIs cover the whole images. + Otherwise, they are likely to be smaller. + Optional output rectangles inside the rectified images where all the pixels are valid. If alpha=0 , the ROIs cover the whole images. + Otherwise, they are likely to be smaller. + + + + computes the rectification transformation for a stereo camera from its intrinsic and extrinsic parameters + + First camera matrix. + First camera distortion parameters. + Second camera matrix. + Second camera distortion parameters. + Size of the image used for stereo calibration. + Rotation matrix between the coordinate systems of the first and the second cameras. + Translation vector between coordinate systems of the cameras. + Output 3x3 rectification transform (rotation matrix) for the first camera. + Output 3x3 rectification transform (rotation matrix) for the second camera. + Output 3x4 projection matrix in the new (rectified) coordinate systems for the first camera. + Output 3x4 projection matrix in the new (rectified) coordinate systems for the second camera. + Output 4x4 disparity-to-depth mapping matrix (see reprojectImageTo3D() ). + Operation flags that may be zero or CV_CALIB_ZERO_DISPARITY. + If the flag is set, the function makes the principal points of each camera have the same pixel coordinates in the rectified views. + And if the flag is not set, the function may still shift the images in the horizontal or vertical direction (depending on the orientation of epipolar lines) to maximize the useful image area. + Free scaling parameter. + If it is -1 or absent, the function performs the default scaling. Otherwise, the parameter should be between 0 and 1. + alpha=0 means that the rectified images are zoomed and shifted so that only valid pixels are visible (no black areas after rectification). + alpha=1 means that the rectified image is decimated and shifted so that all the pixels from the original images from the cameras are retained + in the rectified images (no source image pixels are lost). Obviously, any intermediate value yields an intermediate result between those two extreme cases. + New image resolution after rectification. The same size should be passed to initUndistortRectifyMap(). When (0,0) is passed (default), it is set to the original imageSize . + Setting it to larger value can help you preserve details in the original image, especially when there is a big radial distortion. + + + + computes the rectification transformation for a stereo camera from its intrinsic and extrinsic parameters + + First camera matrix. + First camera distortion parameters. + Second camera matrix. + Second camera distortion parameters. + Size of the image used for stereo calibration. + Rotation matrix between the coordinate systems of the first and the second cameras. + Translation vector between coordinate systems of the cameras. + Output 3x3 rectification transform (rotation matrix) for the first camera. + Output 3x3 rectification transform (rotation matrix) for the second camera. + Output 3x4 projection matrix in the new (rectified) coordinate systems for the first camera. + Output 3x4 projection matrix in the new (rectified) coordinate systems for the second camera. + Output 4x4 disparity-to-depth mapping matrix (see reprojectImageTo3D() ). + Operation flags that may be zero or CV_CALIB_ZERO_DISPARITY. + If the flag is set, the function makes the principal points of each camera have the same pixel coordinates in the rectified views. + And if the flag is not set, the function may still shift the images in the horizontal or vertical direction (depending on the orientation of epipolar lines) to maximize the useful image area. + Free scaling parameter. + If it is -1 or absent, the function performs the default scaling. Otherwise, the parameter should be between 0 and 1. + alpha=0 means that the rectified images are zoomed and shifted so that only valid pixels are visible (no black areas after rectification). + alpha=1 means that the rectified image is decimated and shifted so that all the pixels from the original images from the cameras are retained + in the rectified images (no source image pixels are lost). Obviously, any intermediate value yields an intermediate result between those two extreme cases. + New image resolution after rectification. The same size should be passed to initUndistortRectifyMap(). When (0,0) is passed (default), it is set to the original imageSize . + Setting it to larger value can help you preserve details in the original image, especially when there is a big radial distortion. + Optional output rectangles inside the rectified images where all the pixels are valid. If alpha=0 , the ROIs cover the whole images. + Otherwise, they are likely to be smaller. + Optional output rectangles inside the rectified images where all the pixels are valid. If alpha=0 , the ROIs cover the whole images. + Otherwise, they are likely to be smaller. + + + + computes the rectification transformation for an uncalibrated stereo camera (zero distortion is assumed) + + Array of feature points in the first image. + The corresponding points in the second image. + The same formats as in findFundamentalMat() are supported. + Input fundamental matrix. It can be computed from the same set + of point pairs using findFundamentalMat() . + Size of the image. + Output rectification homography matrix for the first image. + Output rectification homography matrix for the second image. + Optional threshold used to filter out the outliers. + If the parameter is greater than zero, all the point pairs that do not comply + with the epipolar geometry (that is, the points for which |points2[i]^T * F * points1[i]| > threshold ) + are rejected prior to computing the homographies. Otherwise, all the points are considered inliers. + + + + + computes the rectification transformation for an uncalibrated stereo camera (zero distortion is assumed) + + Array of feature points in the first image. + The corresponding points in the second image. + The same formats as in findFundamentalMat() are supported. + Input fundamental matrix. It can be computed from the same set + of point pairs using findFundamentalMat() . + Size of the image. + Output rectification homography matrix for the first image. + Output rectification homography matrix for the second image. + Optional threshold used to filter out the outliers. + If the parameter is greater than zero, all the point pairs that do not comply + with the epipolar geometry (that is, the points for which |points2[i]^T * F * points1[i]| > threshold ) + are rejected prior to computing the homographies. Otherwise, all the points are considered inliers. + + + + + computes the rectification transformations for 3-head camera, where all the heads are on the same line. + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Returns the new camera matrix based on the free scaling parameter. + + Input camera matrix. + Input vector of distortion coefficients (k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6]]) of 4, 5, or 8 elements. + If the array is null, the zero distortion coefficients are assumed. + Original image size. + Free scaling parameter between 0 (when all the pixels in the undistorted image are valid) + and 1 (when all the source image pixels are retained in the undistorted image). + Image size after rectification. By default,it is set to imageSize . + Optional output rectangle that outlines all-good-pixels region in the undistorted image. See roi1, roi2 description in stereoRectify() . + Optional flag that indicates whether in the new camera matrix the principal point + should be at the image center or not. By default, the principal point is chosen to best fit a + subset of the source image (determined by alpha) to the corrected image. + optimal new camera matrix + + + + Returns the new camera matrix based on the free scaling parameter. + + Input camera matrix. + Input vector of distortion coefficients (k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6]]) of 4, 5, or 8 elements. + If the array is null, the zero distortion coefficients are assumed. + Original image size. + Free scaling parameter between 0 (when all the pixels in the undistorted image are valid) + and 1 (when all the source image pixels are retained in the undistorted image). + Image size after rectification. By default,it is set to imageSize . + Optional output rectangle that outlines all-good-pixels region in the undistorted image. See roi1, roi2 description in stereoRectify() . + Optional flag that indicates whether in the new camera matrix the principal point + should be at the image center or not. By default, the principal point is chosen to best fit a + subset of the source image (determined by alpha) to the corrected image. + optimal new camera matrix + + + + converts point coordinates from normal pixel coordinates to homogeneous coordinates ((x,y)->(x,y,1)) + + Input vector of N-dimensional points. + Output vector of N+1-dimensional points. + + + + converts point coordinates from normal pixel coordinates to homogeneous coordinates ((x,y)->(x,y,1)) + + Input vector of N-dimensional points. + Output vector of N+1-dimensional points. + + + + converts point coordinates from normal pixel coordinates to homogeneous coordinates ((x,y)->(x,y,1)) + + Input vector of N-dimensional points. + Output vector of N+1-dimensional points. + + + + converts point coordinates from homogeneous to normal pixel coordinates ((x,y,z)->(x/z, y/z)) + + Input vector of N-dimensional points. + Output vector of N-1-dimensional points. + + + + converts point coordinates from homogeneous to normal pixel coordinates ((x,y,z)->(x/z, y/z)) + + Input vector of N-dimensional points. + Output vector of N-1-dimensional points. + + + + converts point coordinates from homogeneous to normal pixel coordinates ((x,y,z)->(x/z, y/z)) + + Input vector of N-dimensional points. + Output vector of N-1-dimensional points. + + + + Converts points to/from homogeneous coordinates. + + Input array or vector of 2D, 3D, or 4D points. + Output vector of 2D, 3D, or 4D points. + + + + Calculates a fundamental matrix from the corresponding points in two images. + + Array of N points from the first image. + The point coordinates should be floating-point (single or double precision). + Array of the second image points of the same size and format as points1 . + Method for computing a fundamental matrix. + Parameter used for RANSAC. + It is the maximum distance from a point to an epipolar line in pixels, beyond which the point is + considered an outlier and is not used for computing the final fundamental matrix. It can be set to + something like 1-3, depending on the accuracy of the point localization, image resolution, and the image noise. + Parameter used for the RANSAC or LMedS methods only. + It specifies a desirable level of confidence (probability) that the estimated matrix is correct. + Output array of N elements, every element of which is set to 0 for outliers and + to 1 for the other points. The array is computed only in the RANSAC and LMedS methods. For other methods, it is set to all 1’s. + fundamental matrix + + + + Calculates a fundamental matrix from the corresponding points in two images. + + Array of N points from the first image. + The point coordinates should be floating-point (single or double precision). + Array of the second image points of the same size and format as points1 . + Method for computing a fundamental matrix. + Parameter used for RANSAC. + It is the maximum distance from a point to an epipolar line in pixels, beyond which the point is + considered an outlier and is not used for computing the final fundamental matrix. It can be set to + something like 1-3, depending on the accuracy of the point localization, image resolution, and the image noise. + Parameter used for the RANSAC or LMedS methods only. + It specifies a desirable level of confidence (probability) that the estimated matrix is correct. + Output array of N elements, every element of which is set to 0 for outliers and + to 1 for the other points. The array is computed only in the RANSAC and LMedS methods. For other methods, it is set to all 1’s. + fundamental matrix + + + + For points in an image of a stereo pair, computes the corresponding epilines in the other image. + + Input points. N \times 1 or 1 x N matrix of type CV_32FC2 or CV_64FC2. + Index of the image (1 or 2) that contains the points . + Fundamental matrix that can be estimated using findFundamentalMat() or stereoRectify() . + Output vector of the epipolar lines corresponding to the points in the other image. + Each line ax + by + c=0 is encoded by 3 numbers (a, b, c) . + + + + For points in an image of a stereo pair, computes the corresponding epilines in the other image. + + Input points. N \times 1 or 1 x N matrix of type CV_32FC2 or CV_64FC2. + Index of the image (1 or 2) that contains the points . + Fundamental matrix that can be estimated using findFundamentalMat() or stereoRectify() . + Output vector of the epipolar lines corresponding to the points in the other image. + Each line ax + by + c=0 is encoded by 3 numbers (a, b, c) . + + + + For points in an image of a stereo pair, computes the corresponding epilines in the other image. + + Input points. N \times 1 or 1 x N matrix of type CV_32FC2 or CV_64FC2. + Index of the image (1 or 2) that contains the points . + Fundamental matrix that can be estimated using findFundamentalMat() or stereoRectify() . + Output vector of the epipolar lines corresponding to the points in the other image. + Each line ax + by + c=0 is encoded by 3 numbers (a, b, c) . + + + + Reconstructs points by triangulation. + + 3x4 projection matrix of the first camera. + 3x4 projection matrix of the second camera. + 2xN array of feature points in the first image. In case of c++ version + it can be also a vector of feature points or two-channel matrix of size 1xN or Nx1. + 2xN array of corresponding points in the second image. In case of c++ version + it can be also a vector of feature points or two-channel matrix of size 1xN or Nx1. + 4xN array of reconstructed points in homogeneous coordinates. + + + + Reconstructs points by triangulation. + + 3x4 projection matrix of the first camera. + 3x4 projection matrix of the second camera. + 2xN array of feature points in the first image. In case of c++ version + it can be also a vector of feature points or two-channel matrix of size 1xN or Nx1. + 2xN array of corresponding points in the second image. In case of c++ version + it can be also a vector of feature points or two-channel matrix of size 1xN or Nx1. + 4xN array of reconstructed points in homogeneous coordinates. + + + + Refines coordinates of corresponding points. + + 3x3 fundamental matrix. + 1xN array containing the first set of points. + 1xN array containing the second set of points. + The optimized points1. + The optimized points2. + + + + Refines coordinates of corresponding points. + + 3x3 fundamental matrix. + 1xN array containing the first set of points. + 1xN array containing the second set of points. + The optimized points1. + The optimized points2. + + + + filters off speckles (small regions of incorrectly computed disparity) + + The input 16-bit signed disparity image + The disparity value used to paint-off the speckles + The maximum speckle size to consider it a speckle. Larger blobs are not affected by the algorithm + Maximum difference between neighbor disparity pixels to put them into the same blob. + Note that since StereoBM, StereoSGBM and may be other algorithms return a fixed-point disparity map, where disparity values + are multiplied by 16, this scale factor should be taken into account when specifying this parameter value. + The optional temporary buffer to avoid memory allocation within the function. + + + + computes valid disparity ROI from the valid ROIs of the rectified images (that are returned by cv::stereoRectify()) + + + + + + + + + + + validates disparity using the left-right check. The matrix "cost" should be computed by the stereo correspondence algorithm + + + + + + + + + + reprojects disparity image to 3D: (x,y,d)->(X,Y,Z) using the matrix Q returned by cv::stereoRectify + + Input single-channel 8-bit unsigned, 16-bit signed, 32-bit signed or 32-bit floating-point disparity image. + Output 3-channel floating-point image of the same size as disparity. + Each element of _3dImage(x,y) contains 3D coordinates of the point (x,y) computed from the disparity map. + 4 x 4 perspective transformation matrix that can be obtained with stereoRectify(). + Indicates, whether the function should handle missing values (i.e. points where the disparity was not computed). + If handleMissingValues=true, then pixels with the minimal disparity that corresponds to the outliers (see StereoBM::operator() ) are + transformed to 3D points with a very large Z value (currently set to 10000). + he optional output array depth. If it is -1, the output image will have CV_32F depth. + ddepth can also be set to CV_16S, CV_32S or CV_32F. + + + + Computes an optimal affine transformation between two 3D point sets. + + First input 3D point set. + Second input 3D point set. + Output 3D affine transformation matrix 3 x 4 . + Output vector indicating which points are inliers. + Maximum reprojection error in the RANSAC algorithm to consider a point as an inlier. + Confidence level, between 0 and 1, for the estimated transformation. + Anything between 0.95 and 0.99 is usually good enough. Values too close to 1 can slow down the estimation significantly. + Values lower than 0.8-0.9 can result in an incorrectly estimated transformation. + + + + + Creates a window. + + Name of the window in the window caption that may be used as a window identifier. + + + + Creates a window. + + Name of the window in the window caption that may be used as a window identifier. + + Flags of the window. Currently the only supported flag is CV WINDOW AUTOSIZE. If this is set, + the window size is automatically adjusted to fit the displayed image (see imshow ), and the user can not change the window size manually. + + + + + + + + + + + + + + + + Displays the image in the specified window + + Name of the window. + Image to be shown. + + + + Loads an image from a file. + + Name of file to be loaded. + Specifies color type of the loaded image + + + + + Saves an image to a specified file. + + + + + + + + + Saves an image to a specified file. + + + + + + + + + Reads image from the specified buffer in memory. + + The input array of vector of bytes. + The same flags as in imread + + + + + Reads image from the specified buffer in memory. + + The input array of vector of bytes. + The same flags as in imread + + + + + Compresses the image and stores it in the memory buffer + + The file extension that defines the output format + The image to be written + + + + + + Compresses the image and stores it in the memory buffer + + The file extension that defines the output format + The image to be written + + + + + + + + + + + + Waits for a pressed key. + + Delay in milliseconds. 0 is the special value that means ”forever” + Returns the code of the pressed key or -1 if no key was pressed before the specified time had elapsed. + + + + Resizes window to the specified size + + Window name + The new window width + The new window height + + + + Moves window to the specified position + + Window name + The new x-coordinate of the window + The new y-coordinate of the window + + + + Changes parameters of a window dynamically. + + Name of the window. + Window property to retrieve. + New value of the window property. + + + + Changes parameters of a window dynamically. + + Name of the window. + Window property to retrieve. + New value of the window property. + + + + Provides parameters of a window. + + Name of the window. + Window property to retrieve. + + + + + Sets the callback function for mouse events occuting within the specified window. + + Name of the window. + Reference to the function to be called every time mouse event occurs in the specified window. + + + + utility function: convert one image to another with optional vertical flip + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Turns on/off available optimization. + The function turns on or off the optimized code in OpenCV. Some optimization can not be enabled + or disabled, but, for example, most of SSE code in OpenCV can be temporarily turned on or off this way. + + + + + + Returns the current optimization status. + The function returns the current optimization status, which is controlled by cv::setUseOptimized(). + + + + + + Aligns buffer size by the certain number of bytes + This small inline function aligns a buffer size by + the certian number of bytes by enlarging it. + + + + + + + + + + + + + + + + + + Extract the selected image channel + + The source array. It should be a pointer to CvMat or IplImage + The destination array; will have single-channel, and the same size and the same depth as src + If the parameter is >=0, it specifies the channel to extract; + If it is <0, src must be a pointer to IplImage with valid COI set - then the selected COI is extracted. [By default this is -1] + + + + + + + + [By default this is -1] + + + + Computes absolute value of each matrix element + + matrix + + + + + Computes absolute value of each matrix element + + matrix expression + + + + + Computes the per-element sum of two arrays or an array and a scalar. + + The first source array + The second source array. It must have the same size and same type as src1 + The destination array; it will have the same size and same type as src1 + The optional operation mask, 8-bit single channel array; specifies elements of the destination array to be changed. [By default this is null] + + + + + Calculates per-element difference between two arrays or array and a scalar + + The first source array + The second source array. It must have the same size and same type as src1 + The destination array; it will have the same size and same type as src1 + The optional operation mask, 8-bit single channel array; specifies elements of the destination array to be changed. [By default this is null] + + + + + Calculates the per-element scaled product of two arrays + + The first source array + The second source array of the same size and the same type as src1 + The destination array; will have the same size and the same type as src1 + The optional scale factor. [By default this is 1] + + + + + Performs per-element division of two arrays or a scalar by an array. + + The first source array + The second source array; should have the same size and same type as src1 + The destination array; will have the same size and same type as src2 + Scale factor [By default this is 1] + + + + + Performs per-element division of two arrays or a scalar by an array. + + Scale factor + The first source array + The destination array; will have the same size and same type as src2 + + + + + adds scaled array to another one (dst = alpha*src1 + src2) + + + + + + + + + computes weighted sum of two arrays (dst = alpha*src1 + beta*src2 + gamma) + + + + + + + + + + + + Scales, computes absolute values and converts the result to 8-bit. + + The source array + The destination array + The optional scale factor. [By default this is 1] + The optional delta added to the scaled values. [By default this is 0] + + + + transforms array of numbers using a lookup table: dst(i)=lut(src(i)) + + Source array of 8-bit elements + Look-up table of 256 elements. + In the case of multi-channel source array, the table should either have + a single channel (in this case the same table is used for all channels) + or the same number of channels as in the source array + Destination array; + will have the same size and the same number of channels as src, + and the same depth as lut + + + + + transforms array of numbers using a lookup table: dst(i)=lut(src(i)) + + Source array of 8-bit elements + Look-up table of 256 elements. + In the case of multi-channel source array, the table should either have + a single channel (in this case the same table is used for all channels) + or the same number of channels as in the source array + Destination array; + will have the same size and the same number of channels as src, + and the same depth as lut + + + + + computes sum of array elements + + The source array; must have 1 to 4 channels + + + + + computes the number of nonzero array elements + + Single-channel array + number of non-zero elements in mtx + + + + returns the list of locations of non-zero pixels + + + + + + + computes mean value of selected array elements + + The source array; it should have 1 to 4 channels + (so that the result can be stored in Scalar) + The optional operation mask + + + + + computes mean value and standard deviation of all or selected array elements + + The source array; it should have 1 to 4 channels + (so that the results can be stored in Scalar's) + The output parameter: computed mean value + The output parameter: computed standard deviation + The optional operation mask + + + + computes mean value and standard deviation of all or selected array elements + + The source array; it should have 1 to 4 channels + (so that the results can be stored in Scalar's) + The output parameter: computed mean value + The output parameter: computed standard deviation + The optional operation mask + + + + Calculates absolute array norm, absolute difference norm, or relative difference norm. + + The first source array + Type of the norm + The optional operation mask + + + + + computes norm of selected part of the difference between two arrays + + The first source array + The second source array of the same size and the same type as src1 + Type of the norm + The optional operation mask + + + + + naive nearest neighbor finder + + + + + + + + + + + + + + + scales and shifts array elements so that either the specified norm (alpha) + or the minimum (alpha) and maximum (beta) array values get the specified values + + The source array + The destination array; will have the same size as src + The norm value to normalize to or the lower range boundary + in the case of range normalization + The upper range boundary in the case of range normalization; + not used for norm normalization + The normalization type + When the parameter is negative, + the destination array will have the same type as src, + otherwise it will have the same number of channels as src and the depth =CV_MAT_DEPTH(rtype) + The optional operation mask + + + + finds global minimum and maximum array elements and returns their values and their locations + + The source single-channel array + Pointer to returned minimum value + Pointer to returned maximum value + + + + finds global minimum and maximum array elements and returns their values and their locations + + The source single-channel array + Pointer to returned minimum location + Pointer to returned maximum location + + + + finds global minimum and maximum array elements and returns their values and their locations + + The source single-channel array + Pointer to returned minimum value + Pointer to returned maximum value + Pointer to returned minimum location + Pointer to returned maximum location + The optional mask used to select a sub-array + + + + finds global minimum and maximum array elements and returns their values and their locations + + The source single-channel array + Pointer to returned minimum value + Pointer to returned maximum value + + + + finds global minimum and maximum array elements and returns their values and their locations + + The source single-channel array + + + + + + finds global minimum and maximum array elements and returns their values and their locations + + The source single-channel array + Pointer to returned minimum value + Pointer to returned maximum value + + + + + + + transforms 2D matrix to 1D row or column vector by taking sum, minimum, maximum or mean value over all the rows + + The source 2D matrix + The destination vector. + Its size and type is defined by dim and dtype parameters + The dimension index along which the matrix is reduced. + 0 means that the matrix is reduced to a single row and 1 means that the matrix is reduced to a single column + + When it is negative, the destination vector will have + the same type as the source matrix, otherwise, its type will be CV_MAKE_TYPE(CV_MAT_DEPTH(dtype), mtx.channels()) + + + + makes multi-channel array out of several single-channel arrays + + + + + + + Copies each plane of a multi-channel array to a dedicated array + + The source multi-channel array + The destination array or vector of arrays; + The number of arrays must match mtx.channels() . + The arrays themselves will be reallocated if needed + + + + Copies each plane of a multi-channel array to a dedicated array + + The source multi-channel array + The number of arrays must match mtx.channels() . + The arrays themselves will be reallocated if needed + + + + copies selected channels from the input arrays to the selected channels of the output arrays + + + + + + + + extracts a single channel from src (coi is 0-based index) + + + + + + + + inserts a single channel to dst (coi is 0-based index) + + + + + + + + reverses the order of the rows, columns or both in a matrix + + The source array + The destination array; will have the same size and same type as src + Specifies how to flip the array: + 0 means flipping around the x-axis, positive (e.g., 1) means flipping around y-axis, + and negative (e.g., -1) means flipping around both axes. See also the discussion below for the formulas. + + + + replicates the input matrix the specified number of times in the horizontal and/or vertical direction + + The source array to replicate + How many times the src is repeated along the vertical axis + How many times the src is repeated along the horizontal axis + The destination array; will have the same type as src + + + + replicates the input matrix the specified number of times in the horizontal and/or vertical direction + + The source array to replicate + How many times the src is repeated along the vertical axis + How many times the src is repeated along the horizontal axis + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + computes bitwise conjunction of the two arrays (dst = src1 & src2) + + + + + + + + + computes bitwise disjunction of the two arrays (dst = src1 | src2) + + + + + + + + + computes bitwise exclusive-or of the two arrays (dst = src1 ^ src2) + + + + + + + + + inverts each bit of array (dst = ~src) + + + + + + + + computes element-wise absolute difference of two arrays (dst = abs(src1 - src2)) + + + + + + + + set mask elements for those array elements which are within the element-specific bounding box (dst = lowerb <= src && src < upperb) + + The first source array + The inclusive lower boundary array of the same size and type as src + The exclusive upper boundary array of the same size and type as src + The destination array, will have the same size as src and CV_8U type + + + + set mask elements for those array elements which are within the element-specific bounding box (dst = lowerb <= src && src < upperb) + + The first source array + The inclusive lower boundary array of the same size and type as src + The exclusive upper boundary array of the same size and type as src + The destination array, will have the same size as src and CV_8U type + + + + compares elements of two arrays (dst = src1 [cmpop] src2) + + + + + + + + + computes per-element minimum of two arrays (dst = min(src1, src2)) + + + + + + + + computes per-element minimum of two arrays (dst = min(src1, src2)) + + + + + + + + computes per-element minimum of array and scalar (dst = min(src1, src2)) + + + + + + + + computes per-element maximum of two arrays (dst = max(src1, src2)) + + + + + + + + computes per-element maximum of two arrays (dst = max(src1, src2)) + + + + + + + + computes per-element maximum of array and scalar (dst = max(src1, src2)) + + + + + + + + computes square root of each matrix element (dst = src**0.5) + + The source floating-point array + The destination array; will have the same size and the same type as src + + + + raises the input matrix elements to the specified power (b = a**power) + + The source array + The exponent of power + The destination array; will have the same size and the same type as src + + + + computes exponent of each matrix element (dst = e**src) + + The source array + The destination array; will have the same size and same type as src + + + + + + The source array + + + + + computes natural logarithm of absolute value of each matrix element: dst = log(abs(src)) + + The source array + The destination array; will have the same size and same type as src + + + + + + The source array + + + + + computes cube root of the argument + + + + + + + computes the angle in degrees (0..360) of the vector (x,y) + + + + + + + + + + + + + + + + + converts polar coordinates to Cartesian + + + + + + + + + + converts Cartesian coordinates to polar + + + + + + + + + + computes angle (angle(i)) of each (x(i), y(i)) vector + + + + + + + + + computes magnitude (magnitude(i)) of each (x(i), y(i)) vector + + + + + + + + + + + + + + + + checks that each matrix element is within the specified range. + + The array to check + The flag indicating whether the functions quietly + return false when the array elements are out of range, + or they throw an exception. + + + + + checks that each matrix element is within the specified range. + + The array to check + The flag indicating whether the functions quietly + return false when the array elements are out of range, + or they throw an exception. + The optional output parameter, where the position of + the first outlier is stored. + The inclusive lower boundary of valid values range + The exclusive upper boundary of valid values range + + + + + converts NaN's to the given number + + + + + + + implements generalized matrix product algorithm GEMM from BLAS + + + + + + + + + + + + multiplies matrix by its transposition from the left or from the right + + The source matrix + The destination square matrix + Specifies the multiplication ordering; see the description below + The optional delta matrix, subtracted from src before the + multiplication. When the matrix is empty ( delta=Mat() ), it’s assumed to be + zero, i.e. nothing is subtracted, otherwise if it has the same size as src, + then it’s simply subtracted, otherwise it is "repeated" to cover the full src + and then subtracted. Type of the delta matrix, when it's not empty, must be the + same as the type of created destination matrix, see the rtype description + The optional scale factor for the matrix product + When it’s negative, the destination matrix will have the + same type as src . Otherwise, it will have type=CV_MAT_DEPTH(rtype), + which should be either CV_32F or CV_64F + + + + transposes the matrix + + The source array + The destination array of the same type as src + + + + performs affine transformation of each element of multi-channel input matrix + + The source array; must have as many channels (1 to 4) as mtx.cols or mtx.cols-1 + The destination array; will have the same size and depth as src and as many channels as mtx.rows + The transformation matrix + + + + performs perspective transformation of each element of multi-channel input matrix + + The source two-channel or three-channel floating-point array; + each element is 2D/3D vector to be transformed + The destination array; it will have the same size and same type as src + 3x3 or 4x4 transformation matrix + + + + performs perspective transformation of each element of multi-channel input matrix + + The source two-channel or three-channel floating-point array; + each element is 2D/3D vector to be transformed + 3x3 or 4x4 transformation matrix + The destination array; it will have the same size and same type as src + + + + performs perspective transformation of each element of multi-channel input matrix + + The source two-channel or three-channel floating-point array; + each element is 2D/3D vector to be transformed + 3x3 or 4x4 transformation matrix + The destination array; it will have the same size and same type as src + + + + performs perspective transformation of each element of multi-channel input matrix + + The source two-channel or three-channel floating-point array; + each element is 2D/3D vector to be transformed + 3x3 or 4x4 transformation matrix + The destination array; it will have the same size and same type as src + + + + performs perspective transformation of each element of multi-channel input matrix + + The source two-channel or three-channel floating-point array; + each element is 2D/3D vector to be transformed + 3x3 or 4x4 transformation matrix + The destination array; it will have the same size and same type as src + + + + extends the symmetrical matrix from the lower half or from the upper half + + Input-output floating-point square matrix + If true, the lower half is copied to the upper half, + otherwise the upper half is copied to the lower half + + + + initializes scaled identity matrix + + The matrix to initialize (not necessarily square) + The value to assign to the diagonal elements + + + + computes determinant of a square matrix + + The input matrix; must have CV_32FC1 or CV_64FC1 type and square size + determinant of the specified matrix. + + + + computes trace of a matrix + + The source matrix + + + + + computes inverse or pseudo-inverse matrix + + The source floating-point MxN matrix + The destination matrix; will have NxM size and the same type as src + The inversion method + + + + + solves linear system or a least-square problem + + + + + + + + + + sorts independently each matrix row or each matrix column + + The source single-channel array + The destination array of the same size and the same type as src + The operation flags, a combination of the SortFlag values + + + + sorts independently each matrix row or each matrix column + + The source single-channel array + The destination integer array of the same size as src + The operation flags, a combination of SortFlag values + + + + finds real roots of a cubic polynomial + + The equation coefficients, an array of 3 or 4 elements + The destination array of real roots which will have 1 or 3 elements + + + + + finds real and complex roots of a polynomial + + The array of polynomial coefficients + The destination (complex) array of roots + The maximum number of iterations the algorithm does + + + + + Computes eigenvalues of a symmetric matrix. + + The input matrix; must have CV_32FC1 or CV_64FC1 type, + square size and be symmetric: src^T == src + The output vector of eigenvalues of the same type as src; + The eigenvalues are stored in the descending order. + Optional index of largest eigenvalue/-vector to calculate. + Optional index of smallest eigenvalue/-vector to calculate. + + + + + Computes eigenvalues and eigenvectors of a symmetric matrix. + + The input matrix; must have CV_32FC1 or CV_64FC1 type, + square size and be symmetric: src^T == src + The output vector of eigenvalues of the same type as src; + The eigenvalues are stored in the descending order. + The output matrix of eigenvectors; + It will have the same size and the same type as src; The eigenvectors are stored + as subsequent matrix rows, in the same order as the corresponding eigenvalues + Optional index of largest eigenvalue/-vector to calculate. + Optional index of smallest eigenvalue/-vector to calculate. + + + + + Computes eigenvalues and eigenvectors of a symmetric matrix. + + The input matrix; must have CV_32FC1 or CV_64FC1 type, + square size and be symmetric: src^T == src + + The output vector of eigenvalues of the same type as src; + The eigenvalues are stored in the descending order. + The output matrix of eigenvectors; + It will have the same size and the same type as src; The eigenvectors are stored + as subsequent matrix rows, in the same order as the corresponding eigenvalues + + + + + computes covariation matrix of a set of samples + + + + + + + + + computes covariation matrix of a set of samples + + + + + + + + + + computes covariation matrix of a set of samples + + + + + + + + + computes covariation matrix of a set of samples + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + computes SVD of src + + + + + + + + + + performs back substitution for the previously computed SVD + + + + + + + + + + + + + + + + + + + computes Mahalanobis distance between two vectors: sqrt((v1-v2)'*icovar*(v1-v2)), where icovar is the inverse covariation matrix + + + + + + + + + Performs a forward Discrete Fourier transform of 1D or 2D floating-point array. + + The source array, real or complex + The destination array, which size and type depends on the flags + Transformation flags, a combination of the DftFlag2 values + When the parameter != 0, the function assumes that + only the first nonzeroRows rows of the input array ( DFT_INVERSE is not set) + or only the first nonzeroRows of the output array ( DFT_INVERSE is set) contain non-zeros, + thus the function can handle the rest of the rows more efficiently and + thus save some time. This technique is very useful for computing array cross-correlation + or convolution using DFT + + + + Performs an inverse Discrete Fourier transform of 1D or 2D floating-point array. + + The source array, real or complex + The destination array, which size and type depends on the flags + Transformation flags, a combination of the DftFlag2 values + When the parameter != 0, the function assumes that + only the first nonzeroRows rows of the input array ( DFT_INVERSE is not set) + or only the first nonzeroRows of the output array ( DFT_INVERSE is set) contain non-zeros, + thus the function can handle the rest of the rows more efficiently and + thus save some time. This technique is very useful for computing array cross-correlation + or convolution using DFT + + + + Performs forward or inverse 1D or 2D Discrete Cosine Transformation + + The source floating-point array + The destination array; will have the same size and same type as src + Transformation flags, a combination of DctFlag2 values + + + + Performs inverse 1D or 2D Discrete Cosine Transformation + + The source floating-point array + The destination array; will have the same size and same type as src + Transformation flags, a combination of DctFlag2 values + + + + computes element-wise product of the two Fourier spectrums. The second spectrum can optionally be conjugated before the multiplication + + + + + + + + + + computes the minimal vector size vecsize1 >= vecsize so that the dft() of the vector of length vecsize1 can be computed efficiently + + + + + + + clusters the input data using k-Means algorithm + + + + + + + + + + + + + returns the thread-local Random number generator + + + + + + fills array with uniformly-distributed random numbers from the range [low, high) + + The output array of random numbers. + The array must be pre-allocated and have 1 to 4 channels + The inclusive lower boundary of the generated random numbers + The exclusive upper boundary of the generated random numbers + + + + fills array with uniformly-distributed random numbers from the range [low, high) + + The output array of random numbers. + The array must be pre-allocated and have 1 to 4 channels + The inclusive lower boundary of the generated random numbers + The exclusive upper boundary of the generated random numbers + + + + fills array with normally-distributed random numbers with the specified mean and the standard deviation + + The output array of random numbers. + The array must be pre-allocated and have 1 to 4 channels + The mean value (expectation) of the generated random numbers + The standard deviation of the generated random numbers + + + + fills array with normally-distributed random numbers with the specified mean and the standard deviation + + The output array of random numbers. + The array must be pre-allocated and have 1 to 4 channels + The mean value (expectation) of the generated random numbers + The standard deviation of the generated random numbers + + + + shuffles the input array elements + + The input/output numerical 1D array + The scale factor that determines the number of random swap operations. + The optional random number generator used for shuffling. + If it is null, theRng() is used instead. + + + + Draws a line segment connecting two points + + The image. + First point's x-coordinate of the line segment. + First point's y-coordinate of the line segment. + Second point's x-coordinate of the line segment. + Second point's y-coordinate of the line segment. + Line color. + Line thickness. [By default this is 1] + Type of the line. [By default this is LineType.Link8] + Number of fractional bits in the point coordinates. [By default this is 0] + + + + Draws a line segment connecting two points + + The image. + First point of the line segment. + Second point of the line segment. + Line color. + Line thickness. [By default this is 1] + Type of the line. [By default this is LineType.Link8] + Number of fractional bits in the point coordinates. [By default this is 0] + + + + Draws simple, thick or filled rectangle + + Image. + One of the rectangle vertices. + Opposite rectangle vertex. + Line color (RGB) or brightness (grayscale image). + Thickness of lines that make up the rectangle. Negative values make the function to draw a filled rectangle. [By default this is 1] + Type of the line, see cvLine description. [By default this is LineType.Link8] + Number of fractional bits in the point coordinates. [By default this is 0] + + + + Draws simple, thick or filled rectangle + + Image. + Rectangle. + Line color (RGB) or brightness (grayscale image). + Thickness of lines that make up the rectangle. Negative values make the function to draw a filled rectangle. [By default this is 1] + Type of the line, see cvLine description. [By default this is LineType.Link8] + Number of fractional bits in the point coordinates. [By default this is 0] + + + + Draws a circle + + Image where the circle is drawn. + X-coordinate of the center of the circle. + Y-coordinate of the center of the circle. + Radius of the circle. + Circle color. + Thickness of the circle outline if positive, otherwise indicates that a filled circle has to be drawn. [By default this is 1] + Type of the circle boundary. [By default this is LineType.Link8] + Number of fractional bits in the center coordinates and radius value. [By default this is 0] + + + + Draws a circle + + Image where the circle is drawn. + Center of the circle. + Radius of the circle. + Circle color. + Thickness of the circle outline if positive, otherwise indicates that a filled circle has to be drawn. [By default this is 1] + Type of the circle boundary. [By default this is LineType.Link8] + Number of fractional bits in the center coordinates and radius value. [By default this is 0] + + + + Draws simple or thick elliptic arc or fills ellipse sector + + Image. + Center of the ellipse. + Length of the ellipse axes. + Rotation angle. + Starting angle of the elliptic arc. + Ending angle of the elliptic arc. + Ellipse color. + Thickness of the ellipse arc. [By default this is 1] + Type of the ellipse boundary. [By default this is LineType.Link8] + Number of fractional bits in the center coordinates and axes' values. [By default this is 0] + + + + Draws simple or thick elliptic arc or fills ellipse sector + + Image. + The enclosing box of the ellipse drawn + Ellipse color. + Thickness of the ellipse boundary. [By default this is 1] + Type of the ellipse boundary. [By default this is LineType.Link8] + + + + Fills a convex polygon. + + Image + The polygon vertices + Polygon color + Type of the polygon boundaries + The number of fractional bits in the vertex coordinates + + + + Fills the area bounded by one or more polygons + + Image + Array of polygons, each represented as an array of points + Polygon color + Type of the polygon boundaries + The number of fractional bits in the vertex coordinates + + + + + draws one or more polygonal curves + + + + + + + + + + + + Clips the line against the image rectangle + + The image size + The first line point + The second line point + + + + + Clips the line against the image rectangle + + sThe image rectangle + The first line point + The second line point + + + + + renders text string in the image + + + + + + + + + + + + + + returns bounding box of the text string + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Forms a border around the image + + The source image + The destination image; will have the same type as src and + the size Size(src.cols+left+right, src.rows+top+bottom) + Specify how much pixels in each direction from the source image rectangle one needs to extrapolate + Specify how much pixels in each direction from the source image rectangle one needs to extrapolate + Specify how much pixels in each direction from the source image rectangle one needs to extrapolate + Specify how much pixels in each direction from the source image rectangle one needs to extrapolate + The border type + The border value if borderType == Constant + + + + Smoothes image using median filter + + The source 1-, 3- or 4-channel image. + When ksize is 3 or 5, the image depth should be CV_8U , CV_16U or CV_32F. + For larger aperture sizes it can only be CV_8U + The destination array; will have the same size and the same type as src + The aperture linear size. It must be odd and more than 1, i.e. 3, 5, 7 ... + + + + Blurs an image using a Gaussian filter. + + input image; the image can have any number of channels, which are processed independently, + but the depth should be CV_8U, CV_16U, CV_16S, CV_32F or CV_64F. + output image of the same size and type as src. + Gaussian kernel size. ksize.width and ksize.height can differ but they both must be positive and odd. + Or, they can be zero’s and then they are computed from sigma* . + Gaussian kernel standard deviation in X direction. + Gaussian kernel standard deviation in Y direction; if sigmaY is zero, it is set to be equal to sigmaX, + if both sigmas are zeros, they are computed from ksize.width and ksize.height, + respectively (see getGaussianKernel() for details); to fully control the result + regardless of possible future modifications of all this semantics, it is recommended to specify all of ksize, sigmaX, and sigmaY. + pixel extrapolation method + + + + Applies bilateral filter to the image + + The source 8-bit or floating-point, 1-channel or 3-channel image + The destination image; will have the same size and the same type as src + The diameter of each pixel neighborhood, that is used during filtering. + If it is non-positive, it's computed from sigmaSpace + Filter sigma in the color space. + Larger value of the parameter means that farther colors within the pixel neighborhood + will be mixed together, resulting in larger areas of semi-equal color + Filter sigma in the coordinate space. + Larger value of the parameter means that farther pixels will influence each other + (as long as their colors are close enough; see sigmaColor). Then d>0 , it specifies + the neighborhood size regardless of sigmaSpace, otherwise d is proportional to sigmaSpace + + + + + Applies the adaptive bilateral filter to an image. + + The source image + The destination image; will have the same size and the same type as src + The kernel size. This is the neighborhood where the local variance will be calculated, + and where pixels will contribute (in a weighted manner). + Filter sigma in the coordinate space. + Larger value of the parameter means that farther pixels will influence each other + (as long as their colors are close enough; see sigmaColor). Then d>0, it specifies the neighborhood + size regardless of sigmaSpace, otherwise d is proportional to sigmaSpace. + Maximum allowed sigma color (will clamp the value calculated in the + ksize neighborhood. Larger value of the parameter means that more dissimilar pixels will + influence each other (as long as their colors are close enough; see sigmaColor). + Then d>0, it specifies the neighborhood size regardless of sigmaSpace, otherwise d is proportional to sigmaSpace. + The anchor point. The default value Point(-1,-1) means that the anchor is at the kernel center + Pixel extrapolation method. + + + + Smoothes image using box filter + + The source image + The destination image; will have the same size and the same type as src + + The smoothing kernel size + The anchor point. The default value Point(-1,-1) means that the anchor is at the kernel center + Indicates, whether the kernel is normalized by its area or not + The border mode used to extrapolate pixels outside of the image + + + + Smoothes image using normalized box filter + + The source image + The destination image; will have the same size and the same type as src + The smoothing kernel size + The anchor point. The default value Point(-1,-1) means that the anchor is at the kernel center + The border mode used to extrapolate pixels outside of the image + + + + Convolves an image with the kernel + + The source image + The destination image. It will have the same size and the same number of channels as src + The desired depth of the destination image. If it is negative, it will be the same as src.depth() + Convolution kernel (or rather a correlation kernel), + a single-channel floating point matrix. If you want to apply different kernels to + different channels, split the image into separate color planes using split() and process them individually + The anchor of the kernel that indicates the relative position of + a filtered point within the kernel. The anchor should lie within the kernel. + The special default value (-1,-1) means that the anchor is at the kernel center + The optional value added to the filtered pixels before storing them in dst + The pixel extrapolation method + + + + Applies separable linear filter to an image + + The source image + The destination image; will have the same size and the same number of channels as src + The destination image depth + The coefficients for filtering each row + The coefficients for filtering each column + The anchor position within the kernel; The default value (-1, 1) means that the anchor is at the kernel center + The value added to the filtered results before storing them + The pixel extrapolation method + + + + Calculates the first, second, third or mixed image derivatives using an extended Sobel operator + + The source image + The destination image; will have the same size and the same number of channels as src + The destination image depth + Order of the derivative x + Order of the derivative y + Size of the extended Sobel kernel, must be 1, 3, 5 or 7 + The optional scale factor for the computed derivative values (by default, no scaling is applied + The optional delta value, added to the results prior to storing them in dst + The pixel extrapolation method + + + + Calculates the first x- or y- image derivative using Scharr operator + + The source image + The destination image; will have the same size and the same number of channels as src + The destination image depth + Order of the derivative x + Order of the derivative y + The optional scale factor for the computed derivative values (by default, no scaling is applie + The optional delta value, added to the results prior to storing them in dst + The pixel extrapolation method + + + + Calculates the Laplacian of an image + + Source image + Destination image; will have the same size and the same number of channels as src + The desired depth of the destination image + The aperture size used to compute the second-derivative filters + The optional scale factor for the computed Laplacian values (by default, no scaling is applied + The optional delta value, added to the results prior to storing them in dst + The pixel extrapolation method + + + + Finds edges in an image using Canny algorithm. + + Single-channel 8-bit input image + The output edge map. It will have the same size and the same type as image + The first threshold for the hysteresis procedure + The second threshold for the hysteresis procedure + Aperture size for the Sobel operator [By default this is ApertureSize.Size3] + Indicates, whether the more accurate L2 norm should be used to compute the image gradient magnitude (true), or a faster default L1 norm is enough (false). [By default this is false] + + + + + + + + + + + + computes both eigenvalues and the eigenvectors of 2x2 derivative covariation matrix at each pixel. The output is stored as 6-channel matrix. + + + + + + + + + + computes another complex cornerness criteria at each pixel + + + + + + + + + adjusts the corner locations with sub-pixel accuracy to maximize the certain cornerness criteria + + Input image. + Initial coordinates of the input corners and refined coordinates provided for output. + Half of the side length of the search window. + Half of the size of the dead region in the middle of the search zone + over which the summation in the formula below is not done. It is used sometimes to avoid possible singularities + of the autocorrelation matrix. The value of (-1,-1) indicates that there is no such a size. + Criteria for termination of the iterative process of corner refinement. + That is, the process of corner position refinement stops either after criteria.maxCount iterations + or when the corner position moves by less than criteria.epsilon on some iteration. + + + + + finds the strong enough corners where the cornerMinEigenVal() or cornerHarris() report the local maxima + + Input 8-bit or floating-point 32-bit, single-channel image. + Maximum number of corners to return. If there are more corners than are found, + the strongest of them is returned. + Parameter characterizing the minimal accepted quality of image corners. + The parameter value is multiplied by the best corner quality measure, which is the minimal eigenvalue + or the Harris function response (see cornerHarris() ). The corners with the quality measure less than + the product are rejected. For example, if the best corner has the quality measure = 1500, and the qualityLevel=0.01, + then all the corners with the quality measure less than 15 are rejected. + Minimum possible Euclidean distance between the returned corners. + Optional region of interest. If the image is not empty + (it needs to have the type CV_8UC1 and the same size as image ), it specifies the region + in which the corners are detected. + Size of an average block for computing a derivative covariation matrix over each pixel neighborhood. + Parameter indicating whether to use a Harris detector + Free parameter of the Harris detector. + Output vector of detected corners. + + + + Finds lines in a binary image using standard Hough transform. + + The 8-bit, single-channel, binary source image. The image may be modified by the function + Distance resolution of the accumulator in pixels + Angle resolution of the accumulator in radians + The accumulator threshold parameter. Only those lines are returned that get enough votes ( > threshold ) + For the multi-scale Hough transform it is the divisor for the distance resolution rho. [By default this is 0] + For the multi-scale Hough transform it is the divisor for the distance resolution theta. [By default this is 0] + The output vector of lines. Each line is represented by a two-element vector (rho, theta) . + rho is the distance from the coordinate origin (0,0) (top-left corner of the image) and theta is the line rotation angle in radians + + + + Finds lines segments in a binary image using probabilistic Hough transform. + + + Distance resolution of the accumulator in pixels + Angle resolution of the accumulator in radians + The accumulator threshold parameter. Only those lines are returned that get enough votes ( > threshold ) + The minimum line length. Line segments shorter than that will be rejected. [By default this is 0] + The maximum allowed gap between points on the same line to link them. [By default this is 0] + The output lines. Each line is represented by a 4-element vector (x1, y1, x2, y2) + + + + Finds circles in a grayscale image using a Hough transform. + + The 8-bit, single-channel, grayscale input image + Currently, the only implemented method is HoughCirclesMethod.Gradient + The inverse ratio of the accumulator resolution to the image resolution. + Minimum distance between the centers of the detected circles. + The first method-specific parameter. [By default this is 100] + The second method-specific parameter. [By default this is 100] + Minimum circle radius. [By default this is 0] + Maximum circle radius. [By default this is 0] + The output vector found circles. Each vector is encoded as 3-element floating-point vector (x, y, radius) + + + + Default borderValue for Dilate/Erode + + + + + + Dilates an image by using a specific structuring element. + + The source image + The destination image. It will have the same size and the same type as src + The structuring element used for dilation. If element=new Mat() , a 3x3 rectangular structuring element is used + Position of the anchor within the element. The default value (-1, -1) means that the anchor is at the element center + The number of times dilation is applied. [By default this is 1] + The pixel extrapolation method. [By default this is BorderType.Constant] + The border value in case of a constant border. The default value has a special meaning. [By default this is CvCpp.MorphologyDefaultBorderValue()] + + + + Erodes an image by using a specific structuring element. + + The source image + The destination image. It will have the same size and the same type as src + The structuring element used for dilation. If element=new Mat(), a 3x3 rectangular structuring element is used + Position of the anchor within the element. The default value (-1, -1) means that the anchor is at the element center + The number of times erosion is applied + The pixel extrapolation method + The border value in case of a constant border. The default value has a special meaning. [By default this is CvCpp.MorphologyDefaultBorderValue()] + + + + Performs advanced morphological transformations + + Source image + Destination image. It will have the same size and the same type as src + Type of morphological operation + Structuring element + Position of the anchor within the element. The default value (-1, -1) means that the anchor is at the element center + Number of times erosion and dilation are applied. [By default this is 1] + The pixel extrapolation method. [By default this is BorderType.Constant] + The border value in case of a constant border. The default value has a special meaning. [By default this is CvCpp.MorphologyDefaultBorderValue()] + + + + Resizes an image. + + input image. + output image; it has the size dsize (when it is non-zero) or the size computed + from src.size(), fx, and fy; the type of dst is the same as of src. + output image size; if it equals zero, it is computed as: + dsize = Size(round(fx*src.cols), round(fy*src.rows)) + Either dsize or both fx and fy must be non-zero. + scale factor along the horizontal axis; when it equals 0, + it is computed as: (double)dsize.width/src.cols + scale factor along the vertical axis; when it equals 0, + it is computed as: (double)dsize.height/src.rows + interpolation method + + + + Applies an affine transformation to an image. + + input image. + output image that has the size dsize and the same type as src. + 2x3 transformation matrix. + size of the output image. + combination of interpolation methods and the optional flag + WARP_INVERSE_MAP that means that M is the inverse transformation (dst -> src) . + pixel extrapolation method; when borderMode=BORDER_TRANSPARENT, + it means that the pixels in the destination image corresponding to the "outliers" + in the source image are not modified by the function. + value used in case of a constant border; by default, it is 0. + + + + Applies a perspective transformation to an image. + + input image. + output image that has the size dsize and the same type as src. + 3x3 transformation matrix. + size of the output image. + combination of interpolation methods (INTER_LINEAR or INTER_NEAREST) + and the optional flag WARP_INVERSE_MAP, that sets M as the inverse transformation (dst -> src). + pixel extrapolation method (BORDER_CONSTANT or BORDER_REPLICATE). + value used in case of a constant border; by default, it equals 0. + + + + Applies a perspective transformation to an image. + + input image. + output image that has the size dsize and the same type as src. + 3x3 transformation matrix. + size of the output image. + combination of interpolation methods (INTER_LINEAR or INTER_NEAREST) + and the optional flag WARP_INVERSE_MAP, that sets M as the inverse transformation (dst -> src). + pixel extrapolation method (BORDER_CONSTANT or BORDER_REPLICATE). + value used in case of a constant border; by default, it equals 0. + + + + Applies a generic geometrical transformation to an image. + + Source image. + Destination image. It has the same size as map1 and the same type as src + The first map of either (x,y) points or just x values having the type CV_16SC2, CV_32FC1, or CV_32FC2. + The second map of y values having the type CV_16UC1, CV_32FC1, or none (empty map if map1 is (x,y) points), respectively. + Interpolation method. The method INTER_AREA is not supported by this function. + Pixel extrapolation method. When borderMode=BORDER_TRANSPARENT, + it means that the pixels in the destination image that corresponds to the "outliers" in + the source image are not modified by the function. + Value used in case of a constant border. By default, it is 0. + + + + + + + + + + + + + + + + + + + + + + + + Inverts an affine transformation. + + Original affine transformation. + Output reverse affine transformation. + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Retrieves a pixel rectangle from an image with sub-pixel accuracy. + + Source image. + Size of the extracted patch. + Floating point coordinates of the center of the extracted rectangle + within the source image. The center must be inside the image. + Extracted patch that has the size patchSize and the same number of channels as src . + Depth of the extracted pixels. By default, they have the same depth as src. + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Adds an image to the accumulator. + + Input image as 1- or 3-channel, 8-bit or 32-bit floating point. + Accumulator image with the same number of channels as input image, 32-bit or 64-bit floating-point. + Optional operation mask. + + + + Adds the square of a source image to the accumulator. + + Input image as 1- or 3-channel, 8-bit or 32-bit floating point. + Accumulator image with the same number of channels as input image, 32-bit or 64-bit floating-point. + Optional operation mask. + + + + Adds the per-element product of two input images to the accumulator. + + First input image, 1- or 3-channel, 8-bit or 32-bit floating point. + Second input image of the same type and the same size as src1 + Accumulator with the same number of channels as input images, 32-bit or 64-bit floating-point. + Optional operation mask. + + + + Updates a running average. + + Input image as 1- or 3-channel, 8-bit or 32-bit floating point. + Accumulator image with the same number of channels as input image, 32-bit or 64-bit floating-point. + Weight of the input image. + Optional operation mask. + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Computes a Hanning window coefficients in two dimensions. + + Destination array to place Hann coefficients in + The window size specifications + Created array type + + + + Applies a fixed-level threshold to each array element. + + input array (single-channel, 8-bit or 32-bit floating point). + output array of the same size and type as src. + threshold value. + maximum value to use with the THRESH_BINARY and THRESH_BINARY_INV thresholding types. + thresholding type (see the details below). + the computed threshold value when type == OTSU + + + + Applies an adaptive threshold to an array. + + Source 8-bit single-channel image. + Destination image of the same size and the same type as src . + Non-zero value assigned to the pixels for which the condition is satisfied. See the details below. + Adaptive thresholding algorithm to use, ADAPTIVE_THRESH_MEAN_C or ADAPTIVE_THRESH_GAUSSIAN_C . + Thresholding type that must be either THRESH_BINARY or THRESH_BINARY_INV . + Size of a pixel neighborhood that is used to calculate a threshold value for the pixel: 3, 5, 7, and so on. + Constant subtracted from the mean or weighted mean (see the details below). + Normally, it is positive but may be zero or negative as well. + + + + Blurs an image and downsamples it. + + input image. + output image; it has the specified size and the same type as src. + size of the output image; by default, it is computed as Size((src.cols+1)/2 + + + + + Upsamples an image and then blurs it. + + input image. + output image. It has the specified size and the same type as src. + size of the output image; by default, it is computed as Size(src.cols*2, (src.rows*2) + + + + + corrects lens distortion for the given camera matrix and distortion coefficients + + Input (distorted) image. + Output (corrected) image that has the same size and type as src . + Input camera matrix + Input vector of distortion coefficients (k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6]]) of 4, 5, + or 8 elements. If the vector is null, the zero distortion coefficients are assumed. + Camera matrix of the distorted image. + By default, it is the same as cameraMatrix but you may additionally scale + and shift the result by using a different matrix. + + + + initializes maps for cv::remap() to correct lens distortion and optionally rectify the image + + + + + + + + + + + + + initializes maps for cv::remap() for wide-angle + + + + + + + + + + + + + + + returns the default new camera matrix (by default it is the same as cameraMatrix unless centerPricipalPoint=true) + + Input camera matrix. + Camera view image size in pixels. + Location of the principal point in the new camera matrix. + The parameter indicates whether this location should be at the image center or not. + the camera matrix that is either an exact copy of the input cameraMatrix + (when centerPrinicipalPoint=false), or the modified one (when centerPrincipalPoint=true). + + + + Computes the ideal point coordinates from the observed point coordinates. + + Observed point coordinates, 1xN or Nx1 2-channel (CV_32FC2 or CV_64FC2). + Output ideal point coordinates after undistortion and reverse perspective transformation. + If matrix P is identity or omitted, dst will contain normalized point coordinates. + Camera matrix + Input vector of distortion coefficients (k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6]]) of 4, 5, or 8 elements. + If the vector is null, the zero distortion coefficients are assumed. + Rectification transformation in the object space (3x3 matrix). + R1 or R2 computed by stereoRectify() can be passed here. + If the matrix is empty, the identity transformation is used. + New camera matrix (3x3) or new projection matrix (3x4). + P1 or P2 computed by stereoRectify() can be passed here. If the matrix is empty, + the identity new camera matrix is used. + + + + computes the joint dense histogram for a set of images. + + + + + + + + + + + + + + computes the joint dense histogram for a set of images. + + + + + + + + + + + + + + computes the joint dense histogram for a set of images. + + + + + + + + + + + compares two histograms stored in dense arrays + + The first compared histogram + The second compared histogram of the same size as h1 + The comparison method + + + + + normalizes the grayscale image brightness and contrast by normalizing its histogram + + The source 8-bit single channel image + The destination image; will have the same size and the same type as src + + + + Creates a predefined CLAHE object + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Performs a marker-based image segmentation using the watershed algorithm. + + Input 8-bit 3-channel image. + Input/output 32-bit single-channel image (map) of markers. + It should have the same size as image. + + + + Performs initial step of meanshift segmentation of an image. + + The source 8-bit, 3-channel image. + The destination image of the same format and the same size as the source. + The spatial window radius. + The color window radius. + Maximum level of the pyramid for the segmentation. + Termination criteria: when to stop meanshift iterations. + + + + Segments the image using GrabCut algorithm + + Input 8-bit 3-channel image. + Input/output 8-bit single-channel mask. + The mask is initialized by the function when mode is set to GC_INIT_WITH_RECT. + Its elements may have Cv2.GC_BGD / Cv2.GC_FGD / Cv2.GC_PR_BGD / Cv2.GC_PR_FGD + ROI containing a segmented object. The pixels outside of the ROI are + marked as "obvious background". The parameter is only used when mode==GC_INIT_WITH_RECT. + Temporary array for the background model. Do not modify it while you are processing the same image. + Temporary arrays for the foreground model. Do not modify it while you are processing the same image. + Number of iterations the algorithm should make before returning the result. + Note that the result can be refined with further calls with mode==GC_INIT_WITH_MASK or mode==GC_EVAL . + Operation mode that could be one of GrabCutFlag value. + + + + GrabCut mask value [background] + + + + + GrabCut mask value [foreground] + + + + + GrabCut mask value [most probably background] + + + + + GrabCut mask value [most probably foreground] + + + + + builds the discrete Voronoi diagram + + + + + + + + + + + computes the distance transform map + + + + + + + + + Fills a connected component with the given color. + + Input/output 1- or 3-channel, 8-bit, or floating-point image. + It is modified by the function unless the FLOODFILL_MASK_ONLY flag is set in the + second variant of the function. See the details below. + Starting point. + New value of the repainted domain pixels. + + + + + Fills a connected component with the given color. + + Input/output 1- or 3-channel, 8-bit, or floating-point image. + It is modified by the function unless the FLOODFILL_MASK_ONLY flag is set in the + second variant of the function. See the details below. + Starting point. + New value of the repainted domain pixels. + Optional output parameter set by the function to the + minimum bounding rectangle of the repainted domain. + Maximal lower brightness/color difference between the currently + observed pixel and one of its neighbors belonging to the component, or a seed pixel + being added to the component. + Maximal upper brightness/color difference between the currently + observed pixel and one of its neighbors belonging to the component, or a seed pixel + being added to the component. + Operation flags. Lower bits contain a connectivity value, + 4 (default) or 8, used within the function. Connectivity determines which + neighbors of a pixel are considered. + + + + + Fills a connected component with the given color. + + Input/output 1- or 3-channel, 8-bit, or floating-point image. + It is modified by the function unless the FLOODFILL_MASK_ONLY flag is set in the + second variant of the function. See the details below. + (For the second function only) Operation mask that should be a single-channel 8-bit image, + 2 pixels wider and 2 pixels taller. The function uses and updates the mask, so you take responsibility of + initializing the mask content. Flood-filling cannot go across non-zero pixels in the mask. For example, + an edge detector output can be used as a mask to stop filling at edges. It is possible to use the same mask + in multiple calls to the function to make sure the filled area does not overlap. + Starting point. + New value of the repainted domain pixels. + + + + + Fills a connected component with the given color. + + Input/output 1- or 3-channel, 8-bit, or floating-point image. + It is modified by the function unless the FLOODFILL_MASK_ONLY flag is set in the + second variant of the function. See the details below. + (For the second function only) Operation mask that should be a single-channel 8-bit image, + 2 pixels wider and 2 pixels taller. The function uses and updates the mask, so you take responsibility of + initializing the mask content. Flood-filling cannot go across non-zero pixels in the mask. For example, + an edge detector output can be used as a mask to stop filling at edges. It is possible to use the same mask + in multiple calls to the function to make sure the filled area does not overlap. + Starting point. + New value of the repainted domain pixels. + Optional output parameter set by the function to the + minimum bounding rectangle of the repainted domain. + Maximal lower brightness/color difference between the currently + observed pixel and one of its neighbors belonging to the component, or a seed pixel + being added to the component. + Maximal upper brightness/color difference between the currently + observed pixel and one of its neighbors belonging to the component, or a seed pixel + being added to the component. + Operation flags. Lower bits contain a connectivity value, + 4 (default) or 8, used within the function. Connectivity determines which + neighbors of a pixel are considered. + + + + + Converts image from one color space to another + + The source image, 8-bit unsigned, 16-bit unsigned or single-precision floating-point + The destination image; will have the same size and the same depth as src + The color space conversion code + The number of channels in the destination image; if the parameter is 0, the number of the channels will be derived automatically from src and the code + + + + Calculates all of the moments + up to the third order of a polygon or rasterized shape. + + A raster image (single-channel, 8-bit or floating-point + 2D array) or an array ( 1xN or Nx1 ) of 2D points ( Point or Point2f ) + If it is true, then all the non-zero image pixels are treated as 1’s + + + + + Calculates all of the moments + up to the third order of a polygon or rasterized shape. + + A raster image (8-bit) 2D array + If it is true, then all the non-zero image pixels are treated as 1’s + + + + + Calculates all of the moments + up to the third order of a polygon or rasterized shape. + + A raster image (floating-point) 2D array + If it is true, then all the non-zero image pixels are treated as 1’s + + + + + Calculates all of the moments + up to the third order of a polygon or rasterized shape. + + Array of 2D points + If it is true, then all the non-zero image pixels are treated as 1’s + + + + + Calculates all of the moments + up to the third order of a polygon or rasterized shape. + + Array of 2D points + If it is true, then all the non-zero image pixels are treated as 1’s + + + + + Computes the proximity map for the raster template and the image where the template is searched for + + Image where the search is running; should be 8-bit or 32-bit floating-point + Searched template; must be not greater than the source image and have the same data type + A map of comparison results; will be single-channel 32-bit floating-point. + If image is WxH and templ is wxh then result will be (W-w+1) x (H-h+1). + Specifies the comparison method + + + + Finds contours in a binary image. + + Source, an 8-bit single-channel image. Non-zero pixels are treated as 1’s. + Zero pixels remain 0’s, so the image is treated as binary. + The function modifies the image while extracting the contours. + Detected contours. Each contour is stored as a vector of points. + Optional output vector, containing information about the image topology. + It has as many elements as the number of contours. For each i-th contour contours[i], + the members of the elements hierarchy[i] are set to 0-based indices in contours of the next + and previous contours at the same hierarchical level, the first child contour and the parent contour, respectively. + If for the contour i there are no next, previous, parent, or nested contours, the corresponding elements of hierarchy[i] will be negative. + Contour retrieval mode + Contour approximation method + Optional offset by which every contour point is shifted. + This is useful if the contours are extracted from the image ROI and then they should be analyzed in the whole image context. + + + + Finds contours in a binary image. + + Source, an 8-bit single-channel image. Non-zero pixels are treated as 1’s. + Zero pixels remain 0’s, so the image is treated as binary. + The function modifies the image while extracting the contours. + Detected contours. Each contour is stored as a vector of points. + Optional output vector, containing information about the image topology. + It has as many elements as the number of contours. For each i-th contour contours[i], + the members of the elements hierarchy[i] are set to 0-based indices in contours of the next + and previous contours at the same hierarchical level, the first child contour and the parent contour, respectively. + If for the contour i there are no next, previous, parent, or nested contours, the corresponding elements of hierarchy[i] will be negative. + Contour retrieval mode + Contour approximation method + Optional offset by which every contour point is shifted. + This is useful if the contours are extracted from the image ROI and then they should be analyzed in the whole image context. + + + + Finds contours in a binary image. + + Source, an 8-bit single-channel image. Non-zero pixels are treated as 1’s. + Zero pixels remain 0’s, so the image is treated as binary. + The function modifies the image while extracting the contours. + Contour retrieval mode + Contour approximation method + Optional offset by which every contour point is shifted. + This is useful if the contours are extracted from the image ROI and then they should be analyzed in the whole image context. + Detected contours. Each contour is stored as a vector of points. + + + + Finds contours in a binary image. + + Source, an 8-bit single-channel image. Non-zero pixels are treated as 1’s. + Zero pixels remain 0’s, so the image is treated as binary. + The function modifies the image while extracting the contours. + Contour retrieval mode + Contour approximation method + Optional offset by which every contour point is shifted. + This is useful if the contours are extracted from the image ROI and then they should be analyzed in the whole image context. + Detected contours. Each contour is stored as a vector of points. + + + + draws contours in the image + + Destination image. + All the input contours. Each contour is stored as a point vector. + Parameter indicating a contour to draw. If it is negative, all the contours are drawn. + Color of the contours. + Thickness of lines the contours are drawn with. If it is negative (for example, thickness=CV_FILLED ), + the contour interiors are drawn. + Line connectivity. + Optional information about hierarchy. It is only needed if you want to draw only some of the contours + Maximal level for drawn contours. If it is 0, only the specified contour is drawn. + If it is 1, the function draws the contour(s) and all the nested contours. If it is 2, the function draws the contours, + all the nested contours, all the nested-to-nested contours, and so on. This parameter is only taken into account + when there is hierarchy available. + Optional contour shift parameter. Shift all the drawn contours by the specified offset = (dx, dy) + + + + draws contours in the image + + Destination image. + All the input contours. Each contour is stored as a point vector. + Parameter indicating a contour to draw. If it is negative, all the contours are drawn. + Color of the contours. + Thickness of lines the contours are drawn with. If it is negative (for example, thickness=CV_FILLED ), + the contour interiors are drawn. + Line connectivity. + Optional information about hierarchy. It is only needed if you want to draw only some of the contours + Maximal level for drawn contours. If it is 0, only the specified contour is drawn. + If it is 1, the function draws the contour(s) and all the nested contours. If it is 2, the function draws the contours, + all the nested contours, all the nested-to-nested contours, and so on. This parameter is only taken into account + when there is hierarchy available. + Optional contour shift parameter. Shift all the drawn contours by the specified offset = (dx, dy) + + + + Approximates contour or a curve using Douglas-Peucker algorithm + + The polygon or curve to approximate. + Must be 1 x N or N x 1 matrix of type CV_32SC2 or CV_32FC2. + The result of the approximation; + The type should match the type of the input curve + Specifies the approximation accuracy. + This is the maximum distance between the original curve and its approximation. + The result of the approximation; + The type should match the type of the input curve + + + + Approximates contour or a curve using Douglas-Peucker algorithm + + The polygon or curve to approximate. + Specifies the approximation accuracy. + This is the maximum distance between the original curve and its approximation. + The result of the approximation; + The type should match the type of the input curve + The result of the approximation; + The type should match the type of the input curve + + + + Approximates contour or a curve using Douglas-Peucker algorithm + + The polygon or curve to approximate. + Specifies the approximation accuracy. + This is the maximum distance between the original curve and its approximation. + If true, the approximated curve is closed + (i.e. its first and last vertices are connected), otherwise it’s not + The result of the approximation; + The type should match the type of the input curve + + + + Calculates a contour perimeter or a curve length. + + The input vector of 2D points, represented by CV_32SC2 or CV_32FC2 matrix. + Indicates, whether the curve is closed or not. + + + + + Calculates a contour perimeter or a curve length. + + The input vector of 2D points. + Indicates, whether the curve is closed or not. + + + + + Calculates a contour perimeter or a curve length. + + The input vector of 2D points. + Indicates, whether the curve is closed or not. + + + + + Calculates the up-right bounding rectangle of a point set. + + The input 2D point set, represented by CV_32SC2 or CV_32FC2 matrix. + Minimal up-right bounding rectangle for the specified point set. + + + + Calculates the up-right bounding rectangle of a point set. + + The input 2D point set, represented by CV_32SC2 or CV_32FC2 matrix. + Minimal up-right bounding rectangle for the specified point set. + + + + Calculates the up-right bounding rectangle of a point set. + + The input 2D point set, represented by CV_32SC2 or CV_32FC2 matrix. + Minimal up-right bounding rectangle for the specified point set. + + + + Calculates the contour area + + The contour vertices, represented by CV_32SC2 or CV_32FC2 matrix + + + + + + Calculates the contour area + + The contour vertices, represented by CV_32SC2 or CV_32FC2 matrix + + + + + + Calculates the contour area + + The contour vertices, represented by CV_32SC2 or CV_32FC2 matrix + + + + + + Finds the minimum area rotated rectangle enclosing a 2D point set. + + The input 2D point set, represented by CV_32SC2 or CV_32FC2 matrix. + + + + + Finds the minimum area rotated rectangle enclosing a 2D point set. + + The input 2D point set, represented by CV_32SC2 or CV_32FC2 matrix. + + + + + Finds the minimum area rotated rectangle enclosing a 2D point set. + + The input 2D point set, represented by CV_32SC2 or CV_32FC2 matrix. + + + + + Finds the minimum area circle enclosing a 2D point set. + + The input 2D point set, represented by CV_32SC2 or CV_32FC2 matrix. + The output center of the circle + The output radius of the circle + + + + Finds the minimum area circle enclosing a 2D point set. + + The input 2D point set, represented by CV_32SC2 or CV_32FC2 matrix. + The output center of the circle + The output radius of the circle + + + + Finds the minimum area circle enclosing a 2D point set. + + The input 2D point set, represented by CV_32SC2 or CV_32FC2 matrix. + The output center of the circle + The output radius of the circle + + + + matches two contours using one of the available algorithms + + + + + + + + + + matches two contours using one of the available algorithms + + + + + + + + + + Computes convex hull for a set of 2D points. + + The input 2D point set, represented by CV_32SC2 or CV_32FC2 matrix + The output convex hull. It is either a vector of points that form the + hull (must have the same type as the input points), or a vector of 0-based point + indices of the hull points in the original array (since the set of convex hull + points is a subset of the original point set). + If true, the output convex hull will be oriented clockwise, + otherwise it will be oriented counter-clockwise. Here, the usual screen coordinate + system is assumed - the origin is at the top-left corner, x axis is oriented to the right, + and y axis is oriented downwards. + + + + + Computes convex hull for a set of 2D points. + + The input 2D point set, represented by CV_32SC2 or CV_32FC2 matrix + If true, the output convex hull will be oriented clockwise, + otherwise it will be oriented counter-clockwise. Here, the usual screen coordinate + system is assumed - the origin is at the top-left corner, x axis is oriented to the right, + and y axis is oriented downwards. + The output convex hull. It is a vector of points that form + the hull (must have the same type as the input points). + + + + Computes convex hull for a set of 2D points. + + The input 2D point set, represented by CV_32SC2 or CV_32FC2 matrix + If true, the output convex hull will be oriented clockwise, + otherwise it will be oriented counter-clockwise. Here, the usual screen coordinate + system is assumed - the origin is at the top-left corner, x axis is oriented to the right, + and y axis is oriented downwards. + The output convex hull. It is a vector of points that form + the hull (must have the same type as the input points). + + + + Computes convex hull for a set of 2D points. + + The input 2D point set, represented by CV_32SC2 or CV_32FC2 matrix + If true, the output convex hull will be oriented clockwise, + otherwise it will be oriented counter-clockwise. Here, the usual screen coordinate + system is assumed - the origin is at the top-left corner, x axis is oriented to the right, + and y axis is oriented downwards. + The output convex hull. It is a vector of 0-based point indices of the + hull points in the original array (since the set of convex hull points is a subset of the original point set). + + + + Computes convex hull for a set of 2D points. + + The input 2D point set, represented by CV_32SC2 or CV_32FC2 matrix + If true, the output convex hull will be oriented clockwise, + otherwise it will be oriented counter-clockwise. Here, the usual screen coordinate + system is assumed - the origin is at the top-left corner, x axis is oriented to the right, + and y axis is oriented downwards. + The output convex hull. It is a vector of 0-based point indices of the + hull points in the original array (since the set of convex hull points is a subset of the original point set). + + + + Computes the contour convexity defects + + Input contour. + Convex hull obtained using convexHull() that + should contain indices of the contour points that make the hull. + + The output vector of convexity defects. + Each convexity defect is represented as 4-element integer vector + (a.k.a. cv::Vec4i): (start_index, end_index, farthest_pt_index, fixpt_depth), + where indices are 0-based indices in the original contour of the convexity defect beginning, + end and the farthest point, and fixpt_depth is fixed-point approximation + (with 8 fractional bits) of the distance between the farthest contour point and the hull. + That is, to get the floating-point value of the depth will be fixpt_depth/256.0. + + + + + Computes the contour convexity defects + + Input contour. + Convex hull obtained using convexHull() that + should contain indices of the contour points that make the hull. + The output vector of convexity defects. + Each convexity defect is represented as 4-element integer vector + (a.k.a. cv::Vec4i): (start_index, end_index, farthest_pt_index, fixpt_depth), + where indices are 0-based indices in the original contour of the convexity defect beginning, + end and the farthest point, and fixpt_depth is fixed-point approximation + (with 8 fractional bits) of the distance between the farthest contour point and the hull. + That is, to get the floating-point value of the depth will be fixpt_depth/256.0. + + + + Computes the contour convexity defects + + Input contour. + Convex hull obtained using convexHull() that + should contain indices of the contour points that make the hull. + The output vector of convexity defects. + Each convexity defect is represented as 4-element integer vector + (a.k.a. cv::Vec4i): (start_index, end_index, farthest_pt_index, fixpt_depth), + where indices are 0-based indices in the original contour of the convexity defect beginning, + end and the farthest point, and fixpt_depth is fixed-point approximation + (with 8 fractional bits) of the distance between the farthest contour point and the hull. + That is, to get the floating-point value of the depth will be fixpt_depth/256.0. + + + + returns true if the contour is convex. + Does not support contours with self-intersection + + Input vector of 2D points + + + + + returns true if the contour is convex. + Does not support contours with self-intersection + + Input vector of 2D points + + + + + returns true if the contour is convex. D + oes not support contours with self-intersection + + Input vector of 2D points + + + + + finds intersection of two convex polygons + + + + + + + + + + finds intersection of two convex polygons + + + + + + + + + + finds intersection of two convex polygons + + + + + + + + + + Fits ellipse to the set of 2D points. + + Input 2D point set + + + + + Fits ellipse to the set of 2D points. + + Input 2D point set + + + + + Fits ellipse to the set of 2D points. + + Input 2D point set + + + + + Fits line to the set of 2D points using M-estimator algorithm + + Input vector of 2D or 3D points + Output line parameters. + In case of 2D fitting, it should be a vector of 4 elements + (like Vec4f) - (vx, vy, x0, y0), where (vx, vy) is a normalized vector + collinear to the line and (x0, y0) is a point on the line. + In case of 3D fitting, it should be a vector of 6 elements + (like Vec6f) - (vx, vy, vz, x0, y0, z0), where (vx, vy, vz) is a + normalized vector collinear to the line and (x0, y0, z0) is a point on the line. + Distance used by the M-estimator + Numerical parameter ( C ) for some types of distances. + If it is 0, an optimal value is chosen. + Sufficient accuracy for the radius + (distance between the coordinate origin and the line). + Sufficient accuracy for the angle. + 0.01 would be a good default value for reps and aeps. + + + + Fits line to the set of 2D points using M-estimator algorithm + + Input vector of 2D or 3D points + Distance used by the M-estimator + Numerical parameter ( C ) for some types of distances. + If it is 0, an optimal value is chosen. + Sufficient accuracy for the radius + (distance between the coordinate origin and the line). + Sufficient accuracy for the angle. + 0.01 would be a good default value for reps and aeps. + Output line parameters. + + + + Fits line to the set of 2D points using M-estimator algorithm + + Input vector of 2D or 3D points + Distance used by the M-estimator + Numerical parameter ( C ) for some types of distances. + If it is 0, an optimal value is chosen. + Sufficient accuracy for the radius + (distance between the coordinate origin and the line). + Sufficient accuracy for the angle. + 0.01 would be a good default value for reps and aeps. + Output line parameters. + + + + Fits line to the set of 3D points using M-estimator algorithm + + Input vector of 2D or 3D points + Distance used by the M-estimator + Numerical parameter ( C ) for some types of distances. + If it is 0, an optimal value is chosen. + Sufficient accuracy for the radius + (distance between the coordinate origin and the line). + Sufficient accuracy for the angle. + 0.01 would be a good default value for reps and aeps. + Output line parameters. + + + + Fits line to the set of 3D points using M-estimator algorithm + + Input vector of 2D or 3D points + Distance used by the M-estimator + Numerical parameter ( C ) for some types of distances. + If it is 0, an optimal value is chosen. + Sufficient accuracy for the radius + (distance between the coordinate origin and the line). + Sufficient accuracy for the angle. + 0.01 would be a good default value for reps and aeps. + Output line parameters. + + + + Checks if the point is inside the contour. Optionally computes the signed distance from the point to the contour boundary + + + + + + + + + Checks if the point is inside the contour. Optionally computes the signed distance from the point to the contour boundary + + + + + + + + + Checks if the point is inside the contour. + Optionally computes the signed distance from the point to the contour boundary. + + Input contour. + Point tested against the contour. + If true, the function estimates the signed distance + from the point to the nearest contour edge. Otherwise, the function only checks + if the point is inside a contour or not. + Positive (inside), negative (outside), or zero (on an edge) value. + + + + IEnumerable<T> extension methods for .NET Framework 2.0 + + + + + Enumerable.Select + + + + + + + + + + Enumerable.Select -> ToArray + + + + + + + + + + Enumerable.Select -> ToArray + + + + + + + + + + Enumerable.Select -> ToArray + + + + + + + Enumerable.Select -> ToArray + + + + + + + Enumerable.Where + + + + + + + + + Enumerable.Where -> ToArray + + + + + + + + + Enumerable.ToArray + + + + + + + + Enumerable.Any + + + + + + + + + Enumerable.Any + + + + + + + + Enumerable.All + + + + + + + + + Enumerable.Count + + + + + + + + + Enumerable.Count + + + + + + + + Enumerable.Count + + + + + + + + + + + + + + + + + + + + + + + Creates instance from cv::Ptr<T> . + ptr is disposed when the wrapper disposes. + + + + + + Creates instance from raw pointer T* + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Releases the resources + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + Pointer to algorithm information (cv::AlgorithmInfo*) + + + + + + Trains a FaceRecognizer. + + + + + + + Updates a FaceRecognizer. + + + + + + + Gets a prediction from a FaceRecognizer. + + + + + + + Predicts the label and confidence for a given sample. + + + + + + + + Serializes this object to a given filename. + + + + + + Deserializes this object from a given filename. + + + + + + Serializes this object to a given cv::FileStorage. + + + + + + Deserializes this object from a given cv::FileStorage. + + + + + + Flags for applyColorMap + + + + + Transformation flags for cv::dct + + + + + Zero + [0] + + + + + Do inverse 1D or 2D transform. + (Forward and Inverse are mutually exclusive, of course.) + [DFT_INVERSE] + + + + + Do forward or inverse transform of every individual row of the input matrix. + This flag allows user to transform multiple vectors simultaneously and can be used to decrease the overhead + (which is sometimes several times larger than the processing itself), to do 3D and higher-dimensional transforms etc. + [DFT_ROWS] + + + + + Transformation flags for cv::dft + + + + + Zero + [0] + + + + + Do inverse 1D or 2D transform. The result is not scaled. + (Forward and Inverse are mutually exclusive, of course.) + [DFT_INVERSE] + + + + + Scale the result: divide it by the number of array elements. Usually, it is combined with Inverse. + [DFT_SCALE] + + + + + Do forward or inverse transform of every individual row of the input matrix. + This flag allows user to transform multiple vectors simultaneously and can be used to decrease the overhead + (which is sometimes several times larger than the processing itself), to do 3D and higher-dimensional transforms etc. + [CV_DXT_ROWS] + + + + + then the function performs forward transformation of 1D or 2D real array, the result, + though being a complex array, has complex-conjugate symmetry ( CCS ), see the description below. + Such an array can be packed into real array of the same size as input, which is the fastest option + and which is what the function does by default. However, you may wish to get the full complex array + (for simpler spectrum analysis etc.). Pass the flag to tell the function to produce full-size complex output array. + [DFT_COMPLEX_OUTPUT] + + + + + then the function performs inverse transformation of 1D or 2D complex array, the result is normally a complex array + of the same size. However, if the source array has conjugate-complex symmetry (for example, it is a result of + forward transformation with DFT_COMPLEX_OUTPUT flag), then the output is real array. While the function itself + does not check whether the input is symmetrical or not, you can pass the flag and then the function will assume + the symmetry and produce the real output array. Note that when the input is packed real array and + inverse transformation is executed, the function treats the input as packed complex-conjugate symmetrical array, + so the output will also be real array + [DFT_REAL_OUTPUT] + + + + + Method for solving a PnP problem: + + + + + uses symmetric pattern of circles. + + + + + uses asymmetric pattern of circles. + + + + + uses a special algorithm for grid detection. It is more robust to perspective distortions but much more sensitive to background clutter. + + + + + XML/YAML File Storage Class. + + + + + Default constructor. + You should call FileStorage::open() after initialization. + + + + + The full constructor + + Name of the file to open or the text string to read the data from. + Extension of the file (.xml or .yml/.yaml) determines its format + (XML or YAML respectively). Also you can append .gz to work with + compressed files, for example myHugeMatrix.xml.gz. + If both FileStorage::WRITE and FileStorage::MEMORY flags are specified, + source is used just to specify the output file format + (e.g. mydata.xml, .yml etc.). + + Encoding of the file. Note that UTF-16 XML encoding is not supported + currently and you should use 8-bit encoding instead of it. + + + + + + + + + + Returns the specified element of the top-level mapping + + + + + + + the currently written element + + + + + the stack of written structures + + + + + the writer state + + + + + operator that performs PCA. The previously stored data, if any, is released + + + + Encoding of the file. Note that UTF-16 XML encoding is not supported + currently and you should use 8-bit encoding instead of it. + + + + + Returns true if the object is associated with currently opened file. + + + + + + Closes the file and releases all the memory buffers + + + + + Closes the file, releases all the memory buffers and returns the text string + + + + + + Returns the first element of the top-level mapping + + + + + + Returns the top-level mapping. YAML supports multiple streams + + + + + + + Returns pointer to the underlying C FileStorage structure + + + + + + + Returns pointer to the underlying C FileStorage structure + + + + + + Writes one or more numbers of the specified format to the currently written structure + + + + + + + + Writes the registered C structure (CvMat, CvMatND, CvSeq). See cvWrite() + + + + + + + Returns the normalized object name for the specified file name + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + File Storage Node class + + + + + The default constructor + + + + + The full constructor wrapping CvFileNode structure. + + + + + + + The copy constructor + + + + + + Initializes from cv::FileNode* + + + + + + + + + + + + Returns the node content as an integer. If the node stores floating-point number, it is rounded. + + + + + + + Returns the node content as float + + + + + + + Returns the node content as double + + + + + + + Returns the node content as text string + + + + + + + returns element of a mapping node + + + + + returns element of a sequence node + + + + + Returns true if the node is empty + + + + + + Returns true if the node is a "none" object + + + + + + Returns true if the node is a sequence + + + + + + Returns true if the node is a mapping + + + + + + Returns true if the node is an integer + + + + + + Returns true if the node is a floating-point number + + + + + + Returns true if the node is a text string + + + + + + Returns true if the node has a name + + + + + + Returns the node name or an empty string if the node is nameless + + + + + + Returns the number of elements in the node, if it is a sequence or mapping, or 1 otherwise. + + + + + + Returns pointer to the underlying C FileStorage structure + + + + + + + Returns pointer to the underlying C FileStorage structure + + + + + + Reads node elements to the buffer with the specified format + + + + + + + + Reads the registered object and returns pointer to it + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Matrix expression + + + + + Computes absolute value of each matrix element + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + A matrix whose element is 32SC1 (cv::Mat_<int>) + + + + + Creates empty Mat + + + + + Creates from native cv::Mat* pointer + + + + + + Initializes by Mat object + + Managed Mat object + + + + constructs 2D matrix of the specified size and type + + Number of rows in a 2D array. + Number of columns in a 2D array. + + + + constructs 2D matrix of the specified size and type + + 2D array size: Size(cols, rows) . In the Size() constructor, + the number of rows and the number of columns go in the reverse order. + + + + constucts 2D matrix and fills it with the specified Scalar value. + + Number of rows in a 2D array. + Number of columns in a 2D array. + An optional value to initialize each matrix element with. + To set all the matrix elements to the particular value after the construction, use SetTo(Scalar s) method . + + + + constucts 2D matrix and fills it with the specified Scalar value. + + 2D array size: Size(cols, rows) . In the Size() constructor, + the number of rows and the number of columns go in the reverse order. + An optional value to initialize each matrix element with. + To set all the matrix elements to the particular value after the construction, use SetTo(Scalar s) method . + + + + creates a matrix header for a part of the bigger matrix + + Array that (as a whole or partly) is assigned to the constructed matrix. + No data is copied by these constructors. Instead, the header pointing to m data or its sub-array + is constructed and associated with it. The reference counter, if any, is incremented. + So, when you modify the matrix formed using such a constructor, you also modify the corresponding elements of m . + If you want to have an independent copy of the sub-array, use Mat::clone() . + Range of the m rows to take. As usual, the range start is inclusive and the range end is exclusive. + Use Range.All to take all the rows. + Range of the m columns to take. Use Range.All to take all the columns. + + + + creates a matrix header for a part of the bigger matrix + + Array that (as a whole or partly) is assigned to the constructed matrix. + No data is copied by these constructors. Instead, the header pointing to m data or its sub-array + is constructed and associated with it. The reference counter, if any, is incremented. + So, when you modify the matrix formed using such a constructor, you also modify the corresponding elements of m . + If you want to have an independent copy of the sub-array, use Mat.Clone() . + Array of selected ranges of m along each dimensionality. + + + + creates a matrix header for a part of the bigger matrix + + Array that (as a whole or partly) is assigned to the constructed matrix. + No data is copied by these constructors. Instead, the header pointing to m data or its sub-array + is constructed and associated with it. The reference counter, if any, is incremented. + So, when you modify the matrix formed using such a constructor, you also modify the corresponding elements of m . + If you want to have an independent copy of the sub-array, use Mat.Clone() . + Region of interest. + + + + constructor for matrix headers pointing to user-allocated data + + Number of rows in a 2D array. + Number of columns in a 2D array. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Number of bytes each matrix row occupies. The value should include the padding bytes at the end of each row, if any. + If the parameter is missing (set to AUTO_STEP ), no padding is assumed and the actual step is calculated as cols*elemSize() . + + + + constructor for matrix headers pointing to user-allocated data + + Number of rows in a 2D array. + Number of columns in a 2D array. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Number of bytes each matrix row occupies. The value should include the padding bytes at the end of each row, if any. + If the parameter is missing (set to AUTO_STEP ), no padding is assumed and the actual step is calculated as cols*elemSize() . + + + + constructor for matrix headers pointing to user-allocated data + + Number of rows in a 2D array. + Number of columns in a 2D array. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Number of bytes each matrix row occupies. The value should include the padding bytes at the end of each row, if any. + If the parameter is missing (set to AUTO_STEP ), no padding is assumed and the actual step is calculated as cols*elemSize() . + + + + constructor for matrix headers pointing to user-allocated data + + Array of integers specifying an n-dimensional array shape. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Array of ndims-1 steps in case of a multi-dimensional array (the last step is always set to the element size). + If not specified, the matrix is assumed to be continuous. + + + + constructor for matrix headers pointing to user-allocated data + + Array of integers specifying an n-dimensional array shape. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Array of ndims-1 steps in case of a multi-dimensional array (the last step is always set to the element size). + If not specified, the matrix is assumed to be continuous. + + + + constructor for matrix headers pointing to user-allocated data + + Array of integers specifying an n-dimensional array shape. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Array of ndims-1 steps in case of a multi-dimensional array (the last step is always set to the element size). + If not specified, the matrix is assumed to be continuous. + + + + constructs n-dimensional matrix + + Array of integers specifying an n-dimensional array shape. + + + + constructs n-dimensional matrix + + Array of integers specifying an n-dimensional array shape. + An optional value to initialize each matrix element with. + To set all the matrix elements to the particular value after the construction, use SetTo(Scalar s) method . + + + + converts old-style CvMat to the new matrix; the data is not copied by default + + Old style CvMat object + Flag to specify whether the underlying data of the the old-style CvMat should be + copied to (true) or shared with (false) the newly constructed matrix. When the data is copied, + the allocated buffer is managed using Mat reference counting mechanism. While the data is shared, + the reference counter is NULL, and you should not deallocate the data until the matrix is not destructed. + + + + converts old-style IplImage to the new matrix; the data is not copied by default + + Old style IplImage object + Flag to specify whether the underlying data of the the old-style IplImage should be + copied to (true) or shared with (false) the newly constructed matrix. When the data is copied, + the allocated buffer is managed using Mat reference counting mechanism. While the data is shared, + the reference counter is NULL, and you should not deallocate the data until the matrix is not destructed. + + + + Matrix indexer + + + + + 1-dimensional indexer + + Index along the dimension 0 + A value to the specified array element. + + + + 2-dimensional indexer + + Index along the dimension 0 + Index along the dimension 1 + A value to the specified array element. + + + + 3-dimensional indexer + + Index along the dimension 0 + Index along the dimension 1 + Index along the dimension 2 + A value to the specified array element. + + + + n-dimensional indexer + + Array of Mat::dims indices. + A value to the specified array element. + + + + Gets a type-specific indexer. The indexer has getters/setters to access each matrix element. + + + + + + Initializes as N x 1 matrix and copys array data to this + + Source array data to be copied to this + + + + Initializes as M x N matrix and copys array data to this + + Source array data to be copied to this + + + + Initializes as N x 1 matrix and copys array data to this + + Source array data to be copied to this + + + + Convert this mat to managed array + + + + + + Convert this mat to managed rectangular array + + + + + + + + + + + + Adds elements to the bottom of the matrix. (Mat::push_back) + + Added element(s) + + + + OpenCV C++ n-dimensional dense array class (cv::Mat) + + + + + Computes absolute value of each matrix element + + + + + + Scales, computes absolute values and converts the result to 8-bit. + + The optional scale factor. [By default this is 1] + The optional delta added to the scaled values. [By default this is 0] + + + + + transforms array of numbers using a lookup table: dst(i)=lut(src(i)) + + Look-up table of 256 elements. + In the case of multi-channel source array, the table should either have + a single channel (in this case the same table is used for all channels) + or the same number of channels as in the source array + + + + + + transforms array of numbers using a lookup table: dst(i)=lut(src(i)) + + Look-up table of 256 elements. + In the case of multi-channel source array, the table should either have + a single channel (in this case the same table is used for all channels) + or the same number of channels as in the source array + + + + + + computes sum of array elements + + + + + + computes the number of nonzero array elements + + number of non-zero elements in mtx + + + + returns the list of locations of non-zero pixels + + + + + + computes mean value of selected array elements + + The optional operation mask + + + + + computes mean value and standard deviation of all or selected array elements + + The output parameter: computed mean value + The output parameter: computed standard deviation + The optional operation mask + + + + computes norm of the selected array part + + Type of the norm + The optional operation mask + + + + + scales and shifts array elements so that either the specified norm (alpha) + or the minimum (alpha) and maximum (beta) array values get the specified values + + The norm value to normalize to or the lower range boundary + in the case of range normalization + The upper range boundary in the case of range normalization; + not used for norm normalization + The normalization type + When the parameter is negative, + the destination array will have the same type as src, + otherwise it will have the same number of channels as src and the depth =CV_MAT_DEPTH(rtype) + The optional operation mask + + + + + finds global minimum and maximum array elements and returns their values and their locations + + Pointer to returned minimum value + Pointer to returned maximum value + + + + finds global minimum and maximum array elements and returns their values and their locations + + Pointer to returned minimum location + Pointer to returned maximum location + + + + finds global minimum and maximum array elements and returns their values and their locations + + Pointer to returned minimum value + Pointer to returned maximum value + Pointer to returned minimum location + Pointer to returned maximum location + The optional mask used to select a sub-array + + + + finds global minimum and maximum array elements and returns their values and their locations + + Pointer to returned minimum value + Pointer to returned maximum value + + + + finds global minimum and maximum array elements and returns their values and their locations + + + + + + + finds global minimum and maximum array elements and returns their values and their locations + + Pointer to returned minimum value + Pointer to returned maximum value + + + + + + + transforms 2D matrix to 1D row or column vector by taking sum, minimum, maximum or mean value over all the rows + + The dimension index along which the matrix is reduced. + 0 means that the matrix is reduced to a single row and 1 means that the matrix is reduced to a single column + + When it is negative, the destination vector will have + the same type as the source matrix, otherwise, its type will be CV_MAKE_TYPE(CV_MAT_DEPTH(dtype), mtx.channels()) + + + + + Copies each plane of a multi-channel array to a dedicated array + + The number of arrays must match mtx.channels() . + The arrays themselves will be reallocated if needed + + + + extracts a single channel from src (coi is 0-based index) + + + + + + + inserts a single channel to dst (coi is 0-based index) + + + + + + + reverses the order of the rows, columns or both in a matrix + + Specifies how to flip the array: + 0 means flipping around the x-axis, positive (e.g., 1) means flipping around y-axis, + and negative (e.g., -1) means flipping around both axes. See also the discussion below for the formulas. + The destination array; will have the same size and same type as src + + + + replicates the input matrix the specified number of times in the horizontal and/or vertical direction + + How many times the src is repeated along the vertical axis + How many times the src is repeated along the horizontal axis + + + + + set mask elements for those array elements which are within the element-specific bounding box (dst = lowerb <= src && src < upperb) + + The inclusive lower boundary array of the same size and type as src + The exclusive upper boundary array of the same size and type as src + The destination array, will have the same size as src and CV_8U type + + + + set mask elements for those array elements which are within the element-specific bounding box (dst = lowerb <= src && src < upperb) + + The inclusive lower boundary array of the same size and type as src + The exclusive upper boundary array of the same size and type as src + The destination array, will have the same size as src and CV_8U type + + + + computes square root of each matrix element (dst = src**0.5) + + The destination array; will have the same size and the same type as src + + + + raises the input matrix elements to the specified power (b = a**power) + + The exponent of power + The destination array; will have the same size and the same type as src + + + + computes exponent of each matrix element (dst = e**src) + + The destination array; will have the same size and same type as src + + + + computes natural logarithm of absolute value of each matrix element: dst = log(abs(src)) + + The destination array; will have the same size and same type as src + + + + checks that each matrix element is within the specified range. + + The flag indicating whether the functions quietly + return false when the array elements are out of range, + or they throw an exception. + + + + + checks that each matrix element is within the specified range. + + The flag indicating whether the functions quietly + return false when the array elements are out of range, + or they throw an exception. + The optional output parameter, where the position of + the first outlier is stored. + The inclusive lower boundary of valid values range + The exclusive upper boundary of valid values range + + + + + converts NaN's to the given number + + + + + + multiplies matrix by its transposition from the left or from the right + + Specifies the multiplication ordering; see the description below + The optional delta matrix, subtracted from src before the + multiplication. When the matrix is empty ( delta=Mat() ), it’s assumed to be + zero, i.e. nothing is subtracted, otherwise if it has the same size as src, + then it’s simply subtracted, otherwise it is "repeated" to cover the full src + and then subtracted. Type of the delta matrix, when it's not empty, must be the + same as the type of created destination matrix, see the rtype description + The optional scale factor for the matrix product + When it’s negative, the destination matrix will have the + same type as src . Otherwise, it will have type=CV_MAT_DEPTH(rtype), + which should be either CV_32F or CV_64F + + + + transposes the matrix + + The destination array of the same type as src + + + + performs affine transformation of each element of multi-channel input matrix + + The transformation matrix + The destination array; will have the same size and depth as src and as many channels as mtx.rows + + + + performs perspective transformation of each element of multi-channel input matrix + + 3x3 or 4x4 transformation matrix + The destination array; it will have the same size and same type as src + + + + extends the symmetrical matrix from the lower half or from the upper half + + If true, the lower half is copied to the upper half, + otherwise the upper half is copied to the lower half + + + + initializes scaled identity matrix (not necessarily square). + + The value to assign to the diagonal elements + + + + computes determinant of a square matrix. + The input matrix must have CV_32FC1 or CV_64FC1 type and square size. + + determinant of the specified matrix. + + + + computes trace of a matrix + + + + + + sorts independently each matrix row or each matrix column + + The operation flags, a combination of the SortFlag values + The destination array of the same size and the same type as src + + + + sorts independently each matrix row or each matrix column + + The operation flags, a combination of SortFlag values + The destination integer array of the same size as src + + + + Performs a forward Discrete Fourier transform of 1D or 2D floating-point array. + + Transformation flags, a combination of the DftFlag2 values + When the parameter != 0, the function assumes that + only the first nonzeroRows rows of the input array ( DFT_INVERSE is not set) + or only the first nonzeroRows of the output array ( DFT_INVERSE is set) contain non-zeros, + thus the function can handle the rest of the rows more efficiently and + thus save some time. This technique is very useful for computing array cross-correlation + or convolution using DFT + The destination array, which size and type depends on the flags + + + + Performs an inverse Discrete Fourier transform of 1D or 2D floating-point array. + + Transformation flags, a combination of the DftFlag2 values + When the parameter != 0, the function assumes that + only the first nonzeroRows rows of the input array ( DFT_INVERSE is not set) + or only the first nonzeroRows of the output array ( DFT_INVERSE is set) contain non-zeros, + thus the function can handle the rest of the rows more efficiently and + thus save some time. This technique is very useful for computing array cross-correlation + or convolution using DFT + The destination array, which size and type depends on the flags + + + + performs forward or inverse 1D or 2D Discrete Cosine Transformation + + Transformation flags, a combination of DctFlag2 values + The destination array; will have the same size and same type as src + + + + performs inverse 1D or 2D Discrete Cosine Transformation + + Transformation flags, a combination of DctFlag2 values + The destination array; will have the same size and same type as src + + + + fills array with uniformly-distributed random numbers from the range [low, high) + + The inclusive lower boundary of the generated random numbers + The exclusive upper boundary of the generated random numbers + + + + fills array with uniformly-distributed random numbers from the range [low, high) + + The inclusive lower boundary of the generated random numbers + The exclusive upper boundary of the generated random numbers + + + + fills array with normally-distributed random numbers with the specified mean and the standard deviation + + The mean value (expectation) of the generated random numbers + The standard deviation of the generated random numbers + + + + fills array with normally-distributed random numbers with the specified mean and the standard deviation + + The mean value (expectation) of the generated random numbers + The standard deviation of the generated random numbers + + + + shuffles the input array elements + + The scale factor that determines the number of random swap operations. + The optional random number generator used for shuffling. + If it is null, theRng() is used instead. + The input/output numerical 1D array + + + + Draws a line segment connecting two points + + First point's x-coordinate of the line segment. + First point's y-coordinate of the line segment. + Second point's x-coordinate of the line segment. + Second point's y-coordinate of the line segment. + Line color. + Line thickness. [By default this is 1] + Type of the line. [By default this is LineType.Link8] + Number of fractional bits in the point coordinates. [By default this is 0] + + + + Draws a line segment connecting two points + + First point of the line segment. + Second point of the line segment. + Line color. + Line thickness. [By default this is 1] + Type of the line. [By default this is LineType.Link8] + Number of fractional bits in the point coordinates. [By default this is 0] + + + + Draws simple, thick or filled rectangle + + One of the rectangle vertices. + Opposite rectangle vertex. + Line color (RGB) or brightness (grayscale image). + Thickness of lines that make up the rectangle. Negative values make the function to draw a filled rectangle. [By default this is 1] + Type of the line, see cvLine description. [By default this is LineType.Link8] + Number of fractional bits in the point coordinates. [By default this is 0] + + + + Draws simple, thick or filled rectangle + + Rectangle. + Line color (RGB) or brightness (grayscale image). + Thickness of lines that make up the rectangle. Negative values make the function to draw a filled rectangle. [By default this is 1] + Type of the line, see cvLine description. [By default this is LineType.Link8] + Number of fractional bits in the point coordinates. [By default this is 0] + + + + Draws a circle + + X-coordinate of the center of the circle. + Y-coordinate of the center of the circle. + Radius of the circle. + Circle color. + Thickness of the circle outline if positive, otherwise indicates that a filled circle has to be drawn. [By default this is 1] + Type of the circle boundary. [By default this is LineType.Link8] + Number of fractional bits in the center coordinates and radius value. [By default this is 0] + + + + Draws a circle + + Center of the circle. + Radius of the circle. + Circle color. + Thickness of the circle outline if positive, otherwise indicates that a filled circle has to be drawn. [By default this is 1] + Type of the circle boundary. [By default this is LineType.Link8] + Number of fractional bits in the center coordinates and radius value. [By default this is 0] + + + + Draws simple or thick elliptic arc or fills ellipse sector + + Center of the ellipse. + Length of the ellipse axes. + Rotation angle. + Starting angle of the elliptic arc. + Ending angle of the elliptic arc. + Ellipse color. + Thickness of the ellipse arc. [By default this is 1] + Type of the ellipse boundary. [By default this is LineType.Link8] + Number of fractional bits in the center coordinates and axes' values. [By default this is 0] + + + + Draws simple or thick elliptic arc or fills ellipse sector + + The enclosing box of the ellipse drawn + Ellipse color. + Thickness of the ellipse boundary. [By default this is 1] + Type of the ellipse boundary. [By default this is LineType.Link8] + + + + Fills a convex polygon. + + The polygon vertices + Polygon color + Type of the polygon boundaries + The number of fractional bits in the vertex coordinates + + + + Fills the area bounded by one or more polygons + + Array of polygons, each represented as an array of points + Polygon color + Type of the polygon boundaries + The number of fractional bits in the vertex coordinates + + + + + draws one or more polygonal curves + + + + + + + + + + + renders text string in the image + + + + + + + + + + + + + Encodes an image into a memory buffer. + + Encodes an image into a memory buffer. + Format-specific parameters. + + + + + Encodes an image into a memory buffer. + + Encodes an image into a memory buffer. + Format-specific parameters. + + + + + Saves an image to a specified file. + + + + + + + + Saves an image to a specified file. + + + + + + + + Saves an image to a specified file. + + + + + + + + Saves an image to a specified file. + + + + + + + + Forms a border around the image + + Specify how much pixels in each direction from the source image rectangle one needs to extrapolate + Specify how much pixels in each direction from the source image rectangle one needs to extrapolate + Specify how much pixels in each direction from the source image rectangle one needs to extrapolate + Specify how much pixels in each direction from the source image rectangle one needs to extrapolate + The border type + The border value if borderType == Constant + + + + Smoothes image using median filter. + The source image must have 1-, 3- or 4-channel and + its depth should be CV_8U , CV_16U or CV_32F. + + The aperture linear size. It must be odd and more than 1, i.e. 3, 5, 7 ... + The destination array; will have the same size and the same type as src. + + + + Blurs an image using a Gaussian filter. + The input image can have any number of channels, which are processed independently, + but the depth should be CV_8U, CV_16U, CV_16S, CV_32F or CV_64F. + + Gaussian kernel size. ksize.width and ksize.height can differ but they both must be positive and odd. + Or, they can be zero’s and then they are computed from sigma* . + Gaussian kernel standard deviation in X direction. + Gaussian kernel standard deviation in Y direction; if sigmaY is zero, it is set to be equal to sigmaX, + if both sigmas are zeros, they are computed from ksize.width and ksize.height, + respectively (see getGaussianKernel() for details); to fully control the result + regardless of possible future modifications of all this semantics, it is recommended to specify all of ksize, sigmaX, and sigmaY. + pixel extrapolation method + + + + Applies bilateral filter to the image + The source image must be a 8-bit or floating-point, 1-channel or 3-channel image. + + The diameter of each pixel neighborhood, that is used during filtering. + If it is non-positive, it's computed from sigmaSpace + Filter sigma in the color space. + Larger value of the parameter means that farther colors within the pixel neighborhood + will be mixed together, resulting in larger areas of semi-equal color + Filter sigma in the coordinate space. + Larger value of the parameter means that farther pixels will influence each other + (as long as their colors are close enough; see sigmaColor). Then d>0 , it specifies + the neighborhood size regardless of sigmaSpace, otherwise d is proportional to sigmaSpace + + The destination image; will have the same size and the same type as src + + + + Applies the adaptive bilateral filter to an image. + + The kernel size. This is the neighborhood where the local variance will be calculated, + and where pixels will contribute (in a weighted manner). + Filter sigma in the coordinate space. + Larger value of the parameter means that farther pixels will influence each other + (as long as their colors are close enough; see sigmaColor). Then d>0, it specifies the neighborhood + size regardless of sigmaSpace, otherwise d is proportional to sigmaSpace. + Maximum allowed sigma color (will clamp the value calculated in the + ksize neighborhood. Larger value of the parameter means that more dissimilar pixels will + influence each other (as long as their colors are close enough; see sigmaColor). + Then d>0, it specifies the neighborhood size regardless of sigmaSpace, otherwise d is proportional to sigmaSpace. + The anchor point. The default value Point(-1,-1) means that the anchor is at the kernel center + Pixel extrapolation method. + The destination image; will have the same size and the same type as src + + + + Smoothes image using box filter + + + The smoothing kernel size + The anchor point. The default value Point(-1,-1) means that the anchor is at the kernel center + Indicates, whether the kernel is normalized by its area or not + The border mode used to extrapolate pixels outside of the image + The destination image; will have the same size and the same type as src + + + + Smoothes image using normalized box filter + + The smoothing kernel size + The anchor point. The default value Point(-1,-1) means that the anchor is at the kernel center + The border mode used to extrapolate pixels outside of the image + The destination image; will have the same size and the same type as src + + + + Convolves an image with the kernel + + The desired depth of the destination image. If it is negative, it will be the same as src.depth() + Convolution kernel (or rather a correlation kernel), + a single-channel floating point matrix. If you want to apply different kernels to + different channels, split the image into separate color planes using split() and process them individually + The anchor of the kernel that indicates the relative position of + a filtered point within the kernel. The anchor should lie within the kernel. + The special default value (-1,-1) means that the anchor is at the kernel center + The optional value added to the filtered pixels before storing them in dst + The pixel extrapolation method + The destination image. It will have the same size and the same number of channels as src + + + + Applies separable linear filter to an image + + The destination image depth + The coefficients for filtering each row + The coefficients for filtering each column + The anchor position within the kernel; The default value (-1, 1) means that the anchor is at the kernel center + The value added to the filtered results before storing them + The pixel extrapolation method + The destination image; will have the same size and the same number of channels as src + + + + Calculates the first, second, third or mixed image derivatives using an extended Sobel operator + + The destination image depth + Order of the derivative x + Order of the derivative y + Size of the extended Sobel kernel, must be 1, 3, 5 or 7 + The optional scale factor for the computed derivative values (by default, no scaling is applied + The optional delta value, added to the results prior to storing them in dst + The pixel extrapolation method + The destination image; will have the same size and the same number of channels as src + + + + Calculates the first x- or y- image derivative using Scharr operator + + The destination image depth + Order of the derivative x + Order of the derivative y + The optional scale factor for the computed derivative values (by default, no scaling is applie + The optional delta value, added to the results prior to storing them in dst + The pixel extrapolation method + The destination image; will have the same size and the same number of channels as src + + + + Calculates the Laplacian of an image + + The desired depth of the destination image + The aperture size used to compute the second-derivative filters + The optional scale factor for the computed Laplacian values (by default, no scaling is applied + The optional delta value, added to the results prior to storing them in dst + The pixel extrapolation method + Destination image; will have the same size and the same number of channels as src + + + + Finds edges in an image using Canny algorithm. + + The first threshold for the hysteresis procedure + The second threshold for the hysteresis procedure + Aperture size for the Sobel operator [By default this is ApertureSize.Size3] + Indicates, whether the more accurate L2 norm should be used to compute the image gradient magnitude (true), or a faster default L1 norm is enough (false). [By default this is false] + The output edge map. It will have the same size and the same type as image + + + + computes both eigenvalues and the eigenvectors of 2x2 derivative covariation matrix at each pixel. The output is stored as 6-channel matrix. + + + + + + + + computes another complex cornerness criteria at each pixel + + + + + + + adjusts the corner locations with sub-pixel accuracy to maximize the certain cornerness criteria + + Initial coordinates of the input corners and refined coordinates provided for output. + Half of the side length of the search window. + Half of the size of the dead region in the middle of the search zone + over which the summation in the formula below is not done. It is used sometimes to avoid possible singularities + of the autocorrelation matrix. The value of (-1,-1) indicates that there is no such a size. + Criteria for termination of the iterative process of corner refinement. + That is, the process of corner position refinement stops either after criteria.maxCount iterations + or when the corner position moves by less than criteria.epsilon on some iteration. + + + + + Finds the strong enough corners where the cornerMinEigenVal() or cornerHarris() report the local maxima. + Input matrix must be 8-bit or floating-point 32-bit, single-channel image. + + Maximum number of corners to return. If there are more corners than are found, + the strongest of them is returned. + Parameter characterizing the minimal accepted quality of image corners. + The parameter value is multiplied by the best corner quality measure, which is the minimal eigenvalue + or the Harris function response (see cornerHarris() ). The corners with the quality measure less than + the product are rejected. For example, if the best corner has the quality measure = 1500, and the qualityLevel=0.01, + then all the corners with the quality measure less than 15 are rejected. + Minimum possible Euclidean distance between the returned corners. + Optional region of interest. If the image is not empty + (it needs to have the type CV_8UC1 and the same size as image ), it specifies the region + in which the corners are detected. + Size of an average block for computing a derivative covariation matrix over each pixel neighborhood. + Parameter indicating whether to use a Harris detector + Free parameter of the Harris detector. + Output vector of detected corners. + + + + Finds lines in a binary image using standard Hough transform. + The input matrix must be 8-bit, single-channel, binary source image. + This image may be modified by the function. + + Distance resolution of the accumulator in pixels + Angle resolution of the accumulator in radians + The accumulator threshold parameter. Only those lines are returned that get enough votes ( > threshold ) + For the multi-scale Hough transform it is the divisor for the distance resolution rho. [By default this is 0] + For the multi-scale Hough transform it is the divisor for the distance resolution theta. [By default this is 0] + The output vector of lines. Each line is represented by a two-element vector (rho, theta) . + rho is the distance from the coordinate origin (0,0) (top-left corner of the image) and theta is the line rotation angle in radians + + + + Finds lines segments in a binary image using probabilistic Hough transform. + + Distance resolution of the accumulator in pixels + Angle resolution of the accumulator in radians + The accumulator threshold parameter. Only those lines are returned that get enough votes ( > threshold ) + The minimum line length. Line segments shorter than that will be rejected. [By default this is 0] + The maximum allowed gap between points on the same line to link them. [By default this is 0] + The output lines. Each line is represented by a 4-element vector (x1, y1, x2, y2) + + + + Finds circles in a grayscale image using a Hough transform. + The input matrix must be 8-bit, single-channel and grayscale. + + Currently, the only implemented method is HoughCirclesMethod.Gradient + The inverse ratio of the accumulator resolution to the image resolution. + Minimum distance between the centers of the detected circles. + The first method-specific parameter. [By default this is 100] + The second method-specific parameter. [By default this is 100] + Minimum circle radius. [By default this is 0] + Maximum circle radius. [By default this is 0] + The output vector found circles. Each vector is encoded as 3-element floating-point vector (x, y, radius) + + + + Dilates an image by using a specific structuring element. + + The structuring element used for dilation. If element=new Mat() , a 3x3 rectangular structuring element is used + Position of the anchor within the element. The default value (-1, -1) means that the anchor is at the element center + The number of times dilation is applied. [By default this is 1] + The pixel extrapolation method. [By default this is BorderType.Constant] + The border value in case of a constant border. The default value has a special meaning. [By default this is CvCpp.MorphologyDefaultBorderValue()] + The destination image. It will have the same size and the same type as src + + + + Erodes an image by using a specific structuring element. + + The structuring element used for dilation. If element=new Mat(), a 3x3 rectangular structuring element is used + Position of the anchor within the element. The default value (-1, -1) means that the anchor is at the element center + The number of times erosion is applied + The pixel extrapolation method + The border value in case of a constant border. The default value has a special meaning. [By default this is CvCpp.MorphologyDefaultBorderValue()] + The destination image. It will have the same size and the same type as src + + + + Performs advanced morphological transformations + + Type of morphological operation + Structuring element + Position of the anchor within the element. The default value (-1, -1) means that the anchor is at the element center + Number of times erosion and dilation are applied. [By default this is 1] + The pixel extrapolation method. [By default this is BorderType.Constant] + The border value in case of a constant border. The default value has a special meaning. [By default this is CvCpp.MorphologyDefaultBorderValue()] + Destination image. It will have the same size and the same type as src + + + + Resizes an image. + + output image size; if it equals zero, it is computed as: + dsize = Size(round(fx*src.cols), round(fy*src.rows)) + Either dsize or both fx and fy must be non-zero. + scale factor along the horizontal axis; when it equals 0, + it is computed as: (double)dsize.width/src.cols + scale factor along the vertical axis; when it equals 0, + it is computed as: (double)dsize.height/src.rows + interpolation method + output image; it has the size dsize (when it is non-zero) or the size computed + from src.size(), fx, and fy; the type of dst is the same as of src. + + + + Applies an affine transformation to an image. + + output image that has the size dsize and the same type as src. + 2x3 transformation matrix. + size of the output image. + combination of interpolation methods and the optional flag + WARP_INVERSE_MAP that means that M is the inverse transformation (dst -> src) . + pixel extrapolation method; when borderMode=BORDER_TRANSPARENT, + it means that the pixels in the destination image corresponding to the "outliers" + in the source image are not modified by the function. + value used in case of a constant border; by default, it is 0. + + + + Applies a perspective transformation to an image. + + 3x3 transformation matrix. + size of the output image. + combination of interpolation methods (INTER_LINEAR or INTER_NEAREST) + and the optional flag WARP_INVERSE_MAP, that sets M as the inverse transformation (dst -> src). + pixel extrapolation method (BORDER_CONSTANT or BORDER_REPLICATE). + value used in case of a constant border; by default, it equals 0. + output image that has the size dsize and the same type as src. + + + + Applies a generic geometrical transformation to an image. + + The first map of either (x,y) points or just x values having the type CV_16SC2, CV_32FC1, or CV_32FC2. + The second map of y values having the type CV_16UC1, CV_32FC1, or none (empty map if map1 is (x,y) points), respectively. + Interpolation method. The method INTER_AREA is not supported by this function. + Pixel extrapolation method. When borderMode=BORDER_TRANSPARENT, + it means that the pixels in the destination image that corresponds to the "outliers" in + the source image are not modified by the function. + Value used in case of a constant border. By default, it is 0. + Destination image. It has the same size as map1 and the same type as src + + + + Inverts an affine transformation. + + Output reverse affine transformation. + + + + Retrieves a pixel rectangle from an image with sub-pixel accuracy. + + Size of the extracted patch. + Floating point coordinates of the center of the extracted rectangle + within the source image. The center must be inside the image. + Depth of the extracted pixels. By default, they have the same depth as src. + Extracted patch that has the size patchSize and the same number of channels as src . + + + + Adds an image to the accumulator. + + Optional operation mask. + Accumulator image with the same number of channels as input image, 32-bit or 64-bit floating-point. + + + + Adds the square of a source image to the accumulator. + + Optional operation mask. + Accumulator image with the same number of channels as input image, 32-bit or 64-bit floating-point. + + + + Computes a Hanning window coefficients in two dimensions. + + The window size specifications + Created array type + + + + Applies a fixed-level threshold to each array element. + The input matrix must be single-channel, 8-bit or 32-bit floating point. + + threshold value. + maximum value to use with the THRESH_BINARY and THRESH_BINARY_INV thresholding types. + thresholding type (see the details below). + output array of the same size and type as src. + + + + Applies an adaptive threshold to an array. + Source matrix must be 8-bit single-channel image. + + Non-zero value assigned to the pixels for which the condition is satisfied. See the details below. + Adaptive thresholding algorithm to use, ADAPTIVE_THRESH_MEAN_C or ADAPTIVE_THRESH_GAUSSIAN_C . + Thresholding type that must be either THRESH_BINARY or THRESH_BINARY_INV . + Size of a pixel neighborhood that is used to calculate a threshold value for the pixel: 3, 5, 7, and so on. + Constant subtracted from the mean or weighted mean (see the details below). + Normally, it is positive but may be zero or negative as well. + Destination image of the same size and the same type as src. + + + + Blurs an image and downsamples it. + + size of the output image; by default, it is computed as Size((src.cols+1)/2 + + + + + + Upsamples an image and then blurs it. + + size of the output image; by default, it is computed as Size(src.cols*2, (src.rows*2) + + + + + + corrects lens distortion for the given camera matrix and distortion coefficients + + Input camera matrix + Input vector of distortion coefficients (k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6]]) of 4, 5, + or 8 elements. If the vector is null, the zero distortion coefficients are assumed. + Camera matrix of the distorted image. + By default, it is the same as cameraMatrix but you may additionally scale + and shift the result by using a different matrix. + Output (corrected) image that has the same size and type as src . + + + + returns the default new camera matrix (by default it is the same as cameraMatrix unless centerPricipalPoint=true) + + Camera view image size in pixels. + Location of the principal point in the new camera matrix. + The parameter indicates whether this location should be at the image center or not. + the camera matrix that is either an exact copy of the input cameraMatrix + (when centerPrinicipalPoint=false), or the modified one (when centerPrincipalPoint=true). + + + + Computes the ideal point coordinates from the observed point coordinates. + Input matrix is an observed point coordinates, 1xN or Nx1 2-channel (CV_32FC2 or CV_64FC2). + + Camera matrix + Input vector of distortion coefficients (k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6]]) of 4, 5, or 8 elements. + If the vector is null, the zero distortion coefficients are assumed. + Rectification transformation in the object space (3x3 matrix). + R1 or R2 computed by stereoRectify() can be passed here. + If the matrix is empty, the identity transformation is used. + New camera matrix (3x3) or new projection matrix (3x4). + P1 or P2 computed by stereoRectify() can be passed here. If the matrix is empty, + the identity new camera matrix is used. + Output ideal point coordinates after undistortion and reverse perspective transformation. + If matrix P is identity or omitted, dst will contain normalized point coordinates. + + + + Normalizes the grayscale image brightness and contrast by normalizing its histogram. + The source matrix is 8-bit single channel image. + + The destination image; will have the same size and the same type as src + + + + Performs a marker-based image segmentation using the watershed algorithm. + Input matrix is 8-bit 3-channel image. + + Input/output 32-bit single-channel image (map) of markers. + It should have the same size as image. + + + + Performs initial step of meanshift segmentation of an image. + The source matrix is 8-bit, 3-channel image. + + The spatial window radius. + The color window radius. + Maximum level of the pyramid for the segmentation. + Termination criteria: when to stop meanshift iterations. + The destination image of the same format and the same size as the source. + + + + Segments the image using GrabCut algorithm. + The input is 8-bit 3-channel image. + + Input/output 8-bit single-channel mask. + The mask is initialized by the function when mode is set to GC_INIT_WITH_RECT. + Its elements may have Cv2.GC_BGD / Cv2.GC_FGD / Cv2.GC_PR_BGD / Cv2.GC_PR_FGD + ROI containing a segmented object. The pixels outside of the ROI are + marked as "obvious background". The parameter is only used when mode==GC_INIT_WITH_RECT. + Temporary array for the background model. Do not modify it while you are processing the same image. + Temporary arrays for the foreground model. Do not modify it while you are processing the same image. + Number of iterations the algorithm should make before returning the result. + Note that the result can be refined with further calls with mode==GC_INIT_WITH_MASK or mode==GC_EVAL . + Operation mode that could be one of GrabCutFlag value. + + + + Fills a connected component with the given color. + Input/output 1- or 3-channel, 8-bit, or floating-point image. + It is modified by the function unless the FLOODFILL_MASK_ONLY flag is set in the + second variant of the function. See the details below. + + Starting point. + New value of the repainted domain pixels. + + + + + Fills a connected component with the given color. + Input/output 1- or 3-channel, 8-bit, or floating-point image. + It is modified by the function unless the FLOODFILL_MASK_ONLY flag is set in the + second variant of the function. See the details below. + + Starting point. + New value of the repainted domain pixels. + Optional output parameter set by the function to the + minimum bounding rectangle of the repainted domain. + Maximal lower brightness/color difference between the currently + observed pixel and one of its neighbors belonging to the component, or a seed pixel + being added to the component. + Maximal upper brightness/color difference between the currently + observed pixel and one of its neighbors belonging to the component, or a seed pixel + being added to the component. + Operation flags. Lower bits contain a connectivity value, + 4 (default) or 8, used within the function. Connectivity determines which + neighbors of a pixel are considered. + + + + + Fills a connected component with the given color. + Input/output 1- or 3-channel, 8-bit, or floating-point image. + It is modified by the function unless the FLOODFILL_MASK_ONLY flag is set in the + second variant of the function. See the details below. + + (For the second function only) Operation mask that should be a single-channel 8-bit image, + 2 pixels wider and 2 pixels taller. The function uses and updates the mask, so you take responsibility of + initializing the mask content. Flood-filling cannot go across non-zero pixels in the mask. For example, + an edge detector output can be used as a mask to stop filling at edges. It is possible to use the same mask + in multiple calls to the function to make sure the filled area does not overlap. + Starting point. + New value of the repainted domain pixels. + + + + + Fills a connected component with the given color. + Input/output 1- or 3-channel, 8-bit, or floating-point image. + It is modified by the function unless the FLOODFILL_MASK_ONLY flag is set in the + second variant of the function. See the details below. + + (For the second function only) Operation mask that should be a single-channel 8-bit image, + 2 pixels wider and 2 pixels taller. The function uses and updates the mask, so you take responsibility of + initializing the mask content. Flood-filling cannot go across non-zero pixels in the mask. For example, + an edge detector output can be used as a mask to stop filling at edges. It is possible to use the same mask + in multiple calls to the function to make sure the filled area does not overlap. + Starting point. + New value of the repainted domain pixels. + Optional output parameter set by the function to the + minimum bounding rectangle of the repainted domain. + Maximal lower brightness/color difference between the currently + observed pixel and one of its neighbors belonging to the component, or a seed pixel + being added to the component. + Maximal upper brightness/color difference between the currently + observed pixel and one of its neighbors belonging to the component, or a seed pixel + being added to the component. + Operation flags. Lower bits contain a connectivity value, + 4 (default) or 8, used within the function. Connectivity determines which + neighbors of a pixel are considered. + + + + + Converts image from one color space to another + + The color space conversion code + The number of channels in the destination image; if the parameter is 0, the number of the channels will be derived automatically from src and the code + The destination image; will have the same size and the same depth as src + + + + Calculates all of the moments + up to the third order of a polygon or rasterized shape. + The input is a raster image (single-channel, 8-bit or floating-point 2D array). + + If it is true, then all the non-zero image pixels are treated as 1’s + + + + + Computes the proximity map for the raster template and the image where the template is searched for + The input is Image where the search is running; should be 8-bit or 32-bit floating-point. + + Searched template; must be not greater than the source image and have the same data type + Specifies the comparison method + A map of comparison results; will be single-channel 32-bit floating-point. + If image is WxH and templ is wxh then result will be (W-w+1) x (H-h+1). + + + + Finds contours in a binary image. + The source is an 8-bit single-channel image. Non-zero pixels are treated as 1’s. + Zero pixels remain 0’s, so the image is treated as binary. The function modifies this image while extracting the contours. + + Detected contours. Each contour is stored as a vector of points. + Optional output vector, containing information about the image topology. + It has as many elements as the number of contours. For each i-th contour contours[i], + the members of the elements hierarchy[i] are set to 0-based indices in contours of the next + and previous contours at the same hierarchical level, the first child contour and the parent contour, respectively. + If for the contour i there are no next, previous, parent, or nested contours, the corresponding elements of hierarchy[i] will be negative. + Contour retrieval mode + Contour approximation method + Optional offset by which every contour point is shifted. + This is useful if the contours are extracted from the image ROI and then they should be analyzed in the whole image context. + + + + Finds contours in a binary image. + The source is an 8-bit single-channel image. Non-zero pixels are treated as 1’s. + Zero pixels remain 0’s, so the image is treated as binary. The function modifies this image while extracting the contours. + + Detected contours. Each contour is stored as a vector of points. + Optional output vector, containing information about the image topology. + It has as many elements as the number of contours. For each i-th contour contours[i], + the members of the elements hierarchy[i] are set to 0-based indices in contours of the next + and previous contours at the same hierarchical level, the first child contour and the parent contour, respectively. + If for the contour i there are no next, previous, parent, or nested contours, the corresponding elements of hierarchy[i] will be negative. + Contour retrieval mode + Contour approximation method + Optional offset by which every contour point is shifted. + This is useful if the contours are extracted from the image ROI and then they should be analyzed in the whole image context. + + + + Finds contours in a binary image. + The source is an 8-bit single-channel image. Non-zero pixels are treated as 1’s. + Zero pixels remain 0’s, so the image is treated as binary. The function modifies this image while extracting the contours. + + Contour retrieval mode + Contour approximation method + Optional offset by which every contour point is shifted. + This is useful if the contours are extracted from the image ROI and then they should be analyzed in the whole image context. + Detected contours. Each contour is stored as a vector of points. + + + + Finds contours in a binary image. + The source is an 8-bit single-channel image. Non-zero pixels are treated as 1’s. + Zero pixels remain 0’s, so the image is treated as binary. The function modifies this image while extracting the contours. + + Contour retrieval mode + Contour approximation method + Optional offset by which every contour point is shifted. + This is useful if the contours are extracted from the image ROI and then they should be analyzed in the whole image context. + Detected contours. Each contour is stored as a vector of points. + + + + Draws contours in the image + + All the input contours. Each contour is stored as a point vector. + Parameter indicating a contour to draw. If it is negative, all the contours are drawn. + Color of the contours. + Thickness of lines the contours are drawn with. If it is negative (for example, thickness=CV_FILLED ), + the contour interiors are drawn. + Line connectivity. + Optional information about hierarchy. It is only needed if you want to draw only some of the contours + Maximal level for drawn contours. If it is 0, only the specified contour is drawn. + If it is 1, the function draws the contour(s) and all the nested contours. If it is 2, the function draws the contours, + all the nested contours, all the nested-to-nested contours, and so on. This parameter is only taken into account + when there is hierarchy available. + Optional contour shift parameter. Shift all the drawn contours by the specified offset = (dx, dy) + + + + Draws contours in the image + + Destination image. + All the input contours. Each contour is stored as a point vector. + Parameter indicating a contour to draw. If it is negative, all the contours are drawn. + Color of the contours. + Thickness of lines the contours are drawn with. If it is negative (for example, thickness=CV_FILLED ), + the contour interiors are drawn. + Line connectivity. + Optional information about hierarchy. It is only needed if you want to draw only some of the contours + Maximal level for drawn contours. If it is 0, only the specified contour is drawn. + If it is 1, the function draws the contour(s) and all the nested contours. If it is 2, the function draws the contours, + all the nested contours, all the nested-to-nested contours, and so on. This parameter is only taken into account + when there is hierarchy available. + Optional contour shift parameter. Shift all the drawn contours by the specified offset = (dx, dy) + + + + Approximates contour or a curve using Douglas-Peucker algorithm. + The input is the polygon or curve to approximate and + it must be 1 x N or N x 1 matrix of type CV_32SC2 or CV_32FC2. + + Specifies the approximation accuracy. + This is the maximum distance between the original curve and its approximation. + The result of the approximation; + The type should match the type of the input curve + The result of the approximation; + The type should match the type of the input curve + + + + Calculates a contour perimeter or a curve length. + The input is 2D point set, represented by CV_32SC2 or CV_32FC2 matrix. + + Indicates, whether the curve is closed or not + + + + + Calculates the up-right bounding rectangle of a point set. + The input is 2D point set, represented by CV_32SC2 or CV_32FC2 matrix. + + Minimal up-right bounding rectangle for the specified point set. + + + + Calculates the contour area. + The input is 2D point set, represented by CV_32SC2 or CV_32FC2 matrix. + + + + + + + Finds the minimum area rotated rectangle enclosing a 2D point set. + The input is 2D point set, represented by CV_32SC2 or CV_32FC2 matrix. + + + + + + Finds the minimum area circle enclosing a 2D point set. + The input is 2D point set, represented by CV_32SC2 or CV_32FC2 matrix. + + The output center of the circle + The output radius of the circle + + + + Computes convex hull for a set of 2D points. + + The input 2D point set, represented by CV_32SC2 or CV_32FC2 matrix + If true, the output convex hull will be oriented clockwise, + otherwise it will be oriented counter-clockwise. Here, the usual screen coordinate + system is assumed - the origin is at the top-left corner, x axis is oriented to the right, + and y axis is oriented downwards. + + The output convex hull. It is either a vector of points that form the + hull (must have the same type as the input points), or a vector of 0-based point + indices of the hull points in the original array (since the set of convex hull + points is a subset of the original point set). + + + + Computes convex hull for a set of 2D points. + + The input 2D point set, represented by CV_32SC2 or CV_32FC2 matrix + If true, the output convex hull will be oriented clockwise, + otherwise it will be oriented counter-clockwise. Here, the usual screen coordinate + system is assumed - the origin is at the top-left corner, x axis is oriented to the right, + and y axis is oriented downwards. + The output convex hull. It is a vector of points that form the + hull (must have the same type as the input points). + + + + Computes convex hull for a set of 2D points. + + The input 2D point set, represented by CV_32SC2 or CV_32FC2 matrix + If true, the output convex hull will be oriented clockwise, + otherwise it will be oriented counter-clockwise. Here, the usual screen coordinate + system is assumed - the origin is at the top-left corner, x axis is oriented to the right, + and y axis is oriented downwards. + The output convex hull. It is a vector of points that form the + hull (must have the same type as the input points). + + + + Computes convex hull for a set of 2D points. + + The input 2D point set, represented by CV_32SC2 or CV_32FC2 matrix + If true, the output convex hull will be oriented clockwise, + otherwise it will be oriented counter-clockwise. Here, the usual screen coordinate + system is assumed - the origin is at the top-left corner, x axis is oriented to the right, + and y axis is oriented downwards. + The output convex hull. It is a vector of 0-based point + indices of the hull points in the original array (since the set of convex hull + points is a subset of the original point set). + + + + Computes the contour convexity defects + + Convex hull obtained using convexHull() that + should contain indices of the contour points that make the hull. + The output vector of convexity defects. + Each convexity defect is represented as 4-element integer vector + (a.k.a. cv::Vec4i): (start_index, end_index, farthest_pt_index, fixpt_depth), + where indices are 0-based indices in the original contour of the convexity defect beginning, + end and the farthest point, and fixpt_depth is fixed-point approximation + (with 8 fractional bits) of the distance between the farthest contour point and the hull. + That is, to get the floating-point value of the depth will be fixpt_depth/256.0. + + + + Computes the contour convexity defects + + Convex hull obtained using convexHull() that + should contain indices of the contour points that make the hull. + The output vector of convexity defects. + Each convexity defect is represented as 4-element integer vector + (a.k.a. cv::Vec4i): (start_index, end_index, farthest_pt_index, fixpt_depth), + where indices are 0-based indices in the original contour of the convexity defect beginning, + end and the farthest point, and fixpt_depth is fixed-point approximation + (with 8 fractional bits) of the distance between the farthest contour point and the hull. + That is, to get the floating-point value of the depth will be fixpt_depth/256.0. + + + + Returns true if the contour is convex. + Does not support contours with self-intersection + + + + + + Fits ellipse to the set of 2D points. + + + + + + Fits line to the set of 2D points using M-estimator algorithm. + The input is vector of 2D points. + + Distance used by the M-estimator + Numerical parameter ( C ) for some types of distances. + If it is 0, an optimal value is chosen. + Sufficient accuracy for the radius + (distance between the coordinate origin and the line). + Sufficient accuracy for the angle. + 0.01 would be a good default value for reps and aeps. + Output line parameters. + + + + Fits line to the set of 3D points using M-estimator algorithm. + The input is vector of 3D points. + + Distance used by the M-estimator + Numerical parameter ( C ) for some types of distances. + If it is 0, an optimal value is chosen. + Sufficient accuracy for the radius + (distance between the coordinate origin and the line). + Sufficient accuracy for the angle. + 0.01 would be a good default value for reps and aeps. + Output line parameters. + + + + Checks if the point is inside the contour. + Optionally computes the signed distance from the point to the contour boundary. + + Point tested against the contour. + If true, the function estimates the signed distance + from the point to the nearest contour edge. Otherwise, the function only checks + if the point is inside a contour or not. + Positive (inside), negative (outside), or zero (on an edge) value. + + + + computes the distance transform map + + + + + + + Creates from native cv::Mat* pointer + + + + + + Creates empty Mat + + + + + Loads an image from a file. (cv::imread) + + Name of file to be loaded. + Specifies color type of the loaded image + + + + constructs 2D matrix of the specified size and type + + Number of rows in a 2D array. + Number of columns in a 2D array. + Array type. Use MatType.CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, + or MatType. CV_8UC(n), ..., CV_64FC(n) to create multi-channel matrices. + + + + constructs 2D matrix of the specified size and type + + 2D array size: Size(cols, rows) . In the Size() constructor, + the number of rows and the number of columns go in the reverse order. + Array type. Use MatType.CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, + or MatType.CV_8UC(n), ..., CV_64FC(n) to create multi-channel matrices. + + + + constucts 2D matrix and fills it with the specified Scalar value. + + Number of rows in a 2D array. + Number of columns in a 2D array. + Array type. Use MatType.CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, + or MatType. CV_8UC(n), ..., CV_64FC(n) to create multi-channel matrices. + An optional value to initialize each matrix element with. + To set all the matrix elements to the particular value after the construction, use SetTo(Scalar s) method . + + + + constucts 2D matrix and fills it with the specified Scalar value. + + 2D array size: Size(cols, rows) . In the Size() constructor, + the number of rows and the number of columns go in the reverse order. + Array type. Use MatType.CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, + or CV_8UC(n), ..., CV_64FC(n) to create multi-channel (up to CV_CN_MAX channels) matrices. + An optional value to initialize each matrix element with. + To set all the matrix elements to the particular value after the construction, use SetTo(Scalar s) method . + + + + creates a matrix header for a part of the bigger matrix + + Array that (as a whole or partly) is assigned to the constructed matrix. + No data is copied by these constructors. Instead, the header pointing to m data or its sub-array + is constructed and associated with it. The reference counter, if any, is incremented. + So, when you modify the matrix formed using such a constructor, you also modify the corresponding elements of m . + If you want to have an independent copy of the sub-array, use Mat::clone() . + Range of the m rows to take. As usual, the range start is inclusive and the range end is exclusive. + Use Range.All to take all the rows. + Range of the m columns to take. Use Range.All to take all the columns. + + + + creates a matrix header for a part of the bigger matrix + + Array that (as a whole or partly) is assigned to the constructed matrix. + No data is copied by these constructors. Instead, the header pointing to m data or its sub-array + is constructed and associated with it. The reference counter, if any, is incremented. + So, when you modify the matrix formed using such a constructor, you also modify the corresponding elements of m . + If you want to have an independent copy of the sub-array, use Mat.Clone() . + Array of selected ranges of m along each dimensionality. + + + + creates a matrix header for a part of the bigger matrix + + Array that (as a whole or partly) is assigned to the constructed matrix. + No data is copied by these constructors. Instead, the header pointing to m data or its sub-array + is constructed and associated with it. The reference counter, if any, is incremented. + So, when you modify the matrix formed using such a constructor, you also modify the corresponding elements of m . + If you want to have an independent copy of the sub-array, use Mat.Clone() . + Region of interest. + + + + constructor for matrix headers pointing to user-allocated data + + Number of rows in a 2D array. + Number of columns in a 2D array. + Array type. Use MatType.CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, + or MatType. CV_8UC(n), ..., CV_64FC(n) to create multi-channel matrices. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Number of bytes each matrix row occupies. The value should include the padding bytes at the end of each row, if any. + If the parameter is missing (set to AUTO_STEP ), no padding is assumed and the actual step is calculated as cols*elemSize() . + + + + constructor for matrix headers pointing to user-allocated data + + Number of rows in a 2D array. + Number of columns in a 2D array. + Array type. Use MatType.CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, + or MatType. CV_8UC(n), ..., CV_64FC(n) to create multi-channel matrices. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Number of bytes each matrix row occupies. The value should include the padding bytes at the end of each row, if any. + If the parameter is missing (set to AUTO_STEP ), no padding is assumed and the actual step is calculated as cols*elemSize() . + + + + constructor for matrix headers pointing to user-allocated data + + Array of integers specifying an n-dimensional array shape. + Array type. Use MatType.CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, + or MatType. CV_8UC(n), ..., CV_64FC(n) to create multi-channel matrices. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Array of ndims-1 steps in case of a multi-dimensional array (the last step is always set to the element size). + If not specified, the matrix is assumed to be continuous. + + + + constructor for matrix headers pointing to user-allocated data + + Array of integers specifying an n-dimensional array shape. + Array type. Use MatType.CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, + or MatType. CV_8UC(n), ..., CV_64FC(n) to create multi-channel matrices. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Array of ndims-1 steps in case of a multi-dimensional array (the last step is always set to the element size). + If not specified, the matrix is assumed to be continuous. + + + + constructs n-dimensional matrix + + Array of integers specifying an n-dimensional array shape. + Array type. Use MatType.CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, + or MatType. CV_8UC(n), ..., CV_64FC(n) to create multi-channel matrices. + + + + constructs n-dimensional matrix + + Array of integers specifying an n-dimensional array shape. + Array type. Use MatType.CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, + or MatType. CV_8UC(n), ..., CV_64FC(n) to create multi-channel matrices. + An optional value to initialize each matrix element with. + To set all the matrix elements to the particular value after the construction, use SetTo(Scalar s) method . + + + + converts old-style CvMat to the new matrix; the data is not copied by default + + Old style CvMat object + Flag to specify whether the underlying data of the the old-style CvMat should be + copied to (true) or shared with (false) the newly constructed matrix. When the data is copied, + the allocated buffer is managed using Mat reference counting mechanism. While the data is shared, + the reference counter is NULL, and you should not deallocate the data until the matrix is not destructed. + + + + converts old-style IplImage to the new matrix; the data is not copied by default + + Old style IplImage object + Flag to specify whether the underlying data of the the old-style IplImage should be + copied to (true) or shared with (false) the newly constructed matrix. When the data is copied, + the allocated buffer is managed using Mat reference counting mechanism. While the data is shared, + the reference counter is NULL, and you should not deallocate the data until the matrix is not destructed. + + + + Releases the resources + + + + + Releases the resources + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + Creates the Mat instance from System.IO.Stream + + + + + + + + Creates the Mat instance from image data (using cv::imdecode) + + + + + + + + Creates the Mat instance from image data (using cv::imdecode) + + + + + + + + sizeof(cv::Mat) + + + + + Extracts a diagonal from a matrix, or creates a diagonal matrix. + + + + + + + Returns an identity matrix of the specified size and type. + + Alternative to the matrix size specification Size(cols, rows) . + Created matrix type. + + + + + Returns an identity matrix of the specified size and type. + + Number of rows. + Number of columns. + Created matrix type. + + + + + Returns an array of all 1’s of the specified size and type. + + Number of rows. + Number of columns. + Created matrix type. + + + + + Returns an array of all 1’s of the specified size and type. + + Alternative to the matrix size specification Size(cols, rows) . + Created matrix type. + + + + + Returns an array of all 1’s of the specified size and type. + + Created matrix type. + Array of integers specifying the array shape. + + + + + Returns a zero array of the specified size and type. + + Number of rows. + Number of columns. + Created matrix type. + + + + + Returns a zero array of the specified size and type. + + Alternative to the matrix size specification Size(cols, rows) . + Created matrix type. + + + + + Returns a zero array of the specified size and type. + + Created matrix type. + + + + + + Creates the IplImage clone instance for the matrix. + + + + + + + Creates the IplImage clone instance or header for the matrix. + + If true, this method returns an IplImage that is adjusted alignment; + otherwise, a header of IplImage is returned. + + + + + Creates the CvMat clone instance for the matrix. + + + + + + + Creates the CvMat header or clone instance for the matrix. + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + operator < + + + + + + + operator < + + + + + + + operator <= + + + + + + + operator <= + + + + + + + operator == + + + + + + + operator == + + + + + + + operator != + + + + + + + operator != + + + + + + + operator > + + + + + + + operator > + + + + + + + operator >= + + + + + + + operator >= + + + + + + + Extracts a rectangular submatrix. + + Start row of the extracted submatrix. The upper boundary is not included. + End row of the extracted submatrix. The upper boundary is not included. + Start column of the extracted submatrix. The upper boundary is not included. + End column of the extracted submatrix. The upper boundary is not included. + + + + + Extracts a rectangular submatrix. + + Start and end row of the extracted submatrix. The upper boundary is not included. + To select all the rows, use Range.All(). + Start and end column of the extracted submatrix. + The upper boundary is not included. To select all the columns, use Range.All(). + + + + + Extracts a rectangular submatrix. + + Extracted submatrix specified as a rectangle. + + + + + Extracts a rectangular submatrix. + + Array of selected ranges along each array dimension. + + + + + + + + + + + + + + + + Extracts a rectangular submatrix. + + Start row of the extracted submatrix. The upper boundary is not included. + End row of the extracted submatrix. The upper boundary is not included. + Start column of the extracted submatrix. The upper boundary is not included. + End column of the extracted submatrix. The upper boundary is not included. + + + + + Extracts a rectangular submatrix. + + Start and end row of the extracted submatrix. The upper boundary is not included. + To select all the rows, use Range.All(). + Start and end column of the extracted submatrix. + The upper boundary is not included. To select all the columns, use Range.All(). + + + + + Extracts a rectangular submatrix. + + Extracted submatrix specified as a rectangle. + + + + + Extracts a rectangular submatrix. + + Array of selected ranges along each array dimension. + + + + + Indexer to access partial Mat as MatExpr + + + + + + Mat column's indexer object + + + + + + + + + + + Creates a matrix header for the specified matrix column. + + A 0-based column index. + + + + + Creates a matrix header for the specified column span. + + An inclusive 0-based start index of the column span. + An exclusive 0-based ending index of the column span. + + + + + Indexer to access Mat column as MatExpr + + + + + + Mat row's indexer object + + + + + + + + + + + Creates a matrix header for the specified matrix row. [Mat::row] + + A 0-based row index. + + + + + Creates a matrix header for the specified row span. (Mat::rowRange) + + An inclusive 0-based start index of the row span. + An exclusive 0-based ending index of the row span. + + + + + Indexer to access Mat row as MatExpr + + + + + + Adjusts a submatrix size and position within the parent matrix. + + Shift of the top submatrix boundary upwards. + Shift of the bottom submatrix boundary downwards. + Shift of the left submatrix boundary to the left. + Shift of the right submatrix boundary to the right. + + + + + Provides a functional form of convertTo. + + Destination array. + Desired destination array depth (or -1 if it should be the same as the source type). + + + + Provides a functional form of convertTo. + + Destination array. + + + + Returns the number of matrix channels. + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Creates a full copy of the matrix. + + + + + + Returns the partial Mat of the specified Mat + + + + + + + the number of columns or -1 when the array has more than 2 dimensions + + + + + + the number of columns or -1 when the array has more than 2 dimensions + + + + + + the array dimensionality, >= 2 + + + + + Converts an array to another data type with optional scaling. + + output matrix; if it does not have a proper size or type before the operation, it is reallocated. + desired output matrix type or, rather, the depth since the number of channels are the same as the input has; + if rtype is negative, the output matrix will have the same type as the input. + optional scale factor. + optional delta added to the scaled values. + + + + Copies the matrix to another one. + + Destination matrix. If it does not have a proper size or type before the operation, it is reallocated. + + + + Copies the matrix to another one. + + Destination matrix. If it does not have a proper size or type before the operation, it is reallocated. + Operation mask. Its non-zero elements indicate which matrix elements need to be copied. + + + + Allocates new array data if needed. + + New number of rows. + New number of columns. + New matrix type. + + + + Allocates new array data if needed. + + Alternative new matrix size specification: Size(cols, rows) + New matrix type. + + + + Allocates new array data if needed. + + Array of integers specifying a new array shape. + New matrix type. + + + + Computes a cross-product of two 3-element vectors. + + Another cross-product operand. + + + + + pointer to the data + + + + + unsafe pointer to the data + + + + + The pointer that is possible to compute a relative sub-array position in the main container array using locateROI() + + + + + The pointer that is possible to compute a relative sub-array position in the main container array using locateROI() + + + + + The pointer that is possible to compute a relative sub-array position in the main container array using locateROI() + + + + + Returns the depth of a matrix element. + + + + + + Single-column matrix that forms a diagonal matrix or index of the diagonal, with the following values: + + Single-column matrix that forms a diagonal matrix or index of the diagonal, with the following values: + + + + + Computes a dot-product of two vectors. + + another dot-product operand. + + + + + Returns the matrix element size in bytes. + + + + + + Returns the size of each matrix element channel in bytes. + + + + + + Returns true if the array has no elements. + + + + + + Inverses a matrix. + + Matrix inversion method + + + + + Reports whether the matrix is continuous or not. + + + + + + Returns whether this matrix is a part of other matrix or not. + + + + + + Locates the matrix header within a parent matrix. + + Output parameter that contains the size of the whole matrix containing *this as a part. + Output parameter that contains an offset of *this inside the whole matrix. + + + + Performs an element-wise multiplication or division of the two matrices. + + + + + + + + pointer to the reference counter; + when matrix points to user-allocated data, the pointer is NULL + + pointer to the reference counter + + + + Changes the shape and/or the number of channels of a 2D matrix without copying the data. + + New number of channels. If the parameter is 0, the number of channels remains the same. + New number of rows. If the parameter is 0, the number of rows remains the same. + + + + + Changes the shape and/or the number of channels of a 2D matrix without copying the data. + + New number of channels. If the parameter is 0, the number of channels remains the same. + New number of rows. If the parameter is 0, the number of rows remains the same. + + + + + the number of rows or -1 when the array has more than 2 dimensions + + + + + the number of rows or -1 when the array has more than 2 dimensions + + + + + + Sets all or some of the array elements to the specified value. + + + + + + + + Sets all or some of the array elements to the specified value. + + + + + + + + Returns a matrix size. + + + + + + Returns a matrix size. + + + + + + + + + + + + + + + + + + + + Returns a normalized step. + + + + + + Returns a normalized step. + + + + + + + Transposes a matrix. + + + + + + Returns the total number of array elements. + + + + + + Returns the type of a matrix element. + + + + + + Returns a string that represents this Mat. + + + + + + Returns a string that represents each element value of Mat. + This method corresponds to std::ostream << Mat + + + + + + + Makes a Mat that have the same size, depth and channels as this image + + + + + + Returns a pointer to the specified matrix row. + + Index along the dimension 0 + + + + + Returns a pointer to the specified matrix element. + + Index along the dimension 0 + Index along the dimension 1 + + + + + Returns a pointer to the specified matrix element. + + Index along the dimension 0 + Index along the dimension 1 + Index along the dimension 2 + + + + + Returns a pointer to the specified matrix element. + + Array of Mat::dims indices. + + + + + Mat Indexer + + + + + + 1-dimensional indexer + + Index along the dimension 0 + A value to the specified array element. + + + + 2-dimensional indexer + + Index along the dimension 0 + Index along the dimension 1 + A value to the specified array element. + + + + 3-dimensional indexer + + Index along the dimension 0 + Index along the dimension 1 + Index along the dimension 2 + A value to the specified array element. + + + + n-dimensional indexer + + Array of Mat::dims indices. + A value to the specified array element. + + + + Gets a type-specific indexer. The indexer has getters/setters to access each matrix element. + + + + + + + Returns a value to the specified array element. + + + Index along the dimension 0 + A value to the specified array element. + + + + Returns a value to the specified array element. + + + Index along the dimension 0 + Index along the dimension 1 + A value to the specified array element. + + + + Returns a value to the specified array element. + + + Index along the dimension 0 + Index along the dimension 1 + Index along the dimension 2 + A value to the specified array element. + + + + Returns a value to the specified array element. + + + Array of Mat::dims indices. + A value to the specified array element. + + + + Returns a value to the specified array element. + + + Index along the dimension 0 + A value to the specified array element. + + + + Returns a value to the specified array element. + + + Index along the dimension 0 + Index along the dimension 1 + A value to the specified array element. + + + + Returns a value to the specified array element. + + + Index along the dimension 0 + Index along the dimension 1 + Index along the dimension 2 + A value to the specified array element. + + + + Returns a value to the specified array element. + + + Array of Mat::dims indices. + A value to the specified array element. + + + + Set a value to the specified array element. + + + Index along the dimension 0 + + + + + Set a value to the specified array element. + + + Index along the dimension 0 + Index along the dimension 1 + + + + + Set a value to the specified array element. + + + Index along the dimension 0 + Index along the dimension 1 + Index along the dimension 2 + + + + + Set a value to the specified array element. + + + Array of Mat::dims indices. + + + + + + + + + + + + + + + + + + + + Mat column's indexer object + + + + + + + + + + + Creates a matrix header for the specified matrix column. + + A 0-based column index. + + + + + Creates a matrix header for the specified column span. + + An inclusive 0-based start index of the column span. + An exclusive 0-based ending index of the column span. + + + + + Indexer to access Mat column as Mat + + + + + + + + + + + + + + + + + + + + + Mat row's indexer object + + + + + + + + + + + Creates a matrix header for the specified matrix column. + + A 0-based column index. + + + + + Creates a matrix header for the specified column span. + + An inclusive 0-based start index of the column span. + An exclusive 0-based ending index of the column span. + + + + + Indexer to access Mat row as Mat + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Get the data of this matrix as array + + + + + + + + Get the data of this matrix as array + + + + + + + + Get the data of this matrix as array + + + + + + + + Get the data of this matrix as array + + + + + + + + Get the data of this matrix as array + + + + + + + + Get the data of this matrix as array + + + + + + + + Get the data of this matrix as array + + + + + + + + Get the data of this matrix as array + + + + + + + + Get the data of this matrix as array + + + + + + + + Get the data of this matrix as array + + + + + + + + Get the data of this matrix as array + + + + + + + + Get the data of this matrix as array + + + + + + + + Get the data of this matrix as array + + + + + + + + Get the data of this matrix as array + + + + + + + + Get the data of this matrix as array + + + + + + + + Get the data of this matrix as array + + + + + + + + Get the data of this matrix as array + + + + + + + + Get the data of this matrix as array + + + + + + + + Get the data of this matrix as array + + + + + + + + Get the data of this matrix as array + + + + + + + + Get the data of this matrix as array + + + + + + + + Get the data of this matrix as array + + + + + + + + Get the data of this matrix as array + + + + + + + + Get the data of this matrix as array + + + + + + + + Get the data of this matrix as array + + + + + + + + Get the data of this matrix as array + + + + + + + + Get the data of this matrix as array + + + + + + + + Get the data of this matrix as array + + + + + + + + Get the data of this matrix as array + + + + + + + + Get the data of this matrix as array + + + + + + + + Get the data of this matrix as array + + + + + + + + Get the data of this matrix as array + + + + + + + + Get the data of this matrix as array + + + + + + + + Get the data of this matrix as array + + + + + + + + Get the data of this matrix as array + + + + + + + + Get the data of this matrix as array + + + + + + + + Get the data of this matrix as array + + + + + + + + Get the data of this matrix as array + + + + + + + + Get the data of this matrix as array + + + + + + + + Set the specified array data to this matrix + + + + + + + + Set the specified array data to this matrix + + + + + + + + Set the specified array data to this matrix + + + + + + + + Set the specified array data to this matrix + + + + + + + + Set the specified array data to this matrix + + + + + + + + Set the specified array data to this matrix + + + + + + + + Set the specified array data to this matrix + + + + + + + + Set the specified array data to this matrix + + + + + + + + Set the specified array data to this matrix + + + + + + + + Set the specified array data to this matrix + + + + + + + + Set the specified array data to this matrix + + + + + + + + Set the specified array data to this matrix + + + + + + + + Set the specified array data to this matrix + + + + + + + + Set the specified array data to this matrix + + + + + + + + Set the specified array data to this matrix + + + + + + + + Set the specified array data to this matrix + + + + + + + + Set the specified array data to this matrix + + + + + + + + Set the specified array data to this matrix + + + + + + + + Set the specified array data to this matrix + + + + + + + + Set the specified array data to this matrix + + + + + + + + Set the specified array data to this matrix + + + + + + + + Set the specified array data to this matrix + + + + + + + + Set the specified array data to this matrix + + + + + + + + Set the specified array data to this matrix + + + + + + + + Set the specified array data to this matrix + + + + + + + + Set the specified array data to this matrix + + + + + + + + Set the specified array data to this matrix + + + + + + + + Set the specified array data to this matrix + + + + + + + + Set the specified array data to this matrix + + + + + + + + Set the specified array data to this matrix + + + + + + + + Set the specified array data to this matrix + + + + + + + + Set the specified array data to this matrix + + + + + + + + Set the specified array data to this matrix + + + + + + + + Set the specified array data to this matrix + + + + + + + + Set the specified array data to this matrix + + + + + + + + Set the specified array data to this matrix + + + + + + + + Set the specified array data to this matrix + + + + + + + + Set the specified array data to this matrix + + + + + + + + reserves enough space to fit sz hyper-planes + + + + + + resizes matrix to the specified number of hyper-planes + + + + + + resizes matrix to the specified number of hyper-planes; initializes the newly added elements + + + + + + + Adds elements to the bottom of the matrix. (Mat.push_back) + + Added line(s) + + + + Adds elements to the bottom of the matrix. (Mat.push_back) + + Added line(s) + + + + removes several hyper-planes from bottom of the matrix (Mat.pop_back) + + + + + + Encodes an image into a memory buffer. + + Encodes an image into a memory buffer. + Format-specific parameters. + + + + + Encodes an image into a memory buffer. + + Encodes an image into a memory buffer. + Format-specific parameters. + + + + + Converts Mat to System.IO.MemoryStream + + + + + + + + Writes image data encoded from this Mat to System.IO.Stream + + + + + + + + + + + + + + + + Creates type-specific Mat instance from this. + + + + + + + Proxy datatype for passing Mat's and List<>'s as output parameters + + + + + + + + + + + + + + + + + + + + + + + + + + + + Proxy datatype for passing Mat's and List<>'s as output parameters + + + + + + + + + + + + + + + + + + + + + + Mersenne Twister random number generator + + operations.hpp + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + updates the state and returns the next 32-bit unsigned integer random number + + + + + + returns a random integer sampled uniformly from [0, N). + + + + + + + + + + + + + returns uniformly distributed integer random number from [a,b) range + + + + + + + + returns uniformly distributed floating-point random number from [a,b) range + + + + + + + + returns uniformly distributed double-precision floating-point random number from [a,b) range + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + sizeof(Rect) + + + + + Represents a CvRect structure with its properties left uninitialized. + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Specifies whether this object contains the same members as the specified Object. + + The Object to test. + This method returns true if obj is the same type as this object and has the same members as this object. + + + + Compares two Rectf objects. The result specifies whether the members of each object are equal. + + A Point to compare. + A Point to compare. + This operator returns true if the members of left and right are equal; otherwise, false. + + + + Compares two Rectf objects. The result specifies whether the members of each object are unequal. + + A Point to compare. + A Point to compare. + This operator returns true if the members of left and right are unequal; otherwise, false. + + + + Shifts rectangle by a certain offset + + + + + + + + Shifts rectangle by a certain offset + + + + + + + + Expands or shrinks rectangle by a certain amount + + + + + + + + Expands or shrinks rectangle by a certain amount + + + + + + + + Determines the CvRect structure that represents the intersection of two rectangles. + + A rectangle to intersect. + A rectangle to intersect. + + + + + Gets a CvRect structure that contains the union of two CvRect structures. + + A rectangle to union. + A rectangle to union. + + + + + Gets the y-coordinate of the top edge of this CvRect structure. + + + + + Gets the y-coordinate that is the sum of the Y and Height property values of this CvRect structure. + + + + + Gets the x-coordinate of the left edge of this CvRect structure. + + + + + Gets the x-coordinate that is the sum of X and Width property values of this CvRect structure. + + + + + Coordinate of the left-most rectangle corner [Point2f(X, Y)] + + + + + Size of the rectangle [CvSize(Width, Height)] + + + + + Coordinate of the left-most rectangle corner [Point2f(X, Y)] + + + + + Coordinate of the right-most rectangle corner [Point2f(X+Width, Y+Height)] + + + + + Determines if the specified point is contained within the rectangular region defined by this Rectangle. + + x-coordinate of the point + y-coordinate of the point + + + + + Determines if the specified point is contained within the rectangular region defined by this Rectangle. + + point + + + + + Determines if the specified rectangle is contained within the rectangular region defined by this Rectangle. + + rectangle + + + + + Inflates this Rect by the specified amount. + + The amount to inflate this Rectangle horizontally. + The amount to inflate this Rectangle vertically. + + + + Inflates this Rect by the specified amount. + + The amount to inflate this rectangle. + + + + Creates and returns an inflated copy of the specified CvRect structure. + + The Rectangle with which to start. This rectangle is not modified. + The amount to inflate this Rectangle horizontally. + The amount to inflate this Rectangle vertically. + + + + + Determines the CvRect structure that represents the intersection of two rectangles. + + A rectangle to intersect. + A rectangle to intersect. + + + + + Determines the CvRect structure that represents the intersection of two rectangles. + + A rectangle to intersect. + + + + + Determines if this rectangle intersects with rect. + + Rectangle + + + + + Gets a CvRect structure that contains the union of two CvRect structures. + + A rectangle to union. + + + + + Gets a CvRect structure that contains the union of two CvRect structures. + + A rectangle to union. + A rectangle to union. + + + + + Specifies whether this object contains the same members as the specified Object. + + The Object to test. + This method returns true if obj is the same type as this object and has the same members as this object. + + + + Returns a hash code for this object. + + An integer value that specifies a hash value for this object. + + + + Converts this object to a human readable string. + + A string that represents this object. + + + + Brute-force descriptor matcher. + For each descriptor in the first set, this matcher finds the closest descriptor in the second set by trying each one. + + + + + The constructor. + + Descriptor extractor that is used to compute descriptors for an input image and its keypoints. + Descriptor matcher that is used to find the nearest word of the trained vocabulary for each keypoint descriptor of the image. + + + + Releases the resources + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + Sets a visual vocabulary. + + Vocabulary (can be trained using the inheritor of BOWTrainer ). + Each row of the vocabulary is a visual word(cluster center). + + + + Returns the set vocabulary. + + + + + + Computes an image descriptor using the set visual vocabulary. + + Image, for which the descriptor is computed. + Keypoints detected in the input image. + Computed output image descriptor. + pointIdxsOfClusters Indices of keypoints that belong to the cluster. + This means that pointIdxsOfClusters[i] are keypoint indices that belong to the i -th cluster(word of vocabulary) returned if it is non-zero. + Descriptors of the image keypoints that are returned if they are non-zero. + + + + Computes an image descriptor using the set visual vocabulary. + + Image, for which the descriptor is computed. + Keypoints detected in the input image. + Computed output image descriptor. + + + + Returns an image descriptor size if the vocabulary is set. Otherwise, it returns 0. + + + + + + Returns an image descriptor type. + + + + + + Brute-force descriptor matcher. + For each descriptor in the first set, this matcher finds the closest descriptor in the second set by trying each one. + + + + + + + + + + + + + + Releases the resources + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + Clusters train descriptors. + + + + + + Clusters train descriptors. + + Descriptors to cluster. Each row of the descriptors matrix is a descriptor. Descriptors are not added to the inner train descriptor set. + The vocabulary consists of cluster centers. So, this method returns the vocabulary. In the first variant of the method, train descriptors stored in the object + are clustered.In the second variant, input descriptors are clustered. + + + + + Brute-force descriptor matcher. + For each descriptor in the first set, this matcher finds the closest descriptor in the second set by trying each one. + + + + + Adds descriptors to a training set. + + descriptors Descriptors to add to a training set. Each row of the descriptors matrix is a descriptor. + The training set is clustered using clustermethod to construct the vocabulary. + + + + Returns a training set of descriptors. + + + + + + Returns the count of all descriptors stored in the training set. + + + + + + + + + + + Clusters train descriptors. + + + + + + Clusters train descriptors. + + Descriptors to cluster. Each row of the descriptors matrix is a descriptor. Descriptors are not added to the inner train descriptor set. + The vocabulary consists of cluster centers. So, this method returns the vocabulary. In the first variant of the method, train descriptors stored in the object + are clustered.In the second variant, input descriptors are clustered. + + + + + Brute-force descriptor matcher. + For each descriptor in the first set, this matcher finds the closest descriptor in the second set by trying each one. + + + + + + + + + + + + Creates instance by cv::Ptr<T> + + + + + Creates instance by raw pointer T* + + + + + Creates instance from cv::Ptr<T> . + ptr is disposed when the wrapper disposes. + + + + + + Releases the resources + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + Return true if the matcher supports mask in match methods. + + + + + + Pointer to algorithm information (cv::AlgorithmInfo*) + + + + + + Add descriptors to train descriptor collection. + + Descriptors to add. Each descriptors[i] is a descriptors set from one image. + + + + Clear train descriptors collection. + + + + + Train matcher (e.g. train flann index). + In all methods to match the method train() is run every time before matching. + Some descriptor matchers (e.g. BruteForceMatcher) have empty implementation + of this method, other matchers really train their inner structures + (e.g. FlannBasedMatcher trains flann::Index). So nonempty implementation + of train() should check the class object state and do traing/retraining + only if the state requires that (e.g. FlannBasedMatcher trains flann::Index + if it has not trained yet or if new descriptors have been added to the train collection). + + + + + BRIEF Descriptor + + + + + cv::Ptr<DescriptorExtractor> + + + + + bytes is a length of descriptor in bytes. It can be equal 16, 32 or 64 bytes. + + + + + + + + + + + Creates instance from cv::Ptr<T> . + ptr is disposed when the wrapper disposes. + + + + + + Creates instance from raw T* + + + + + + Releases the resources + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + Pointer to algorithm information (cv::AlgorithmInfo*) + + + + + + + + + + + + + + + + + + Abstract base class for computing descriptors for image keypoints. + + + + + cv::Ptr<DescriptorExtractor> + + + + + + + + + + Creates instance from cv::Ptr<T> . + ptr is disposed when the wrapper disposes. + + + + + + Creates instance from raw T* + + + + + + Releases the resources + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + Compute the descriptors for a set of keypoints in an image. + + The image. + The input keypoints. Keypoints for which a descriptor cannot be computed are removed. + Copmputed descriptors. Row i is the descriptor for keypoint i.param> + + + + Compute the descriptors for a keypoints collection detected in image collection. + + Image collection. + Input keypoints collection. keypoints[i] is keypoints detected in images[i]. + Keypoints for which a descriptor cannot be computed are removed. + Descriptor collection. descriptors[i] are descriptors computed for set keypoints[i]. + + + + Return true if detector object is empty + + + + + + Pointer to algorithm information (cv::AlgorithmInfo*) + + + + + + + + + + + + + + + + + + Abstract base class for computing descriptors for image keypoints. + + + + + Compute the descriptors for a set of keypoints in an image. + + The image. + + Copmputed descriptors. Row i is the descriptor for keypoint i. + The input keypoints. Keypoints for which a descriptor cannot be computed are removed. + + + + Compute the descriptors for a keypoints collection detected in image collection. + + Image collection. + Input keypoints collection. keypoints[i] is keypoints detected in images[i]. + Keypoints for which a descriptor cannot be computed are removed. + Descriptor collection. descriptors[i] are descriptors computed for set keypoints[i]. + + + + Return true if detector object is empty + + + + + + + + + + + The algorithm to use for selecting the initial centers when performing a k-means clustering step. + + + + + picks the initial cluster centers randomly + [flann_centers_init_t::CENTERS_RANDOM] + + + + + picks the initial centers using Gonzales’ algorithm + [flann_centers_init_t::CENTERS_GONZALES] + + + + + picks the initial centers using the algorithm suggested in [arthur_kmeanspp_2007] + [flann_centers_init_t::CENTERS_KMEANSPP] + + + + + The FLANN nearest neighbor index class. + + + + + Constructs a nearest neighbor search index for a given dataset. + + features – Matrix of type CV _ 32F containing the features(points) to index. The size of the matrix is num _ features x feature _ dimensionality. + Structure containing the index parameters. The type of index that will be constructed depends on the type of this parameter. + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + Performs a K-nearest neighbor search for multiple query points. + + The query points, one per row + Indices of the nearest neighbors found + Distances to the nearest neighbors found + Number of nearest neighbors to search for + Search parameters + + + + Performs a K-nearest neighbor search for multiple query points. + + The query points, one per row + Indices of the nearest neighbors found + Distances to the nearest neighbors found + Number of nearest neighbors to search for + Search parameters + + + + Performs a K-nearest neighbor search for multiple query points. + + The query points, one per row + Indices of the nearest neighbors found + Distances to the nearest neighbors found + Number of nearest neighbors to search for + Search parameters + + + + Performs a radius nearest neighbor search for a given query point. + + The query point + Indices of the nearest neighbors found + Distances to the nearest neighbors found + Number of nearest neighbors to search for + + Search parameters + + + + Performs a radius nearest neighbor search for a given query point. + + The query point + Indices of the nearest neighbors found + Distances to the nearest neighbors found + Number of nearest neighbors to search for + + Search parameters + + + + Performs a radius nearest neighbor search for a given query point. + + The query point + Indices of the nearest neighbors found + Distances to the nearest neighbors found + Number of nearest neighbors to search for + + Search parameters + + + + Saves the index to a file. + + The file to save the index to + + + + hierarchical k-means tree. + + + + + + + Is a number between 0 and 1 specifying the percentage of the approximate nearest-neighbor searches that return the exact nearest-neighbor. + Using a higher value for this parameter gives more accurate results, but the search takes longer. The optimum value usually depends on the application. + Specifies the importance of the index build time raported to the nearest-neighbor search time. + In some applications it’s acceptable for the index build step to take a long time if the subsequent searches in the index can be performed very fast. + In other applications it’s required that the index be build as fast as possible even if that leads to slightly longer search times. + Is used to specify the tradeoff between time (index build time and search time) and memory used by the index. + A value less than 1 gives more importance to the time spent and a value greater than 1 gives more importance to the memory usage. + Is a number between 0 and 1 indicating what fraction of the dataset to use in the automatic parameter configuration algorithm. + Running the algorithm on the full dataset gives the most accurate results, but for very large datasets can take longer than desired. + In such case using just a fraction of the data helps speeding up this algorithm while still giving good approximations of the optimum parameters. + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + When using a parameters object of this type the index created combines the randomized kd-trees and the hierarchical k-means tree. + + + + + + + The number of parallel kd-trees to use. Good values are in the range [1..16] + The branching factor to use for the hierarchical k-means tree + The maximum number of iterations to use in the k-means clustering stage when building the k-means tree. A value of -1 used here means that the k-means clustering should be iterated until convergence + The algorithm to use for selecting the initial centers when performing a k-means clustering step. + This parameter (cluster boundary index) influences the way exploration is performed in the hierarchical kmeans tree. When cb_index is zero the next kmeans domain to be explored is choosen to be the one with the closest center. A value greater then zero also takes into account the size of the domain. + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + + + + + + + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + When passing an object of this type the index constructed will consist of a set + of randomized kd-trees which will be searched in parallel. + + + + + + + The number of parallel kd-trees to use. Good values are in the range [1..16] + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + When passing an object of this type the index constructed will be a hierarchical k-means tree. + + + + + + + The branching factor to use for the hierarchical k-means tree + The maximum number of iterations to use in the k-means clustering stage when building the k-means tree. A value of -1 used here means that the k-means clustering should be iterated until convergence + The algorithm to use for selecting the initial centers when performing a k-means clustering step. + This parameter (cluster boundary index) influences the way exploration is performed in the hierarchical kmeans tree. When cb_index is zero the next kmeans domain to be explored is choosen to be the one with the closest center. A value greater then zero also takes into account the size of the domain. + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + the index will perform a linear, brute-force search. + + + + + + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + This object type is used for loading a previously saved index from the disk. + + + + + + + インデックスが保存されたファイル名 + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + Functions of OpenCV GPU module + + + + + Returns the number of installed CUDA-enabled devices. + Use this function before any other GPU functions calls. + If OpenCV is compiled without GPU support, this function returns 0. + + + + + + Returns the current device index set by SetDevice() or initialized by default. + + + + + + Sets a device and initializes it for the current thread. + + System index of a GPU device starting with 0. + + + + + Explicitly destroys and cleans up all resources associated with the current device in the current process. + Any subsequent API call to this device will reinitialize the device. + + + + + + + + + + + + + + + + + Page-locks the matrix m memory and maps it for the device(s) + + + + + + Unmaps the memory of matrix m, and makes it pageable again. + + + + + + Creates continuous GPU matrix + + Number of rows in a 2D array. + Number of columns in a 2D array. + Array type. + + + + + Creates continuous GPU matrix + + Number of rows in a 2D array. + Number of columns in a 2D array. + Array type. + + + + + Creates continuous GPU matrix + + Number of rows and columns in a 2D array. + Array type. + + + + + Creates continuous GPU matrix + + Number of rows and columns in a 2D array. + Array type. + + + + + Ensures that size of the given matrix is not less than (rows, cols) size + and matrix type is match specified one too + + Number of rows in a 2D array. + Number of columns in a 2D array. + Array type. + + + + + Ensures that size of the given matrix is not less than (rows, cols) size + and matrix type is match specified one too + + Number of rows and columns in a 2D array. + Array type. + + + + + + + Number of rows in a 2D array. + Number of columns in a 2D array. + Array type. + + + + + + Smooths the image using the normalized box filter. + + Input image. CV_8UC1 and CV_8UC4 source types are supported. + Output image type. The size and type is the same as src. + Output image depth. If -1, the output image has the same depth as the input one. + The only values allowed here are CV_8U and -1. + Kernel size. + Anchor point. The default value Point(-1, -1) means that + the anchor is at the kernel center. + Stream for the asynchronous version. + + + + Acts as a synonym for the normalized box filter. + + Input image. CV_8UC1 and CV_8UC4 source types are supported. + Output image type. The size and type is the same as src. + Kernel size. + Anchor point. The default value Point(-1, -1) means that + the anchor is at the kernel center. + Stream for the asynchronous version. + + + + Erodes an image by using a specific structuring element. + + Source image. Only CV_8UC1 and CV_8UC4 types are supported. + Destination image with the same size and type as src. + Structuring element used for erosion. If kernel=Mat(), + a 3x3 rectangular structuring element is used. + Position of an anchor within the element. + The default value (-1, -1) means that the anchor is at the element center. + Number of times erosion to be applied. + + + + Erodes an image by using a specific structuring element. + + Source image. Only CV_8UC1 and CV_8UC4 types are supported. + Destination image with the same size and type as src. + Structuring element used for erosion. If kernel=Mat(), + a 3x3 rectangular structuring element is used. + + Position of an anchor within the element. + The default value (-1, -1) means that the anchor is at the element center. + Number of times erosion to be applied. + Stream for the asynchronous version. + + + + Dilates an image by using a specific structuring element. + + Source image. Only CV_8UC1 and CV_8UC4 types are supported. + Destination image with the same size and type as src. + Structuring element used for erosion. If kernel=Mat(), + a 3x3 rectangular structuring element is used. + Position of an anchor within the element. + The default value (-1, -1) means that the anchor is at the element center. + Number of times erosion to be applied. + + + + Dilates an image by using a specific structuring element. + + Source image. Only CV_8UC1 and CV_8UC4 types are supported. + Destination image with the same size and type as src. + Structuring element used for erosion. If kernel=Mat(), + a 3x3 rectangular structuring element is used. + + Position of an anchor within the element. + The default value (-1, -1) means that the anchor is at the element center. + Number of times erosion to be applied. + Stream for the asynchronous version. + + + + Applies an advanced morphological operation to an image. + + Source image. CV_8UC1 and CV_8UC4 source types are supported. + Destination image with the same size and type as src. + Type of morphological operation + Structuring element. + Position of an anchor within the element. + The default value Point(-1, -1) means that the anchor is at the element center. + Number of times erosion and dilation to be applied. + + + + Applies an advanced morphological operation to an image. + + Source image. CV_8UC1 and CV_8UC4 source types are supported. + Destination image with the same size and type as src. + Type of morphological operation + Structuring element. + + + Position of an anchor within the element. + The default value Point(-1, -1) means that the anchor is at the element center. + Number of times erosion and dilation to be applied. + Stream for the asynchronous version. + + + + Applies the non-separable 2D linear filter to an image. + + Source image. Supports CV_8U, CV_16U and CV_32F one and four channel image. + Destination image. The size and the number of channels is the same as src. + Desired depth of the destination image. If it is negative, it is the same as src.depth(). + It supports only the same depth as the source image depth. + 2D array of filter coefficients. + Anchor of the kernel that indicates the relative position of + a filtered point within the kernel. The anchor resides within the kernel. + The special default value (-1,-1) means that the anchor is at the kernel center. + Pixel extrapolation method. + Stream for the asynchronous version. + + + + Applies a separable 2D linear filter to an image. + + Source image. + CV_8UC1, CV_8UC4, CV_16SC1, CV_16SC2, CV_32SC1, CV_32FC1 source types are supported. + Destination image with the same size and number of channels as src. + Destination image depth. CV_8U, CV_16S, CV_32S, and CV_32F are supported. + Horizontal filter coefficients. + Vertical filter coefficients. + Anchor position within the kernel. + The default value (-1, 1) means that the anchor is at the kernel center. + Pixel extrapolation method in the vertical direction. + Pixel extrapolation method in the horizontal direction. + + + + Applies a separable 2D linear filter to an image. + + Source image. + CV_8UC1, CV_8UC4, CV_16SC1, CV_16SC2, CV_32SC1, CV_32FC1 source types are supported. + Destination image with the same size and number of channels as src. + Destination image depth. CV_8U, CV_16S, CV_32S, and CV_32F are supported. + Horizontal filter coefficients. + Vertical filter coefficients. + + Anchor position within the kernel. + The default value (-1, 1) means that the anchor is at the kernel center. + Pixel extrapolation method in the vertical direction. + Pixel extrapolation method in the horizontal direction. + Stream for the asynchronous version. + + + + Applies the generalized Sobel operator to an image. + + Source image. + CV_8UC1, CV_8UC4, CV_16SC1, CV_16SC2, CV_16SC3, CV_32SC1, CV_32FC1 source types are supported. + Destination image with the same size and number of channels as source image. + Destination image depth. CV_8U, CV_16S, CV_32S, and CV_32F are supported. + Derivative order in respect of x. + Derivative order in respect of y. + Size of the extended Sobel kernel. Possible values are 1, 3, 5 or 7. + Optional scale factor for the computed derivative values. By default, no scaling is applied. + Pixel extrapolation method in the vertical direction. + Pixel extrapolation method in the horizontal direction. + + + + Applies the generalized Sobel operator to an image. + + Source image. + CV_8UC1, CV_8UC4, CV_16SC1, CV_16SC2, CV_16SC3, CV_32SC1, CV_32FC1 source types are supported. + Destination image with the same size and number of channels as source image. + Destination image depth. CV_8U, CV_16S, CV_32S, and CV_32F are supported. + Derivative order in respect of x. + Derivative order in respect of y. + + Size of the extended Sobel kernel. Possible values are 1, 3, 5 or 7. + Optional scale factor for the computed derivative values. By default, no scaling is applied. + Pixel extrapolation method in the vertical direction. + Pixel extrapolation method in the horizontal direction. + Stream for the asynchronous version. + + + + Calculates the first x- or y- image derivative using the Scharr operator. + + Source image. + CV_8UC1, CV_8UC4, CV_16SC1, CV_16SC2, CV_16SC3, CV_32SC1, CV_32FC1 source types are supported. + Destination image with the same size and number of channels as source image. + Destination image depth. CV_8U, CV_16S, CV_32S, and CV_32F are supported. + Derivative order in respect of x. + Derivative order in respect of y. + Optional scale factor for the computed derivative values. By default, no scaling is applied. + Pixel extrapolation method in the vertical direction. + Pixel extrapolation method in the horizontal direction. + + + + Calculates the first x- or y- image derivative using the Scharr operator. + + Source image. + CV_8UC1, CV_8UC4, CV_16SC1, CV_16SC2, CV_16SC3, CV_32SC1, CV_32FC1 source types are supported. + Destination image with the same size and number of channels as source image. + Destination image depth. CV_8U, CV_16S, CV_32S, and CV_32F are supported. + Derivative order in respect of x. + Derivative order in respect of y. + + Optional scale factor for the computed derivative values. By default, no scaling is applied. + Pixel extrapolation method in the vertical direction. + Pixel extrapolation method in the horizontal direction. + Stream for the asynchronous version. + + + + + + + + + + + + + + + + Smooths an image using the Gaussian filter. + + Source image. + CV_8UC1, CV_8UC4, CV_16SC1, CV_16SC2, CV_16SC3, CV_32SC1, CV_32FC1 source types are supported. + Destination image with the same size and type as src. + Gaussian kernel size. ksize.Width and ksize.Height can differ + but they both must be positive and odd. If they are zeros, + they are computed from sigma1 and sigma2 . + + Gaussian kernel standard deviation in X direction. + Gaussian kernel standard deviation in Y direction. + If sigma2 is zero, it is set to be equal to sigma1 . If they are both zeros, + they are computed from ksize.Width and ksize.Height, respectively. + To fully control the result regardless of possible future modification of all + this semantics, you are recommended to specify all of ksize, sigma1, and sigma2. + Pixel extrapolation method in the vertical direction. + Pixel extrapolation method in the horizontal direction. + Stream for the asynchronous version. + + + + Applies the Laplacian operator to an image. + + Source image. CV_8UC1 and CV_8UC4 source types are supported. + Destination image. The size and number of channels is the same as src. + Desired depth of the destination image. It supports only the same depth as the source image depth. + Aperture size used to compute the second-derivative filters. + It must be positive and odd. Only ksize = 1 and ksize = 3 are supported. + Optional scale factor for the computed Laplacian values. + Pixel extrapolation method. + Stream for the asynchronous version. + + + + Finds global minimum and maximum array elements and returns their values with locations + + Single-channel source image. + Pointer to the returned minimum value. + Pointer to the returned maximum value. + Pointer to the returned minimum location. + Pointer to the returned maximum location. + Optional mask to select a sub-matrix. + + + + Finds global minimum and maximum array elements and returns their values with locations + + Single-channel source image. + Pointer to the returned minimum value. + Pointer to the returned maximum value. + Pointer to the returned minimum location. + Pointer to the returned maximum location. + Optional mask to select a sub-matrix. + Optional values buffer to avoid extra memory allocations. + It is resized automatically. + Optional locations buffer to avoid extra memory allocations. + It is resized automatically. + + + + Computes a proximity map for a raster template and an image where the template is searched for. + + Source image. CV_32F and CV_8U depth images (1..4 channels) are supported for now. + Template image with the size and type the same as image. + Map containing comparison results (CV_32FC1). If image is W x H and templ is w x h, then result must be W-w+1 x H-h+1. + Specifies the way to compare the template with the image. + Stream for the asynchronous version. + + + + + + + + + The cascade classifier class for object detection: + supports old haar and new lbp xml formats and nvbin for haar cascades only. + + + + + Track whether Dispose has been called + + + + + Default constructor + + + + + CascadeClassifier_GPU Constructor + + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + + + + + + + + + + + releases all inner buffers + + + + + + + + + + + + number of detected objects + + + + + + + + + + + + number of detected objects + + + + + + + + + An abstract class in GPU module that implements DisposableCvObject + + + + + Default constructor + + + + + + + + + + + + + + + + + + + + + + + + Checks whether the opencv_gpu*.dll includes CUDA support. + + + + + + + + + + Gaussian Mixture-based Backbround/Foreground Segmentation Algorithm + + + The class implements the following algorithm: + "Improved adaptive Gausian mixture model for background subtraction" + Z.Zivkovic + International Conference Pattern Recognition, UK, August, 2004. + http://www.zoranz.net/Publications/zivkovic2004ICPR.pdf + + + + + Track whether Dispose has been called + + + + + the default constructor + + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + + + + + + The maximum allowed number of mixture components. + Actual number is determined dynamically per pixel + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + re-initiaization method + + + + + the update operator [MOG_GPU::operator()] + + + + + + + + + Computes a background image which are the mean of all background gaussians + + + + + + + releases all inner buffers + + + + + Gaussian Mixture-based Backbround/Foreground Segmentation Algorithm + + + + + Track whether Dispose has been called + + + + + the default constructor + + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + + + + + + The maximum allowed number of mixture components. + Actual number is determined dynamically per pixel + + + + + + + + + + + + + + + re-initiaization method + + + + + the update operator [MOG_GPU::operator()] + + + + + + + + + Computes a background image which are the mean of all background gaussians + + + + + + + releases all inner buffers + + + + + + + + + + + + + Encapculates Cuda Stream. Provides interface for async coping. + + + + + Track whether Dispose has been called + + + + + Creates from native cv::gpu::Stream* pointer + + + + + + Creates empty Stream + + + + + + + + + + + Clean up any resources being used. + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + Empty stream + + + + + + + + + + + + + + + + + + + + + + + Downloads asynchronously. + Warning! cv::Mat must point to page locked memory (i.e. to CudaMem data or to its subMat) + + + + + + + Downloads asynchronously. + Warning! cv::Mat must point to page locked memory (i.e. to CudaMem data or to its subMat) + + + + + + + Uploads asynchronously. + Warning! cv::Mat must point to page locked memory (i.e. to CudaMem data or to its ROI) + + + + + + + Uploads asynchronously. + Warning! cv::Mat must point to page locked memory (i.e. to CudaMem data or to its ROI) + + + + + + + Copy asynchronously + + + + + + + Memory set asynchronously + + + + + + + Memory set asynchronously + + + + + + + + converts matrix type, ex from float to uchar depending on type + + + + + + + + + + Adds a callback to be called on the host after all currently enqueued items + in the stream have completed + + + Not supported + + + + TODO + + + + + + [HOGDescriptor::DESCR_FORMAT_ROW_BY_ROW] + + + + + + [HOGDescriptor::DESCR_FORMAT_COL_BY_COL] + + + + + Gives information about the given GPU + + + + + Creates DeviceInfo object for the current GPU + + + + + Creates DeviceInfo object for the given GPU + + + + + + Releases the resources + + + + + + + + + + + + + + + + Return compute capability versions + + + + + Return compute capability versions + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Checks whether device supports the given feature + + + + + + + Checks whether the GPU module can be run on the given device + + + + + + CudaMem is limited cv::Mat with page locked memory allocation. + + + + + Track whether Dispose has been called + + + + + Creates from native cv::gpu::CudaMem* pointer + + + + + + Creates empty CudaMem + + + + + + + + + + + + + Number of rows in a 2D array. + Number of columns in a 2D array. + Array type. + + + + + + + 2D array size: Size(cols, rows) + Array type. + + + + + Clean up any resources being used. + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + returns matrix header with disabled reference counting for CudaMem data. + + + + + + + maps host memory into device address space and returns GpuMat header for it. + Throws exception if not supported by hardware. + + + + + + + includes several bit-fields: + 1.the magic signature + 2.continuity flag + 3.depth + 4.number of channels + + + + + the number of rows + + + + + the number of columns + + + + + the number of rows + + + + + the number of columns + + + + + pointer to the data + + + + + pointer to the reference counter; + when matrix points to user-allocated data, the pointer is NULL + + + + + helper fields used in locateROI and adjustROI + + + + + helper fields used in locateROI and adjustROI + + + + + + + + + + returns true iff the GpuMatrix data is continuous + (i.e. when there are no gaps between successive rows). + similar to CV_IS_GpuMat_CONT(cvGpuMat->type) + + + + + + Returns the number of matrix channels. + + + + + + Returns the depth of a matrix element. + + + + + + Returns the matrix element size in bytes. + + + + + + Returns the size of each matrix element channel in bytes. + + + + + + Returns a matrix size. + + + + + + a distance between successive rows in bytes; includes the gap if any + + + + + Returns a normalized step. + + + + + Returns the type of a matrix element. + + + + + + returns true if GpuMatrix data is NULL + + + + + + returns deep copy of the matrix, i.e. the data is copied + + + + + + + + + + + + allocates new matrix data unless the matrix already has specified size and type. + + Number of rows in a 2D array. + Number of columns in a 2D array. + Array type. + + + + + returns matrix header with disabled reference counting for CudaMem data. + + + + + + maps host memory into device address space and returns GpuMat header for it. Throws exception if not supported by hardware. + + + + + + returns if host memory can be mapperd to gpu address space; + + + + + + Smart pointer for GPU memory with reference counting. Its interface is mostly similar with cv::Mat. + + + + + Track whether Dispose has been called + + + + + Creates from native cv::gpu::GpuMat* pointer + + + + + + Creates empty GpuMat + + + + + constructs 2D matrix of the specified size and type + + Number of rows in a 2D array. + Number of columns in a 2D array. + Array type. Use MatType.CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, + or MatType. CV_8UC(n), ..., CV_64FC(n) to create multi-channel matrices. + + + + constructor for matrix headers pointing to user-allocated data + + Number of rows in a 2D array. + Number of columns in a 2D array. + Array type. Use MatType.CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, + or MatType. CV_8UC(n), ..., CV_64FC(n) to create multi-channel matrices. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Number of bytes each matrix row occupies. The value should include the padding bytes at the end of each row, if any. + If the parameter is missing (set to AUTO_STEP ), no padding is assumed and the actual step is calculated as cols*elemSize() . + + + + constructs 2D matrix of the specified size and type + + 2D array size: Size(cols, rows) + Array type. Use MatType.CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, + or MatType.CV_8UC(n), ..., CV_64FC(n) to create multi-channel matrices. + + + + constructor for matrix headers pointing to user-allocated data + + 2D array size: Size(cols, rows) + Array type. Use MatType.CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, + or MatType. CV_8UC(n), ..., CV_64FC(n) to create multi-channel matrices. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Number of bytes each matrix row occupies. The value should include the padding bytes at the end of each row, if any. + If the parameter is missing (set to AUTO_STEP ), no padding is assumed and the actual step is calculated as cols*elemSize() . + + + + creates a matrix for other matrix + + Array that (as a whole) is assigned to the constructed matrix. + + + + creates a matrix for other matrix + + GpuMat that (as a whole) is assigned to the constructed matrix. + + + + constucts 2D matrix and fills it with the specified Scalar value. + + Number of rows in a 2D array. + Number of columns in a 2D array. + Array type. Use MatType.CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, + or MatType. CV_8UC(n), ..., CV_64FC(n) to create multi-channel matrices. + An optional value to initialize each matrix element with. + To set all the matrix elements to the particular value after the construction, use SetTo(Scalar s) method . + + + + constucts 2D matrix and fills it with the specified Scalar value. + + 2D array size: Size(cols, rows) . + Array type. Use MatType.CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, + or CV_8UC(n), ..., CV_64FC(n) to create multi-channel (up to CV_CN_MAX channels) matrices. + An optional value to initialize each matrix element with. + To set all the matrix elements to the particular value after the construction, use SetTo(Scalar s) method . + + + + creates a matrix header for a part of the bigger matrix + + Array that (as a whole or partly) is assigned to the constructed matrix. + Range of the m rows to take. As usual, the range start is inclusive and the range end is exclusive. + Use Range.All to take all the rows. + Range of the m columns to take. Use Range.All to take all the columns. + + + + creates a matrix header for a part of the bigger matrix + + Array that (as a whole or partly) is assigned to the constructed matrix.. + Region of interest. + + + + Clean up any resources being used. + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + converts header to GpuMat + + + + + + + converts header to Mat + + + + + + + includes several bit-fields: + 1.the magic signature + 2.continuity flag + 3.depth + 4.number of channels + + + + + the number of rows + + + + + the number of columns + + + + + the number of rows + + + + + the number of columns + + + + + pointer to the data + + + + + pointer to the reference counter; + when matrix points to user-allocated data, the pointer is NULL + + + + + helper fields used in locateROI and adjustROI + + + + + helper fields used in locateROI and adjustROI + + + + + + + + + + + + + + + + + + + + + + + + + Extracts a rectangular submatrix. + + Start row of the extracted submatrix. The upper boundary is not included. + End row of the extracted submatrix. The upper boundary is not included. + Start column of the extracted submatrix. The upper boundary is not included. + End column of the extracted submatrix. The upper boundary is not included. + + + + + GpuMat Indexer + + + + + + 2-dimensional indexer + + Index along the dimension 0 + Index along the dimension 1 + A value to the specified array element. + + + + Gets a type-specific indexer. The indexer has getters/setters to access each matrix element. + + + + + + + Returns a value to the specified array element. + + + Index along the dimension 0 + Index along the dimension 1 + A value to the specified array element. + + + + Returns a value to the specified array element. + + + Index along the dimension 0 + Index along the dimension 1 + A value to the specified array element. + + + + Set a value to the specified array element. + + + Index along the dimension 0 + Index along the dimension 1 + + + + + returns a new matrix header for the specified column span + + + + + + + + returns a new matrix header for the specified column span + + + + + + + Mat column's indexer object + + + + + + + + + + + Creates a matrix header for the specified matrix column. + + A 0-based column index. + + + + + Creates a matrix header for the specified column span. + + An inclusive 0-based start index of the column span. + An exclusive 0-based ending index of the column span. + + + + + Indexer to access GpuMat column + + + + + + returns a new matrix header for the specified row span + + + + + + + + returns a new matrix header for the specified row span + + + + + + + Mat row's indexer object + + + + + + + + + + + Creates a matrix header for the specified matrix column. + + A 0-based column index. + + + + + Creates a matrix header for the specified column span. + + An inclusive 0-based start index of the column span. + An exclusive 0-based ending index of the column span. + + + + + Indexer to access GpuMat row + + + + + + returns true iff the GpuMatrix data is continuous + (i.e. when there are no gaps between successive rows). + similar to CV_IS_GpuMat_CONT(cvGpuMat->type) + + + + + + Returns the number of matrix channels. + + + + + + Returns the depth of a matrix element. + + + + + + Returns the matrix element size in bytes. + + + + + + Returns the size of each matrix element channel in bytes. + + + + + + Returns a matrix size. + + + + + + a distance between successive rows in bytes; includes the gap if any + + + + + Returns a normalized step. + + + + + Returns the type of a matrix element. + + + + + + returns true if GpuMatrix data is NULL + + + + + + Pefroms blocking upload data to GpuMat. + + + + + + Downloads data from device to host memory. Blocking calls. + + + + + + returns deep copy of the matrix, i.e. the data is copied + + + + + + copies those matrix elements to "m" + + + + + + copies those matrix elements to "m" that are marked with non-zero mask elements. + + + + + + + converts matrix to another datatype with optional scalng. See cvConvertScale. + + + + + + + + + + + + + + + + + + + + + + + sets some of the matrix elements to s, according to the mask + + + + + + + + creates alternative matrix header for the same data, with different + number of channels and/or different number of rows. see cvReshape. + + + + + + + + allocates new matrix data unless the matrix already has specified size and type. + previous data is unreferenced if needed. + + Number of rows in a 2D array. + Number of columns in a 2D array. + Array type. + + + + allocates new matrix data unless the matrix already has specified size and type. + previous data is unreferenced if needed. + + 2D array size: Size(cols, rows) + Array type. + + + + swaps with other smart pointer + + + + + + locates matrix header within a parent matrix. + + + + + + + moves/resizes the current matrix ROI inside the parent matrix. + + + + + + + + + + returns pointer to y-th row + + + + + + + Returns a string that represents this Mat. + + + + + + Abstract definition of Mat indexer + + + + + + 2-dimensional indexer + + Index along the dimension 0 + Index along the dimension 1 + A value to the specified array element. + + + + Parent matrix object + + + + + Step byte length for each dimension + + + + + sizeof(T) + + + + + Constructor + + + + + + + + + + + + + + + + + + + + + + Creates/Sets a matrix header for the specified matrix row/column. + + + + + + + Creates/Sets a matrix header for the specified row/column span. + + + + + + + + Creates/Sets a matrix header for the specified row/column span. + + + + + + + Creates a matrix header for the specified matrix row/column. + + + + + + + Creates a matrix header for the specified row/column span. + + + + + + + + Creates a matrix header for the specified row/column span. + + + + + + + Creates/Sets a matrix header for the specified matrix row/column. + + + + + + + Creates/Sets a matrix header for the specified row/column span. + + + + + + + + Creates/Sets a matrix header for the specified row/column span. + + + + + + + HOG (Histogram-of-Oriented-Gradients) Descriptor and Object Detector + + + + + + + + + + + + + + + + + + + + setSVMDetector parameter vector + + + + + Track whether Dispose has been called + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Initializes from pointer + + class HOGDescriptor* + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Track whether Dispose has been called + + + + + + + + + + + + + + + + + + + + + + + + + Default constructor + + + + + StereoBM_GPU Constructor + + + + + + + + Clean up any resources being used. + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Class used for corner detection using the FAST algorithm. + + + + + Track whether Dispose has been called + + + + + all features have same size + + + + + Constructor. + + Threshold on difference between intensity of the central pixel and pixels on a circle around this pixel. + If it is true, non-maximum suppression is applied to detected corners (keypoints). + Inner buffer size for keypoints store is determined as (keypointsRatio * image_width * image_height). + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + + + + + + + + + + + max keypoints = keypointsRatio * img.size().area() + + + + + Releases inner buffer memory. + + + + + Finds the keypoints using FAST detector. + + Image where keypoints (corners) are detected. + Only 8-bit grayscale images are supported. + Optional input mask that marks the regions where we should detect features. + The output vector of keypoints. + + + + Finds the keypoints using FAST detector. + + Image where keypoints (corners) are detected. + Only 8-bit grayscale images are supported. + Optional input mask that marks the regions where we should detect features. + The output vector of keypoints. + + + + Download keypoints from GPU to CPU memory. + + + + + + + Converts keypoints from GPU representation to vector of KeyPoint. + + + + + + + Find keypoints and compute it’s response if nonmaxSuppression is true. + + Image where keypoints (corners) are detected. Only 8-bit grayscale images are supported. + Optional input mask that marks the regions where we should detect features. + count of detected keypoints + + + + Gets final array of keypoints. + Performs nonmax suppression if needed. + + + Final count of keypoints + + + + Class for extracting ORB features and descriptors from an image. + + + + + Track whether Dispose has been called + + + + + all features have same size + + + + + Constructor. + + The number of desired features. + Coefficient by which we divide the dimensions from one scale pyramid level to the next. + The number of levels in the scale pyramid. + How far from the boundary the points should be. + The level at which the image is given. If 1, that means we will also look at the image scaleFactor times bigger. + + + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + + + + + + + + + + + Releases inner buffer memory. + + + + + Detects keypoints and computes descriptors for them. + + Image where keypoints (corners) are detected. + Only 8-bit grayscale images are supported. + Optional input mask that marks the regions where we should detect features. + The output vector of keypoints. + + + + Detects keypoints and computes descriptors for them. + + Image where keypoints (corners) are detected. + Only 8-bit grayscale images are supported. + Optional input mask that marks the regions where we should detect features. + The output vector of keypoints. + + + + Detects keypoints and computes descriptors for them. + + Image where keypoints (corners) are detected. + Only 8-bit grayscale images are supported. + Optional input mask that marks the regions where we should detect features. + The output vector of keypoints. + + + + + Detects keypoints and computes descriptors for them. + + Image where keypoints (corners) are detected. + Only 8-bit grayscale images are supported. + Optional input mask that marks the regions where we should detect features. + The output vector of keypoints. + + + + + Download keypoints from GPU to CPU memory. + + + + + + + Converts keypoints from GPU representation to vector of KeyPoint. + + + + + + + + + + + Final count of keypoints + + + + Contrast Limited Adaptive Histogram Equalization + + + + + cv::Ptr<CLAHE> + + + + + + + + + + Creates instance from cv::Ptr<T> . + ptr is disposed when the wrapper disposes. + + + + + + Creates a predefined CLAHE object + + + + + + + + Releases the resources + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + Pointer to algorithm information (cv::AlgorithmInfo*) + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Decision tree node + + + + + Default constructor + + + + + + The assigned to the node normalized class index (to 0..class_count-1 range), it is used internally in classification trees and tree ensembles. + + + + + The tree index in a ordered sequence of trees. The indices are used during and after the pruning procedure. + The root node has the maximum value Tn of the whole tree, child nodes have Tn less than or equal to the parent's Tn, + and the nodes with Tn≤CvDTree::pruned_tree_idx are not taken into consideration at the prediction stage (the corresponding branches are considered as cut-off), + even if they have not been physically deleted from the tree at the pruning stage. + + + + + When true, the inverse split rule is used (i.e. left and right branches are exchanged in the expressions below) + + + + + Pointers to the parent node + + + + + Pointers to the left node + + + + + Pointers to the right node + + + + + Pointer to the first (primary) split. + + + + + The number of samples that fall into the node at the training stage. + It is used to resolve the difficult cases - when the variable for the primary split is missing, + and all the variables for other surrogate splits are missing too, + the sample is directed to the left if left-<sample_count<right-<sample_count and to the right otherwise. + + + + + The node depth, the root node depth is 0, the child nodes depth is the parent's depth + 1. + + + + + Decision tree node split + + + + + + + + + + + Index of the variable used in the split + + + + + When true, the inverse split rule is used (i.e. left and right branches are exchanged in the expressions below) + + + + + The split quality, a positive number. + It is used to choose the best primary split, then to choose and sort the surrogate splits. + After the tree is constructed, it is also used to compute variable importance. + + + + + Pointer to the next split in the node split list. + + + + + Bit array indicating the value subset in case of split on a categorical variable. + The rule is: if var_value in subset then next_node<-left else next_node<-right + + + + + The threshold value in case of split on an ordered variable. + The rule is: if var_value < c then next_node<-left else next_node<-right + + + + + Used internally by the training algorithm. + + + + + Decision tree node + + + + + Track whether Dispose has been called + + + + + Default constructor + + + + + Initializes from pointer + + + + + Training constructor + + + + + + + + + + + + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + i-th element = + k<0 - ordered, + k>=0 - categorical, see k-th element of cat_* arrays + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Track whether Dispose has been called + + + + + Default constructor + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + A grid for the SVM algorithm. + + + + + + + + + + + + + + + + + + + + Constructor + + + + + + + + + + + Training Parameters of Random Trees + + + + + Track whether Dispose has been called + + + + + Default constructor + + + + + Training constructor + + This parameter specifies the maximum possible depth of the tree. That is the training algorithms attempts to split a node while its depth is less than max_depth. The actual depth may be smaller if the other termination criteria are met (see the outline of the training procedure in the beginning of the section), and/or if the tree is pruned. + A node is not split if the number of samples directed to the node is less than the parameter value. + Another stop criteria - only for regression trees. As soon as the estimated node value differs from the node training samples responses by less than the parameter value, the node is not split further. + If true, surrogate splits are built. Surrogate splits are needed to handle missing measurements and for variable importance estimation. + If a discrete variable, on which the training procedure tries to make a split, takes more than max_categories values, the precise best subset estimation may take a very long time (as the algorithm is exponential). Instead, many decision trees engines (including ML) try to find sub-optimal split in this case by clustering all the samples into max_categories clusters (i.e. some categories are merged together). Note that this technique is used only in N(>2)-class classification problems. In case of regression and 2-class classification the optimal split can be found efficiently without employing clustering, thus the parameter is not used in these cases. + The array of a priori class probabilities, sorted by the class label value. The parameter can be used to tune the decision tree preferences toward a certain class. For example, if users want to detect some rare anomaly occurrence, the training base will likely contain much more normal cases than anomalies, so a very good classification performance will be achieved just by considering every case as normal. To avoid this, the priors can be specified, where the anomaly probability is artificially increased (up to 0.5 or even greater), so the weight of the misclassified anomalies becomes much bigger, and the tree is adjusted properly. + If it is set, then variable importance is computed by the training procedure. To retrieve the computed variable importance array, call the method CvRTrees::get_var_importance(). + The number of variables that are randomly selected at each tree node and that are used to find the best split(s). + Termination criteria for growing the forest: term_crit.max_iter is the maximum number of trees in the forest (see also max_tree_count parameter of the constructor, by default it is set to 50) term_crit.epsilon is the sufficient accuracy (OOB error). + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + If it is set, then variable importance is computed by the training procedure. To retrieve the computed variable importance array, call the method CvRTrees::get_var_importance(). + + + + + The number of variables that are randomly selected at each tree node and that are used to find the best split(s). + + + + + Termination criteria for growing the forest: + term_crit.max_iter is the maximum number of trees in the forest (see also max_tree_count parameter of the constructor, by default it is set to 50) + term_crit.epsilon is the sufficient accuracy (OOB error). + + + + + SVM training parameters + + + + + + + + + + + Default constructor + + + + + Constructor + + Type of SVM + The kernel type + for poly + for poly/rbf/sigmoid + for poly/sigmoid + for SVMType.CSvc, SVMType.EpsSvr and SVMType.NuSvr + for SVMType.NuSvc, SVMType.OneClass and SVMType.NuSvr + for SVMType.EpsSvr + for SVMType.CSvc + Termination criteria + + + + Native struct + + + + + + Type of SVM + + + + + The kernel type + + + + + for poly + + + + + for poly/rbf/sigmoid + + + + + for poly/sigmoid + + + + + for SVMType.CSvc, SVMType.EpsSvr and SVMType.NuSvr + + + + + for SVMType.NuSvc, SVMType.OneClass and SVMType.NuSvr + + + + + for SVMType.EpsSvr + + + + + for SVMType.CSvc + + + + + Termination criteria + + + + + + + + + + Track whether Dispose has been called + + + + + Default constructor + + + + + + + + + + + + + + + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + + + + + + + + + + + + + + + + + + + + + Boosted tree classifier + + + + + Track whether Dispose has been called + + + + + Default constructor + + + + + Training constructor + + + + + + + + + + + + + Training constructor + + + + + + + + + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + Trains boosted tree classifier + + + + + + + + + + + + + + + Trains boosted tree classifier + + + + + + + + + + + + + + + Predicts response for the input sample + + The input sample. + The optional mask of missing measurements. To handle missing measurements, the weak classifiers must include surrogate splits. + The optional output parameter, a floating-point vector, of responses from each individual weak classifier. The number of elements in the vector must be equal to the slice length. + The continuous subset of the sequence of weak classifiers to be used for prediction. By default, all the weak classifiers are used. + The last parameter is normally set to false that implies a regular input. If it is true, the method assumes that all the values of the discrete input variables have been already normalized to 0..<num_of_categoriesi>-1 ranges. (as the decision tree uses such normalized representation internally). It is useful for faster prediction with tree ensembles. For ordered input variables the flag is not used. + + the output class label based on the weighted voting. + + + + Predicts response for the input sample + + The input sample. + The optional mask of missing measurements. To handle missing measurements, the weak classifiers must include surrogate splits. + The continuous subset of the sequence of weak classifiers to be used for prediction. By default, all the weak classifiers are used. + The last parameter is normally set to false that implies a regular input. If it is true, the method assumes that all the values of the discrete input variables have been already normalized to 0..<num_of_categoriesi>-1 ranges. (as the decision tree uses such normalized representation internally). It is useful for faster prediction with tree ensembles. For ordered input variables the flag is not used. + + the output class label based on the weighted voting. + + + + Removes specified weak classifiers + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Deallocates memory and resets the model state + + + + + Writes the model to file storage + + + + + + + Reads the model from file storage + + + + + + + Boosting training parameters + + + + + Track whether Dispose has been called + + + + + + + + + + + + Default constructor + + + + + Training constructor + + Boosting type + The number of weak classifiers to build. + he weight trimming ratio, within 0..1. If the parameter is ≤0 or >1, the trimming is not used, all the samples are used at each iteration. The default value is 0.95. + This parameter specifies the maximum possible depth of the tree. That is the training algorithms attempts to split a node while its depth is less than max_depth. The actual depth may be smaller if the other termination criteria are met (see the outline of the training procedure in the beginning of the section), and/or if the tree is pruned. + If true, surrogate splits are built. Surrogate splits are needed to handle missing measurements and for variable importance estimation. + The array of a priori class probabilities, sorted by the class label value. The parameter can be used to tune the decision tree preferences toward a certain class. For example, if users want to detect some rare anomaly occurrence, the training base will likely contain much more normal cases than anomalies, so a very good classification performance will be achieved just by considering every case as normal. To avoid this, the priors can be specified, where the anomaly probability is artificially increased (up to 0.5 or even greater), so the weight of the misclassified anomalies becomes much bigger, and the tree is adjusted properly. + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + Boosting type + + + + + The number of weak classifiers to build. + + + + + Splitting criteria, used to choose optimal splits during a weak tree construction + + + + + The weight trimming ratio, within 0..1. + If the parameter is ≤0 or >1, the trimming is not used, + all the samples are used at each iteration. The default value is 0.95. + + + + + Decision tree training parameters + + + + + Track whether Dispose has been called + + + + + + + + + + + Default constructor + + + + + Training constructor + + This parameter specifies the maximum possible depth of the tree. That is the training algorithms attempts to split a node while its depth is less than max_depth. The actual depth may be smaller if the other termination criteria are met (see the outline of the training procedure in the beginning of the section), and/or if the tree is pruned. + A node is not split if the number of samples directed to the node is less than the parameter value. + Another stop criteria - only for regression trees. As soon as the estimated node value differs from the node training samples responses by less than the parameter value, the node is not split further. + If true, surrogate splits are built. Surrogate splits are needed to handle missing measurements and for variable importance estimation. + If a discrete variable, on which the training procedure tries to make a split, takes more than max_categories values, the precise best subset estimation may take a very long time (as the algorithm is exponential). Instead, many decision trees engines (including ML) try to find sub-optimal split in this case by clustering all the samples into max_categories clusters (i.e. some categories are merged together). Note that this technique is used only in N(>2)-class classification problems. In case of regression and 2-class classification the optimal split can be found efficiently without employing clustering, thus the parameter is not used in these cases. + If this parameter is >1, the tree is pruned using cv_folds-fold cross validation. + If true, the tree is truncated a bit more by the pruning procedure. That leads to compact, and more resistant to the training data noise, but a bit less accurate decision tree. + If true, the cut off nodes (with Tn≤CvDTree::pruned_tree_idx) are physically removed from the tree. Otherwise they are kept, and by decreasing CvDTree::pruned_tree_idx (e.g. setting it to -1) it is still possible to get the results from the original un-pruned (or pruned less aggressively) tree. + The array of a priori class probabilities, sorted by the class label value. The parameter can be used to tune the decision tree preferences toward a certain class. For example, if users want to detect some rare anomaly occurrence, the training base will likely contain much more normal cases than anomalies, so a very good classification performance will be achieved just by considering every case as normal. To avoid this, the priors can be specified, where the anomaly probability is artificially increased (up to 0.5 or even greater), so the weight of the misclassified anomalies becomes much bigger, and the tree is adjusted properly. + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + If a discrete variable, on which the training procedure tries to make a split, takes more than MaxCategories values, + the precise best subset estimation may take a very long time (as the algorithm is exponential). + Instead, many decision trees engines (including ML) try to find sub-optimal split in this case by clustering + all the samples into MaxCategories clusters (i.e. some categories are merged together). + Note that this technique is used only in N(>2)-class classification problems. In case of regression and 2-class classification + the optimal split can be found efficiently without employing clustering, thus the parameter is not used in these cases. + + + + + This parameter specifies the maximum possible depth of the tree. That is the training algorithms attempts to split a node + while its depth is less than max_depth. The actual depth may be smaller if the other termination criteria are met + (see the outline of the training procedure in the beginning of the section), and/or if the tree is pruned. + + + + + A node is not split if the number of samples directed to the node is less than the parameter value. + + + + + If this parameter is >1, the tree is pruned using cv_folds-fold cross validation. + + + + + If true, surrogate splits are built. Surrogate splits are needed to handle missing measurements and for variable importance estimation. + + + + + If true, the tree is truncated a bit more by the pruning procedure. + That leads to compact, and more resistant to the training data noise, but a bit less accurate decision tree. + + + + + If true, the cut off nodes (with Tn≤CvDTree::pruned_tree_idx) are physically removed from the tree. + Otherwise they are kept, and by decreasing CvDTree::PrunedTreeIdx (e.g. setting it to -1) + it is still possible to get the results from the original un-pruned (or pruned less aggressively) tree. + + + + + Another stop criteria - only for regression trees. As soon as the estimated node value differs + from the node training samples responses by less than the parameter value, the node is not split further. + + + + + The array of a priori class probabilities, sorted by the class label value. + The parameter can be used to tune the decision tree preferences toward a certain class. + For example, if users want to detect some rare anomaly occurrence, the training base will likely contain much more normal cases + than anomalies, so a very good classification performance will be achieved just by considering every case as normal. + To avoid this, the priors can be specified, where the anomaly probability is artificially increased (up to 0.5 or even greater), + so the weight of the misclassified anomalies becomes much bigger, and the tree is adjusted properly. + + + + + Weak tree classifier + + + + + Track whether Dispose has been called + + + + + Default constructor + + + + + Initializes by pointer + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + Trains decision tree + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Decision tree + + + + + Track whether Dispose has been called + + + + + Default constructor + + + + + Initializes by pointer + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + Trains decision tree + + + + + + + + + + + + + + Trains decision tree + + + + + + + + + + + + + + Trains decision tree + + + + + + + + Trains decision tree + + + + + + + + Returns the leaf node of decision tree corresponding to the input vector + + + + + + + + + Returns the leaf node of decision tree corresponding to the input vector + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Reads the model from file storage + + + + + + + Reads the model from file storage + + + + + + + + Writes the model to file storage + + + + + + Writes the model to file storage + + + + + + + Deallocates memory and resets the model state + + + + + + + + + + Track whether Dispose has been called + + + + + Default constructor + + + + + Initializes by pointer + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Track whether Dispose has been called + + + + + Default constructor + + + + + Initializes by pointer + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Bayes classifier for normally distributed data + + + + + Track whether Dispose has been called + + + + + Default constructor + + + + + Bayes classifier for normally distributed data + + Known samples (m*n) + Classes for known samples (m*1) + + + + + + + Bayes classifier for normally distributed data + + Known samples (m*n) + Classes for known samples (m*1) + + + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + Trains the model + + Known samples (m*n) + Classes for known samples (m*1) + + + Adds known samples to model(true) or makes a new one(false) + + + + + Trains the model + + Known samples (m*n) + Classes for known samples (m*1) + + + Adds known samples to model(true) or makes a new one(false) + + + + + Predicts the response for sample(s) + + Unkown samples (l*n) + Classes for known samples (l*1) + + + + Predicts the response for sample(s) + + Unkown samples (l*n) + Classes for known samples (l*1) + + + + Deallocates memory and resets the model state + + + + + Writes the model to file storage + + + + + + + Reads the model from file storage + + + + + + + Random Trees + + + + + Track whether Dispose has been called + + + + + Default constructor + + + + + Initializes by pointer + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + Trains Random Trees model + + + + + + + + + + + + + + Trains Random Trees model + + + + + + + + + + + + + + Predicts the output for the input sample + + + + + + + + Predicts the output for the input sample + + + + + + + + Predicts the output for the input sample + + + + + + + + Predicts the output for the input sample + + + + + + + + Retrieves the variable importance array + + + + + + Retrieves proximity measure between two training samples + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Deallocates memory and resets the model state + + + + + Writes the model to file storage + + + + + + + Reads the model from file storage + + + + + + + EM model (cv::EM) + + + + + Track whether Dispose has been called + + + + + Training constructor + + + + + + + + Creates instance by cv::Ptr<cv::SURF> + + + + + Creates instance by raw pointer cv::SURF* + + + + + Creates instance from cv::Ptr<T> . + ptr is disposed when the wrapper disposes. + + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + Pointer to algorithm information (cv::AlgorithmInfo*) + + + + + + + + + + + Estimates Gaussian mixture parameters from the sample set + + + + + + + + + Estimates Gaussian mixture parameters from the sample set + + + + + + + + + + + + Estimates Gaussian mixture parameters from the sample set + + + + + + + + + + Predicts the response for sample + + + + + + + Deallocates memory and resets the model state + + + + + K nearest neighbors classifier + + + + + Track whether Dispose has been called + + + + + Default constructor + + + + + Training constructor + + Known samples (m*n) + Classes for known samples (m*1) + + + Maximum number of neighbors to return + + + + Training constructor + + Known samples (m*n) + Classes for known samples (m*1) + + + Maximum number of neighbors to return + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + Trains the model + + Known samples (m*n) + Classes for known samples (m*1) + + + Maximum number of neighbors to return + Adds known samples to model(true) or makes a new one(false) + + + + + Trains the model + + Known samples (m*n) + Classes for known samples (m*1) + + + Maximum number of neighbors to return + Adds known samples to model(true) or makes a new one(false) + + + + + Finds the K nearest neighbors of samples + + Known samples (l*n) + max neighbors to find + + + Neighbors for each samples (l*k) + Distance from each sample to neighbors + + + + + Finds the K nearest neighbors of samples + + Known samples (l*n) + max neighbors to find + + Neighbors for each samples (l*k) + Distance from each sample to neighbors + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Deallocates memory and resets the model state + + + + + Support Vector Machines + + + + + Track whether Dispose has been called + + + + + Default constructor + + + + + Training constructor + + + + + + + + + + Training constructor + + + + + + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + Generates a grid for SVM parameters + + + + + + + Retrieves the number of support vectors + + + + + + Retrieves the particular vector + + + + + + + Returns current SVM parameters + + + + + + + + + + + + Trains SVM + + + + + + + + + + Trains SVM + + + + + + + + + + Trains SVM with optimal parameters + + + + + + + Cross-validation parameter. The training set is divided into k_fold subsets, one subset being used to train the model, the others forming the test set. So, the SVM algorithm is executed k_fold times. + + + + + + + + + + + + Trains SVM with optimal parameters + + + + + + + Cross-validation parameter. The training set is divided into k_fold subsets, one subset being used to train the model, the others forming the test set. So, the SVM algorithm is executed k_fold times. + + + + + + + + + + + + Predicts the response for sample + + + + + + + + Predicts the response for sample + + + + + + + + Predicts the response for sample + + + + + + + + Predicts the response for sample + + + + + + + + Deallocates memory and resets the model state + + + + + Writes the model to file storage + + + + + + + Reads the model from file storage + + + + + + + Splitting criteria, used to choose optimal splits during a weak tree construction + + + + + Use the default criteria for the particular boosting method. + [CvBoost::DEFAULT] + + + + + Use Gini index. This is default option for Real AdaBoost; may be also used for Discrete AdaBoost. + [CvBoost::GINI] + + + + + Use misclassification rate. This is default option for Discrete AdaBoost; may be also used for Real AdaBoost. + [CvBoost::MISCLASS] + + + + + Use least squares criteria. This is default and the only option for LogitBoost and Gentle AdaBoost.最小二乗基準を用いる． + [CvBoost::SQERR] + + + + + Data layout of decision tree + + + + + Discrete AdaBoost + [CvBoost::DISCRETE] + + + + + Real AdaBoost + [CvBoost::REAL] + + + + + LogitBoost + [CvBoost::LOGIT] + + + + + Gentle AdaBoost + [CvBoost::GENTLE] + + + + + Data layout of decision tree + + + + + + [CV_ROW_SAMPLE] + + + + + + [CV_COL_SAMPLE] + + + + + The type of the mixture covariation matrices + + + + + A covariation matrix of each mixture is a scaled identity matrix, μk*I, + so the only parameter to be estimated is μk. The option may be used in special cases, + when the constraint is relevant, or as a first step in the optimization + (e.g. in case when the data is preprocessed with PCA). The results of such preliminary estimation + may be passed again to the optimization procedure, this time with cov_mat_type=Diagonal. + [CvEM::COV_MAT_SPHERICAL] + + + + + A covariation matrix of each mixture may be arbitrary diagonal matrix with positive diagonal elements, + that is, non-diagonal elements are forced to be 0's, so the number of free parameters is d for each matrix. + This is most commonly used option yielding good estimation results. + [CvEM::COV_MAT_DIAGONAL] + + + + + A covariation matrix of each mixture may be arbitrary symmetrical positively defined matrix, + so the number of free parameters in each matrix is about d^2/2. + It is not recommended to use this option, unless there is pretty accurate + initial estimation of the parameters and/or a huge number of training samples. + [CvEM::COV_MAT_GENERIC] + + + + + The initial step the algorithm starts from + + + + + The algorithm starts with E-step. + At least, the initial values of mean vectors, CvEMParams.Means must be passed. + Optionally, the user may also provide initial values for weights (CvEMParams.Weights) + and/or covariation matrices (CvEMParams.Covs). + [CvEM::START_E_STEP] + + + + + The algorithm starts with M-step. The initial probabilities p_i,k must be provided. + [CvEM::START_M_STEP] + + + + + No values are required from the user, k-means algorithm is used to estimate initial mixtures parameters. + [CvEM::START_AUTO_STEP] + + + + + Splitting criteria, used to choose optimal splits during a weak tree construction + + + + + + [CvANN_MLP::IDENTITY] + + + + + U + [CvANN_MLP::SIGMOID_SYM] + + + + + + [CvANN_MLP::GAUSSIAN] + + + + + The MLP training algorithm to use + + + + + No flags + [0] + + + + + 1 - algorithm updates the network weights, rather than computes them from scratch + (in the latter case the weights are initialized using Nguyen-Widrow algorithm). + [CvANN_MLP::UPDATE_WEIGHTS] + + + + + algorithm does not normalize the input vectors. + If this flag is not set, the training algorithm normalizes each input feature independently, + shifting its mean value to 0 and making the standard deviation =1. If the network is assumed to be updated frequently, + the new training data could be much different from original one. In this case user should take care of proper normalization. + [CvANN_MLP::NO_INPUT_SCALE] + + + + + algorithm does not normalize the output vectors. + If the flag is not set, the training algorithm normalizes each output features independently, + by transforming it to the certain range depending on the activation function used. + [CvANN_MLP::NO_OUTPUT_SCALE] + + + + + The MLP training algorithm to use + + + + + sequential backpropagation algorithm + [CvANN_MLP_TrainParams::BACKPROP] + + + + + RPROP algorithm, default value + [CvANN_MLP_TrainParams::RPROP] + + + + + The kernel type of SVM + + + + + no mapping is done, linear discrimination (or regression) is done in the original feature space. It is the fastest option. d(x,y) = x•y == (x,y) + [CvSVM::LINEAR] + + + + + polynomial kernel: d(x,y) = (gamma*(x•y)+coef0)^degree + [CvSVM::POLY] + + + + + radial-basis-function kernel; a good choice in most cases: d(x,y) = exp(-gamma*|x-y|^2) + [CvSVM::RBF] + + + + + sigmoid function is used as a kernel: d(x,y) = tanh(gamma*(x•y)+coef0) + [CvSVM::SIGMOID] + + + + + SVM params type + + + + + [CvSVM::C] + + + + + [CvSVM::GAMMA] + + + + + [CvSVM::P] + + + + + [CvSVM::NU] + + + + + [CvSVM::COEF] + + + + + [CvSVM::DEGREE] + + + + + Type of SVM + + + + + n-class classification (n>=2), allows imperfect separation of classes with penalty multiplier C for outliers. + [CvSVM::C_SVC] + + + + + n-class classification with possible imperfect separation. Parameter nu (in the range 0..1, the larger the value, the smoother the decision boundary) is used instead of C. + [CvSVM::NU_SVC] + + + + + one-class SVM. All the training data are from the same class, SVM builds a boundary that separates the class from the rest of the feature space. + [CvSVM::ONE_CLASS] + + + + + regression. The distance between feature vectors from the training set and the fitting hyper-plane must be less than p. For outliers the penalty multiplier C is used. + [CvSVM::EPS_SVR] + + + + + regression; nu is used instead of p. + [CvSVM::NU_SVR] + + + + + + + + + + [CV_COUNT] + + + + + [CV_PORTION] + + + + + High level image stitcher. + It's possible to use this class without being aware of the entire stitching + pipeline. However, to be able to achieve higher stitching stability and + quality of the final images at least being familiar with the theory is recommended + + + + + Status code + + + + + Constructor + + cv::Stitcher* + + + + Creates a stitcher with the default parameters. + + Flag indicating whether GPU should be used + whenever it's possible. + + + + Deletes all resources + + + + + + Try to stitch the given images. + + Input images. + Final pano. + Status code. + + + + Try to stitch the given images. + + Input images. + Final pano. + Status code. + + + + Try to stitch the given images. + + Input images. + Region of interest rectangles. + Final pano. + Status code. + + + + Try to stitch the given images. + + Input images. + Region of interest rectangles. + Final pano. + Status code. + + + + cv::calcOpticalFlowPyrLK flags + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Method for solving a PnP problem: + + + + + Iterative method is based on Levenberg-Marquardt optimization. + In this case the function finds such a pose that minimizes reprojection error, + that is the sum of squared distances between the observed projections imagePoints and the projected (using projectPoints() ) objectPoints . + + + + + Method is based on the paper of X.S. Gao, X.-R. Hou, J. Tang, H.-F. Chang“Complete Solution Classification for + the Perspective-Three-Point Problem”. In this case the function requires exactly four object and image points. + + + + + Method has been introduced by F.Moreno-Noguer, V.Lepetit and P.Fua in the paper “EPnP: Efficient Perspective-n-Point Camera Pose Estimation”. + + + + + + + + + + Output image matrix will be created (Mat::create), + i.e. existing memory of output image may be reused. + Two source image, matches and single keypoints will be drawn. + For each keypoint only the center point will be drawn (without + the circle around keypoint with keypoint size and orientation). + + + + + Output image matrix will not be created (Mat::create). + Matches will be drawn on existing content of output image. + + + + + Single keypoints will not be drawn. + + + + + For each keypoint the circle around keypoint with keypoint size and + orientation will be drawn. + + + + + cv::ORB score flags + + + + + + + + + + + + + + + cv::initWideAngleProjMap flags + + + + + + + + + + + + + + + + + + + + GrabCut algorithm flags + + + + + The function initializes the state and the mask using the provided rectangle. + After that it runs iterCount iterations of the algorithm. + [GC_INIT_WITH_RECT] + + + + + The function initializes the state using the provided mask. + Note that GC_INIT_WITH_RECT and GC_INIT_WITH_MASK can be combined. + Then, all the pixels outside of the ROI are automatically initialized with GC_BGD . + [GC_INIT_WITH_MASK] + + + + + The value means that the algorithm should just resume. + [GC_EVAL] + + + + + Mask size for distance transform + + + + + + [CV_DIST_MASK_3] + + + + + + [CV_DIST_MASK_5] + + + + + + [CV_DIST_MASK_PRECISE] + + + + + cv::Algorithm parameter type + + + + + Abstract definition of Mat indexer + + + + + + 1-dimensional indexer + + Index along the dimension 0 + If hashVal is not null, the element hash value is not computed but hashval is taken instead. + A value to the specified array element. + + + + 2-dimensional indexer + + Index along the dimension 0 + Index along the dimension 1 + If hashVal is not null, the element hash value is not computed but hashval is taken instead. + A value to the specified array element. + + + + 3-dimensional indexer + + Index along the dimension 0 + Index along the dimension 1 + Index along the dimension 2 + If hashVal is not null, the element hash value is not computed but hashval is taken instead. + A value to the specified array element. + + + + n-dimensional indexer + + Array of Mat::dims indices. + If hashVal is not null, the element hash value is not computed but hashval is taken instead. + A value to the specified array element. + + + + Parent matrix object + + + + + Constructor + + + + + + Sparse matrix class. + + + + + Creates from native cv::SparseMat* pointer + + + + + + Creates empty SparseMat + + + + + constructs n-dimensional sparse matrix + + Array of integers specifying an n-dimensional array shape. + Array type. Use MatType.CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, + or MatType. CV_8UC(n), ..., CV_64FC(n) to create multi-channel matrices. + + + + converts old-style CvMat to the new matrix; the data is not copied by default + + cv::Mat object + + + + converts old-style CvSparseMat to the new matrix; the data is not copied by default + + Old style CvSparseMat object + + + + Releases the resources + + + + + Releases the resources + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + + + + + + + + + + + + + + + sizeof(cv::Mat) + + + + + Creates the CvMat clone instance for the matrix. + + + + + + + Creates the CvMat header or clone instance for the matrix. + + + + + + Assignment operator. This is O(1) operation, i.e. no data is copied + + + + + + + Assignment operator. equivalent to the corresponding constructor. + + + + + + + creates full copy of the matrix + + + + + + copies all the data to the destination matrix. All the previous content of m is erased. + + + + + + converts sparse matrix to dense matrix. + + + + + + multiplies all the matrix elements by the specified scale factor alpha and converts the results to the specified data type + + + + + + + + converts sparse matrix to dense n-dim matrix with optional type conversion and scaling. + + + The output matrix data type. When it is =-1, the output array will have the same data type as (*this) + The scale factor + The optional delta added to the scaled values before the conversion + + + + not used now + + + + + + + Reallocates sparse matrix. + If the matrix already had the proper size and type, + it is simply cleared with clear(), otherwise, + the old matrix is released (using release()) and the new one is allocated. + + + + + + + sets all the sparse matrix elements to 0, which means clearing the hash table. + + + + + manually increments the reference counter to the header. + + + + + returns the size of each element in bytes (not including the overhead - the space occupied by SparseMat::Node elements) + + + + + + returns elemSize()/channels() + + + + + + Returns the type of sparse matrix element. + + + + + + Returns the depth of sparse matrix element. + + + + + + Returns the matrix dimensionality + + + + + Returns the number of sparse matrix channels. + + + + + + Returns the array of sizes, or null if the matrix is not allocated + + + + + + Returns the size of i-th matrix dimension (or 0) + + + + + + + Computes the element hash value (1D case) + + Index along the dimension 0 + + + + + Computes the element hash value (2D case) + + Index along the dimension 0 + Index along the dimension 1 + + + + + Computes the element hash value (3D case) + + Index along the dimension 0 + Index along the dimension 1 + Index along the dimension 2 + + + + + Computes the element hash value (nD case) + + Array of Mat::dims indices. + + + + + Low-level element-access function. + + Index along the dimension 0 + Create new element with 0 value if it does not exist in SparseMat. + If hashVal is not null, the element hash value is not computed but hashval is taken instead. + + + + + Low-level element-access function. + + Index along the dimension 0 + Index along the dimension 1 + Create new element with 0 value if it does not exist in SparseMat. + If hashVal is not null, the element hash value is not computed but hashval is taken instead. + + + + + Low-level element-access function. + + Index along the dimension 0 + Index along the dimension 1 + Index along the dimension 2 + Create new element with 0 value if it does not exist in SparseMat. + If hashVal is not null, the element hash value is not computed but hashval is taken instead. + + + + + Low-level element-access function. + + Array of Mat::dims indices. + Create new element with 0 value if it does not exist in SparseMat. + If hashVal is not null, the element hash value is not computed but hashval is taken instead. + + + + + Return pthe specified sparse matrix element if it exists; otherwise, null. + + Index along the dimension 0 + If hashVal is not null, the element hash value is not computed but hashval is taken instead. + + + + + Return pthe specified sparse matrix element if it exists; otherwise, null. + + Index along the dimension 0 + Index along the dimension 1 + If hashVal is not null, the element hash value is not computed but hashval is taken instead. + + + + + Return pthe specified sparse matrix element if it exists; otherwise, null. + + Index along the dimension 0 + Index along the dimension 1 + Index along the dimension 2 + If hashVal is not null, the element hash value is not computed but hashval is taken instead. + + + + + Return pthe specified sparse matrix element if it exists; otherwise, null. + + Array of Mat::dims indices. + If hashVal is not null, the element hash value is not computed but hashval is taken instead. + + + + + Return pthe specified sparse matrix element if it exists; otherwise, default(T). + + Index along the dimension 0 + If hashVal is not null, the element hash value is not computed but hashval is taken instead. + + + + + Return pthe specified sparse matrix element if it exists; otherwise, default(T). + + Index along the dimension 0 + Index along the dimension 1 + If hashVal is not null, the element hash value is not computed but hashval is taken instead. + + + + + Return pthe specified sparse matrix element if it exists; otherwise, default(T). + + Index along the dimension 0 + Index along the dimension 1 + Index along the dimension 2 + If hashVal is not null, the element hash value is not computed but hashval is taken instead. + + + + + Return pthe specified sparse matrix element if it exists; otherwise, default(T). + + Array of Mat::dims indices. + If hashVal is not null, the element hash value is not computed but hashval is taken instead. + + + + + Mat Indexer + + + + + + 1-dimensional indexer + + Index along the dimension 0 + If hashVal is not null, the element hash value is not computed but hashval is taken instead. + A value to the specified array element. + + + + 2-dimensional indexer + + Index along the dimension 0 + Index along the dimension 1 + If hashVal is not null, the element hash value is not computed but hashval is taken instead. + A value to the specified array element. + + + + 3-dimensional indexer + + Index along the dimension 0 + Index along the dimension 1 + Index along the dimension 2 + If hashVal is not null, the element hash value is not computed but hashval is taken instead. + A value to the specified array element. + + + + n-dimensional indexer + + Array of Mat::dims indices. + If hashVal is not null, the element hash value is not computed but hashval is taken instead. + A value to the specified array element. + + + + Gets a type-specific indexer. + The indexer has getters/setters to access each matrix element. + + + + + + + Gets a type-specific indexer. + The indexer has getters/setters to access each matrix element. + + + + + + + Returns a value to the specified array element. + + + Index along the dimension 0 + If hashVal is not null, the element hash value is not computed but hashval is taken instead. + A value to the specified array element. + + + + Returns a value to the specified array element. + + + Index along the dimension 0 + Index along the dimension 1 + If hashVal is not null, the element hash value is not computed but hashval is taken instead. + A value to the specified array element. + + + + Returns a value to the specified array element. + + + Index along the dimension 0 + Index along the dimension 1 + Index along the dimension 2 + If hashVal is not null, the element hash value is not computed but hashval is taken instead. + A value to the specified array element. + + + + Returns a value to the specified array element. + + + Array of Mat::dims indices. + If hashVal is not null, the element hash value is not computed but hashval is taken instead. + A value to the specified array element. + + + + Set a value to the specified array element. + + + Index along the dimension 0 + + + + + + Set a value to the specified array element. + + + Index along the dimension 0 + Index along the dimension 1 + + If hashVal is not null, the element hash value is not computed but hashval is taken instead. + + + + Set a value to the specified array element. + + + Index along the dimension 0 + Index along the dimension 1 + Index along the dimension 2 + + If hashVal is not null, the element hash value is not computed but hashval is taken instead. + + + + Set a value to the specified array element. + + + Array of Mat::dims indices. + + If hashVal is not null, the element hash value is not computed but hashval is taken instead. + + + + Returns a string that represents this Mat. + + + + + + MLP model + + + + + Track whether Dispose has been called + + + + + Default constructor + + + + + Training constructor + + The integer vector specifies the number of neurons in each layer including the input and output layers. + Specifies the activation function for each neuron + Free parameter α of the activation function + Free parameter β of the activation function + + + + Training constructor + + The integer vector specifies the number of neurons in each layer including the input and output layers. + Specifies the activation function for each neuron + Free parameter α of the activation function + Free parameter β of the activation function + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + Constructs the MLP with the specified topology + + The integer vector specifies the number of neurons in each layer including the input and output layers. + Specifies the activation function for each neuron + Free parameter α of the activation function + Free parameter β of the activation function + + + + Constructs the MLP with the specified topology + + The integer vector specifies the number of neurons in each layer including the input and output layers. + Specifies the activation function for each neuron + Free parameter α of the activation function + Free parameter β of the activation function + + + + Trains/updates MLP + + A floating-point matrix of input vectors, one vector per row. + A floating-point matrix of the corresponding output vectors, one vector per row. + (RPROP only) The optional floating-point vector of weights for each sample. Some samples may be more important than others for training, e.g. user may want to gain the weight of certain classes to find the right balance between hit-rate and false-alarm rate etc. + The optional integer vector indicating the samples (i.e. rows of _inputs and _outputs) that are taken into account. + The training params. + The various parameters to control the training algorithm. + the number of done iterations. + + + + Trains/updates MLP + + A floating-point matrix of input vectors, one vector per row. + A floating-point matrix of the corresponding output vectors, one vector per row. + (RPROP only) The optional floating-point vector of weights for each sample. Some samples may be more important than others for training, e.g. user may want to gain the weight of certain classes to find the right balance between hit-rate and false-alarm rate etc. + The optional integer vector indicating the samples (i.e. rows of _inputs and _outputs) that are taken into account. + The training params. + The various parameters to control the training algorithm. + the number of done iterations. + + + + Predicts response for the input sample + + The input sample. + + + + + + Predicts response for the input sample + + The input sample. + + + + + + + + + + + + + + + + + + Deallocates memory and resets the model state + + + + + Writes the model to file storage + + + + + + + Reads the model from file storage + + + + + + + Parameters of MLP training algorithm + + + + + Default constructor + + + + + Training constructor + + The termination criteria for the training algorithm. It identifies how many iterations is done by the algorithm (for sequential backpropagation algorithm the number is multiplied by the size of the training set) and how much the weights could change between the iterations to make the algorithm continue. + The training algorithm to use + + + + + + The termination criteria for the training algorithm. + It identifies how many iterations is done by the algorithm (for sequential backpropagation algorithm the number is multiplied by the size of the training set) + and how much the weights could change between the iterations to make the algorithm continue. + + + + + The training algorithm to use + + + + + (Backpropagation only): The coefficient to multiply the computed weight gradient by. + The recommended value is about 0.1. The parameter can be set via param1 of the constructor. + + + + + (Backpropagation only): The coefficient to multiply the difference between weights on the 2 previous iterations. + This parameter provides some inertia to smooth the random fluctuations of the weights. It can vary from 0 (the feature is disabled) to 1 and beyond. + The value 0.1 or so is good enough. The parameter can be set via param2 of the constructor. + + + + + (RPROP only): Initial magnitude of the weight delta. + The default value is 0.1. This parameter can be set via param1 of the constructor. + + + + + (RPROP only): The increase factor for the weight delta. + It must be >1, default value is 1.2 that should work well in most cases, according to the algorithm's author. + The parameter can only be changed explicitly by modifying the structure member. + + + + + (RPROP only): The decrease factor for the weight delta. + It must be <1, default value is 0.5 that should work well in most cases, according to the algorithm's author. + The parameter can only be changed explicitly by modifying the structure member. + + + + + (RPROP only): The minimum value of the weight delta. + It must be >0, the default value is FLT_EPSILON. The parameter can be set via param2 of the constructor. + + + + + (RPROP only): The maximum value of the weight delta. + It must be >1, the default value is 50. The parameter can only be changed explicitly by modifying the structure member. + + + + + Base class for statistical models in ML + + + + + Default constructor + + + + + Releases the resources + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + Deallocates memory and resets the model state + + + + + Saves the model to file + + + + + + Saves the model to file + + + + + + + Loads the model from file + + + + + + Loads the model from file + + + + + + + Writes the model to file storage + + + + + + + Reads the model from file storage + + + + + + + Cascade classifier class for object detection. + + + + + Track whether Dispose has been called + + + + + Default constructor + + + + + Loads a classifier from a file. + + Name of the file from which the classifier is loaded. + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + Checks whether the classifier has been loaded. + + + + + + Loads a classifier from a file. + + Name of the file from which the classifier is loaded. + The file may contain an old HAAR classifier trained by the haartraining application + or a new cascade classifier trained by the traincascade application. + + + + + Detects objects of different sizes in the input image. The detected objects are returned as a list of rectangles. + + Matrix of the type CV_8U containing an image where objects are detected. + Parameter specifying how much the image size is reduced at each image scale. + Parameter specifying how many neighbors each candidate rectangle should have to retain it. + Parameter with the same meaning for an old cascade as in the function cvHaarDetectObjects. + It is not used for a new cascade. + Minimum possible object size. Objects smaller than that are ignored. + Maximum possible object size. Objects larger than that are ignored. + Vector of rectangles where each rectangle contains the detected object. + + + + Detects objects of different sizes in the input image. The detected objects are returned as a list of rectangles. + + Matrix of the type CV_8U containing an image where objects are detected. + + + Parameter specifying how much the image size is reduced at each image scale. + Parameter specifying how many neighbors each candidate rectangle should have to retain it. + Parameter with the same meaning for an old cascade as in the function cvHaarDetectObjects. + It is not used for a new cascade. + Minimum possible object size. Objects smaller than that are ignored. + Maximum possible object size. Objects larger than that are ignored. + + Vector of rectangles where each rectangle contains the detected object. + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Class for grouping object candidates, detected by Cascade Classifier, HOG etc. + instance of the class is to be passed to cv::partition (see cxoperations.hpp) + + + + + + + + + + + + + + Find rectangular regions in the given image that are likely + to contain objects and corresponding confidence levels + + + + + Structure contains the detection information. + + + + + + + + + + + + + bounding box for a detected object + + + + + confidence level + + + + + class (model or detector) ID that detect an object + + + + + Track whether Dispose has been called + + + + + Default constructor + + + + + Creates the HOG descriptor and detector. + + A set of filenames storing the trained detectors (models). Each file contains one model. + See examples of such files here /opencv_extra/testdata/cv/latentsvmdetector/models_VOC2007/. + A set of trained models names. If it’s empty then the name of each model will be + constructed from the name of file containing the model. E.g. the model stored in "/home/user/cat.xml" will get the name "cat". + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + Clear all trained models and their names stored in an class object. + + + + + + + + + + + + A set of filenames storing the trained detectors (models). Each file contains one model. + See examples of such files here /opencv_extra/testdata/cv/latentsvmdetector/models_VOC2007/. + A set of trained models names. If it’s empty then the name of each model will be + constructed from the name of file containing the model. E.g. the model stored in "/home/user/cat.xml" will get the name "cat". + + + + Find rectangular regions in the given image that are likely to contain objects of + loaded classes (models) and corresponding confidence levels. + + An image. + Threshold for the non-maximum suppression algorithm. + Number of threads used in parallel version of the algorithm. + The detections: rectangulars, scores and class IDs. + + + + Return the class (model) names that were passed in constructor or method load or extracted from models filenames in those methods. + + + + + + Return a count of loaded models (classes). + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Clear all inner buffers. + + + + + + + + + + + + + + Base class for Super Resolution algorithms. + + + + + + + + + + + + + + + + + + + + Create Bilateral TV-L1 Super Resolution. + + + + + + Create Bilateral TV-L1 Super Resolution. + + + + + + Create Bilateral TV-L1 Super Resolution. + + + + + + Set input frame source for Super Resolution algorithm. + + Input frame source + + + + Process next frame from input and return output result. + + Output result + + + + + + + + + Clear all inner buffers. + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Creates instance from cv::Ptr<T> . + ptr is disposed when the wrapper disposes. + + + + + + Creates instance from raw pointer T* + + + + + + Releases the resources + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + Pointer to algorithm information (cv::AlgorithmInfo*) + + + + + + + + + + + + + + + + + + + + class for defined Super Resolution algorithm. + + + + + + + + + + + + + + + Creates instance from cv::Ptr<T> . + ptr is disposed when the wrapper disposes. + + + + + + Creates instance from raw pointer T* + + + + + + Releases the resources + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + Pointer to algorithm information (cv::AlgorithmInfo*) + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Creates instance from cv::Ptr<T> . + ptr is disposed when the wrapper disposes. + + + + + + Creates instance from raw pointer T* + + + + + + Releases the resources + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + + + + + + + + + + + + The Base Class for Background/Foreground Segmentation. + The class is only used to define the common interface for + the whole family of background/foreground segmentation algorithms. + + + + + the default constructor + + + + + Creates instance from cv::Ptr<T> . + ptr is disposed when the wrapper disposes. + + + + + + Creates instance from raw T* + + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + Total number of distinct colors to maintain in histogram. + + + + + Set between 0.0 and 1.0, determines how quickly features are "forgotten" from histograms. + + + + + Number of frames of video to use to initialize histograms. + + + + + Number of discrete levels in each channel to be used in histograms. + + + + + Prior probability that any given pixel is a background pixel. A sensitivity parameter. + + + + + Value above which pixel is determined to be FG. + + + + + Smoothing radius, in pixels, for cleaning up FG image. + + + + + Perform background model update + + + + + Performs single-frame background subtraction and builds up a statistical background image + + Input image + Output mask image representing foreground and background pixels + + + + + Validate parameters and set up data structures for appropriate image size. + Must call before running on data. + + input frame size + minimum value taken on by pixels in image sequence. Usually 0 + maximum value taken on by pixels in image sequence. e.g. 1.0 or 255 + + + + Releases all inner buffers. + + + + + Pointer to algorithm information (cv::AlgorithmInfo*) + + + + + + The Base Class for Background/Foreground Segmentation. + The class is only used to define the common interface for + the whole family of background/foreground segmentation algorithms. + + + + + cv::Ptr<FeatureDetector> + + + + + + + + + + the default constructor + + + + + the full constructor that takes the length of the history, the number of gaussian mixtures, the background ratio parameter and the noise strength + + + + + + + + Creates instance from cv::Ptr<T> . + ptr is disposed when the wrapper disposes. + + + + + + Creates instance from raw T* + + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + the update operator + + + + + + + + computes a background image + + + + + + re-initiaization method + + + + + + + Pointer to algorithm information (cv::AlgorithmInfo*) + + + + + + + + + + + + + + + + + + + + + + Clear all inner buffers. + + + + + + + + + + + + + + + + + + + + + + + + + + + + Creates instance from cv::Ptr<T> . + ptr is disposed when the wrapper disposes. + + + + + + Creates instance from raw pointer T* + + + + + + Releases the resources + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + Pointer to algorithm information (cv::AlgorithmInfo*) + + + + + + + + + + + + + + + + + + + Kalman filter. + The class implements standard Kalman filter \url{http://en.wikipedia.org/wiki/Kalman_filter}. + However, you can modify KalmanFilter::transitionMatrix, KalmanFilter::controlMatrix and + KalmanFilter::measurementMatrix to get the extended Kalman filter functionality. + + + + + the default constructor + + + + + the full constructor taking the dimensionality of the state, of the measurement and of the control vector + + + + + + + + + + + + + + + predicted state (x'(k)): x(k)=A*x(k-1)+B*u(k) + + + + + corrected state (x(k)): x(k)=x'(k)+K(k)*(z(k)-H*x'(k)) + + + + + state transition matrix (A) + + + + + control matrix (B) (not used if there is no control) + + + + + measurement matrix (H) + + + + + process noise covariance matrix (Q) + + + + + measurement noise covariance matrix (R) + + + + + priori error estimate covariance matrix (P'(k)): P'(k)=A*P(k-1)*At + Q)*/ + + + + + Kalman gain matrix (K(k)): K(k)=P'(k)*Ht*inv(H*P'(k)*Ht+R) + + + + + posteriori error estimate covariance matrix (P(k)): P(k)=(I-K(k)*H)*P'(k) + + + + + re-initializes Kalman filter. The previous content is destroyed. + + + + + + + + + computes predicted state + + + + + + + updates the predicted state from the measurement + + + + + + + P/Invoke methods of OpenCV 2.x C++ interface + + + + + Is tried P/Invoke once + + + + + DLL file name + + + + + Static constructor + + + + + Load DLL files dynamically using Win32 LoadLibrary + + + + + + Checks whether PInvoke functions can be called + + + + + Class for computing stereo correspondence using the block matching algorithm. + + + + + Track whether Dispose has been called + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Default constructor + + + + + + + + + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + separate initialization function + + + + + + + + computes the disparity for the two rectified 8-bit single-channel images. + the disparity will be 16-bit signed (fixed-point) or 32-bit floating-point image of the same size as left. + + + + + + + + + Abstract definition of Mat indexer + + + + + + 1-dimensional indexer + + Index along the dimension 0 + A value to the specified array element. + + + + 2-dimensional indexer + + Index along the dimension 0 + Index along the dimension 1 + A value to the specified array element. + + + + 3-dimensional indexer + + Index along the dimension 0 + Index along the dimension 1 + Index along the dimension 2 + A value to the specified array element. + + + + n-dimensional indexer + + Array of Mat::dims indices. + A value to the specified array element. + + + + Parent matrix object + + + + + Step byte length for each dimension + + + + + Constructor + + + + + + A matrix whose element is 64FC1 (cv::Mat_<double>) + + + + + Creates empty Mat + + + + + Creates from native cv::Mat* pointer + + + + + + Initializes by Mat object + + Managed Mat object + + + + constructs 2D matrix of the specified size and type + + Number of rows in a 2D array. + Number of columns in a 2D array. + + + + constructs 2D matrix of the specified size and type + + 2D array size: Size(cols, rows) . In the Size() constructor, + the number of rows and the number of columns go in the reverse order. + + + + constucts 2D matrix and fills it with the specified Scalar value. + + Number of rows in a 2D array. + Number of columns in a 2D array. + An optional value to initialize each matrix element with. + To set all the matrix elements to the particular value after the construction, use SetTo(Scalar s) method . + + + + constucts 2D matrix and fills it with the specified Scalar value. + + 2D array size: Size(cols, rows) . In the Size() constructor, + the number of rows and the number of columns go in the reverse order. + An optional value to initialize each matrix element with. + To set all the matrix elements to the particular value after the construction, use SetTo(Scalar s) method . + + + + creates a matrix header for a part of the bigger matrix + + Array that (as a whole or partly) is assigned to the constructed matrix. + No data is copied by these constructors. Instead, the header pointing to m data or its sub-array + is constructed and associated with it. The reference counter, if any, is incremented. + So, when you modify the matrix formed using such a constructor, you also modify the corresponding elements of m . + If you want to have an independent copy of the sub-array, use Mat::clone() . + Range of the m rows to take. As usual, the range start is inclusive and the range end is exclusive. + Use Range.All to take all the rows. + Range of the m columns to take. Use Range.All to take all the columns. + + + + creates a matrix header for a part of the bigger matrix + + Array that (as a whole or partly) is assigned to the constructed matrix. + No data is copied by these constructors. Instead, the header pointing to m data or its sub-array + is constructed and associated with it. The reference counter, if any, is incremented. + So, when you modify the matrix formed using such a constructor, you also modify the corresponding elements of m . + If you want to have an independent copy of the sub-array, use Mat.Clone() . + Array of selected ranges of m along each dimensionality. + + + + creates a matrix header for a part of the bigger matrix + + Array that (as a whole or partly) is assigned to the constructed matrix. + No data is copied by these constructors. Instead, the header pointing to m data or its sub-array + is constructed and associated with it. The reference counter, if any, is incremented. + So, when you modify the matrix formed using such a constructor, you also modify the corresponding elements of m . + If you want to have an independent copy of the sub-array, use Mat.Clone() . + Region of interest. + + + + constructor for matrix headers pointing to user-allocated data + + Number of rows in a 2D array. + Number of columns in a 2D array. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Number of bytes each matrix row occupies. The value should include the padding bytes at the end of each row, if any. + If the parameter is missing (set to AUTO_STEP ), no padding is assumed and the actual step is calculated as cols*elemSize() . + + + + constructor for matrix headers pointing to user-allocated data + + Number of rows in a 2D array. + Number of columns in a 2D array. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Number of bytes each matrix row occupies. The value should include the padding bytes at the end of each row, if any. + If the parameter is missing (set to AUTO_STEP ), no padding is assumed and the actual step is calculated as cols*elemSize() . + + + + constructor for matrix headers pointing to user-allocated data + + Number of rows in a 2D array. + Number of columns in a 2D array. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Number of bytes each matrix row occupies. The value should include the padding bytes at the end of each row, if any. + If the parameter is missing (set to AUTO_STEP ), no padding is assumed and the actual step is calculated as cols*elemSize() . + + + + constructor for matrix headers pointing to user-allocated data + + Array of integers specifying an n-dimensional array shape. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Array of ndims-1 steps in case of a multi-dimensional array (the last step is always set to the element size). + If not specified, the matrix is assumed to be continuous. + + + + constructor for matrix headers pointing to user-allocated data + + Array of integers specifying an n-dimensional array shape. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Array of ndims-1 steps in case of a multi-dimensional array (the last step is always set to the element size). + If not specified, the matrix is assumed to be continuous. + + + + constructor for matrix headers pointing to user-allocated data + + Array of integers specifying an n-dimensional array shape. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Array of ndims-1 steps in case of a multi-dimensional array (the last step is always set to the element size). + If not specified, the matrix is assumed to be continuous. + + + + constructs n-dimensional matrix + + Array of integers specifying an n-dimensional array shape. + + + + constructs n-dimensional matrix + + Array of integers specifying an n-dimensional array shape. + An optional value to initialize each matrix element with. + To set all the matrix elements to the particular value after the construction, use SetTo(Scalar s) method . + + + + converts old-style CvMat to the new matrix; the data is not copied by default + + Old style CvMat object + Flag to specify whether the underlying data of the the old-style CvMat should be + copied to (true) or shared with (false) the newly constructed matrix. When the data is copied, + the allocated buffer is managed using Mat reference counting mechanism. While the data is shared, + the reference counter is NULL, and you should not deallocate the data until the matrix is not destructed. + + + + converts old-style IplImage to the new matrix; the data is not copied by default + + Old style IplImage object + Flag to specify whether the underlying data of the the old-style IplImage should be + copied to (true) or shared with (false) the newly constructed matrix. When the data is copied, + the allocated buffer is managed using Mat reference counting mechanism. While the data is shared, + the reference counter is NULL, and you should not deallocate the data until the matrix is not destructed. + + + + Matrix indexer + + + + + 1-dimensional indexer + + Index along the dimension 0 + A value to the specified array element. + + + + 2-dimensional indexer + + Index along the dimension 0 + Index along the dimension 1 + A value to the specified array element. + + + + 3-dimensional indexer + + Index along the dimension 0 + Index along the dimension 1 + Index along the dimension 2 + A value to the specified array element. + + + + n-dimensional indexer + + Array of Mat::dims indices. + A value to the specified array element. + + + + Gets a type-specific indexer. The indexer has getters/setters to access each matrix element. + + + + + + Initializes as N x 1 matrix and copys array data to this + + Source array data to be copied to this + + + + Initializes as M x N matrix and copys array data to this + + Source array data to be copied to this + + + + Initializes as N x 1 matrix and copys array data to this + + Source array data to be copied to this + + + + Convert this mat to managed array + + + + + + Convert this mat to managed rectangular array + + + + + + + + + + + + Adds elements to the bottom of the matrix. (Mat::push_back) + + Added element(s) + + + + A matrix whose element is 32FC6 (cv::Mat_<cv::Vec6f>) + + + + + Creates empty Mat + + + + + Creates from native cv::Mat* pointer + + + + + + Initializes by Mat object + + Managed Mat object + + + + constructs 2D matrix of the specified size and type + + Number of rows in a 2D array. + Number of columns in a 2D array. + + + + constructs 2D matrix of the specified size and type + + 2D array size: Size(cols, rows) . In the Size() constructor, + the number of rows and the number of columns go in the reverse order. + + + + constucts 2D matrix and fills it with the specified Scalar value. + + Number of rows in a 2D array. + Number of columns in a 2D array. + An optional value to initialize each matrix element with. + To set all the matrix elements to the particular value after the construction, use SetTo(Scalar s) method . + + + + constucts 2D matrix and fills it with the specified Scalar value. + + 2D array size: Size(cols, rows) . In the Size() constructor, + the number of rows and the number of columns go in the reverse order. + An optional value to initialize each matrix element with. + To set all the matrix elements to the particular value after the construction, use SetTo(Scalar s) method . + + + + creates a matrix header for a part of the bigger matrix + + Array that (as a whole or partly) is assigned to the constructed matrix. + No data is copied by these constructors. Instead, the header pointing to m data or its sub-array + is constructed and associated with it. The reference counter, if any, is incremented. + So, when you modify the matrix formed using such a constructor, you also modify the corresponding elements of m . + If you want to have an independent copy of the sub-array, use Mat::clone() . + Range of the m rows to take. As usual, the range start is inclusive and the range end is exclusive. + Use Range.All to take all the rows. + Range of the m columns to take. Use Range.All to take all the columns. + + + + creates a matrix header for a part of the bigger matrix + + Array that (as a whole or partly) is assigned to the constructed matrix. + No data is copied by these constructors. Instead, the header pointing to m data or its sub-array + is constructed and associated with it. The reference counter, if any, is incremented. + So, when you modify the matrix formed using such a constructor, you also modify the corresponding elements of m . + If you want to have an independent copy of the sub-array, use Mat.Clone() . + Array of selected ranges of m along each dimensionality. + + + + creates a matrix header for a part of the bigger matrix + + Array that (as a whole or partly) is assigned to the constructed matrix. + No data is copied by these constructors. Instead, the header pointing to m data or its sub-array + is constructed and associated with it. The reference counter, if any, is incremented. + So, when you modify the matrix formed using such a constructor, you also modify the corresponding elements of m . + If you want to have an independent copy of the sub-array, use Mat.Clone() . + Region of interest. + + + + constructor for matrix headers pointing to user-allocated data + + Number of rows in a 2D array. + Number of columns in a 2D array. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Number of bytes each matrix row occupies. The value should include the padding bytes at the end of each row, if any. + If the parameter is missing (set to AUTO_STEP ), no padding is assumed and the actual step is calculated as cols*elemSize() . + + + + constructor for matrix headers pointing to user-allocated data + + Number of rows in a 2D array. + Number of columns in a 2D array. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Number of bytes each matrix row occupies. The value should include the padding bytes at the end of each row, if any. + If the parameter is missing (set to AUTO_STEP ), no padding is assumed and the actual step is calculated as cols*elemSize() . + + + + constructor for matrix headers pointing to user-allocated data + + Number of rows in a 2D array. + Number of columns in a 2D array. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Number of bytes each matrix row occupies. The value should include the padding bytes at the end of each row, if any. + If the parameter is missing (set to AUTO_STEP ), no padding is assumed and the actual step is calculated as cols*elemSize() . + + + + constructor for matrix headers pointing to user-allocated data + + Array of integers specifying an n-dimensional array shape. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Array of ndims-1 steps in case of a multi-dimensional array (the last step is always set to the element size). + If not specified, the matrix is assumed to be continuous. + + + + constructor for matrix headers pointing to user-allocated data + + Array of integers specifying an n-dimensional array shape. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Array of ndims-1 steps in case of a multi-dimensional array (the last step is always set to the element size). + If not specified, the matrix is assumed to be continuous. + + + + constructor for matrix headers pointing to user-allocated data + + Array of integers specifying an n-dimensional array shape. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Array of ndims-1 steps in case of a multi-dimensional array (the last step is always set to the element size). + If not specified, the matrix is assumed to be continuous. + + + + constructs n-dimensional matrix + + Array of integers specifying an n-dimensional array shape. + + + + constructs n-dimensional matrix + + Array of integers specifying an n-dimensional array shape. + An optional value to initialize each matrix element with. + To set all the matrix elements to the particular value after the construction, use SetTo(Scalar s) method . + + + + converts old-style CvMat to the new matrix; the data is not copied by default + + Old style CvMat object + Flag to specify whether the underlying data of the the old-style CvMat should be + copied to (true) or shared with (false) the newly constructed matrix. When the data is copied, + the allocated buffer is managed using Mat reference counting mechanism. While the data is shared, + the reference counter is NULL, and you should not deallocate the data until the matrix is not destructed. + + + + converts old-style IplImage to the new matrix; the data is not copied by default + + Old style IplImage object + Flag to specify whether the underlying data of the the old-style IplImage should be + copied to (true) or shared with (false) the newly constructed matrix. When the data is copied, + the allocated buffer is managed using Mat reference counting mechanism. While the data is shared, + the reference counter is NULL, and you should not deallocate the data until the matrix is not destructed. + + + + Matrix indexer + + + + + 1-dimensional indexer + + Index along the dimension 0 + A value to the specified array element. + + + + 2-dimensional indexer + + Index along the dimension 0 + Index along the dimension 1 + A value to the specified array element. + + + + 3-dimensional indexer + + Index along the dimension 0 + Index along the dimension 1 + Index along the dimension 2 + A value to the specified array element. + + + + n-dimensional indexer + + Array of Mat::dims indices. + A value to the specified array element. + + + + Gets a type-specific indexer. The indexer has getters/setters to access each matrix element. + + + + + + Initializes as N x 1 matrix and copys array data to this + + Source array data to be copied to this + + + + Initializes as M x N matrix and copys array data to this + + Source array data to be copied to this + + + + Initializes as N x 1 matrix and copys array data to this + + Source array data to be copied to this + + + + Convert this mat to managed array + + + + + + + + + + + + Convert this mat to managed rectangular array + + + + + + + + + + + + Adds elements to the bottom of the matrix. (Mat::push_back) + + Added element(s) + + + + A matrix whose element is 32FC4 (cv::Mat_<cv::Vec4f>) + + + + + Creates empty Mat + + + + + Creates from native cv::Mat* pointer + + + + + + Initializes by Mat object + + Managed Mat object + + + + constructs 2D matrix of the specified size and type + + Number of rows in a 2D array. + Number of columns in a 2D array. + + + + constructs 2D matrix of the specified size and type + + 2D array size: Size(cols, rows) . In the Size() constructor, + the number of rows and the number of columns go in the reverse order. + + + + constucts 2D matrix and fills it with the specified Scalar value. + + Number of rows in a 2D array. + Number of columns in a 2D array. + An optional value to initialize each matrix element with. + To set all the matrix elements to the particular value after the construction, use SetTo(Scalar s) method . + + + + constucts 2D matrix and fills it with the specified Scalar value. + + 2D array size: Size(cols, rows) . In the Size() constructor, + the number of rows and the number of columns go in the reverse order. + An optional value to initialize each matrix element with. + To set all the matrix elements to the particular value after the construction, use SetTo(Scalar s) method . + + + + creates a matrix header for a part of the bigger matrix + + Array that (as a whole or partly) is assigned to the constructed matrix. + No data is copied by these constructors. Instead, the header pointing to m data or its sub-array + is constructed and associated with it. The reference counter, if any, is incremented. + So, when you modify the matrix formed using such a constructor, you also modify the corresponding elements of m . + If you want to have an independent copy of the sub-array, use Mat::clone() . + Range of the m rows to take. As usual, the range start is inclusive and the range end is exclusive. + Use Range.All to take all the rows. + Range of the m columns to take. Use Range.All to take all the columns. + + + + creates a matrix header for a part of the bigger matrix + + Array that (as a whole or partly) is assigned to the constructed matrix. + No data is copied by these constructors. Instead, the header pointing to m data or its sub-array + is constructed and associated with it. The reference counter, if any, is incremented. + So, when you modify the matrix formed using such a constructor, you also modify the corresponding elements of m . + If you want to have an independent copy of the sub-array, use Mat.Clone() . + Array of selected ranges of m along each dimensionality. + + + + creates a matrix header for a part of the bigger matrix + + Array that (as a whole or partly) is assigned to the constructed matrix. + No data is copied by these constructors. Instead, the header pointing to m data or its sub-array + is constructed and associated with it. The reference counter, if any, is incremented. + So, when you modify the matrix formed using such a constructor, you also modify the corresponding elements of m . + If you want to have an independent copy of the sub-array, use Mat.Clone() . + Region of interest. + + + + constructor for matrix headers pointing to user-allocated data + + Number of rows in a 2D array. + Number of columns in a 2D array. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Number of bytes each matrix row occupies. The value should include the padding bytes at the end of each row, if any. + If the parameter is missing (set to AUTO_STEP ), no padding is assumed and the actual step is calculated as cols*elemSize() . + + + + constructor for matrix headers pointing to user-allocated data + + Number of rows in a 2D array. + Number of columns in a 2D array. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Number of bytes each matrix row occupies. The value should include the padding bytes at the end of each row, if any. + If the parameter is missing (set to AUTO_STEP ), no padding is assumed and the actual step is calculated as cols*elemSize() . + + + + constructor for matrix headers pointing to user-allocated data + + Number of rows in a 2D array. + Number of columns in a 2D array. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Number of bytes each matrix row occupies. The value should include the padding bytes at the end of each row, if any. + If the parameter is missing (set to AUTO_STEP ), no padding is assumed and the actual step is calculated as cols*elemSize() . + + + + constructor for matrix headers pointing to user-allocated data + + Array of integers specifying an n-dimensional array shape. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Array of ndims-1 steps in case of a multi-dimensional array (the last step is always set to the element size). + If not specified, the matrix is assumed to be continuous. + + + + constructor for matrix headers pointing to user-allocated data + + Array of integers specifying an n-dimensional array shape. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Array of ndims-1 steps in case of a multi-dimensional array (the last step is always set to the element size). + If not specified, the matrix is assumed to be continuous. + + + + constructor for matrix headers pointing to user-allocated data + + Array of integers specifying an n-dimensional array shape. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Array of ndims-1 steps in case of a multi-dimensional array (the last step is always set to the element size). + If not specified, the matrix is assumed to be continuous. + + + + constructs n-dimensional matrix + + Array of integers specifying an n-dimensional array shape. + + + + constructs n-dimensional matrix + + Array of integers specifying an n-dimensional array shape. + An optional value to initialize each matrix element with. + To set all the matrix elements to the particular value after the construction, use SetTo(Scalar s) method . + + + + converts old-style CvMat to the new matrix; the data is not copied by default + + Old style CvMat object + Flag to specify whether the underlying data of the the old-style CvMat should be + copied to (true) or shared with (false) the newly constructed matrix. When the data is copied, + the allocated buffer is managed using Mat reference counting mechanism. While the data is shared, + the reference counter is NULL, and you should not deallocate the data until the matrix is not destructed. + + + + converts old-style IplImage to the new matrix; the data is not copied by default + + Old style IplImage object + Flag to specify whether the underlying data of the the old-style IplImage should be + copied to (true) or shared with (false) the newly constructed matrix. When the data is copied, + the allocated buffer is managed using Mat reference counting mechanism. While the data is shared, + the reference counter is NULL, and you should not deallocate the data until the matrix is not destructed. + + + + Matrix indexer + + + + + 1-dimensional indexer + + Index along the dimension 0 + A value to the specified array element. + + + + 2-dimensional indexer + + Index along the dimension 0 + Index along the dimension 1 + A value to the specified array element. + + + + 3-dimensional indexer + + Index along the dimension 0 + Index along the dimension 1 + Index along the dimension 2 + A value to the specified array element. + + + + n-dimensional indexer + + Array of Mat::dims indices. + A value to the specified array element. + + + + Gets a type-specific indexer. The indexer has getters/setters to access each matrix element. + + + + + + Initializes as N x 1 matrix and copys array data to this + + Source array data to be copied to this + + + + Initializes as M x N matrix and copys array data to this + + Source array data to be copied to this + + + + Initializes as N x 1 matrix and copys array data to this + + Source array data to be copied to this + + + + Convert this mat to managed array + + + + + + + + + + + + Convert this mat to managed rectangular array + + + + + + + + + + + + Adds elements to the bottom of the matrix. (Mat::push_back) + + Added element(s) + + + + A matrix whose element is cv::DMatch (cv::Mat_<cv::Vec4f>) + + + + + Creates empty Mat + + + + + Creates from native cv::Mat* pointer + + + + + + Initializes by Mat object + + Managed Mat object + + + + constructs 2D matrix of the specified size and type + + Number of rows in a 2D array. + Number of columns in a 2D array. + + + + constructs 2D matrix of the specified size and type + + 2D array size: Size(cols, rows) . In the Size() constructor, + the number of rows and the number of columns go in the reverse order. + + + + constucts 2D matrix and fills it with the specified Scalar value. + + Number of rows in a 2D array. + Number of columns in a 2D array. + An optional value to initialize each matrix element with. + To set all the matrix elements to the particular value after the construction, use SetTo(Scalar s) method . + + + + constucts 2D matrix and fills it with the specified Scalar value. + + 2D array size: Size(cols, rows) . In the Size() constructor, + the number of rows and the number of columns go in the reverse order. + An optional value to initialize each matrix element with. + To set all the matrix elements to the particular value after the construction, use SetTo(Scalar s) method . + + + + creates a matrix header for a part of the bigger matrix + + Array that (as a whole or partly) is assigned to the constructed matrix. + No data is copied by these constructors. Instead, the header pointing to m data or its sub-array + is constructed and associated with it. The reference counter, if any, is incremented. + So, when you modify the matrix formed using such a constructor, you also modify the corresponding elements of m . + If you want to have an independent copy of the sub-array, use Mat::clone() . + Range of the m rows to take. As usual, the range start is inclusive and the range end is exclusive. + Use Range.All to take all the rows. + Range of the m columns to take. Use Range.All to take all the columns. + + + + creates a matrix header for a part of the bigger matrix + + Array that (as a whole or partly) is assigned to the constructed matrix. + No data is copied by these constructors. Instead, the header pointing to m data or its sub-array + is constructed and associated with it. The reference counter, if any, is incremented. + So, when you modify the matrix formed using such a constructor, you also modify the corresponding elements of m . + If you want to have an independent copy of the sub-array, use Mat.Clone() . + Array of selected ranges of m along each dimensionality. + + + + creates a matrix header for a part of the bigger matrix + + Array that (as a whole or partly) is assigned to the constructed matrix. + No data is copied by these constructors. Instead, the header pointing to m data or its sub-array + is constructed and associated with it. The reference counter, if any, is incremented. + So, when you modify the matrix formed using such a constructor, you also modify the corresponding elements of m . + If you want to have an independent copy of the sub-array, use Mat.Clone() . + Region of interest. + + + + constructs n-dimensional matrix + + Array of integers specifying an n-dimensional array shape. + + + + constructs n-dimensional matrix + + Array of integers specifying an n-dimensional array shape. + An optional value to initialize each matrix element with. + To set all the matrix elements to the particular value after the construction, use SetTo(Scalar s) method . + + + + Matrix indexer + + + + + 1-dimensional indexer + + Index along the dimension 0 + A value to the specified array element. + + + + 2-dimensional indexer + + Index along the dimension 0 + Index along the dimension 1 + A value to the specified array element. + + + + 3-dimensional indexer + + Index along the dimension 0 + Index along the dimension 1 + Index along the dimension 2 + A value to the specified array element. + + + + n-dimensional indexer + + Array of Mat::dims indices. + A value to the specified array element. + + + + Gets a type-specific indexer. The indexer has getters/setters to access each matrix element. + + + + + + Initializes as N x 1 matrix and copys array data to this + + Source array data to be copied to this + + + + Initializes as M x N matrix and copys array data to this + + Source array data to be copied to this + + + + Initializes as N x 1 matrix and copys array data to this + + Source array data to be copied to this + + + + Convert this mat to managed array + + + + + + Convert this mat to managed rectangular array + + + + + + + + + + + + Adds elements to the bottom of the matrix. (Mat::push_back) + + Added element(s) + + + + A matrix whose element is cv::Vec3d [CV_64FC3] (cv::Mat_<cv::Vec3d>) + + + + + Creates empty Mat + + + + + Creates from native cv::Mat* pointer + + + + + + Initializes by Mat object + + Managed Mat object + + + + constructs 2D matrix of the specified size and type + + Number of rows in a 2D array. + Number of columns in a 2D array. + + + + constructs 2D matrix of the specified size and type + + 2D array size: Size(cols, rows) . In the Size() constructor, + the number of rows and the number of columns go in the reverse order. + + + + constucts 2D matrix and fills it with the specified Scalar value. + + Number of rows in a 2D array. + Number of columns in a 2D array. + An optional value to initialize each matrix element with. + To set all the matrix elements to the particular value after the construction, use SetTo(Scalar s) method . + + + + constucts 2D matrix and fills it with the specified Scalar value. + + 2D array size: Size(cols, rows) . In the Size() constructor, + the number of rows and the number of columns go in the reverse order. + An optional value to initialize each matrix element with. + To set all the matrix elements to the particular value after the construction, use SetTo(Scalar s) method . + + + + creates a matrix header for a part of the bigger matrix + + Array that (as a whole or partly) is assigned to the constructed matrix. + No data is copied by these constructors. Instead, the header pointing to m data or its sub-array + is constructed and associated with it. The reference counter, if any, is incremented. + So, when you modify the matrix formed using such a constructor, you also modify the corresponding elements of m . + If you want to have an independent copy of the sub-array, use Mat::clone() . + Range of the m rows to take. As usual, the range start is inclusive and the range end is exclusive. + Use Range.All to take all the rows. + Range of the m columns to take. Use Range.All to take all the columns. + + + + creates a matrix header for a part of the bigger matrix + + Array that (as a whole or partly) is assigned to the constructed matrix. + No data is copied by these constructors. Instead, the header pointing to m data or its sub-array + is constructed and associated with it. The reference counter, if any, is incremented. + So, when you modify the matrix formed using such a constructor, you also modify the corresponding elements of m . + If you want to have an independent copy of the sub-array, use Mat.Clone() . + Array of selected ranges of m along each dimensionality. + + + + creates a matrix header for a part of the bigger matrix + + Array that (as a whole or partly) is assigned to the constructed matrix. + No data is copied by these constructors. Instead, the header pointing to m data or its sub-array + is constructed and associated with it. The reference counter, if any, is incremented. + So, when you modify the matrix formed using such a constructor, you also modify the corresponding elements of m . + If you want to have an independent copy of the sub-array, use Mat.Clone() . + Region of interest. + + + + constructor for matrix headers pointing to user-allocated data + + Number of rows in a 2D array. + Number of columns in a 2D array. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Number of bytes each matrix row occupies. The value should include the padding bytes at the end of each row, if any. + If the parameter is missing (set to AUTO_STEP ), no padding is assumed and the actual step is calculated as cols*elemSize() . + + + + constructor for matrix headers pointing to user-allocated data + + Number of rows in a 2D array. + Number of columns in a 2D array. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Number of bytes each matrix row occupies. The value should include the padding bytes at the end of each row, if any. + If the parameter is missing (set to AUTO_STEP ), no padding is assumed and the actual step is calculated as cols*elemSize() . + + + + constructor for matrix headers pointing to user-allocated data + + Number of rows in a 2D array. + Number of columns in a 2D array. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Number of bytes each matrix row occupies. The value should include the padding bytes at the end of each row, if any. + If the parameter is missing (set to AUTO_STEP ), no padding is assumed and the actual step is calculated as cols*elemSize() . + + + + constructor for matrix headers pointing to user-allocated data + + Array of integers specifying an n-dimensional array shape. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Array of ndims-1 steps in case of a multi-dimensional array (the last step is always set to the element size). + If not specified, the matrix is assumed to be continuous. + + + + constructor for matrix headers pointing to user-allocated data + + Array of integers specifying an n-dimensional array shape. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Array of ndims-1 steps in case of a multi-dimensional array (the last step is always set to the element size). + If not specified, the matrix is assumed to be continuous. + + + + constructor for matrix headers pointing to user-allocated data + + Array of integers specifying an n-dimensional array shape. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Array of ndims-1 steps in case of a multi-dimensional array (the last step is always set to the element size). + If not specified, the matrix is assumed to be continuous. + + + + constructs n-dimensional matrix + + Array of integers specifying an n-dimensional array shape. + + + + constructs n-dimensional matrix + + Array of integers specifying an n-dimensional array shape. + An optional value to initialize each matrix element with. + To set all the matrix elements to the particular value after the construction, use SetTo(Scalar s) method . + + + + converts old-style CvMat to the new matrix; the data is not copied by default + + Old style CvMat object + Flag to specify whether the underlying data of the the old-style CvMat should be + copied to (true) or shared with (false) the newly constructed matrix. When the data is copied, + the allocated buffer is managed using Mat reference counting mechanism. While the data is shared, + the reference counter is NULL, and you should not deallocate the data until the matrix is not destructed. + + + + converts old-style IplImage to the new matrix; the data is not copied by default + + Old style IplImage object + Flag to specify whether the underlying data of the the old-style IplImage should be + copied to (true) or shared with (false) the newly constructed matrix. When the data is copied, + the allocated buffer is managed using Mat reference counting mechanism. While the data is shared, + the reference counter is NULL, and you should not deallocate the data until the matrix is not destructed. + + + + Matrix indexer + + + + + 1-dimensional indexer + + Index along the dimension 0 + A value to the specified array element. + + + + 2-dimensional indexer + + Index along the dimension 0 + Index along the dimension 1 + A value to the specified array element. + + + + 3-dimensional indexer + + Index along the dimension 0 + Index along the dimension 1 + Index along the dimension 2 + A value to the specified array element. + + + + n-dimensional indexer + + Array of Mat::dims indices. + A value to the specified array element. + + + + Gets a type-specific indexer. The indexer has getters/setters to access each matrix element. + + + + + + Initializes as N x 1 matrix and copys array data to this + + Source array data to be copied to this + + + + Initializes as M x N matrix and copys array data to this + + Source array data to be copied to this + + + + Initializes as N x 1 matrix and copys array data to this + + Source array data to be copied to this + + + + Convert this mat to managed array + + + + + + Convert this mat to managed array + + + + + + Convert this mat to managed rectangular array + + + + + + + + + + + + Adds elements to the bottom of the matrix. (Mat::push_back) + + Added element(s) + + + + A matrix whose element is cv::Point [CV_64FC2] (cv::Mat_<cv::Point2d>) + + + + + Creates empty Mat + + + + + Creates from native cv::Mat* pointer + + + + + + Initializes by Mat object + + Managed Mat object + + + + constructs 2D matrix of the specified size and type + + Number of rows in a 2D array. + Number of columns in a 2D array. + + + + constructs 2D matrix of the specified size and type + + 2D array size: Size(cols, rows) . In the Size() constructor, + the number of rows and the number of columns go in the reverse order. + + + + constucts 2D matrix and fills it with the specified Scalar value. + + Number of rows in a 2D array. + Number of columns in a 2D array. + An optional value to initialize each matrix element with. + To set all the matrix elements to the particular value after the construction, use SetTo(Scalar s) method . + + + + constucts 2D matrix and fills it with the specified Scalar value. + + 2D array size: Size(cols, rows) . In the Size() constructor, + the number of rows and the number of columns go in the reverse order. + An optional value to initialize each matrix element with. + To set all the matrix elements to the particular value after the construction, use SetTo(Scalar s) method . + + + + creates a matrix header for a part of the bigger matrix + + Array that (as a whole or partly) is assigned to the constructed matrix. + No data is copied by these constructors. Instead, the header pointing to m data or its sub-array + is constructed and associated with it. The reference counter, if any, is incremented. + So, when you modify the matrix formed using such a constructor, you also modify the corresponding elements of m . + If you want to have an independent copy of the sub-array, use Mat::clone() . + Range of the m rows to take. As usual, the range start is inclusive and the range end is exclusive. + Use Range.All to take all the rows. + Range of the m columns to take. Use Range.All to take all the columns. + + + + creates a matrix header for a part of the bigger matrix + + Array that (as a whole or partly) is assigned to the constructed matrix. + No data is copied by these constructors. Instead, the header pointing to m data or its sub-array + is constructed and associated with it. The reference counter, if any, is incremented. + So, when you modify the matrix formed using such a constructor, you also modify the corresponding elements of m . + If you want to have an independent copy of the sub-array, use Mat.Clone() . + Array of selected ranges of m along each dimensionality. + + + + creates a matrix header for a part of the bigger matrix + + Array that (as a whole or partly) is assigned to the constructed matrix. + No data is copied by these constructors. Instead, the header pointing to m data or its sub-array + is constructed and associated with it. The reference counter, if any, is incremented. + So, when you modify the matrix formed using such a constructor, you also modify the corresponding elements of m . + If you want to have an independent copy of the sub-array, use Mat.Clone() . + Region of interest. + + + + constructor for matrix headers pointing to user-allocated data + + Number of rows in a 2D array. + Number of columns in a 2D array. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Number of bytes each matrix row occupies. The value should include the padding bytes at the end of each row, if any. + If the parameter is missing (set to AUTO_STEP ), no padding is assumed and the actual step is calculated as cols*elemSize() . + + + + constructor for matrix headers pointing to user-allocated data + + Number of rows in a 2D array. + Number of columns in a 2D array. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Number of bytes each matrix row occupies. The value should include the padding bytes at the end of each row, if any. + If the parameter is missing (set to AUTO_STEP ), no padding is assumed and the actual step is calculated as cols*elemSize() . + + + + constructor for matrix headers pointing to user-allocated data + + Number of rows in a 2D array. + Number of columns in a 2D array. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Number of bytes each matrix row occupies. The value should include the padding bytes at the end of each row, if any. + If the parameter is missing (set to AUTO_STEP ), no padding is assumed and the actual step is calculated as cols*elemSize() . + + + + constructor for matrix headers pointing to user-allocated data + + Array of integers specifying an n-dimensional array shape. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Array of ndims-1 steps in case of a multi-dimensional array (the last step is always set to the element size). + If not specified, the matrix is assumed to be continuous. + + + + constructor for matrix headers pointing to user-allocated data + + Array of integers specifying an n-dimensional array shape. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Array of ndims-1 steps in case of a multi-dimensional array (the last step is always set to the element size). + If not specified, the matrix is assumed to be continuous. + + + + constructor for matrix headers pointing to user-allocated data + + Array of integers specifying an n-dimensional array shape. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Array of ndims-1 steps in case of a multi-dimensional array (the last step is always set to the element size). + If not specified, the matrix is assumed to be continuous. + + + + constructs n-dimensional matrix + + Array of integers specifying an n-dimensional array shape. + + + + constructs n-dimensional matrix + + Array of integers specifying an n-dimensional array shape. + An optional value to initialize each matrix element with. + To set all the matrix elements to the particular value after the construction, use SetTo(Scalar s) method . + + + + converts old-style CvMat to the new matrix; the data is not copied by default + + Old style CvMat object + Flag to specify whether the underlying data of the the old-style CvMat should be + copied to (true) or shared with (false) the newly constructed matrix. When the data is copied, + the allocated buffer is managed using Mat reference counting mechanism. While the data is shared, + the reference counter is NULL, and you should not deallocate the data until the matrix is not destructed. + + + + converts old-style IplImage to the new matrix; the data is not copied by default + + Old style IplImage object + Flag to specify whether the underlying data of the the old-style IplImage should be + copied to (true) or shared with (false) the newly constructed matrix. When the data is copied, + the allocated buffer is managed using Mat reference counting mechanism. While the data is shared, + the reference counter is NULL, and you should not deallocate the data until the matrix is not destructed. + + + + Matrix indexer + + + + + 1-dimensional indexer + + Index along the dimension 0 + A value to the specified array element. + + + + 2-dimensional indexer + + Index along the dimension 0 + Index along the dimension 1 + A value to the specified array element. + + + + 3-dimensional indexer + + Index along the dimension 0 + Index along the dimension 1 + Index along the dimension 2 + A value to the specified array element. + + + + n-dimensional indexer + + Array of Mat::dims indices. + A value to the specified array element. + + + + Gets a type-specific indexer. The indexer has getters/setters to access each matrix element. + + + + + + Initializes as N x 1 matrix and copys array data to this + + Source array data to be copied to this + + + + Initializes as M x N matrix and copys array data to this + + Source array data to be copied to this + + + + Initializes as N x 1 matrix and copys array data to this + + Source array data to be copied to this + + + + Convert this mat to managed array + + + + + + Convert this mat to managed array + + + + + + Convert this mat to managed rectangular array + + + + + + + + + + + + Adds elements to the bottom of the matrix. (Mat::push_back) + + Added element(s) + + + + A matrix whose element is cv::Point [CV_32FC2] (cv::Mat_<cv::Point2f>) + + + + + Creates empty Mat + + + + + Creates from native cv::Mat* pointer + + + + + + Initializes by Mat object + + Managed Mat object + + + + constructs 2D matrix of the specified size and type + + Number of rows in a 2D array. + Number of columns in a 2D array. + + + + constructs 2D matrix of the specified size and type + + 2D array size: Size(cols, rows) . In the Size() constructor, + the number of rows and the number of columns go in the reverse order. + + + + constucts 2D matrix and fills it with the specified Scalar value. + + Number of rows in a 2D array. + Number of columns in a 2D array. + An optional value to initialize each matrix element with. + To set all the matrix elements to the particular value after the construction, use SetTo(Scalar s) method . + + + + constucts 2D matrix and fills it with the specified Scalar value. + + 2D array size: Size(cols, rows) . In the Size() constructor, + the number of rows and the number of columns go in the reverse order. + An optional value to initialize each matrix element with. + To set all the matrix elements to the particular value after the construction, use SetTo(Scalar s) method . + + + + creates a matrix header for a part of the bigger matrix + + Array that (as a whole or partly) is assigned to the constructed matrix. + No data is copied by these constructors. Instead, the header pointing to m data or its sub-array + is constructed and associated with it. The reference counter, if any, is incremented. + So, when you modify the matrix formed using such a constructor, you also modify the corresponding elements of m . + If you want to have an independent copy of the sub-array, use Mat::clone() . + Range of the m rows to take. As usual, the range start is inclusive and the range end is exclusive. + Use Range.All to take all the rows. + Range of the m columns to take. Use Range.All to take all the columns. + + + + creates a matrix header for a part of the bigger matrix + + Array that (as a whole or partly) is assigned to the constructed matrix. + No data is copied by these constructors. Instead, the header pointing to m data or its sub-array + is constructed and associated with it. The reference counter, if any, is incremented. + So, when you modify the matrix formed using such a constructor, you also modify the corresponding elements of m . + If you want to have an independent copy of the sub-array, use Mat.Clone() . + Array of selected ranges of m along each dimensionality. + + + + creates a matrix header for a part of the bigger matrix + + Array that (as a whole or partly) is assigned to the constructed matrix. + No data is copied by these constructors. Instead, the header pointing to m data or its sub-array + is constructed and associated with it. The reference counter, if any, is incremented. + So, when you modify the matrix formed using such a constructor, you also modify the corresponding elements of m . + If you want to have an independent copy of the sub-array, use Mat.Clone() . + Region of interest. + + + + constructor for matrix headers pointing to user-allocated data + + Number of rows in a 2D array. + Number of columns in a 2D array. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Number of bytes each matrix row occupies. The value should include the padding bytes at the end of each row, if any. + If the parameter is missing (set to AUTO_STEP ), no padding is assumed and the actual step is calculated as cols*elemSize() . + + + + constructor for matrix headers pointing to user-allocated data + + Number of rows in a 2D array. + Number of columns in a 2D array. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Number of bytes each matrix row occupies. The value should include the padding bytes at the end of each row, if any. + If the parameter is missing (set to AUTO_STEP ), no padding is assumed and the actual step is calculated as cols*elemSize() . + + + + constructor for matrix headers pointing to user-allocated data + + Number of rows in a 2D array. + Number of columns in a 2D array. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Number of bytes each matrix row occupies. The value should include the padding bytes at the end of each row, if any. + If the parameter is missing (set to AUTO_STEP ), no padding is assumed and the actual step is calculated as cols*elemSize() . + + + + constructor for matrix headers pointing to user-allocated data + + Array of integers specifying an n-dimensional array shape. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Array of ndims-1 steps in case of a multi-dimensional array (the last step is always set to the element size). + If not specified, the matrix is assumed to be continuous. + + + + constructor for matrix headers pointing to user-allocated data + + Array of integers specifying an n-dimensional array shape. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Array of ndims-1 steps in case of a multi-dimensional array (the last step is always set to the element size). + If not specified, the matrix is assumed to be continuous. + + + + constructor for matrix headers pointing to user-allocated data + + Array of integers specifying an n-dimensional array shape. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Array of ndims-1 steps in case of a multi-dimensional array (the last step is always set to the element size). + If not specified, the matrix is assumed to be continuous. + + + + constructs n-dimensional matrix + + Array of integers specifying an n-dimensional array shape. + + + + constructs n-dimensional matrix + + Array of integers specifying an n-dimensional array shape. + An optional value to initialize each matrix element with. + To set all the matrix elements to the particular value after the construction, use SetTo(Scalar s) method . + + + + converts old-style CvMat to the new matrix; the data is not copied by default + + Old style CvMat object + Flag to specify whether the underlying data of the the old-style CvMat should be + copied to (true) or shared with (false) the newly constructed matrix. When the data is copied, + the allocated buffer is managed using Mat reference counting mechanism. While the data is shared, + the reference counter is NULL, and you should not deallocate the data until the matrix is not destructed. + + + + converts old-style IplImage to the new matrix; the data is not copied by default + + Old style IplImage object + Flag to specify whether the underlying data of the the old-style IplImage should be + copied to (true) or shared with (false) the newly constructed matrix. When the data is copied, + the allocated buffer is managed using Mat reference counting mechanism. While the data is shared, + the reference counter is NULL, and you should not deallocate the data until the matrix is not destructed. + + + + Matrix indexer + + + + + 1-dimensional indexer + + Index along the dimension 0 + A value to the specified array element. + + + + 2-dimensional indexer + + Index along the dimension 0 + Index along the dimension 1 + A value to the specified array element. + + + + 3-dimensional indexer + + Index along the dimension 0 + Index along the dimension 1 + Index along the dimension 2 + A value to the specified array element. + + + + n-dimensional indexer + + Array of Mat::dims indices. + A value to the specified array element. + + + + Gets a type-specific indexer. The indexer has getters/setters to access each matrix element. + + + + + + Initializes as N x 1 matrix and copys array data to this + + Source array data to be copied to this + + + + Initializes as M x N matrix and copys array data to this + + Source array data to be copied to this + + + + Initializes as N x 1 matrix and copys array data to this + + Source array data to be copied to this + + + + Convert this mat to managed array + + + + + + Convert this mat to managed array + + + + + + Convert this mat to managed rectangular array + + + + + + + + + + + + Adds elements to the bottom of the matrix. (Mat::push_back) + + Added element(s) + + + + A matrix whose element is 16UC1 (cv::Mat_<ushort>) + + + + + Creates empty Mat + + + + + Creates from native cv::Mat* pointer + + + + + + Initializes by Mat object + + Managed Mat object + + + + constructs 2D matrix of the specified size and type + + Number of rows in a 2D array. + Number of columns in a 2D array. + + + + constructs 2D matrix of the specified size and type + + 2D array size: Size(cols, rows) . In the Size() constructor, + the number of rows and the number of columns go in the reverse order. + + + + constucts 2D matrix and fills it with the specified Scalar value. + + Number of rows in a 2D array. + Number of columns in a 2D array. + An optional value to initialize each matrix element with. + To set all the matrix elements to the particular value after the construction, use SetTo(Scalar s) method . + + + + constucts 2D matrix and fills it with the specified Scalar value. + + 2D array size: Size(cols, rows) . In the Size() constructor, + the number of rows and the number of columns go in the reverse order. + An optional value to initialize each matrix element with. + To set all the matrix elements to the particular value after the construction, use SetTo(Scalar s) method . + + + + creates a matrix header for a part of the bigger matrix + + Array that (as a whole or partly) is assigned to the constructed matrix. + No data is copied by these constructors. Instead, the header pointing to m data or its sub-array + is constructed and associated with it. The reference counter, if any, is incremented. + So, when you modify the matrix formed using such a constructor, you also modify the corresponding elements of m . + If you want to have an independent copy of the sub-array, use Mat::clone() . + Range of the m rows to take. As usual, the range start is inclusive and the range end is exclusive. + Use Range.All to take all the rows. + Range of the m columns to take. Use Range.All to take all the columns. + + + + creates a matrix header for a part of the bigger matrix + + Array that (as a whole or partly) is assigned to the constructed matrix. + No data is copied by these constructors. Instead, the header pointing to m data or its sub-array + is constructed and associated with it. The reference counter, if any, is incremented. + So, when you modify the matrix formed using such a constructor, you also modify the corresponding elements of m . + If you want to have an independent copy of the sub-array, use Mat.Clone() . + Array of selected ranges of m along each dimensionality. + + + + creates a matrix header for a part of the bigger matrix + + Array that (as a whole or partly) is assigned to the constructed matrix. + No data is copied by these constructors. Instead, the header pointing to m data or its sub-array + is constructed and associated with it. The reference counter, if any, is incremented. + So, when you modify the matrix formed using such a constructor, you also modify the corresponding elements of m . + If you want to have an independent copy of the sub-array, use Mat.Clone() . + Region of interest. + + + + constructor for matrix headers pointing to user-allocated data + + Number of rows in a 2D array. + Number of columns in a 2D array. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Number of bytes each matrix row occupies. The value should include the padding bytes at the end of each row, if any. + If the parameter is missing (set to AUTO_STEP ), no padding is assumed and the actual step is calculated as cols*elemSize() . + + + + constructor for matrix headers pointing to user-allocated data + + Number of rows in a 2D array. + Number of columns in a 2D array. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Number of bytes each matrix row occupies. The value should include the padding bytes at the end of each row, if any. + If the parameter is missing (set to AUTO_STEP ), no padding is assumed and the actual step is calculated as cols*elemSize() . + + + + constructor for matrix headers pointing to user-allocated data + + Number of rows in a 2D array. + Number of columns in a 2D array. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Number of bytes each matrix row occupies. The value should include the padding bytes at the end of each row, if any. + If the parameter is missing (set to AUTO_STEP ), no padding is assumed and the actual step is calculated as cols*elemSize() . + + + + constructor for matrix headers pointing to user-allocated data + + Array of integers specifying an n-dimensional array shape. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Array of ndims-1 steps in case of a multi-dimensional array (the last step is always set to the element size). + If not specified, the matrix is assumed to be continuous. + + + + constructor for matrix headers pointing to user-allocated data + + Array of integers specifying an n-dimensional array shape. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Array of ndims-1 steps in case of a multi-dimensional array (the last step is always set to the element size). + If not specified, the matrix is assumed to be continuous. + + + + constructor for matrix headers pointing to user-allocated data + + Array of integers specifying an n-dimensional array shape. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Array of ndims-1 steps in case of a multi-dimensional array (the last step is always set to the element size). + If not specified, the matrix is assumed to be continuous. + + + + constructs n-dimensional matrix + + Array of integers specifying an n-dimensional array shape. + + + + constructs n-dimensional matrix + + Array of integers specifying an n-dimensional array shape. + An optional value to initialize each matrix element with. + To set all the matrix elements to the particular value after the construction, use SetTo(Scalar s) method . + + + + converts old-style CvMat to the new matrix; the data is not copied by default + + Old style CvMat object + Flag to specify whether the underlying data of the the old-style CvMat should be + copied to (true) or shared with (false) the newly constructed matrix. When the data is copied, + the allocated buffer is managed using Mat reference counting mechanism. While the data is shared, + the reference counter is NULL, and you should not deallocate the data until the matrix is not destructed. + + + + converts old-style IplImage to the new matrix; the data is not copied by default + + Old style IplImage object + Flag to specify whether the underlying data of the the old-style IplImage should be + copied to (true) or shared with (false) the newly constructed matrix. When the data is copied, + the allocated buffer is managed using Mat reference counting mechanism. While the data is shared, + the reference counter is NULL, and you should not deallocate the data until the matrix is not destructed. + + + + Matrix indexer + + + + + 1-dimensional indexer + + Index along the dimension 0 + A value to the specified array element. + + + + 2-dimensional indexer + + Index along the dimension 0 + Index along the dimension 1 + A value to the specified array element. + + + + 3-dimensional indexer + + Index along the dimension 0 + Index along the dimension 1 + Index along the dimension 2 + A value to the specified array element. + + + + n-dimensional indexer + + Array of Mat::dims indices. + A value to the specified array element. + + + + Gets a type-specific indexer. The indexer has getters/setters to access each matrix element. + + + + + + Initializes as N x 1 matrix and copys array data to this + + Source array data to be copied to this + + + + Initializes as M x N matrix and copys array data to this + + Source array data to be copied to this + + + + Initializes as N x 1 matrix and copys array data to this + + Source array data to be copied to this + + + + Convert this mat to managed array + + + + + + Convert this mat to managed rectangular array + + + + + + + + + + + + Adds elements to the bottom of the matrix. (Mat::push_back) + + Added element(s) + + + + A matrix whose element is 16SC1 (cv::Mat_<short>) + + + + + Creates empty Mat + + + + + Creates from native cv::Mat* pointer + + + + + + Initializes by Mat object + + Managed Mat object + + + + constructs 2D matrix of the specified size and type + + Number of rows in a 2D array. + Number of columns in a 2D array. + + + + constructs 2D matrix of the specified size and type + + 2D array size: Size(cols, rows) . In the Size() constructor, + the number of rows and the number of columns go in the reverse order. + + + + constucts 2D matrix and fills it with the specified Scalar value. + + Number of rows in a 2D array. + Number of columns in a 2D array. + An optional value to initialize each matrix element with. + To set all the matrix elements to the particular value after the construction, use SetTo(Scalar s) method . + + + + constucts 2D matrix and fills it with the specified Scalar value. + + 2D array size: Size(cols, rows) . In the Size() constructor, + the number of rows and the number of columns go in the reverse order. + An optional value to initialize each matrix element with. + To set all the matrix elements to the particular value after the construction, use SetTo(Scalar s) method . + + + + creates a matrix header for a part of the bigger matrix + + Array that (as a whole or partly) is assigned to the constructed matrix. + No data is copied by these constructors. Instead, the header pointing to m data or its sub-array + is constructed and associated with it. The reference counter, if any, is incremented. + So, when you modify the matrix formed using such a constructor, you also modify the corresponding elements of m . + If you want to have an independent copy of the sub-array, use Mat::clone() . + Range of the m rows to take. As usual, the range start is inclusive and the range end is exclusive. + Use Range.All to take all the rows. + Range of the m columns to take. Use Range.All to take all the columns. + + + + creates a matrix header for a part of the bigger matrix + + Array that (as a whole or partly) is assigned to the constructed matrix. + No data is copied by these constructors. Instead, the header pointing to m data or its sub-array + is constructed and associated with it. The reference counter, if any, is incremented. + So, when you modify the matrix formed using such a constructor, you also modify the corresponding elements of m . + If you want to have an independent copy of the sub-array, use Mat.Clone() . + Array of selected ranges of m along each dimensionality. + + + + creates a matrix header for a part of the bigger matrix + + Array that (as a whole or partly) is assigned to the constructed matrix. + No data is copied by these constructors. Instead, the header pointing to m data or its sub-array + is constructed and associated with it. The reference counter, if any, is incremented. + So, when you modify the matrix formed using such a constructor, you also modify the corresponding elements of m . + If you want to have an independent copy of the sub-array, use Mat.Clone() . + Region of interest. + + + + constructor for matrix headers pointing to user-allocated data + + Number of rows in a 2D array. + Number of columns in a 2D array. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Number of bytes each matrix row occupies. The value should include the padding bytes at the end of each row, if any. + If the parameter is missing (set to AUTO_STEP ), no padding is assumed and the actual step is calculated as cols*elemSize() . + + + + constructor for matrix headers pointing to user-allocated data + + Number of rows in a 2D array. + Number of columns in a 2D array. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Number of bytes each matrix row occupies. The value should include the padding bytes at the end of each row, if any. + If the parameter is missing (set to AUTO_STEP ), no padding is assumed and the actual step is calculated as cols*elemSize() . + + + + constructor for matrix headers pointing to user-allocated data + + Number of rows in a 2D array. + Number of columns in a 2D array. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Number of bytes each matrix row occupies. The value should include the padding bytes at the end of each row, if any. + If the parameter is missing (set to AUTO_STEP ), no padding is assumed and the actual step is calculated as cols*elemSize() . + + + + constructor for matrix headers pointing to user-allocated data + + Array of integers specifying an n-dimensional array shape. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Array of ndims-1 steps in case of a multi-dimensional array (the last step is always set to the element size). + If not specified, the matrix is assumed to be continuous. + + + + constructor for matrix headers pointing to user-allocated data + + Array of integers specifying an n-dimensional array shape. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Array of ndims-1 steps in case of a multi-dimensional array (the last step is always set to the element size). + If not specified, the matrix is assumed to be continuous. + + + + constructor for matrix headers pointing to user-allocated data + + Array of integers specifying an n-dimensional array shape. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Array of ndims-1 steps in case of a multi-dimensional array (the last step is always set to the element size). + If not specified, the matrix is assumed to be continuous. + + + + constructs n-dimensional matrix + + Array of integers specifying an n-dimensional array shape. + + + + constructs n-dimensional matrix + + Array of integers specifying an n-dimensional array shape. + An optional value to initialize each matrix element with. + To set all the matrix elements to the particular value after the construction, use SetTo(Scalar s) method . + + + + converts old-style CvMat to the new matrix; the data is not copied by default + + Old style CvMat object + Flag to specify whether the underlying data of the the old-style CvMat should be + copied to (true) or shared with (false) the newly constructed matrix. When the data is copied, + the allocated buffer is managed using Mat reference counting mechanism. While the data is shared, + the reference counter is NULL, and you should not deallocate the data until the matrix is not destructed. + + + + converts old-style IplImage to the new matrix; the data is not copied by default + + Old style IplImage object + Flag to specify whether the underlying data of the the old-style IplImage should be + copied to (true) or shared with (false) the newly constructed matrix. When the data is copied, + the allocated buffer is managed using Mat reference counting mechanism. While the data is shared, + the reference counter is NULL, and you should not deallocate the data until the matrix is not destructed. + + + + Matrix indexer + + + + + 1-dimensional indexer + + Index along the dimension 0 + A value to the specified array element. + + + + 2-dimensional indexer + + Index along the dimension 0 + Index along the dimension 1 + A value to the specified array element. + + + + 3-dimensional indexer + + Index along the dimension 0 + Index along the dimension 1 + Index along the dimension 2 + A value to the specified array element. + + + + n-dimensional indexer + + Array of Mat::dims indices. + A value to the specified array element. + + + + Gets a type-specific indexer. The indexer has getters/setters to access each matrix element. + + + + + + Initializes as N x 1 matrix and copys array data to this + + Source array data to be copied to this + + + + Initializes as M x N matrix and copys array data to this + + Source array data to be copied to this + + + + Initializes as N x 1 matrix and copys array data to this + + Source array data to be copied to this + + + + Convert this mat to managed array + + + + + + Convert this mat to managed rectangular array + + + + + + + + + + + + Adds elements to the bottom of the matrix. (Mat::push_back) + + Added element(s) + + + + A matrix whose element is 32SC1 (cv::Mat_<int>) + + + + + Creates empty Mat + + + + + Creates from native cv::Mat* pointer + + + + + + Initializes by Mat object + + Managed Mat object + + + + constructs 2D matrix of the specified size and type + + Number of rows in a 2D array. + Number of columns in a 2D array. + + + + constructs 2D matrix of the specified size and type + + 2D array size: Size(cols, rows) . In the Size() constructor, + the number of rows and the number of columns go in the reverse order. + + + + constucts 2D matrix and fills it with the specified Scalar value. + + Number of rows in a 2D array. + Number of columns in a 2D array. + An optional value to initialize each matrix element with. + To set all the matrix elements to the particular value after the construction, use SetTo(Scalar s) method . + + + + constucts 2D matrix and fills it with the specified Scalar value. + + 2D array size: Size(cols, rows) . In the Size() constructor, + the number of rows and the number of columns go in the reverse order. + An optional value to initialize each matrix element with. + To set all the matrix elements to the particular value after the construction, use SetTo(Scalar s) method . + + + + creates a matrix header for a part of the bigger matrix + + Array that (as a whole or partly) is assigned to the constructed matrix. + No data is copied by these constructors. Instead, the header pointing to m data or its sub-array + is constructed and associated with it. The reference counter, if any, is incremented. + So, when you modify the matrix formed using such a constructor, you also modify the corresponding elements of m . + If you want to have an independent copy of the sub-array, use Mat::clone() . + Range of the m rows to take. As usual, the range start is inclusive and the range end is exclusive. + Use Range.All to take all the rows. + Range of the m columns to take. Use Range.All to take all the columns. + + + + creates a matrix header for a part of the bigger matrix + + Array that (as a whole or partly) is assigned to the constructed matrix. + No data is copied by these constructors. Instead, the header pointing to m data or its sub-array + is constructed and associated with it. The reference counter, if any, is incremented. + So, when you modify the matrix formed using such a constructor, you also modify the corresponding elements of m . + If you want to have an independent copy of the sub-array, use Mat.Clone() . + Array of selected ranges of m along each dimensionality. + + + + creates a matrix header for a part of the bigger matrix + + Array that (as a whole or partly) is assigned to the constructed matrix. + No data is copied by these constructors. Instead, the header pointing to m data or its sub-array + is constructed and associated with it. The reference counter, if any, is incremented. + So, when you modify the matrix formed using such a constructor, you also modify the corresponding elements of m . + If you want to have an independent copy of the sub-array, use Mat.Clone() . + Region of interest. + + + + constructor for matrix headers pointing to user-allocated data + + Number of rows in a 2D array. + Number of columns in a 2D array. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Number of bytes each matrix row occupies. The value should include the padding bytes at the end of each row, if any. + If the parameter is missing (set to AUTO_STEP ), no padding is assumed and the actual step is calculated as cols*elemSize() . + + + + constructor for matrix headers pointing to user-allocated data + + Number of rows in a 2D array. + Number of columns in a 2D array. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Number of bytes each matrix row occupies. The value should include the padding bytes at the end of each row, if any. + If the parameter is missing (set to AUTO_STEP ), no padding is assumed and the actual step is calculated as cols*elemSize() . + + + + constructor for matrix headers pointing to user-allocated data + + Number of rows in a 2D array. + Number of columns in a 2D array. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Number of bytes each matrix row occupies. The value should include the padding bytes at the end of each row, if any. + If the parameter is missing (set to AUTO_STEP ), no padding is assumed and the actual step is calculated as cols*elemSize() . + + + + constructor for matrix headers pointing to user-allocated data + + Array of integers specifying an n-dimensional array shape. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Array of ndims-1 steps in case of a multi-dimensional array (the last step is always set to the element size). + If not specified, the matrix is assumed to be continuous. + + + + constructor for matrix headers pointing to user-allocated data + + Array of integers specifying an n-dimensional array shape. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Array of ndims-1 steps in case of a multi-dimensional array (the last step is always set to the element size). + If not specified, the matrix is assumed to be continuous. + + + + constructor for matrix headers pointing to user-allocated data + + Array of integers specifying an n-dimensional array shape. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Array of ndims-1 steps in case of a multi-dimensional array (the last step is always set to the element size). + If not specified, the matrix is assumed to be continuous. + + + + constructs n-dimensional matrix + + Array of integers specifying an n-dimensional array shape. + + + + constructs n-dimensional matrix + + Array of integers specifying an n-dimensional array shape. + An optional value to initialize each matrix element with. + To set all the matrix elements to the particular value after the construction, use SetTo(Scalar s) method . + + + + converts old-style CvMat to the new matrix; the data is not copied by default + + Old style CvMat object + Flag to specify whether the underlying data of the the old-style CvMat should be + copied to (true) or shared with (false) the newly constructed matrix. When the data is copied, + the allocated buffer is managed using Mat reference counting mechanism. While the data is shared, + the reference counter is NULL, and you should not deallocate the data until the matrix is not destructed. + + + + converts old-style IplImage to the new matrix; the data is not copied by default + + Old style IplImage object + Flag to specify whether the underlying data of the the old-style IplImage should be + copied to (true) or shared with (false) the newly constructed matrix. When the data is copied, + the allocated buffer is managed using Mat reference counting mechanism. While the data is shared, + the reference counter is NULL, and you should not deallocate the data until the matrix is not destructed. + + + + Matrix indexer + + + + + 1-dimensional indexer + + Index along the dimension 0 + A value to the specified array element. + + + + 2-dimensional indexer + + Index along the dimension 0 + Index along the dimension 1 + A value to the specified array element. + + + + 3-dimensional indexer + + Index along the dimension 0 + Index along the dimension 1 + Index along the dimension 2 + A value to the specified array element. + + + + n-dimensional indexer + + Array of Mat::dims indices. + A value to the specified array element. + + + + Gets a type-specific indexer. The indexer has getters/setters to access each matrix element. + + + + + + Initializes as N x 1 matrix and copys array data to this + + Source array data to be copied to this + + + + Initializes as M x N matrix and copys array data to this + + Source array data to be copied to this + + + + Initializes as N x 1 matrix and copys array data to this + + Source array data to be copied to this + + + + Convert this mat to managed array + + + + + + Convert this mat to managed rectangular array + + + + + + + + + + + + Adds elements to the bottom of the matrix. (Mat::push_back) + + Added element(s) + + + + A matrix whose element is 32FC1 (cv::Mat_<float>) + + + + + Creates empty Mat + + + + + Creates from native cv::Mat* pointer + + + + + + Initializes by Mat object + + Managed Mat object + + + + constructs 2D matrix of the specified size and type + + Number of rows in a 2D array. + Number of columns in a 2D array. + + + + constructs 2D matrix of the specified size and type + + 2D array size: Size(cols, rows) . In the Size() constructor, + the number of rows and the number of columns go in the reverse order. + + + + constucts 2D matrix and fills it with the specified Scalar value. + + Number of rows in a 2D array. + Number of columns in a 2D array. + An optional value to initialize each matrix element with. + To set all the matrix elements to the particular value after the construction, use SetTo(Scalar s) method . + + + + constucts 2D matrix and fills it with the specified Scalar value. + + 2D array size: Size(cols, rows) . In the Size() constructor, + the number of rows and the number of columns go in the reverse order. + An optional value to initialize each matrix element with. + To set all the matrix elements to the particular value after the construction, use SetTo(Scalar s) method . + + + + creates a matrix header for a part of the bigger matrix + + Array that (as a whole or partly) is assigned to the constructed matrix. + No data is copied by these constructors. Instead, the header pointing to m data or its sub-array + is constructed and associated with it. The reference counter, if any, is incremented. + So, when you modify the matrix formed using such a constructor, you also modify the corresponding elements of m . + If you want to have an independent copy of the sub-array, use Mat::clone() . + Range of the m rows to take. As usual, the range start is inclusive and the range end is exclusive. + Use Range.All to take all the rows. + Range of the m columns to take. Use Range.All to take all the columns. + + + + creates a matrix header for a part of the bigger matrix + + Array that (as a whole or partly) is assigned to the constructed matrix. + No data is copied by these constructors. Instead, the header pointing to m data or its sub-array + is constructed and associated with it. The reference counter, if any, is incremented. + So, when you modify the matrix formed using such a constructor, you also modify the corresponding elements of m . + If you want to have an independent copy of the sub-array, use Mat.Clone() . + Array of selected ranges of m along each dimensionality. + + + + creates a matrix header for a part of the bigger matrix + + Array that (as a whole or partly) is assigned to the constructed matrix. + No data is copied by these constructors. Instead, the header pointing to m data or its sub-array + is constructed and associated with it. The reference counter, if any, is incremented. + So, when you modify the matrix formed using such a constructor, you also modify the corresponding elements of m . + If you want to have an independent copy of the sub-array, use Mat.Clone() . + Region of interest. + + + + constructor for matrix headers pointing to user-allocated data + + Number of rows in a 2D array. + Number of columns in a 2D array. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Number of bytes each matrix row occupies. The value should include the padding bytes at the end of each row, if any. + If the parameter is missing (set to AUTO_STEP ), no padding is assumed and the actual step is calculated as cols*elemSize() . + + + + constructor for matrix headers pointing to user-allocated data + + Number of rows in a 2D array. + Number of columns in a 2D array. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Number of bytes each matrix row occupies. The value should include the padding bytes at the end of each row, if any. + If the parameter is missing (set to AUTO_STEP ), no padding is assumed and the actual step is calculated as cols*elemSize() . + + + + constructor for matrix headers pointing to user-allocated data + + Number of rows in a 2D array. + Number of columns in a 2D array. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Number of bytes each matrix row occupies. The value should include the padding bytes at the end of each row, if any. + If the parameter is missing (set to AUTO_STEP ), no padding is assumed and the actual step is calculated as cols*elemSize() . + + + + constructor for matrix headers pointing to user-allocated data + + Array of integers specifying an n-dimensional array shape. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Array of ndims-1 steps in case of a multi-dimensional array (the last step is always set to the element size). + If not specified, the matrix is assumed to be continuous. + + + + constructor for matrix headers pointing to user-allocated data + + Array of integers specifying an n-dimensional array shape. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Array of ndims-1 steps in case of a multi-dimensional array (the last step is always set to the element size). + If not specified, the matrix is assumed to be continuous. + + + + constructor for matrix headers pointing to user-allocated data + + Array of integers specifying an n-dimensional array shape. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Array of ndims-1 steps in case of a multi-dimensional array (the last step is always set to the element size). + If not specified, the matrix is assumed to be continuous. + + + + constructs n-dimensional matrix + + Array of integers specifying an n-dimensional array shape. + + + + constructs n-dimensional matrix + + Array of integers specifying an n-dimensional array shape. + An optional value to initialize each matrix element with. + To set all the matrix elements to the particular value after the construction, use SetTo(Scalar s) method . + + + + converts old-style CvMat to the new matrix; the data is not copied by default + + Old style CvMat object + Flag to specify whether the underlying data of the the old-style CvMat should be + copied to (true) or shared with (false) the newly constructed matrix. When the data is copied, + the allocated buffer is managed using Mat reference counting mechanism. While the data is shared, + the reference counter is NULL, and you should not deallocate the data until the matrix is not destructed. + + + + converts old-style IplImage to the new matrix; the data is not copied by default + + Old style IplImage object + Flag to specify whether the underlying data of the the old-style IplImage should be + copied to (true) or shared with (false) the newly constructed matrix. When the data is copied, + the allocated buffer is managed using Mat reference counting mechanism. While the data is shared, + the reference counter is NULL, and you should not deallocate the data until the matrix is not destructed. + + + + Matrix indexer + + + + + 1-dimensional indexer + + Index along the dimension 0 + A value to the specified array element. + + + + 2-dimensional indexer + + Index along the dimension 0 + Index along the dimension 1 + A value to the specified array element. + + + + 3-dimensional indexer + + Index along the dimension 0 + Index along the dimension 1 + Index along the dimension 2 + A value to the specified array element. + + + + n-dimensional indexer + + Array of Mat::dims indices. + A value to the specified array element. + + + + Gets a type-specific indexer. The indexer has getters/setters to access each matrix element. + + + + + + Initializes as N x 1 matrix and copys array data to this + + Source array data to be copied to this + + + + Initializes as M x N matrix and copys array data to this + + Source array data to be copied to this + + + + Initializes as N x 1 matrix and copys array data to this + + Source array data to be copied to this + + + + Convert this mat to managed array + + + + + + Convert this mat to managed rectangular array + + + + + + + + + + + + Adds elements to the bottom of the matrix. (Mat::push_back) + + Added element(s) + + + + A matrix whose element is cv::Point [CV_32SC2] (cv::Mat_<cv::Point>) + + + + + Creates empty Mat + + + + + Creates from native cv::Mat* pointer + + + + + + Initializes by Mat object + + Managed Mat object + + + + constructs 2D matrix of the specified size and type + + Number of rows in a 2D array. + Number of columns in a 2D array. + + + + constructs 2D matrix of the specified size and type + + 2D array size: Size(cols, rows) . In the Size() constructor, + the number of rows and the number of columns go in the reverse order. + + + + constucts 2D matrix and fills it with the specified Scalar value. + + Number of rows in a 2D array. + Number of columns in a 2D array. + An optional value to initialize each matrix element with. + To set all the matrix elements to the particular value after the construction, use SetTo(Scalar s) method . + + + + constucts 2D matrix and fills it with the specified Scalar value. + + 2D array size: Size(cols, rows) . In the Size() constructor, + the number of rows and the number of columns go in the reverse order. + An optional value to initialize each matrix element with. + To set all the matrix elements to the particular value after the construction, use SetTo(Scalar s) method . + + + + creates a matrix header for a part of the bigger matrix + + Array that (as a whole or partly) is assigned to the constructed matrix. + No data is copied by these constructors. Instead, the header pointing to m data or its sub-array + is constructed and associated with it. The reference counter, if any, is incremented. + So, when you modify the matrix formed using such a constructor, you also modify the corresponding elements of m . + If you want to have an independent copy of the sub-array, use Mat::clone() . + Range of the m rows to take. As usual, the range start is inclusive and the range end is exclusive. + Use Range.All to take all the rows. + Range of the m columns to take. Use Range.All to take all the columns. + + + + creates a matrix header for a part of the bigger matrix + + Array that (as a whole or partly) is assigned to the constructed matrix. + No data is copied by these constructors. Instead, the header pointing to m data or its sub-array + is constructed and associated with it. The reference counter, if any, is incremented. + So, when you modify the matrix formed using such a constructor, you also modify the corresponding elements of m . + If you want to have an independent copy of the sub-array, use Mat.Clone() . + Array of selected ranges of m along each dimensionality. + + + + creates a matrix header for a part of the bigger matrix + + Array that (as a whole or partly) is assigned to the constructed matrix. + No data is copied by these constructors. Instead, the header pointing to m data or its sub-array + is constructed and associated with it. The reference counter, if any, is incremented. + So, when you modify the matrix formed using such a constructor, you also modify the corresponding elements of m . + If you want to have an independent copy of the sub-array, use Mat.Clone() . + Region of interest. + + + + constructor for matrix headers pointing to user-allocated data + + Number of rows in a 2D array. + Number of columns in a 2D array. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Number of bytes each matrix row occupies. The value should include the padding bytes at the end of each row, if any. + If the parameter is missing (set to AUTO_STEP ), no padding is assumed and the actual step is calculated as cols*elemSize() . + + + + constructor for matrix headers pointing to user-allocated data + + Number of rows in a 2D array. + Number of columns in a 2D array. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Number of bytes each matrix row occupies. The value should include the padding bytes at the end of each row, if any. + If the parameter is missing (set to AUTO_STEP ), no padding is assumed and the actual step is calculated as cols*elemSize() . + + + + constructor for matrix headers pointing to user-allocated data + + Number of rows in a 2D array. + Number of columns in a 2D array. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Number of bytes each matrix row occupies. The value should include the padding bytes at the end of each row, if any. + If the parameter is missing (set to AUTO_STEP ), no padding is assumed and the actual step is calculated as cols*elemSize() . + + + + constructor for matrix headers pointing to user-allocated data + + Array of integers specifying an n-dimensional array shape. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Array of ndims-1 steps in case of a multi-dimensional array (the last step is always set to the element size). + If not specified, the matrix is assumed to be continuous. + + + + constructor for matrix headers pointing to user-allocated data + + Array of integers specifying an n-dimensional array shape. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Array of ndims-1 steps in case of a multi-dimensional array (the last step is always set to the element size). + If not specified, the matrix is assumed to be continuous. + + + + constructor for matrix headers pointing to user-allocated data + + Array of integers specifying an n-dimensional array shape. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Array of ndims-1 steps in case of a multi-dimensional array (the last step is always set to the element size). + If not specified, the matrix is assumed to be continuous. + + + + constructs n-dimensional matrix + + Array of integers specifying an n-dimensional array shape. + + + + constructs n-dimensional matrix + + Array of integers specifying an n-dimensional array shape. + An optional value to initialize each matrix element with. + To set all the matrix elements to the particular value after the construction, use SetTo(Scalar s) method . + + + + converts old-style CvMat to the new matrix; the data is not copied by default + + Old style CvMat object + Flag to specify whether the underlying data of the the old-style CvMat should be + copied to (true) or shared with (false) the newly constructed matrix. When the data is copied, + the allocated buffer is managed using Mat reference counting mechanism. While the data is shared, + the reference counter is NULL, and you should not deallocate the data until the matrix is not destructed. + + + + converts old-style IplImage to the new matrix; the data is not copied by default + + Old style IplImage object + Flag to specify whether the underlying data of the the old-style IplImage should be + copied to (true) or shared with (false) the newly constructed matrix. When the data is copied, + the allocated buffer is managed using Mat reference counting mechanism. While the data is shared, + the reference counter is NULL, and you should not deallocate the data until the matrix is not destructed. + + + + + + + + + 1-dimensional indexer + + Index along the dimension 0 + A value to the specified array element. + + + + 2-dimensional indexer + + Index along the dimension 0 + Index along the dimension 1 + A value to the specified array element. + + + + 3-dimensional indexer + + Index along the dimension 0 + Index along the dimension 1 + Index along the dimension 2 + A value to the specified array element. + + + + n-dimensional indexer + + Array of Mat::dims indices. + A value to the specified array element. + + + + Gets a type-specific indexer. The indexer has getters/setters to access each matrix element. + + + + + + Initializes as N x 1 matrix and copys array data to this + + Source array data to be copied to this + + + + Initializes as M x N matrix and copys array data to this + + Source array data to be copied to this + + + + Initializes as N x 1 matrix and copys array data to this + + Source array data to be copied to this + + + + Convert this mat to managed array + + + + + + Convert this mat to managed array + + + + + + Convert this mat to managed rectangular array + + + + + + + + + + + + Adds elements to the bottom of the matrix. (Mat::push_back) + + Added element(s) + + + + + + + + + + + + + + + + + + + + Creates a matrix header for the specified matrix row/column. + + + + + + + Creates a matrix header for the specified row/column span. + + + + + + + + Creates a matrix header for the specified row/column span. + + + + + + + Creates a matrix header for the specified matrix row/column. + + + + + + + Creates a matrix header for the specified row/column span. + + + + + + + + Creates a matrix header for the specified row/column span. + + + + + + + Sets a matrix header for the specified matrix row/column. + + + + + + + + Sets a matrix header for the specified matrix row/column span. + + + + + + + + + Sets a matrix header for the specified matrix row/column span. + + + + + + + + + + + + + + + + + + + + + + + + Creates a matrix header for the specified matrix row/column. + + + + + + + + + + Creates a matrix header for the specified row/column span. + + + + + + + + Creates a matrix header for the specified row/column span. + + + + + + + Extracts a rectangular submatrix. + + Array of selected ranges along each array dimension. + + + + + Creates a matrix header for the specified matrix row/column. + + + + + + + + + + Creates a matrix header for the specified row/column span. + + + + + + + + Creates a matrix header for the specified row/column span. + + + + + + + Sets a matrix header for the specified matrix row/column. + + + + + + + + + + + Sets a matrix header for the specified matrix row/column span. + + + + + + + + + Sets a matrix header for the specified matrix row/column span. + + + + + + + + Type-specific abstract matrix + + Element Type + For return value type of re-defined Mat methods + + + + Creates empty Mat + + + + + Creates from native cv::Mat* pointer + + + + + + Initializes by Mat object + + Managed Mat object + + + + constructs 2D matrix of the specified size and type + + Number of rows in a 2D array. + Number of columns in a 2D array. + Array type. Use MatType.CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, + or MatType. CV_8UC(n), ..., CV_64FC(n) to create multi-channel matrices. + + + + constructs 2D matrix of the specified size and type + + 2D array size: Size(cols, rows) . In the Size() constructor, + the number of rows and the number of columns go in the reverse order. + Array type. Use MatType.CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, + or MatType.CV_8UC(n), ..., CV_64FC(n) to create multi-channel matrices. + + + + constucts 2D matrix and fills it with the specified Scalar value. + + Number of rows in a 2D array. + Number of columns in a 2D array. + Array type. Use MatType.CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, + or MatType. CV_8UC(n), ..., CV_64FC(n) to create multi-channel matrices. + An optional value to initialize each matrix element with. + To set all the matrix elements to the particular value after the construction, use SetTo(Scalar s) method . + + + + constucts 2D matrix and fills it with the specified Scalar value. + + 2D array size: Size(cols, rows) . In the Size() constructor, + the number of rows and the number of columns go in the reverse order. + Array type. Use MatType.CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, + or CV_8UC(n), ..., CV_64FC(n) to create multi-channel (up to CV_CN_MAX channels) matrices. + An optional value to initialize each matrix element with. + To set all the matrix elements to the particular value after the construction, use SetTo(Scalar s) method . + + + + creates a matrix header for a part of the bigger matrix + + Array that (as a whole or partly) is assigned to the constructed matrix. + No data is copied by these constructors. Instead, the header pointing to m data or its sub-array + is constructed and associated with it. The reference counter, if any, is incremented. + So, when you modify the matrix formed using such a constructor, you also modify the corresponding elements of m . + If you want to have an independent copy of the sub-array, use Mat::clone() . + Range of the m rows to take. As usual, the range start is inclusive and the range end is exclusive. + Use Range.All to take all the rows. + Range of the m columns to take. Use Range.All to take all the columns. + + + + creates a matrix header for a part of the bigger matrix + + Array that (as a whole or partly) is assigned to the constructed matrix. + No data is copied by these constructors. Instead, the header pointing to m data or its sub-array + is constructed and associated with it. The reference counter, if any, is incremented. + So, when you modify the matrix formed using such a constructor, you also modify the corresponding elements of m . + If you want to have an independent copy of the sub-array, use Mat.Clone() . + Array of selected ranges of m along each dimensionality. + + + + creates a matrix header for a part of the bigger matrix + + Array that (as a whole or partly) is assigned to the constructed matrix. + No data is copied by these constructors. Instead, the header pointing to m data or its sub-array + is constructed and associated with it. The reference counter, if any, is incremented. + So, when you modify the matrix formed using such a constructor, you also modify the corresponding elements of m . + If you want to have an independent copy of the sub-array, use Mat.Clone() . + Region of interest. + + + + constructor for matrix headers pointing to user-allocated data + + Number of rows in a 2D array. + Number of columns in a 2D array. + Array type. Use MatType.CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, + or MatType. CV_8UC(n), ..., CV_64FC(n) to create multi-channel matrices. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Number of bytes each matrix row occupies. The value should include the padding bytes at the end of each row, if any. + If the parameter is missing (set to AUTO_STEP ), no padding is assumed and the actual step is calculated as cols*elemSize() . + + + + constructor for matrix headers pointing to user-allocated data + + Number of rows in a 2D array. + Number of columns in a 2D array. + Array type. Use MatType.CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, + or MatType. CV_8UC(n), ..., CV_64FC(n) to create multi-channel matrices. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Number of bytes each matrix row occupies. The value should include the padding bytes at the end of each row, if any. + If the parameter is missing (set to AUTO_STEP ), no padding is assumed and the actual step is calculated as cols*elemSize() . + + + + constructor for matrix headers pointing to user-allocated data + + Array of integers specifying an n-dimensional array shape. + Array type. Use MatType.CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, + or MatType. CV_8UC(n), ..., CV_64FC(n) to create multi-channel matrices. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Array of ndims-1 steps in case of a multi-dimensional array (the last step is always set to the element size). + If not specified, the matrix is assumed to be continuous. + + + + constructor for matrix headers pointing to user-allocated data + + Array of integers specifying an n-dimensional array shape. + Array type. Use MatType.CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, + or MatType. CV_8UC(n), ..., CV_64FC(n) to create multi-channel matrices. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Array of ndims-1 steps in case of a multi-dimensional array (the last step is always set to the element size). + If not specified, the matrix is assumed to be continuous. + + + + constructs n-dimensional matrix + + Array of integers specifying an n-dimensional array shape. + Array type. Use MatType.CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, + or MatType. CV_8UC(n), ..., CV_64FC(n) to create multi-channel matrices. + + + + constructs n-dimensional matrix + + Array of integers specifying an n-dimensional array shape. + Array type. Use MatType.CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, + or MatType. CV_8UC(n), ..., CV_64FC(n) to create multi-channel matrices. + An optional value to initialize each matrix element with. + To set all the matrix elements to the particular value after the construction, use SetTo(Scalar s) method . + + + + converts old-style CvMat to the new matrix; the data is not copied by default + + Old style CvMat object + Flag to specify whether the underlying data of the the old-style CvMat should be + copied to (true) or shared with (false) the newly constructed matrix. When the data is copied, + the allocated buffer is managed using Mat reference counting mechanism. While the data is shared, + the reference counter is NULL, and you should not deallocate the data until the matrix is not destructed. + + + + converts old-style IplImage to the new matrix; the data is not copied by default + + Old style IplImage object + Flag to specify whether the underlying data of the the old-style IplImage should be + copied to (true) or shared with (false) the newly constructed matrix. When the data is copied, + the allocated buffer is managed using Mat reference counting mechanism. While the data is shared, + the reference counter is NULL, and you should not deallocate the data until the matrix is not destructed. + + + + Releases the resources + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + Gets type-specific indexer for accessing each element + + + + + + Gets read-only enumerator + + + + + + For non-generic IEnumerable + + + + + + Convert this mat to managed array + + + + + + Convert this mat to managed rectangular array + + + + + + + + + + + + + Creates a full copy of the matrix. + + + + + + Changes the shape of channels of a 2D matrix without copying the data. + + New number of rows. If the parameter is 0, the number of rows remains the same. + + + + + Changes the shape of a 2D matrix without copying the data. + + New number of rows. If the parameter is 0, the number of rows remains the same. + + + + + Transposes a matrix. + + + + + + Extracts a rectangular submatrix. + + Start row of the extracted submatrix. The upper boundary is not included. + End row of the extracted submatrix. The upper boundary is not included. + Start column of the extracted submatrix. The upper boundary is not included. + End column of the extracted submatrix. The upper boundary is not included. + + + + + Extracts a rectangular submatrix. + + Start and end row of the extracted submatrix. The upper boundary is not included. + To select all the rows, use Range.All(). + Start and end column of the extracted submatrix. + The upper boundary is not included. To select all the columns, use Range.All(). + + + + + Extracts a rectangular submatrix. + + Extracted submatrix specified as a rectangle. + + + + + Extracts a rectangular submatrix. + + Array of selected ranges along each array dimension. + + + + + Extracts a rectangular submatrix. + + Start row of the extracted submatrix. The upper boundary is not included. + End row of the extracted submatrix. The upper boundary is not included. + Start column of the extracted submatrix. The upper boundary is not included. + End column of the extracted submatrix. The upper boundary is not included. + + + + + Extracts a rectangular submatrix. + + Start and end row of the extracted submatrix. The upper boundary is not included. + To select all the rows, use Range.All(). + Start and end column of the extracted submatrix. + The upper boundary is not included. To select all the columns, use Range.All(). + + + + + Extracts a rectangular submatrix. + + Extracted submatrix specified as a rectangle. + + + + + Extracts a rectangular submatrix. + + Array of selected ranges along each array dimension. + + + + + Adds elements to the bottom of the matrix. (Mat::push_back) + + Added element(s) + + + + Removes the first occurrence of a specific object from the ICollection<T>. + + The object to remove from the ICollection<T>. + true if item was successfully removed from the ICollection<T> otherwise, false. + This method also returns false if item is not found in the original ICollection<T>. + + + + Determines whether the ICollection<T> contains a specific value. + + The object to locate in the ICollection<T>. + true if item is found in the ICollection<T> otherwise, false. + + + + Determines the index of a specific item in the list. + + The object to locate in the list. + The index of value if found in the list; otherwise, -1. + + + + Removes all items from the ICollection<T>. + + + + + Copies the elements of the ICollection<T> to an Array, starting at a particular Array index. + + The one-dimensional Array that is the destination of the elements copied from ICollection<T>. + The Array must have zero-based indexing. + The zero-based index in array at which copying begins. + + + + Returns the total number of matrix elements (Mat.total) + + Total number of list(Mat) elements + + + + Gets a value indicating whether the IList is read-only. + + + + + + A matrix whose element is cv::Rect [CV_32SC4] (cv::Mat_<cv::Rect>) + + + + + Creates empty Mat + + + + + Creates from native cv::Mat* pointer + + + + + + Initializes by Mat object + + Managed Mat object + + + + constructs 2D matrix of the specified size and type + + Number of rows in a 2D array. + Number of columns in a 2D array. + + + + constructs 2D matrix of the specified size and type + + 2D array size: Size(cols, rows) . In the Size() constructor, + the number of rows and the number of columns go in the reverse order. + + + + constucts 2D matrix and fills it with the specified Scalar value. + + Number of rows in a 2D array. + Number of columns in a 2D array. + An optional value to initialize each matrix element with. + To set all the matrix elements to the particular value after the construction, use SetTo(Scalar s) method . + + + + constucts 2D matrix and fills it with the specified Scalar value. + + 2D array size: Size(cols, rows) . In the Size() constructor, + the number of rows and the number of columns go in the reverse order. + An optional value to initialize each matrix element with. + To set all the matrix elements to the particular value after the construction, use SetTo(Scalar s) method . + + + + creates a matrix header for a part of the bigger matrix + + Array that (as a whole or partly) is assigned to the constructed matrix. + No data is copied by these constructors. Instead, the header pointing to m data or its sub-array + is constructed and associated with it. The reference counter, if any, is incremented. + So, when you modify the matrix formed using such a constructor, you also modify the corresponding elements of m . + If you want to have an independent copy of the sub-array, use Mat::clone() . + Range of the m rows to take. As usual, the range start is inclusive and the range end is exclusive. + Use Range.All to take all the rows. + Range of the m columns to take. Use Range.All to take all the columns. + + + + creates a matrix header for a part of the bigger matrix + + Array that (as a whole or partly) is assigned to the constructed matrix. + No data is copied by these constructors. Instead, the header pointing to m data or its sub-array + is constructed and associated with it. The reference counter, if any, is incremented. + So, when you modify the matrix formed using such a constructor, you also modify the corresponding elements of m . + If you want to have an independent copy of the sub-array, use Mat.Clone() . + Array of selected ranges of m along each dimensionality. + + + + creates a matrix header for a part of the bigger matrix + + Array that (as a whole or partly) is assigned to the constructed matrix. + No data is copied by these constructors. Instead, the header pointing to m data or its sub-array + is constructed and associated with it. The reference counter, if any, is incremented. + So, when you modify the matrix formed using such a constructor, you also modify the corresponding elements of m . + If you want to have an independent copy of the sub-array, use Mat.Clone() . + Region of interest. + + + + constructor for matrix headers pointing to user-allocated data + + Number of rows in a 2D array. + Number of columns in a 2D array. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Number of bytes each matrix row occupies. The value should include the padding bytes at the end of each row, if any. + If the parameter is missing (set to AUTO_STEP ), no padding is assumed and the actual step is calculated as cols*elemSize() . + + + + constructor for matrix headers pointing to user-allocated data + + Number of rows in a 2D array. + Number of columns in a 2D array. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Number of bytes each matrix row occupies. The value should include the padding bytes at the end of each row, if any. + If the parameter is missing (set to AUTO_STEP ), no padding is assumed and the actual step is calculated as cols*elemSize() . + + + + constructor for matrix headers pointing to user-allocated data + + Number of rows in a 2D array. + Number of columns in a 2D array. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Number of bytes each matrix row occupies. The value should include the padding bytes at the end of each row, if any. + If the parameter is missing (set to AUTO_STEP ), no padding is assumed and the actual step is calculated as cols*elemSize() . + + + + constructor for matrix headers pointing to user-allocated data + + Array of integers specifying an n-dimensional array shape. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Array of ndims-1 steps in case of a multi-dimensional array (the last step is always set to the element size). + If not specified, the matrix is assumed to be continuous. + + + + constructor for matrix headers pointing to user-allocated data + + Array of integers specifying an n-dimensional array shape. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Array of ndims-1 steps in case of a multi-dimensional array (the last step is always set to the element size). + If not specified, the matrix is assumed to be continuous. + + + + constructor for matrix headers pointing to user-allocated data + + Array of integers specifying an n-dimensional array shape. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Array of ndims-1 steps in case of a multi-dimensional array (the last step is always set to the element size). + If not specified, the matrix is assumed to be continuous. + + + + constructs n-dimensional matrix + + Array of integers specifying an n-dimensional array shape. + + + + constructs n-dimensional matrix + + Array of integers specifying an n-dimensional array shape. + An optional value to initialize each matrix element with. + To set all the matrix elements to the particular value after the construction, use SetTo(Scalar s) method . + + + + converts old-style CvMat to the new matrix; the data is not copied by default + + Old style CvMat object + Flag to specify whether the underlying data of the the old-style CvMat should be + copied to (true) or shared with (false) the newly constructed matrix. When the data is copied, + the allocated buffer is managed using Mat reference counting mechanism. While the data is shared, + the reference counter is NULL, and you should not deallocate the data until the matrix is not destructed. + + + + converts old-style IplImage to the new matrix; the data is not copied by default + + Old style IplImage object + Flag to specify whether the underlying data of the the old-style IplImage should be + copied to (true) or shared with (false) the newly constructed matrix. When the data is copied, + the allocated buffer is managed using Mat reference counting mechanism. While the data is shared, + the reference counter is NULL, and you should not deallocate the data until the matrix is not destructed. + + + + + + + + + 1-dimensional indexer + + Index along the dimension 0 + A value to the specified array element. + + + + 2-dimensional indexer + + Index along the dimension 0 + Index along the dimension 1 + A value to the specified array element. + + + + 3-dimensional indexer + + Index along the dimension 0 + Index along the dimension 1 + Index along the dimension 2 + A value to the specified array element. + + + + n-dimensional indexer + + Array of Mat::dims indices. + A value to the specified array element. + + + + Gets a type-specific indexer. The indexer has getters/setters to access each matrix element. + + + + + + Initializes as N x 1 matrix and copys array data to this + + Source array data to be copied to this + + + + Initializes as M x N matrix and copys array data to this + + Source array data to be copied to this + + + + Initializes as N x 1 matrix and copys array data to this + + Source array data to be copied to this + + + + Convert this mat to managed array + + + + + + Convert this mat to managed array + + + + + + Convert this mat to managed rectangular array + + + + + + + + + + + + Adds elements to the bottom of the matrix. (Mat::push_back) + + Added element(s) + + + + A matrix whose element is cv::Point3i [CV_32SC3] (cv::Mat_<cv::Point3i>) + + + + + Creates empty Mat + + + + + Creates from native cv::Mat* pointer + + + + + + Initializes by Mat object + + Managed Mat object + + + + constructs 2D matrix of the specified size and type + + Number of rows in a 2D array. + Number of columns in a 2D array. + + + + constructs 2D matrix of the specified size and type + + 2D array size: Size(cols, rows) . In the Size() constructor, + the number of rows and the number of columns go in the reverse order. + + + + constucts 2D matrix and fills it with the specified Scalar value. + + Number of rows in a 2D array. + Number of columns in a 2D array. + An optional value to initialize each matrix element with. + To set all the matrix elements to the particular value after the construction, use SetTo(Scalar s) method . + + + + constucts 2D matrix and fills it with the specified Scalar value. + + 2D array size: Size(cols, rows) . In the Size() constructor, + the number of rows and the number of columns go in the reverse order. + An optional value to initialize each matrix element with. + To set all the matrix elements to the particular value after the construction, use SetTo(Scalar s) method . + + + + creates a matrix header for a part of the bigger matrix + + Array that (as a whole or partly) is assigned to the constructed matrix. + No data is copied by these constructors. Instead, the header pointing to m data or its sub-array + is constructed and associated with it. The reference counter, if any, is incremented. + So, when you modify the matrix formed using such a constructor, you also modify the corresponding elements of m . + If you want to have an independent copy of the sub-array, use Mat::clone() . + Range of the m rows to take. As usual, the range start is inclusive and the range end is exclusive. + Use Range.All to take all the rows. + Range of the m columns to take. Use Range.All to take all the columns. + + + + creates a matrix header for a part of the bigger matrix + + Array that (as a whole or partly) is assigned to the constructed matrix. + No data is copied by these constructors. Instead, the header pointing to m data or its sub-array + is constructed and associated with it. The reference counter, if any, is incremented. + So, when you modify the matrix formed using such a constructor, you also modify the corresponding elements of m . + If you want to have an independent copy of the sub-array, use Mat.Clone() . + Array of selected ranges of m along each dimensionality. + + + + creates a matrix header for a part of the bigger matrix + + Array that (as a whole or partly) is assigned to the constructed matrix. + No data is copied by these constructors. Instead, the header pointing to m data or its sub-array + is constructed and associated with it. The reference counter, if any, is incremented. + So, when you modify the matrix formed using such a constructor, you also modify the corresponding elements of m . + If you want to have an independent copy of the sub-array, use Mat.Clone() . + Region of interest. + + + + constructor for matrix headers pointing to user-allocated data + + Number of rows in a 2D array. + Number of columns in a 2D array. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Number of bytes each matrix row occupies. The value should include the padding bytes at the end of each row, if any. + If the parameter is missing (set to AUTO_STEP ), no padding is assumed and the actual step is calculated as cols*elemSize() . + + + + constructor for matrix headers pointing to user-allocated data + + Number of rows in a 2D array. + Number of columns in a 2D array. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Number of bytes each matrix row occupies. The value should include the padding bytes at the end of each row, if any. + If the parameter is missing (set to AUTO_STEP ), no padding is assumed and the actual step is calculated as cols*elemSize() . + + + + constructor for matrix headers pointing to user-allocated data + + Number of rows in a 2D array. + Number of columns in a 2D array. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Number of bytes each matrix row occupies. The value should include the padding bytes at the end of each row, if any. + If the parameter is missing (set to AUTO_STEP ), no padding is assumed and the actual step is calculated as cols*elemSize() . + + + + constructor for matrix headers pointing to user-allocated data + + Array of integers specifying an n-dimensional array shape. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Array of ndims-1 steps in case of a multi-dimensional array (the last step is always set to the element size). + If not specified, the matrix is assumed to be continuous. + + + + constructor for matrix headers pointing to user-allocated data + + Array of integers specifying an n-dimensional array shape. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Array of ndims-1 steps in case of a multi-dimensional array (the last step is always set to the element size). + If not specified, the matrix is assumed to be continuous. + + + + constructor for matrix headers pointing to user-allocated data + + Array of integers specifying an n-dimensional array shape. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Array of ndims-1 steps in case of a multi-dimensional array (the last step is always set to the element size). + If not specified, the matrix is assumed to be continuous. + + + + constructs n-dimensional matrix + + Array of integers specifying an n-dimensional array shape. + + + + constructs n-dimensional matrix + + Array of integers specifying an n-dimensional array shape. + An optional value to initialize each matrix element with. + To set all the matrix elements to the particular value after the construction, use SetTo(Scalar s) method . + + + + converts old-style CvMat to the new matrix; the data is not copied by default + + Old style CvMat object + Flag to specify whether the underlying data of the the old-style CvMat should be + copied to (true) or shared with (false) the newly constructed matrix. When the data is copied, + the allocated buffer is managed using Mat reference counting mechanism. While the data is shared, + the reference counter is NULL, and you should not deallocate the data until the matrix is not destructed. + + + + converts old-style IplImage to the new matrix; the data is not copied by default + + Old style IplImage object + Flag to specify whether the underlying data of the the old-style IplImage should be + copied to (true) or shared with (false) the newly constructed matrix. When the data is copied, + the allocated buffer is managed using Mat reference counting mechanism. While the data is shared, + the reference counter is NULL, and you should not deallocate the data until the matrix is not destructed. + + + + + + + + + 1-dimensional indexer + + Index along the dimension 0 + A value to the specified array element. + + + + 2-dimensional indexer + + Index along the dimension 0 + Index along the dimension 1 + A value to the specified array element. + + + + 3-dimensional indexer + + Index along the dimension 0 + Index along the dimension 1 + Index along the dimension 2 + A value to the specified array element. + + + + n-dimensional indexer + + Array of Mat::dims indices. + A value to the specified array element. + + + + Gets a type-specific indexer. The indexer has getters/setters to access each matrix element. + + + + + + Initializes as N x 1 matrix and copys array data to this + + Source array data to be copied to this + + + + Initializes as M x N matrix and copys array data to this + + Source array data to be copied to this + + + + Initializes as N x 1 matrix and copys array data to this + + Source array data to be copied to this + + + + Convert this mat to managed array + + + + + + Convert this mat to managed array + + + + + + Convert this mat to managed rectangular array + + + + + + + + + + + + Adds elements to the bottom of the matrix. (Mat::push_back) + + Added element(s) + + + + A matrix whose element is cv::Point3f [CV_32FC3] (cv::Mat_<cv::Point3f>) + + + + + Creates empty Mat + + + + + Creates from native cv::Mat* pointer + + + + + + Initializes by Mat object + + Managed Mat object + + + + constructs 2D matrix of the specified size and type + + Number of rows in a 2D array. + Number of columns in a 2D array. + + + + constructs 2D matrix of the specified size and type + + 2D array size: Size(cols, rows) . In the Size() constructor, + the number of rows and the number of columns go in the reverse order. + + + + constucts 2D matrix and fills it with the specified Scalar value. + + Number of rows in a 2D array. + Number of columns in a 2D array. + An optional value to initialize each matrix element with. + To set all the matrix elements to the particular value after the construction, use SetTo(Scalar s) method . + + + + constucts 2D matrix and fills it with the specified Scalar value. + + 2D array size: Size(cols, rows) . In the Size() constructor, + the number of rows and the number of columns go in the reverse order. + An optional value to initialize each matrix element with. + To set all the matrix elements to the particular value after the construction, use SetTo(Scalar s) method . + + + + creates a matrix header for a part of the bigger matrix + + Array that (as a whole or partly) is assigned to the constructed matrix. + No data is copied by these constructors. Instead, the header pointing to m data or its sub-array + is constructed and associated with it. The reference counter, if any, is incremented. + So, when you modify the matrix formed using such a constructor, you also modify the corresponding elements of m . + If you want to have an independent copy of the sub-array, use Mat::clone() . + Range of the m rows to take. As usual, the range start is inclusive and the range end is exclusive. + Use Range.All to take all the rows. + Range of the m columns to take. Use Range.All to take all the columns. + + + + creates a matrix header for a part of the bigger matrix + + Array that (as a whole or partly) is assigned to the constructed matrix. + No data is copied by these constructors. Instead, the header pointing to m data or its sub-array + is constructed and associated with it. The reference counter, if any, is incremented. + So, when you modify the matrix formed using such a constructor, you also modify the corresponding elements of m . + If you want to have an independent copy of the sub-array, use Mat.Clone() . + Array of selected ranges of m along each dimensionality. + + + + creates a matrix header for a part of the bigger matrix + + Array that (as a whole or partly) is assigned to the constructed matrix. + No data is copied by these constructors. Instead, the header pointing to m data or its sub-array + is constructed and associated with it. The reference counter, if any, is incremented. + So, when you modify the matrix formed using such a constructor, you also modify the corresponding elements of m . + If you want to have an independent copy of the sub-array, use Mat.Clone() . + Region of interest. + + + + constructor for matrix headers pointing to user-allocated data + + Number of rows in a 2D array. + Number of columns in a 2D array. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Number of bytes each matrix row occupies. The value should include the padding bytes at the end of each row, if any. + If the parameter is missing (set to AUTO_STEP ), no padding is assumed and the actual step is calculated as cols*elemSize() . + + + + constructor for matrix headers pointing to user-allocated data + + Number of rows in a 2D array. + Number of columns in a 2D array. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Number of bytes each matrix row occupies. The value should include the padding bytes at the end of each row, if any. + If the parameter is missing (set to AUTO_STEP ), no padding is assumed and the actual step is calculated as cols*elemSize() . + + + + constructor for matrix headers pointing to user-allocated data + + Number of rows in a 2D array. + Number of columns in a 2D array. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Number of bytes each matrix row occupies. The value should include the padding bytes at the end of each row, if any. + If the parameter is missing (set to AUTO_STEP ), no padding is assumed and the actual step is calculated as cols*elemSize() . + + + + constructor for matrix headers pointing to user-allocated data + + Array of integers specifying an n-dimensional array shape. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Array of ndims-1 steps in case of a multi-dimensional array (the last step is always set to the element size). + If not specified, the matrix is assumed to be continuous. + + + + constructor for matrix headers pointing to user-allocated data + + Array of integers specifying an n-dimensional array shape. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Array of ndims-1 steps in case of a multi-dimensional array (the last step is always set to the element size). + If not specified, the matrix is assumed to be continuous. + + + + constructor for matrix headers pointing to user-allocated data + + Array of integers specifying an n-dimensional array shape. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Array of ndims-1 steps in case of a multi-dimensional array (the last step is always set to the element size). + If not specified, the matrix is assumed to be continuous. + + + + constructs n-dimensional matrix + + Array of integers specifying an n-dimensional array shape. + + + + constructs n-dimensional matrix + + Array of integers specifying an n-dimensional array shape. + An optional value to initialize each matrix element with. + To set all the matrix elements to the particular value after the construction, use SetTo(Scalar s) method . + + + + converts old-style CvMat to the new matrix; the data is not copied by default + + Old style CvMat object + Flag to specify whether the underlying data of the the old-style CvMat should be + copied to (true) or shared with (false) the newly constructed matrix. When the data is copied, + the allocated buffer is managed using Mat reference counting mechanism. While the data is shared, + the reference counter is NULL, and you should not deallocate the data until the matrix is not destructed. + + + + converts old-style IplImage to the new matrix; the data is not copied by default + + Old style IplImage object + Flag to specify whether the underlying data of the the old-style IplImage should be + copied to (true) or shared with (false) the newly constructed matrix. When the data is copied, + the allocated buffer is managed using Mat reference counting mechanism. While the data is shared, + the reference counter is NULL, and you should not deallocate the data until the matrix is not destructed. + + + + + + + + + 1-dimensional indexer + + Index along the dimension 0 + A value to the specified array element. + + + + 2-dimensional indexer + + Index along the dimension 0 + Index along the dimension 1 + A value to the specified array element. + + + + 3-dimensional indexer + + Index along the dimension 0 + Index along the dimension 1 + Index along the dimension 2 + A value to the specified array element. + + + + n-dimensional indexer + + Array of Mat::dims indices. + A value to the specified array element. + + + + Gets a type-specific indexer. The indexer has getters/setters to access each matrix element. + + + + + + Initializes as N x 1 matrix and copys array data to this + + Source array data to be copied to this + + + + Initializes as M x N matrix and copys array data to this + + Source array data to be copied to this + + + + Initializes as N x 1 matrix and copys array data to this + + Source array data to be copied to this + + + + Convert this mat to managed array + + + + + + Convert this mat to managed array + + + + + + Convert this mat to managed rectangular array + + + + + + + + + + + + Adds elements to the bottom of the matrix. (Mat::push_back) + + Added element(s) + + + + A matrix whose element is cv::Point3d [CV_64FC3] (cv::Mat_<cv::Point3d>) + + + + + Creates empty Mat + + + + + Creates from native cv::Mat* pointer + + + + + + Initializes by Mat object + + Managed Mat object + + + + constructs 2D matrix of the specified size and type + + Number of rows in a 2D array. + Number of columns in a 2D array. + + + + constructs 2D matrix of the specified size and type + + 2D array size: Size(cols, rows) . In the Size() constructor, + the number of rows and the number of columns go in the reverse order. + + + + constucts 2D matrix and fills it with the specified Scalar value. + + Number of rows in a 2D array. + Number of columns in a 2D array. + An optional value to initialize each matrix element with. + To set all the matrix elements to the particular value after the construction, use SetTo(Scalar s) method . + + + + constucts 2D matrix and fills it with the specified Scalar value. + + 2D array size: Size(cols, rows) . In the Size() constructor, + the number of rows and the number of columns go in the reverse order. + An optional value to initialize each matrix element with. + To set all the matrix elements to the particular value after the construction, use SetTo(Scalar s) method . + + + + creates a matrix header for a part of the bigger matrix + + Array that (as a whole or partly) is assigned to the constructed matrix. + No data is copied by these constructors. Instead, the header pointing to m data or its sub-array + is constructed and associated with it. The reference counter, if any, is incremented. + So, when you modify the matrix formed using such a constructor, you also modify the corresponding elements of m . + If you want to have an independent copy of the sub-array, use Mat::clone() . + Range of the m rows to take. As usual, the range start is inclusive and the range end is exclusive. + Use Range.All to take all the rows. + Range of the m columns to take. Use Range.All to take all the columns. + + + + creates a matrix header for a part of the bigger matrix + + Array that (as a whole or partly) is assigned to the constructed matrix. + No data is copied by these constructors. Instead, the header pointing to m data or its sub-array + is constructed and associated with it. The reference counter, if any, is incremented. + So, when you modify the matrix formed using such a constructor, you also modify the corresponding elements of m . + If you want to have an independent copy of the sub-array, use Mat.Clone() . + Array of selected ranges of m along each dimensionality. + + + + creates a matrix header for a part of the bigger matrix + + Array that (as a whole or partly) is assigned to the constructed matrix. + No data is copied by these constructors. Instead, the header pointing to m data or its sub-array + is constructed and associated with it. The reference counter, if any, is incremented. + So, when you modify the matrix formed using such a constructor, you also modify the corresponding elements of m . + If you want to have an independent copy of the sub-array, use Mat.Clone() . + Region of interest. + + + + constructor for matrix headers pointing to user-allocated data + + Number of rows in a 2D array. + Number of columns in a 2D array. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Number of bytes each matrix row occupies. The value should include the padding bytes at the end of each row, if any. + If the parameter is missing (set to AUTO_STEP ), no padding is assumed and the actual step is calculated as cols*elemSize() . + + + + constructor for matrix headers pointing to user-allocated data + + Number of rows in a 2D array. + Number of columns in a 2D array. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Number of bytes each matrix row occupies. The value should include the padding bytes at the end of each row, if any. + If the parameter is missing (set to AUTO_STEP ), no padding is assumed and the actual step is calculated as cols*elemSize() . + + + + constructor for matrix headers pointing to user-allocated data + + Number of rows in a 2D array. + Number of columns in a 2D array. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Number of bytes each matrix row occupies. The value should include the padding bytes at the end of each row, if any. + If the parameter is missing (set to AUTO_STEP ), no padding is assumed and the actual step is calculated as cols*elemSize() . + + + + constructor for matrix headers pointing to user-allocated data + + Array of integers specifying an n-dimensional array shape. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Array of ndims-1 steps in case of a multi-dimensional array (the last step is always set to the element size). + If not specified, the matrix is assumed to be continuous. + + + + constructor for matrix headers pointing to user-allocated data + + Array of integers specifying an n-dimensional array shape. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Array of ndims-1 steps in case of a multi-dimensional array (the last step is always set to the element size). + If not specified, the matrix is assumed to be continuous. + + + + constructor for matrix headers pointing to user-allocated data + + Array of integers specifying an n-dimensional array shape. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Array of ndims-1 steps in case of a multi-dimensional array (the last step is always set to the element size). + If not specified, the matrix is assumed to be continuous. + + + + constructs n-dimensional matrix + + Array of integers specifying an n-dimensional array shape. + + + + constructs n-dimensional matrix + + Array of integers specifying an n-dimensional array shape. + An optional value to initialize each matrix element with. + To set all the matrix elements to the particular value after the construction, use SetTo(Scalar s) method . + + + + converts old-style CvMat to the new matrix; the data is not copied by default + + Old style CvMat object + Flag to specify whether the underlying data of the the old-style CvMat should be + copied to (true) or shared with (false) the newly constructed matrix. When the data is copied, + the allocated buffer is managed using Mat reference counting mechanism. While the data is shared, + the reference counter is NULL, and you should not deallocate the data until the matrix is not destructed. + + + + converts old-style IplImage to the new matrix; the data is not copied by default + + Old style IplImage object + Flag to specify whether the underlying data of the the old-style IplImage should be + copied to (true) or shared with (false) the newly constructed matrix. When the data is copied, + the allocated buffer is managed using Mat reference counting mechanism. While the data is shared, + the reference counter is NULL, and you should not deallocate the data until the matrix is not destructed. + + + + + + + + + 1-dimensional indexer + + Index along the dimension 0 + A value to the specified array element. + + + + 2-dimensional indexer + + Index along the dimension 0 + Index along the dimension 1 + A value to the specified array element. + + + + 3-dimensional indexer + + Index along the dimension 0 + Index along the dimension 1 + Index along the dimension 2 + A value to the specified array element. + + + + n-dimensional indexer + + Array of Mat::dims indices. + A value to the specified array element. + + + + Gets a type-specific indexer. The indexer has getters/setters to access each matrix element. + + + + + + Initializes as N x 1 matrix and copys array data to this + + Source array data to be copied to this + + + + Initializes as M x N matrix and copys array data to this + + Source array data to be copied to this + + + + Initializes as N x 1 matrix and copys array data to this + + Source array data to be copied to this + + + + Convert this mat to managed array + + + + + + Convert this mat to managed array + + + + + + Convert this mat to managed rectangular array + + + + + + + + + + + + Adds elements to the bottom of the matrix. (Mat::push_back) + + Added element(s) + + + + Template class for smart reference-counting pointers + + + + + + Static constructor + + + + + Constructor + + + + + + Release function + + + + + + Returns Ptr<T>.obj pointer + + + + + Random Number Generator. + The class implements RNG using Multiply-with-Carry algorithm. + + operations.hpp + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + updates the state and returns the next 32-bit unsigned integer random number + + + + + + returns a random integer sampled uniformly from [0, N). + + + + + + + + + + + + + returns uniformly distributed integer random number from [a,b) range + + + + + + + + returns uniformly distributed floating-point random number from [a,b) range + + + + + + + + returns uniformly distributed double-precision floating-point random number from [a,b) range + + + + + + + + + + + + + + + + + + returns Gaussian random variate with mean zero. + + + + + + + Singular Value Decomposition class + + + + + the default constructor + + + + + the constructor that performs SVD + + + + + + + + + + + + + eigenvalues of the covariation matrix + + + + + eigenvalues of the covariation matrix + + + + + mean value subtracted before the projection and added after the back projection + + + + + the operator that performs SVD. The previously allocated SVD::u, SVD::w are SVD::vt are released. + + + + + + + + performs back substitution, so that dst is the solution or pseudo-solution of m*dst = rhs, where m is the decomposed matrix + + + + + + + + decomposes matrix and stores the results to user-provided matrices + + + + + + + + + + computes singular values of a matrix + + + + + + + + performs back substitution + + + + + + + + + + finds dst = arg min_{|dst|=1} |m*dst| + + + + + + + Principal Component Analysis + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + eigenvalues of the covariation matrix + + + + + eigenvalues of the covariation matrix + + + + + mean value subtracted before the projection and added after the back projection + + + + + operator that performs PCA. The previously stored data, if any, is released + + + + + + + + + + operator that performs PCA. The previously stored data, if any, is released + + + + + + + + + + projects vector from the original space to the principal components subspace + + + + + + + projects vector from the original space to the principal components subspace + + + + + + + reconstructs the original vector from the projection + + + + + + + reconstructs the original vector from the projection + + + + + + + Proxy datatype for passing Mat's and vector<>'s as input parameters. + Synonym for OutputArray. + + + + + + + + + + + + + + + + + + Algorithm Information + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Brute-force descriptor matcher. + For each descriptor in the first set, this matcher finds the closest descriptor in the second set by trying each one. + + + + + + + + + + + + Creates instance by cv::Ptr<T> + + + + + Creates instance by raw pointer T* + + + + + Creates instance from cv::Ptr<T> . + ptr is disposed when the wrapper disposes. + + + + + + Releases the resources + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + Return true if the matcher supports mask in match methods. + + + + + + Pointer to algorithm information (cv::AlgorithmInfo*) + + + + + + FREAK implementation + + + + + Constructor + + enable orientation normalization + enable scale normalization + scaling of the description pattern + number of octaves covered by the detected keypoints + (optional) user defined selected pairs + + + + Creates instance by cv::Ptr<cv::SURF> + + + + + Creates instance by raw pointer cv::SURF* + + + + + Creates instance from cv::Ptr<T> . + ptr is disposed when the wrapper disposes. + + + + + + Releases the resources + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + returns the descriptor size in bytes + + + + + + returns the descriptor type + + + + + + select the 512 "best description pairs" + + grayscale images set + set of detected keypoints + correlation threshold + print construction information + list of best pair indexes + + + + Pointer to algorithm information (cv::AlgorithmInfo*) + + + + + + ORB implementation + + + + + + + + + + + + + + + + + + Creates instance by cv::Ptr<cv::SURF> + + + + + Creates instance by raw pointer cv::SURF* + + + + + Creates instance from cv::Ptr<T> . + ptr is disposed when the wrapper disposes. + + + + + + Releases the resources + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + returns the descriptor size in bytes + + + + + + returns the descriptor type + + + + + + Compute the ORB features on an image + + + + + + + + Compute the ORB features and descriptors on an image + + + + + + + + + + Compute the ORB features and descriptors on an image + + + + + + + + + + Pointer to algorithm information (cv::AlgorithmInfo*) + + + + + + + + + + + cv::Ptr<Feature2D> + + + + + + + + + + Creates instance from cv::Ptr<T> . + ptr is disposed when the wrapper disposes. + + + + + + Creates instance from raw pointer T* + + + + + + Releases the resources + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + Compute the descriptors for a set of keypoints in an image. + + The image. + The input keypoints. Keypoints for which a descriptor cannot be computed are removed. + Copmputed descriptors. Row i is the descriptor for keypoint i.param> + + + + Compute the descriptors for a keypoints collection detected in image collection. + + Image collection. + Input keypoints collection. keypoints[i] is keypoints detected in images[i]. + Keypoints for which a descriptor cannot be computed are removed. + Descriptor collection. descriptors[i] are descriptors computed for set keypoints[i]. + + + + + + + + + + + + + + + + + + + Create descriptor matcher by type name. + + + + + + + Creates instance from cv::Ptr<T> . + ptr is disposed when the wrapper disposes. + + + + + + Creates instance from raw pointer T* + + + + + + Releases the resources + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + Pointer to algorithm information (cv::AlgorithmInfo*) + + + + + + Add descriptors to train descriptor collection. + + Descriptors to add. Each descriptors[i] is a descriptors set from one image. + + + + Get train descriptors collection. + + + + + + Clear train descriptors collection. + + + + + Return true if there are not train descriptors in collection. + + + + + + Return true if the matcher supports mask in match methods. + + + + + + Train matcher (e.g. train flann index). + In all methods to match the method train() is run every time before matching. + Some descriptor matchers (e.g. BruteForceMatcher) have empty implementation + of this method, other matchers really train their inner structures + (e.g. FlannBasedMatcher trains flann::Index). So nonempty implementation + of train() should check the class object state and do traing/retraining + only if the state requires that (e.g. FlannBasedMatcher trains flann::Index + if it has not trained yet or if new descriptors have been added to the train collection). + + + + + Find one best match for each query descriptor (if mask is empty). + + + + + + + + + Find k best matches for each query descriptor (in increasing order of distances). + compactResult is used when mask is not empty. If compactResult is false matches + vector will have the same size as queryDescriptors rows. If compactResult is true + matches vector will not contain matches for fully masked out query descriptors. + + + + + + + + + + + Find best matches for each query descriptor which have distance less than + maxDistance (in increasing order of distances). + + + + + + + + + + + Find one best match for each query descriptor (if mask is empty). + + + + + + + + Find k best matches for each query descriptor (in increasing order of distances). + compactResult is used when mask is not empty. If compactResult is false matches + vector will have the same size as queryDescriptors rows. If compactResult is true + matches vector will not contain matches for fully masked out query descriptors. + + + + + + + + + + Find best matches for each query descriptor which have distance less than + maxDistance (in increasing order of distances). + + + + + + + + + + Good Features To Track Detector + + + + + + + + + + + + + + + + Creates instance by cv::Ptr<cv::SURF> + + + + + Creates instance by raw pointer cv::SURF* + + + + + Creates instance from cv::Ptr<T> . + ptr is disposed when the wrapper disposes. + + + + + + Releases the resources + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + + + + + + + + + Pointer to algorithm information (cv::AlgorithmInfo*) + + + + + + Detects corners using FAST algorithm by E. Rosten + + + + + + + + + + + + Creates instance by cv::Ptr<cv::SURF> + + + + + Creates instance by raw pointer cv::SURF* + + + + + Creates instance from cv::Ptr<T> . + ptr is disposed when the wrapper disposes. + + + + + + Releases the resources + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + + + + + + + + + Pointer to algorithm information (cv::AlgorithmInfo*) + + + + + + BRISK implementation + + + + + + + + + + + + + Creates instance by cv::Ptr<cv::SURF> + + + + + Creates instance by raw pointer cv::SURF* + + + + + Creates instance from cv::Ptr<T> . + ptr is disposed when the wrapper disposes. + + + + + + Releases the resources + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + returns the descriptor size in bytes + + + + + + returns the descriptor type + + + + + + Compute the BRISK features on an image + + + + + + + + Compute the BRISK features and descriptors on an image + + + + + + + + + + Compute the BRISK features and descriptors on an image + + + + + + + + + + Pointer to algorithm information (cv::AlgorithmInfo*) + + + + + + Class for extracting blobs from an image. + + + + + SimpleBlobDetector parameters + + + + + + + + + + + + + + + + Creates instance by cv::Ptr<cv::SURF> + + + + + Creates instance by raw pointer cv::SURF* + + + + + Creates instance from cv::Ptr<T> . + ptr is disposed when the wrapper disposes. + + + + + + Releases the resources + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + + + + + + + + + Pointer to algorithm information (cv::AlgorithmInfo*) + + + + + + Class for generation of image features which are + distributed densely and regularly over the image. + + + + + The detector generates several levels (in the amount of featureScaleLevels) of features. + Features of each level are located in the nodes of a regular grid over the image + (excluding the image boundary of given size). The level parameters (a feature scale, + a node size, a size of boundary) are multiplied by featureScaleMul with level index + growing depending on input flags, viz.: + + + + + + + The grid node size is multiplied if this is true. + Size of image boundary is multiplied if this is true. + + + + Creates instance by cv::Ptr<cv::SURF> + + + + + Creates instance by raw pointer cv::SURF* + + + + + Creates instance from cv::Ptr<T> . + ptr is disposed when the wrapper disposes. + + + + + + Releases the resources + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + Pointer to algorithm information (cv::AlgorithmInfo*) + + + + + + AVI Video File Writer + + + + + Track whether Dispose has been called + + + + + + + + + + Creates video writer structure. + + Name of the output video file. + 4-character code of codec used to compress the frames. For example, "PIM1" is MPEG-1 codec, "MJPG" is motion-jpeg codec etc. + Under Win32 it is possible to pass null in order to choose compression method and additional compression parameters from dialog. + Framerate of the created video stream. + Size of video frames. + If it is true, the encoder will expect and encode color frames, otherwise it will work with grayscale frames (the flag is currently supported on Windows only). + + + + Creates video writer structure. + + Name of the output video file. + 4-character code of codec used to compress the frames. For example, "PIM1" is MPEG-1 codec, "MJPG" is motion-jpeg codec etc. + Under Win32 it is possible to pass null in order to choose compression method and additional compression parameters from dialog. + Framerate of the created video stream. + Size of video frames. + If it is true, the encoder will expect and encode color frames, otherwise it will work with grayscale frames (the flag is currently supported on Windows only). + + + + + Creates video writer structure. + + Name of the output video file. + 4-character code of codec used to compress the frames. For example, "PIM1" is MPEG-1 codec, "MJPG" is motion-jpeg codec etc. + Under Win32 it is possible to pass null in order to choose compression method and additional compression parameters from dialog. + Framerate of the created video stream. + Size of video frames. + If it is true, the encoder will expect and encode color frames, otherwise it will work with grayscale frames (the flag is currently supported on Windows only). + + + + + Initializes from native pointer + + CvVideoWriter* + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + Get output video file name + + + + + Frames per second of the output vide + + + + + Get size of frame image + + + + + Get whether output frames is color or not + + + + + Creates video writer structure. + + Name of the output video file. + 4-character code of codec used to compress the frames. For example, "PIM1" is MPEG-1 codec, "MJPG" is motion-jpeg codec etc. + Under Win32 it is possible to pass null in order to choose compression method and additional compression parameters from dialog. + Framerate of the created video stream. + Size of video frames. + If it is true, the encoder will expect and encode color frames, otherwise it will work with grayscale frames (the flag is currently supported on Windows only). + + + + + Creates video writer structure. + + Name of the output video file. + 4-character code of codec used to compress the frames. For example, "PIM1" is MPEG-1 codec, "MJPG" is motion-jpeg codec etc. + Under Win32 it is possible to pass null in order to choose compression method and additional compression parameters from dialog. + Framerate of the created video stream. + Size of video frames. + If it is true, the encoder will expect and encode color frames, otherwise it will work with grayscale frames (the flag is currently supported on Windows only). + + + + + Creates video writer structure. + + Name of the output video file. + 4-character code of codec used to compress the frames. For example, "PIM1" is MPEG-1 codec, "MJPG" is motion-jpeg codec etc. + Under Win32 it is possible to pass null in order to choose compression method and additional compression parameters from dialog. + Framerate of the created video stream. + Size of video frames. + If it is true, the encoder will expect and encode color frames, otherwise it will work with grayscale frames (the flag is currently supported on Windows only). + + + + + Returns true if video writer has been successfully initialized. + + + + + + + + + + + + Writes/appends one frame to video file. + + the written frame. + + + + + Video capturing class + + + + + Capture type (File or Camera) + + + + + Track whether Dispose has been called + + + + + Initializes empty capture. + To use this, you should call Open. + + + + + + Allocates and initialized the CvCapture structure for reading a video stream from the camera. + Currently two camera interfaces can be used on Windows: Video for Windows (VFW) and Matrox Imaging Library (MIL); and two on Linux: V4L and FireWire (IEEE1394). + + Index of the camera to be used. If there is only one camera or it does not matter what camera to use -1 may be passed. + + + + + Allocates and initialized the CvCapture structure for reading a video stream from the camera. + Currently two camera interfaces can be used on Windows: Video for Windows (VFW) and Matrox Imaging Library (MIL); and two on Linux: V4L and FireWire (IEEE1394). + + Device type + + + + + Allocates and initialized the CvCapture structure for reading a video stream from the camera. + Currently two camera interfaces can be used on Windows: Video for Windows (VFW) and Matrox Imaging Library (MIL); and two on Linux: V4L and FireWire (IEEE1394). + + Device type + Index of the camera to be used. If there is only one camera or it does not matter what camera to use -1 may be passed. + + + + + Allocates and initialized the CvCapture structure for reading a video stream from the camera. + Currently two camera interfaces can be used on Windows: Video for Windows (VFW) and Matrox Imaging Library (MIL); and two on Linux: V4L and FireWire (IEEE1394). + + Index of the camera to be used. If there is only one camera or it does not matter what camera to use -1 may be passed. + + + + + Allocates and initialized the CvCapture structure for reading a video stream from the camera. + Currently two camera interfaces can be used on Windows: Video for Windows (VFW) and Matrox Imaging Library (MIL); and two on Linux: V4L and FireWire (IEEE1394). + + Device type + + + + + Allocates and initialized the CvCapture structure for reading a video stream from the camera. + Currently two camera interfaces can be used on Windows: Video for Windows (VFW) and Matrox Imaging Library (MIL); and two on Linux: V4L and FireWire (IEEE1394). + + Device type + Index of the camera to be used. If there is only one camera or it does not matter what camera to use -1 may be passed. + + + + + Allocates and initialized the CvCapture structure for reading the video stream from the specified file. + After the allocated structure is not used any more it should be released by cvReleaseCapture function. + + Name of the video file. + + + + + Allocates and initialized the CvCapture structure for reading the video stream from the specified file. + After the allocated structure is not used any more it should be released by cvReleaseCapture function. + + Name of the video file. + + + + + Initializes from native pointer + + CvCapture* + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + Gets the capture type (File or Camera) + + + + + Gets or sets film current position in milliseconds or video capture timestamp + + + + + Gets or sets 0-based index of the frame to be decoded/captured next + + + + + Gets or sets relative position of video file + + + + + Gets or sets width of frames in the video stream + + + + + Gets or sets height of frames in the video stream + + + + + Gets or sets frame rate + + + + + Gets or sets 4-character code of codec + + + + + Gets number of frames in video file + + + + + Gets or sets brightness of image (only for cameras) + + + + + Gets or sets contrast of image (only for cameras) + + + + + Gets or sets saturation of image (only for cameras) + + + + + Gets or sets hue of image (only for cameras) + + + + + The format of the Mat objects returned by retrieve() + + + + + A backend-specific value indicating the current capture mode + + + + + Gain of the image (only for cameras) + + + + + Exposure (only for cameras) + + + + + Boolean flags indicating whether images should be converted to RGB + + + + + + + + + + TOWRITE (note: only supported by DC1394 v 2.x backend currently) + + + + + + + + + + + [CV_CAP_PROP_SHARPNESS] + + + + + exposure control done by camera, + user can adjust refernce level using this feature + [CV_CAP_PROP_AUTO_EXPOSURE] + + + + + + [CV_CAP_PROP_GAMMA] + + + + + + [CV_CAP_PROP_TEMPERATURE] + + + + + + [CV_CAP_PROP_TRIGGER] + + + + + + [CV_CAP_PROP_TRIGGER_DELAY] + + + + + + [CV_CAP_PROP_WHITE_BALANCE_RED_V] + + + + + + [CV_CAP_PROP_MAX_DC1394] + + + + + property for highgui class CvCapture_Android only + [CV_CAP_PROP_AUTOGRAB] + + + + + readonly, tricky property, returns cpnst char* indeed + [CV_CAP_PROP_SUPPORTED_PREVIEW_SIZES_STRING] + + + + + readonly, tricky property, returns cpnst char* indeed + [CV_CAP_PROP_PREVIEW_FORMAT] + + + + + + [CV_CAP_PROP_OPENNI_OUTPUT_MODE] + + + + + in mm + [CV_CAP_PROP_OPENNI_FRAME_MAX_DEPTH] + + + + + in mm + [CV_CAP_PROP_OPENNI_BASELINE] + + + + + in pixels + [CV_CAP_PROP_OPENNI_FOCAL_LENGTH] + + + + + flag + [CV_CAP_PROP_OPENNI_REGISTRATION_ON] + + + + + flag that synchronizes the remapping depth map to image map + by changing depth generator's view point (if the flag is "on") or + sets this view point to its normal one (if the flag is "off"). + [CV_CAP_PROP_OPENNI_REGISTRATION] + + + + + + [CV_CAP_OPENNI_IMAGE_GENERATOR_OUTPUT_MODE] + + + + + + [CV_CAP_OPENNI_DEPTH_GENERATOR_BASELINE] + + + + + + [CV_CAP_OPENNI_DEPTH_GENERATOR_FOCAL_LENGTH] + + + + + + [CV_CAP_OPENNI_DEPTH_GENERATOR_REGISTRATION_ON] + + + + + default is 1 + [CV_CAP_GSTREAMER_QUEUE_LENGTH] + + + + + ip for anable multicast master mode. 0 for disable multicast + [CV_CAP_PROP_PVAPI_MULTICASTIP] + + + + + Change image resolution by binning or skipping. + [CV_CAP_PROP_XI_DOWNSAMPLING] + + + + + Output data format. + [CV_CAP_PROP_XI_DATA_FORMAT] + + + + + Horizontal offset from the origin to the area of interest (in pixels). + [CV_CAP_PROP_XI_OFFSET_X] + + + + + Vertical offset from the origin to the area of interest (in pixels). + [CV_CAP_PROP_XI_OFFSET_Y] + + + + + Defines source of trigger. + [CV_CAP_PROP_XI_TRG_SOURCE] + + + + + Generates an internal trigger. PRM_TRG_SOURCE must be set to TRG_SOFTWARE. + [CV_CAP_PROP_XI_TRG_SOFTWARE] + + + + + Selects general purpose input + [CV_CAP_PROP_XI_GPI_SELECTOR] + + + + + Set general purpose input mode + [CV_CAP_PROP_XI_GPI_MODE] + + + + + Get general purpose level + [CV_CAP_PROP_XI_GPI_LEVEL] + + + + + Selects general purpose output + [CV_CAP_PROP_XI_GPO_SELECTOR] + + + + + Set general purpose output mode + [CV_CAP_PROP_XI_GPO_MODE] + + + + + Selects camera signalling LED + [CV_CAP_PROP_XI_LED_SELECTOR] + + + + + Define camera signalling LED functionality + [CV_CAP_PROP_XI_LED_MODE] + + + + + Calculates White Balance(must be called during acquisition) + [CV_CAP_PROP_XI_MANUAL_WB] + + + + + Automatic white balance + [CV_CAP_PROP_XI_AUTO_WB] + + + + + Automatic exposure/gain + [CV_CAP_PROP_XI_AEAG] + + + + + Exposure priority (0.5 - exposure 50%, gain 50%). + [CV_CAP_PROP_XI_EXP_PRIORITY] + + + + + Maximum limit of exposure in AEAG procedure + [CV_CAP_PROP_XI_AE_MAX_LIMIT] + + + + + Maximum limit of gain in AEAG procedure + [CV_CAP_PROP_XI_AG_MAX_LIMIT] + + + + + default is 1 + [CV_CAP_PROP_XI_AEAG_LEVEL] + + + + + default is 1 + [CV_CAP_PROP_XI_TIMEOUT] + + + + + Retrieves the specified property of camera or video file. + + property identifier. + property value + + + + Retrieves the specified property of camera or video file. + + property identifier. + property value + + + + Grabs the frame from camera or file. The grabbed frame is stored internally. + The purpose of this function is to grab frame fast that is important for syncronization in case of reading from several cameras simultaneously. + The grabbed frames are not exposed because they may be stored in compressed format (as defined by camera/driver). + To retrieve the grabbed frame, cvRetrieveFrame should be used. + + + + + + Returns the pointer to the image grabbed with cvGrabFrame function. + + + non-zero streamIdx is only valid for multi-head camera live streams + + + + + Returns the pointer to the image grabbed with cvGrabFrame function. + The returned image should not be released or modified by user. + + + non-zero streamIdx is only valid for multi-head camera live streams + + + + + Grabs a frame from camera or video file, decompresses and returns it. + This function is just a combination of cvGrabFrame and cvRetrieveFrame in one call. + The returned image should not be released or modified by user. + + + + + + Sets the specified property of video capturing. + + property identifier. + value of the property. + + + + + Sets the specified property of video capturing. + + property identifier. + value of the property. + + + + + Opens the specified video file + + + + + + + Allocates and initialized the CvCapture structure for reading a video stream from the camera. + Currently two camera interfaces can be used on Windows: Video for Windows (VFW) and Matrox Imaging Library (MIL); and two on Linux: V4L and FireWire (IEEE1394). + + Index of the camera to be used. If there is only one camera or it does not matter what camera to use -1 may be passed. + + + + + Allocates and initialized the CvCapture structure for reading a video stream from the camera. + Currently two camera interfaces can be used on Windows: Video for Windows (VFW) and Matrox Imaging Library (MIL); and two on Linux: V4L and FireWire (IEEE1394). + + Device type + + + + + Allocates and initialized the CvCapture structure for reading a video stream from the camera. + Currently two camera interfaces can be used on Windows: Video for Windows (VFW) and Matrox Imaging Library (MIL); and two on Linux: V4L and FireWire (IEEE1394). + + Device type + Index of the camera to be used. If there is only one camera or it does not matter what camera to use -1 may be passed. + + + + + Closes video file or capturing device. + + + + + + Returns true if video capturing has been initialized already. + + + + + + For accessing each byte of Int32 value + + + + + Information about the image topology for cv::findContours + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Raster image moments + + + + + spatial moments + + + + + spatial moments + + + + + spatial moments + + + + + spatial moments + + + + + spatial moments + + + + + spatial moments + + + + + spatial moments + + + + + spatial moments + + + + + spatial moments + + + + + spatial moments + + + + + central moments + + + + + central moments + + + + + central moments + + + + + central moments + + + + + central moments + + + + + central moments + + + + + central moments + + + + + central normalized moments + + + + + central normalized moments + + + + + central normalized moments + + + + + central normalized moments + + + + + central normalized moments + + + + + central normalized moments + + + + + central normalized moments + + + + + Default constructor. + All moment values are set to 0. + + + + + + + + + + + + + + + + + + + + Calculates all of the moments + up to the third order of a polygon or rasterized shape. + + A raster image (single-channel, 8-bit or floating-point + 2D array) or an array ( 1xN or Nx1 ) of 2D points ( Point or Point2f ) + If it is true, then all the non-zero image pixels are treated as 1’s + + + + + Calculates all of the moments + up to the third order of a polygon or rasterized shape. + + A raster image (8-bit) 2D array + If it is true, then all the non-zero image pixels are treated as 1’s + + + + + Calculates all of the moments + up to the third order of a polygon or rasterized shape. + + A raster image (floating-point) 2D array + If it is true, then all the non-zero image pixels are treated as 1’s + + + + + Calculates all of the moments + up to the third order of a polygon or rasterized shape. + + Array of 2D points + If it is true, then all the non-zero image pixels are treated as 1’s + + + + + Calculates all of the moments + up to the third order of a polygon or rasterized shape. + + Array of 2D points + If it is true, then all the non-zero image pixels are treated as 1’s + + + + + Calculates all of the moments + up to the third order of a polygon or rasterized shape. + + A raster image (single-channel, 8-bit or floating-point + 2D array) or an array ( 1xN or Nx1 ) of 2D points ( Point or Point2f ) + If it is true, then all the non-zero image pixels are treated as 1’s + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + computes 7 Hu invariants from the moments + + + + + + SIFT implementation. + + + + + The SIFT constructor. + + The number of best features to retain. + The features are ranked by their scores (measured in SIFT algorithm as the local contrast) + The number of layers in each octave. 3 is the value used in D. Lowe paper. + The number of octaves is computed automatically from the image resolution. + The contrast threshold used to filter out weak features in semi-uniform + (low-contrast) regions. The larger the threshold, the less features are produced by the detector. + The threshold used to filter out edge-like features. Note that the its meaning is + different from the contrastThreshold, i.e. the larger the edgeThreshold, the less features are filtered out (more features are retained). + The sigma of the Gaussian applied to the input image at the octave #0. + If your image is captured with a weak camera with soft lenses, you might want to reduce the number. + + + + Creates instance by cv::Ptr<cv::SURF> + + + + + Creates instance by raw pointer cv::SURF* + + + + + Creates a cv::Algorithm object using cv::Algorithm::create() + + The algorithm name, one of the names returned by Algorithm.GetList() + + + + + Creates instance from cv::Ptr<T> . + ptr is disposed when the wrapper disposes. + + + + + + Creates instance from raw pointer T* + + + + + + Releases the resources + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + returns the descriptor size in float's (64 or 128) + + + + + + returns the descriptor type + + + + + + Pointer to algorithm information (cv::AlgorithmInfo*) + + + + + + Extract features and computes their descriptors using SIFT algorithm + + Input 8-bit grayscale image + Optional input mask that marks the regions where we should detect features. + The output vector of keypoints + + + + detects keypoints and computes the SIFT descriptors for them. + + Input 8-bit grayscale image + Optional input mask that marks the regions where we should detect features. + The input/output vector of keypoints + The output matrix of descriptors. + Boolean flag. If it is true, the keypoint detector is not run. + Instead, the provided vector of keypoints is used and the algorithm just computes their descriptors. + + + + detects keypoints and computes the SIFT descriptors for them. + + Input 8-bit grayscale image + Optional input mask that marks the regions where we should detect features. + The input/output vector of keypoints + The output matrix of descriptors. + Boolean flag. If it is true, the keypoint detector is not run. + Instead, the provided vector of keypoints is used and the algorithm just computes their descriptors. + + + + + + + + + + + + + + + + + + + + + + + + + + + Struct for matching: query descriptor index, train descriptor index, train image index and distance between descriptors. + + + + + query descriptor index + + + + + train descriptor index + + + + + train image index + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Compares by distance (less is beter) + + + + + + + + Compares by distance (less is beter) + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Specifies whether this object contains the same members as the specified Object. + + The Object to test. + This method returns true if obj is the same type as this object and has the same members as this object. + + + + Compares two CvPoint objects. The result specifies whether the values of the X and Y properties of the two CvPoint objects are equal. + + A Point to compare. + A Point to compare. + This operator returns true if the X and Y values of left and right are equal; otherwise, false. + + + + Compares two CvPoint2D32f objects. The result specifies whether the values of the X or Y properties of the two CvPoint2D32f objects are unequal. + + A Point to compare. + A Point to compare. + This operator returns true if the values of either the X properties or the Y properties of left and right differ; otherwise, false. + + + + Unary plus operator + + + + + + + Unary minus operator + + + + + + + Shifts point by a certain offset + + + + + + + + Shifts point by a certain offset + + + + + + + + Shifts point by a certain offset + + + + + + + + Specifies whether this object contains the same members as the specified Object. + + The Object to test. + This method returns true if obj is the same type as this object and has the same members as this object. + + + + Returns a hash code for this object. + + An integer value that specifies a hash value for this object. + + + + Converts this object to a human readable string. + + A string that represents this object. + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Specifies whether this object contains the same members as the specified Object. + + The Object to test. + This method returns true if obj is the same type as this object and has the same members as this object. + + + + Compares two CvPoint objects. The result specifies whether the values of the X and Y properties of the two CvPoint objects are equal. + + A Point to compare. + A Point to compare. + This operator returns true if the X and Y values of left and right are equal; otherwise, false. + + + + Compares two CvPoint2D32f objects. The result specifies whether the values of the X or Y properties of the two CvPoint2D32f objects are unequal. + + A Point to compare. + A Point to compare. + This operator returns true if the values of either the X properties or the Y properties of left and right differ; otherwise, false. + + + + Unary plus operator + + + + + + + Unary minus operator + + + + + + + Shifts point by a certain offset + + + + + + + + Shifts point by a certain offset + + + + + + + + Shifts point by a certain offset + + + + + + + + Specifies whether this object contains the same members as the specified Object. + + The Object to test. + This method returns true if obj is the same type as this object and has the same members as this object. + + + + Returns a hash code for this object. + + An integer value that specifies a hash value for this object. + + + + Converts this object to a human readable string. + + A string that represents this object. + + + + float Range class + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Specifies whether this object contains the same members as the specified Object. + + The Object to test. + This method returns true if obj is the same type as this object and has the same members as this object. + + + + Compares two CvPoint objects. The result specifies whether the values of the X and Y properties of the two CvPoint objects are equal. + + A Point to compare. + A Point to compare. + This operator returns true if the X and Y values of left and right are equal; otherwise, false. + + + + Compares two CvPoint2D32f objects. The result specifies whether the values of the X or Y properties of the two CvPoint2D32f objects are unequal. + + A Point to compare. + A Point to compare. + This operator returns true if the values of either the X properties or the Y properties of left and right differ; otherwise, false. + + + + Unary plus operator + + + + + + + Unary minus operator + + + + + + + Shifts point by a certain offset + + + + + + + + Shifts point by a certain offset + + + + + + + + Shifts point by a certain offset + + + + + + + + Specifies whether this object contains the same members as the specified Object. + + The Object to test. + This method returns true if obj is the same type as this object and has the same members as this object. + + + + Returns a hash code for this object. + + An integer value that specifies a hash value for this object. + + + + Converts this object to a human readable string. + + A string that represents this object. + + + + Returns the distance between the specified two points + + + + + + + + Returns the distance between the specified two points + + + + + + + Calculates the dot product of two 2D vectors. + + + + + + + + Calculates the dot product of two 2D vectors. + + + + + + + Calculates the cross product of two 2D vectors. + + + + + + + + Calculates the cross product of two 2D vectors. + + + + + + + + + + + + Track whether Dispose has been called + + + + + + + + + + + + + + + + + + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + vector.size() + + + + + &vector[0] + + + + + Converts std::vector to managed array + + + + + + + + + + + Track whether Dispose has been called + + + + + + + + + + + + + + + + + + + + + + + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + vector.size() + + + + + &vector[0] + + + + + Converts std::vector to managed array + + + + + + + + + + + Track whether Dispose has been called + + + + + + + + + + + + + + + + + + + + + + + + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + vector.size() + + + + + &vector[0] + + + + + Converts std::vector to managed array + + + + + + + + + + + Track whether Dispose has been called + + + + + + + + + + + + + + + + + + + + + + + + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + vector.size() + + + + + &vector[0] + + + + + Converts std::vector to managed array + + + + + + Converts std::vector to managed array + + structure that has four int members (ex. CvLineSegmentPoint, CvRect) + + + + + + + + + + Track whether Dispose has been called + + + + + + + + + + + + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + vector.size() + + + + + vector[i].size() + + + + + &vector[0] + + + + + Converts std::vector to managed array + + + + + + + + + + + Track whether Dispose has been called + + + + + + + + + + + + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + vector.size() + + + + + vector[i].size() + + + + + &vector[0] + + + + + Converts std::vector to managed array + + + + + + + + + + + Track whether Dispose has been called + + + + + + + + + + + + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + vector.size() + + + + + vector[i].size() + + + + + &vector[0] + + + + + Converts std::vector to managed array + + + + + + + + + + + Track whether Dispose has been called + + + + + + + + + + + + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + vector.size() + + + + + vector[i].size() + + + + + &vector[0] + + + + + Converts std::vector to managed array + + + + + + + + + + + Track whether Dispose has been called + + + + + + + + + + + + + + + + + + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + vector.size() + + + + + vector.size() + + + + + &vector[0] + + + + + Converts std::vector to managed array + + + + + + + + + + + Track whether Dispose has been called + + + + + + + + + + + + + + + + + + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + vector.size() + + + + + &vector[0] + + + + + Converts std::vector to managed array + + + + + + Wrapper of HighGUI window + + + + + Track whether Dispose has been called + + + + + Creates a window with a random name + + + + + Creates a window with a random name and a specified image + + + + + + Creates a window with a specified image and flag + + Flags of the window. Currently the only supported flag is WindowMode.AutoSize. + If it is set, window size is automatically adjusted to fit the displayed image (see cvShowImage), while user can not change the window size manually. + + + + + Creates a window + + Name of the window which is used as window identifier and appears in the window caption. + + + + Creates a window + + Name of the window which is used as window identifier and appears in the window caption. + Flags of the window. Currently the only supported flag is WindowMode.AutoSize. + If it is set, window size is automatically adjusted to fit the displayed image (see cvShowImage), while user can not change the window size manually. + + + + Creates a window + + Name of the window which is used as window identifier and appears in the window caption. + Image to be shown. + + + + Creates a window + + Name of the window which is used as window identifier and appears in the window caption. + Flags of the window. Currently the only supported flag is WindowMode.AutoSize. + If it is set, window size is automatically adjusted to fit the displayed image (see cvShowImage), while user can not change the window size manually. + Image to be shown. + + + + ウィンドウ名が指定されなかったときに、適当な名前を作成して返す. + + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + Destroys this window. + + + + + Destroys all the opened HighGUI windows. + + + + + Gets or sets an image to be shown + + + + + Gets window name + + + + + Gets window handle + + + + + + + + + + Event handler to be called every time mouse event occurs in the specified window. + + + + + Returns true if the library is compiled with Qt + + + + + Creates the trackbar and attaches it to this window + + Name of created trackbar. + the function to be called every time the slider changes the position. This function should be prototyped as void Foo(int); + + + + + Creates the trackbar and attaches it to this window + + Name of created trackbar. + The position of the slider + Maximal position of the slider. Minimal position is always 0. + the function to be called every time the slider changes the position. This function should be prototyped as void Foo(int); + + + + + Creates the trackbar and attaches it to this window + + Name of created trackbar. + The position of the slider + Maximal position of the slider. Minimal position is always 0. + the function to be called every time the slider changes the position. This function should be prototyped as void Foo(int); + + + + + + Display text on the window's image as an overlay for delay milliseconds. This is not editing the image's data. The text is display on the top of the image. + + Overlay text to write on the window’s image + Delay to display the overlay text. If this function is called before the previous overlay text time out, the timer is restarted and the text updated. . If this value is zero, the text never disapers. + + + + + + Text to write on the window’s statusbar + Delay to display the text. If this function is called before the previous text time out, the timer is restarted and the text updated. If this value is zero, the text never disapers. + + + + Get Property of the window + + Property identifier + Value of the specified property + + + + Load parameters of the window. + + + + + Sets window position + + New x coordinate of top-left corner + New y coordinate of top-left corner + + + + Sets window size + + New width + New height + + + + Save parameters of the window. + + + + + Set Property of the window + + Property identifier + New value of the specified property + + + + Set Property of the window + + Property identifier + New value of the specified property + + + + Shows the image in this window + + Image to be shown. + + + + Waits for a pressed key + + Key code + + + + Waits for a pressed key + + Delay in milliseconds. + Key code + + + + + + + + + + + + + + + + + Retrieves a created window by name + + + + + + + Abstract base class for 2D image feature detectors. + + + + + cv::Ptr<FeatureDetector> + + + + + + + + + + Creates instance from cv::Ptr<T> . + ptr is disposed when the wrapper disposes. + + + + + + Creates instance from raw T* + + + + + + Releases the resources + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + Pointer to algorithm information (cv::AlgorithmInfo*) + + + + + + Detect keypoints in an image. + + The image. + Mask specifying where to look for keypoints (optional). + Must be a char matrix with non-zero values in the region of interest. + The detected keypoints. + + + + Detect keypoints in an image set. + + Image collection. + Masks for image set. masks[i] is a mask for images[i]. + Collection of keypoints detected in an input images. keypoints[i] is a set of keypoints detected in an images[i]. + + + + Return true if detector object is empty + + + + + + + + + + + Track whether Dispose has been called + + + + + Default constructor + + + + + Subdiv2D Constructor + + + + + + Clean up any resources being used. + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + The Base Class for Background/Foreground Segmentation. + The class is only used to define the common interface for + the whole family of background/foreground segmentation algorithms. + + + + + cv::Ptr<FeatureDetector> + + + + + + + + + + Creates instance from cv::Ptr<T> . + ptr is disposed when the wrapper disposes. + + + + + + Creates instance from raw T* + + + + + + Releases the resources + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + Pointer to algorithm information (cv::AlgorithmInfo*) + + + + + + the update operator that takes the next video frame and returns the current foreground mask as 8-bit binary image. + + + + + + + + computes a background image + + + + + + + + + + + Track whether Dispose has been called + + + + + + + + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + + + + + + + + + + + + + Track whether Dispose has been called + + + + + + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + orientation of the object in degrees + + + + + + the larger linear size of the object + + + + + + the smaller linear size of the object + + + + + + center of the object + + + + + + bounding rectangle for the object + + + + + + thresholding value that applied to back project + + + + + + returns number of histogram dimensions and sets + + + + + + + get the minimum allowed value of the specified channel + + + + + + + get the maximum allowed value of the specified channel + + + + + + + set initial object rectangle (must be called before initial calculation of the histogram) + + + + + + + threshold applied to the histogram bins + + + + + + + + + + + + + + + + set the histogram parameters + + + + + + + + set the minimum allowed value of the specified channel + + + + + + + + set the maximum allowed value of the specified channel + + + + + + + + update object position + + + + + + + update object histogram + + + + + + + reset histogram + + + + + get back project image + + + + + + + + + + + + + Base class for high-level OpenCV algorithms + + + + + + + + + + + + + + + Clean up any resources being used. + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + Returns the algorithm parameter + + The parameter name. + + + + + Returns the algorithm parameter + + The parameter name. + + + + + Returns the algorithm parameter + + The parameter name. + + + + + Returns the algorithm parameter + + The parameter name. + + + + + Returns the algorithm parameter + + The parameter name. + + + + + Returns the algorithm parameter + + The parameter name. + + + + + Returns the algorithm parameter + + The parameter name. + + + + + Sets the algorithm parameter + + The parameter name. + The parameter value. + + + + Sets the algorithm parameter + + The parameter name. + The parameter value. + + + + Sets the algorithm parameter + + The parameter name. + The parameter value. + + + + Sets the algorithm parameter + + The parameter name. + The parameter value. + + + + Sets the algorithm parameter + + The parameter name. + The parameter value. + + + + Sets the algorithm parameter + + The parameter name. + The parameter value. + + + + Sets the algorithm parameter + + The parameter name. + The parameter value. + + + + Returns the algorithm name + + + + + + + + + + + + + + + + + + + + + + + + + Returns the list of registered algorithms + + The output array of algorithm names. + + + + Algorithm information + + + + + + Pointer to algorithm information (cv::AlgorithmInfo*) + + + + + + Returns a string that represents this Algorithm. + + + + + + Output string format of Mat.Dump() + + + + + Default format. + [1, 2, 3, 4, 5, 6; \n + 7, 8, 9, ... ] + + + + + Python format. + [[[1, 2, 3], [4, 5, 6]], \n + [[7, 8, 9], ... ] + + + + + NumPy format. + array([[[1, 2, 3], [4, 5, 6]], \n + [[7, 8, 9], .... ]]], type='uint8'); + + + + + CSV format. + 1, 2, 3, 4, 5, 6\n + 7, 8, 9, ... + + + + + C language format. + {1, 2, 3, 4, 5, 6, \n + 7, 8, 9, ...}; + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + HOG (Histogram-of-Oriented-Gradients) Descriptor and Object Detector + + + + + + + + + + + + + + + sizeof(HOGDescriptor) + + + + + Track whether Dispose has been called + + + + + Returns coefficients of the classifier trained for people detection (for default window size). + + + + + This field returns 1981 SVM coeffs obtained from daimler's base. + To use these coeffs the detection window size should be (48,96) + + + + + Default constructor + + + + + Creates the HOG descriptor and detector. + + Detection window size. Align to block size and block stride. + Block size in pixels. Align to cell size. Only (16,16) is supported for now. + Block stride. It must be a multiple of cell size. + Cell size. Only (8, 8) is supported for now. + Number of bins. Only 9 bins per cell are supported for now. + + Gaussian smoothing window parameter. + + L2-Hys normalization method shrinkage. + Flag to specify whether the gamma correction preprocessing is required or not. + Maximum number of detection window increases. + + + + + + + + + + Initializes from pointer + + class HOGDescriptor* + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Returns coefficients of the classifier trained for people detection (for default window size). + + + + + + This method returns 1981 SVM coeffs obtained from daimler's base. + To use these coeffs the detection window size should be (48,96) + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Performs object detection without a multi-scale window. + + Source image. CV_8UC1 and CV_8UC4 types are supported for now. + Threshold for the distance between features and SVM classifying plane. + Usually it is 0 and should be specfied in the detector coefficients (as the last free coefficient). + But if the free coefficient is omitted (which is allowed), you can specify it manually here. + Window stride. It must be a multiple of block stride. + Mock parameter to keep the CPU interface compatibility. It must be (0,0). + + Left-top corner points of detected objects boundaries. + + + + Performs object detection without a multi-scale window. + + Source image. CV_8UC1 and CV_8UC4 types are supported for now. + + Threshold for the distance between features and SVM classifying plane. + Usually it is 0 and should be specfied in the detector coefficients (as the last free coefficient). + But if the free coefficient is omitted (which is allowed), you can specify it manually here. + Window stride. It must be a multiple of block stride. + Mock parameter to keep the CPU interface compatibility. It must be (0,0). + + Left-top corner points of detected objects boundaries. + + + + Performs object detection with a multi-scale window. + + Source image. CV_8UC1 and CV_8UC4 types are supported for now. + Threshold for the distance between features and SVM classifying plane. + Window stride. It must be a multiple of block stride. + Mock parameter to keep the CPU interface compatibility. It must be (0,0). + Coefficient of the detection window increase. + Coefficient to regulate the similarity threshold. + When detected, some objects can be covered by many rectangles. 0 means not to perform grouping. + Detected objects boundaries. + + + + Performs object detection with a multi-scale window. + + Source image. CV_8UC1 and CV_8UC4 types are supported for now. + + Threshold for the distance between features and SVM classifying plane. + Window stride. It must be a multiple of block stride. + Mock parameter to keep the CPU interface compatibility. It must be (0,0). + Coefficient of the detection window increase. + Coefficient to regulate the similarity threshold. + When detected, some objects can be covered by many rectangles. 0 means not to perform grouping. + Detected objects boundaries. + + + + + + + + + + + + + + evaluate specified ROI and return confidence value for each location + + + + + + + + + + + + evaluate specified ROI and return confidence value for each location in multiple scales + + + + + + + + + + read/parse Dalal's alt model file + + + + + + + + + + + + + + + struct for detection region of interest (ROI) + + + + + scale(size) of the bounding box + + + + + set of requrested locations to be evaluated + + + + + vector that will contain confidence values for each location + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Creates/Sets a matrix header for the specified matrix row/column. + + + + + + + Creates/Sets a matrix header for the specified row/column span. + + + + + + + + Creates/Sets a matrix header for the specified row/column span. + + + + + + + Creates a matrix header for the specified matrix row/column. + + + + + + + Creates a matrix header for the specified row/column span. + + + + + + + + Creates a matrix header for the specified row/column span. + + + + + + + Creates/Sets a matrix header for the specified matrix row/column. + + + + + + + Creates/Sets a matrix header for the specified row/column span. + + + + + + + + Creates/Sets a matrix header for the specified row/column span. + + + + + + + Matrix data type (depth and number of channels) + + + + + Entity value + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + type depth constants + + + + + type depth constants + + + + + type depth constants + + + + + type depth constants + + + + + type depth constants + + + + + type depth constants + + + + + type depth constants + + + + + type depth constants + + + + + predefined type constants + + + + + predefined type constants + + + + + predefined type constants + + + + + predefined type constants + + + + + predefined type constants + + + + + predefined type constants + + + + + predefined type constants + + + + + predefined type constants + + + + + predefined type constants + + + + + predefined type constants + + + + + predefined type constants + + + + + predefined type constants + + + + + predefined type constants + + + + + predefined type constants + + + + + predefined type constants + + + + + predefined type constants + + + + + predefined type constants + + + + + predefined type constants + + + + + predefined type constants + + + + + predefined type constants + + + + + predefined type constants + + + + + predefined type constants + + + + + predefined type constants + + + + + predefined type constants + + + + + predefined type constants + + + + + predefined type constants + + + + + predefined type constants + + + + + predefined type constants + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Specifies whether this object contains the same members as the specified Object. + + The Object to test. + This method returns true if obj is the same type as this object and has the same members as this object. + + + + Compares two CvPoint objects. The result specifies whether the values of the X and Y properties of the two CvPoint objects are equal. + + A Point to compare. + A Point to compare. + This operator returns true if the X and Y values of left and right are equal; otherwise, false. + + + + Compares two CvPoint2D32f objects. The result specifies whether the values of the X or Y properties of the two CvPoint2D32f objects are unequal. + + A Point to compare. + A Point to compare. + This operator returns true if the values of either the X properties or the Y properties of left and right differ; otherwise, false. + + + + Unary plus operator + + + + + + + Unary minus operator + + + + + + + Shifts point by a certain offset + + + + + + + + Shifts point by a certain offset + + + + + + + + Shifts point by a certain offset + + + + + + + + Specifies whether this object contains the same members as the specified Object. + + The Object to test. + This method returns true if obj is the same type as this object and has the same members as this object. + + + + Returns a hash code for this object. + + An integer value that specifies a hash value for this object. + + + + Converts this object to a human readable string. + + A string that represents this object. + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Specifies whether this object contains the same members as the specified Object. + + The Object to test. + This method returns true if obj is the same type as this object and has the same members as this object. + + + + Compares two CvPoint objects. The result specifies whether the values of the X and Y properties of the two CvPoint objects are equal. + + A Point to compare. + A Point to compare. + This operator returns true if the X and Y values of left and right are equal; otherwise, false. + + + + Compares two CvPoint2D32f objects. The result specifies whether the values of the X or Y properties of the two CvPoint2D32f objects are unequal. + + A Point to compare. + A Point to compare. + This operator returns true if the values of either the X properties or the Y properties of left and right differ; otherwise, false. + + + + Unary plus operator + + + + + + + Unary minus operator + + + + + + + Shifts point by a certain offset + + + + + + + + Shifts point by a certain offset + + + + + + + + Shifts point by a certain offset + + + + + + + + Specifies whether this object contains the same members as the specified Object. + + The Object to test. + This method returns true if obj is the same type as this object and has the same members as this object. + + + + Returns a hash code for this object. + + An integer value that specifies a hash value for this object. + + + + Converts this object to a human readable string. + + A string that represents this object. + + + + Returns the distance between the specified two points + + + + + + + + Returns the distance between the specified two points + + + + + + + Calculates the dot product of two 2D vectors. + + + + + + + + Calculates the dot product of two 2D vectors. + + + + + + + Calculates the cross product of two 2D vectors. + + + + + + + + Calculates the cross product of two 2D vectors. + + + + + + + + + + + + the rectangle mass center + + + + + width and height of the rectangle + + + + + the rotation angle. When the angle is 0, 90, 180, 270 etc., the rectangle becomes an up-right rectangle. + + + + + + + + + + + + + + + + + + + returns 4 vertices of the rectangle + + + + + + returns the minimal up-right rectangle containing the rotated rectangle + + + + + + conversion to the old-style CvBox2D structure + + + + + + + conversion to the old-style CvBox2D structure + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Specifies whether this object contains the same members as the specified Object. + + The Object to test. + This method returns true if obj is the same type as this object and has the same members as this object. + + + + Compares two CvPoint objects. The result specifies whether the members of each object are equal. + + A Point to compare. + A Point to compare. + This operator returns true if the members of left and right are equal; otherwise, false. + + + + Compares two CvPoint objects. The result specifies whether the members of each object are unequal. + + A Point to compare. + A Point to compare. + This operator returns true if the members of left and right are unequal; otherwise, false. + + + + Specifies whether this object contains the same members as the specified Object. + + The Object to test. + This method returns true if obj is the same type as this object and has the same members as this object. + + + + Returns a hash code for this object. + + An integer value that specifies a hash value for this object. + + + + Converts this object to a human readable string. + + A string that represents this object. + + + + + + + + + the type of termination criteria: COUNT, EPS or COUNT + EPS + + + + + the maximum number of iterations/elements + + + + + the desired accuracy + + + + + full constructor + + + + + + + + full constructor with both type (count | epsilon) + + + + + + + conversion from CvTermCriteria + + + + + + conversion to CvTermCriteria + + + + + + + conversion to CvTermCriteria + + + + + + + 2-Tuple of int (System.Int32) + + + + + The value of the first component of this object. + + + + + The value of the second component of this object. + + + + + Initializer + + + + + + + Indexer + + + + + + + 3-Tuple of int (System.Int32) + + + + + The value of the first component of this object. + + + + + The value of the second component of this object. + + + + + The value of the third component of this object. + + + + + Initializer + + + + + + + + Indexer + + + + + + + 4-Tuple of int (System.Int32) + + + + + The value of the first component of this object. + + + + + The value of the second component of this object. + + + + + The value of the third component of this object. + + + + + The value of the fourth component of this object. + + + + + Initializer + + + + + + + + + Indexer + + + + + + + 6-Tuple of int (System.Int32) + + + + + The value of the first component of this object. + + + + + The value of the second component of this object. + + + + + The value of the third component of this object. + + + + + The value of the fourth component of this object. + + + + + The value of the fourth component of this object. + + + + + The value of the sixth component of this object. + + + + + Initializer + + + + + + + + + + + Indexer + + + + + + + A matrix whose element is 8UC1 (cv::Mat_<uchar>) + + + + + Creates empty Mat + + + + + Creates from native cv::Mat* pointer + + + + + + Initializes by Mat object + + Managed Mat object + + + + constructs 2D matrix of the specified size and type + + Number of rows in a 2D array. + Number of columns in a 2D array. + + + + constructs 2D matrix of the specified size and type + + 2D array size: Size(cols, rows) . In the Size() constructor, + the number of rows and the number of columns go in the reverse order. + + + + constucts 2D matrix and fills it with the specified Scalar value. + + Number of rows in a 2D array. + Number of columns in a 2D array. + An optional value to initialize each matrix element with. + To set all the matrix elements to the particular value after the construction, use SetTo(Scalar s) method . + + + + constucts 2D matrix and fills it with the specified Scalar value. + + 2D array size: Size(cols, rows) . In the Size() constructor, + the number of rows and the number of columns go in the reverse order. + An optional value to initialize each matrix element with. + To set all the matrix elements to the particular value after the construction, use SetTo(Scalar s) method . + + + + creates a matrix header for a part of the bigger matrix + + Array that (as a whole or partly) is assigned to the constructed matrix. + No data is copied by these constructors. Instead, the header pointing to m data or its sub-array + is constructed and associated with it. The reference counter, if any, is incremented. + So, when you modify the matrix formed using such a constructor, you also modify the corresponding elements of m . + If you want to have an independent copy of the sub-array, use Mat::clone() . + Range of the m rows to take. As usual, the range start is inclusive and the range end is exclusive. + Use Range.All to take all the rows. + Range of the m columns to take. Use Range.All to take all the columns. + + + + creates a matrix header for a part of the bigger matrix + + Array that (as a whole or partly) is assigned to the constructed matrix. + No data is copied by these constructors. Instead, the header pointing to m data or its sub-array + is constructed and associated with it. The reference counter, if any, is incremented. + So, when you modify the matrix formed using such a constructor, you also modify the corresponding elements of m . + If you want to have an independent copy of the sub-array, use Mat.Clone() . + Array of selected ranges of m along each dimensionality. + + + + creates a matrix header for a part of the bigger matrix + + Array that (as a whole or partly) is assigned to the constructed matrix. + No data is copied by these constructors. Instead, the header pointing to m data or its sub-array + is constructed and associated with it. The reference counter, if any, is incremented. + So, when you modify the matrix formed using such a constructor, you also modify the corresponding elements of m . + If you want to have an independent copy of the sub-array, use Mat.Clone() . + Region of interest. + + + + constructor for matrix headers pointing to user-allocated data + + Number of rows in a 2D array. + Number of columns in a 2D array. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Number of bytes each matrix row occupies. The value should include the padding bytes at the end of each row, if any. + If the parameter is missing (set to AUTO_STEP ), no padding is assumed and the actual step is calculated as cols*elemSize() . + + + + constructor for matrix headers pointing to user-allocated data + + Number of rows in a 2D array. + Number of columns in a 2D array. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Number of bytes each matrix row occupies. The value should include the padding bytes at the end of each row, if any. + If the parameter is missing (set to AUTO_STEP ), no padding is assumed and the actual step is calculated as cols*elemSize() . + + + + constructor for matrix headers pointing to user-allocated data + + Number of rows in a 2D array. + Number of columns in a 2D array. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Number of bytes each matrix row occupies. The value should include the padding bytes at the end of each row, if any. + If the parameter is missing (set to AUTO_STEP ), no padding is assumed and the actual step is calculated as cols*elemSize() . + + + + constructor for matrix headers pointing to user-allocated data + + Array of integers specifying an n-dimensional array shape. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Array of ndims-1 steps in case of a multi-dimensional array (the last step is always set to the element size). + If not specified, the matrix is assumed to be continuous. + + + + constructor for matrix headers pointing to user-allocated data + + Array of integers specifying an n-dimensional array shape. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Array of ndims-1 steps in case of a multi-dimensional array (the last step is always set to the element size). + If not specified, the matrix is assumed to be continuous. + + + + constructor for matrix headers pointing to user-allocated data + + Array of integers specifying an n-dimensional array shape. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Array of ndims-1 steps in case of a multi-dimensional array (the last step is always set to the element size). + If not specified, the matrix is assumed to be continuous. + + + + constructs n-dimensional matrix + + Array of integers specifying an n-dimensional array shape. + + + + constructs n-dimensional matrix + + Array of integers specifying an n-dimensional array shape. + An optional value to initialize each matrix element with. + To set all the matrix elements to the particular value after the construction, use SetTo(Scalar s) method . + + + + converts old-style CvMat to the new matrix; the data is not copied by default + + Old style CvMat object + Flag to specify whether the underlying data of the the old-style CvMat should be + copied to (true) or shared with (false) the newly constructed matrix. When the data is copied, + the allocated buffer is managed using Mat reference counting mechanism. While the data is shared, + the reference counter is NULL, and you should not deallocate the data until the matrix is not destructed. + + + + converts old-style IplImage to the new matrix; the data is not copied by default + + Old style IplImage object + Flag to specify whether the underlying data of the the old-style IplImage should be + copied to (true) or shared with (false) the newly constructed matrix. When the data is copied, + the allocated buffer is managed using Mat reference counting mechanism. While the data is shared, + the reference counter is NULL, and you should not deallocate the data until the matrix is not destructed. + + + + Matrix indexer + + + + + 1-dimensional indexer + + Index along the dimension 0 + A value to the specified array element. + + + + 2-dimensional indexer + + Index along the dimension 0 + Index along the dimension 1 + A value to the specified array element. + + + + 3-dimensional indexer + + Index along the dimension 0 + Index along the dimension 1 + Index along the dimension 2 + A value to the specified array element. + + + + n-dimensional indexer + + Array of Mat::dims indices. + A value to the specified array element. + + + + Gets a type-specific indexer. The indexer has getters/setters to access each matrix element. + + + + + + Initializes as N x 1 matrix and copys array data to this + + Source array data to be copied to this + + + + Initializes as M x N matrix and copys array data to this + + Source array data to be copied to this + + + + Initializes as N x 1 matrix and copys array data to this + + Source array data to be copied to this + + + + Convert this mat to managed array + + + + + + Convert this mat to managed rectangular array + + + + + + + + + + + + Adds elements to the bottom of the matrix. (Mat::push_back) + + Added element(s) + + + + Adds elements to the bottom of the matrix. (Mat::push_back) + + Added element(s) + + + + Class for extracting Speeded Up Robust Features from an image. + + + + + Creates SURF default parameters + + + + + The SURF constructor. + + Only features with keypoint.hessian larger than that are extracted. + The number of a gaussian pyramid octaves that the detector uses. It is set to 4 by default. + If you want to get very large features, use the larger value. If you want just small features, decrease it. + The number of images within each octave of a gaussian pyramid. It is set to 2 by default. + false means basic descriptors (64 elements each), true means extended descriptors (128 elements each) + false means that detector computes orientation of each feature. + true means that the orientation is not computed (which is much, much faster). + + + + Creates instance by cv::Ptr<cv::SURF> + + + + + Creates instance by raw pointer cv::SURF* + + + + + Creates instance from cv::Ptr<T> . + ptr is disposed when the wrapper disposes. + + + + + + Creates instance from raw pointer T* + + + + + + Releases the resources + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + returns the descriptor size in float's (64 or 128) + + + + + + returns the descriptor type + + + + + + Threshold for the keypoint detector. Only features, whose hessian is larger than hessianThreshold + are retained by the detector. Therefore, the larger the value, the less keypoints you will get. + A good default value could be from 300 to 500, depending from the image contrast. + + + + + The number of a gaussian pyramid octaves that the detector uses. It is set to 4 by default. + If you want to get very large features, use the larger value. If you want just small features, decrease it. + + + + + The number of images within each octave of a gaussian pyramid. It is set to 2 by default. + + + + + false means that the basic descriptors (64 elements each) shall be computed. + true means that the extended descriptors (128 elements each) shall be computed + + + + + false means that detector computes orientation of each feature. + true means that the orientation is not computed (which is much, much faster). + For example, if you match images from a stereo pair, or do image stitching, the matched features + likely have very similar angles, and you can speed up feature extraction by setting upright=true. + + + + + Pointer to algorithm information (cv::AlgorithmInfo*) + + + + + + detects keypoints using fast multi-scale Hessian detector + + + + + + + + detects keypoints and computes the SURF descriptors for them. [useProvidedKeypoints = true] + + + + + + + + + + detects keypoints and computes the SURF descriptors for them. [useProvidedKeypoints = true] + + + + + + + + + + The "Star" Detector + + + + + Constructor + + + + + + + + + + Creates instance by cv::Ptr<cv::SURF> + + + + + Creates instance by raw pointer cv::SURF* + + + + + Creates instance from cv::Ptr<T> . + ptr is disposed when the wrapper disposes. + + + + + + Releases the resources + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + Retrieves keypoints using the StarDetector algorithm. + + The input 8-bit grayscale image + + + + + Pointer to algorithm information (cv::AlgorithmInfo*) + + + + + + Maximal Stable Extremal Regions class + + + + + Creates MSER parameters + + delta, in the code, it compares (size_{i}-size_{i-delta})/size_{i-delta} + prune the area which smaller than min_area + prune the area which bigger than max_area + prune the area have simliar size to its children + trace back to cut off mser with diversity < min_diversity + for color image, the evolution steps + the area threshold to cause re-initialize + ignore too small margin + the aperture size for edge blur + + + + Creates instance by cv::Ptr<cv::SURF> + + + + + Creates instance by raw pointer cv::SURF* + + + + + Creates instance from cv::Ptr<T> . + ptr is disposed when the wrapper disposes. + + + + + + Releases the resources + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + Extracts the contours of Maximally Stable Extremal Regions + + + + + + + + Pointer to algorithm information (cv::AlgorithmInfo*) + + + + + + Data structure for salient point detectors + + + + + Coordinate of the point + + + + + Feature size + + + + + Feature orientation in degrees (has negative value if the orientation is not defined/not computed) + + + + + Feature strength (can be used to select only the most prominent key points) + + + + + Scale-space octave in which the feature has been found; may correlate with the size + + + + + Point class (can be used by feature classifiers or object detectors) + + + + + Complete constructor + + Coordinate of the point + Feature size + Feature orientation in degrees (has negative value if the orientation is not defined/not computed) + Feature strength (can be used to select only the most prominent key points) + Scale-space octave in which the feature has been found; may correlate with the size + Point class (can be used by feature classifiers or object detectors) + + + + Complete constructor + + X-coordinate of the point + Y-coordinate of the point + Feature size + Feature orientation in degrees (has negative value if the orientation is not defined/not computed) + Feature strength (can be used to select only the most prominent key points) + Scale-space octave in which the feature has been found; may correlate with the size + Point class (can be used by feature classifiers or object detectors) + + + + Specifies whether this object contains the same members as the specified Object. + + The Object to test. + This method returns true if obj is the same type as this object and has the same members as this object. + + + + Compares two CvPoint objects. The result specifies whether the members of each object are equal. + + A Point to compare. + A Point to compare. + This operator returns true if the members of left and right are equal; otherwise, false. + + + + Compares two CvPoint objects. The result specifies whether the members of each object are unequal. + + A Point to compare. + A Point to compare. + This operator returns true if the members of left and right are unequal; otherwise, false. + + + + Specifies whether this object contains the same members as the specified Object. + + The Object to test. + This method returns true if obj is the same type as this object and has the same members as this object. + + + + Returns a hash code for this object. + + An integer value that specifies a hash value for this object. + + + + Converts this object to a human readable string. + + A string that represents this object. + + + + Semi-Global Stereo Matching + + + + + Track whether Dispose has been called + + + + + Default constructor + + + + + StereoSGBM Constructor + + + + + + + + + + + + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diagonal type + + + + + a diagonal from the upper half + [< 0] + + + + + Main dialonal + [= 0] + + + + + a diagonal from the lower half + [> 0] + + + + + MatrixDecomposition + + + + + + + + + + + [CvAdaptiveSkinDetector::MORPHING_METHOD_NONE] + + + + + + [CvAdaptiveSkinDetector::MORPHING_METHOD_ERODE] + + + + + + [CvAdaptiveSkinDetector::MORPHING_METHOD_ERODE_ERODE] + + + + + + [CvAdaptiveSkinDetector::MORPHING_METHOD_ERODE_DILATE] + + + + + 2-Tuple of byte (System.Byte) + + + + + The value of the first component of this object. + + + + + The value of the second component of this object. + + + + + Initializer + + + + + + + Indexer + + + + + + + 3-Tuple of byte (System.Byte) + + + + + The value of the first component of this object. + + + + + The value of the second component of this object. + + + + + The value of the third component of this object. + + + + + Initializer + + + + + + + + Indexer + + + + + + + 4-Tuple of byte (System.Byte) + + + + + The value of the first component of this object. + + + + + The value of the second component of this object. + + + + + The value of the third component of this object. + + + + + The value of the fourth component of this object. + + + + + Initializer + + + + + + + + + Indexer + + + + + + + 6-Tuple of byte (System.Byte) + + + + + The value of the first component of this object. + + + + + The value of the second component of this object. + + + + + The value of the third component of this object. + + + + + The value of the fourth component of this object. + + + + + The value of the fifth component of this object. + + + + + The value of the sizth component of this object. + + + + + Initializer + + + + + + + + + + + Indexer + + + + + + + Constantt values + + + + + cv::Param types + + + + + cv::Param types + + + + + cv::Param types + + + + + cv::Param types + + + + + cv::Param types + + + + + cv::Param types + + + + + cv::Param types + + + + + cv::Param types + + + + + cv::Param types + + + + + cv::Param types + + + + + cv::Param types + + + + + cv::Param types + + + + + matrix decomposition types + + + + + matrix decomposition types + + + + + matrix decomposition types + + + + + matrix decomposition types + + + + + matrix decomposition types + + + + + matrix decomposition types + + + + + InputArray kind + + + + + InputArray kind + + + + + InputArray kind + + + + + InputArray kind + + + + + InputArray kind + + + + + InputArray kind + + + + + InputArray kind + + + + + InputArray kind + + + + + InputArray kind + + + + + InputArray kind + + + + + InputArray kind + + + + + InputArray kind + + + + + InputArray kind + + + + + InputArray kind + + + + + InputArray kind + + + + + various border interpolation methods + + + + + various border interpolation methods + + + + + various border interpolation methods + + + + + various border interpolation methods + + + + + various border interpolation methods + + + + + various border interpolation methods + + + + + various border interpolation methods + + + + + various border interpolation methods + + + + + shape of the structuring element + + + + + shape of the structuring element + + + + + shape of the structuring element + + + + + cv::dft flags + + + + + cv::dft flags + + + + + cv::dft flags + + + + + cv::dft flags + + + + + cv::dft flags + + + + + cv::dct flags + + + + + cv::dct flags + + + + + cv::initWideAngleProjMap flags + + + + + cv::initWideAngleProjMap flags + + + + + GrabCut algorithm flags + + + + + GrabCut algorithm flags + + + + + GrabCut algorithm flags + + + + + Mask size for distance transform + + + + + Mask size for distance transform + + + + + Mask size for distance transform + + + + + DrawMatchesFlags + + + + + DrawMatchesFlags + + + + + DrawMatchesFlags + + + + + DrawMatchesFlags + + + + + cv::ORB + + + + + cv::ORB + + + + + cv::solvePnP + + + + + cv::solvePnP + + + + + cv::solvePnP + + + + + CascadeClassifier + + + + + CascadeClassifier + + + + + CascadeClassifier + + + + + CascadeClassifier + + + + + calcOpticalFlowPyrLK + + + + + calcOpticalFlowPyrLK + + + + + calcOpticalFlowPyrLK + + + + + calcOpticalFlowPyrLK + + + + + calcOpticalFlowPyrLK + + + + + applyColorMap + + + + + applyColorMap + + + + + applyColorMap + + + + + applyColorMap + + + + + applyColorMap + + + + + applyColorMap + + + + + applyColorMap + + + + + applyColorMap + + + + + applyColorMap + + + + + applyColorMap + + + + + applyColorMap + + + + + applyColorMap + + + + + cv::flann distance types + + + + + cv::flann distance types + + + + + cv::flann distance types + + + + + cv::flann distance types + + + + + cv::flann distance types + + + + + cv::flann distance types + + + + + cv::flann distance types + + + + + cv::flann distance types + + + + + cv::flann distance types + + + + + cv::flann distance types + + + + + cv::flann distance types + + + + + cv::flann distance types + + + + + cv::flann distance types + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Specifies whether this object contains the same members as the specified Object. + + The Object to test. + This method returns true if obj is the same type as this object and has the same members as this object. + + + + Compares two Point objects. The result specifies whether the values of the X and Y properties of the two Point objects are equal. + + A Point to compare. + A Point to compare. + This operator returns true if the X and Y values of left and right are equal; otherwise, false. + + + + Compares two Point objects. The result specifies whether the values of the X or Y properties of the two Point objects are unequal. + + A Point to compare. + A Point to compare. + This operator returns true if the values of either the X properties or the Y properties of left and right differ; otherwise, false. + + + + Unary plus operator + + + + + + + Unary minus operator + + + + + + + Shifts point by a certain offset + + + + + + + + Shifts point by a certain offset + + + + + + + + Shifts point by a certain offset + + + + + + + + Specifies whether this object contains the same members as the specified Object. + + The Object to test. + This method returns true if obj is the same type as this object and has the same members as this object. + + + + Returns a hash code for this object. + + An integer value that specifies a hash value for this object. + + + + Converts this object to a human readable string. + + A string that represents this object. + + + + Returns the distance between the specified two points + + + + + + + + Returns the distance between the specified two points + + + + + + + Calculates the dot product of two 2D vectors. + + + + + + + + Calculates the dot product of two 2D vectors. + + + + + + + Calculates the cross product of two 2D vectors. + + + + + + + + Calculates the cross product of two 2D vectors. + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + sizeof(Rect) + + + + + Represents a Rect structure with its properties left uninitialized. + + + + + Initializes a new instance of the Rectangle class with the specified location and size. + + The x-coordinate of the upper-left corner of the rectangle. + The y-coordinate of the upper-left corner of the rectangle. + The width of the rectangle. + The height of the rectangle. + + + + Initializes a new instance of the Rectangle class with the specified location and size. + + A Point that represents the upper-left corner of the rectangular region. + A Size that represents the width and height of the rectangular region. + + + + Creates a Rectangle structure with the specified edge locations. + + The x-coordinate of the upper-left corner of this Rectangle structure. + The y-coordinate of the upper-left corner of this Rectangle structure. + The x-coordinate of the lower-right corner of this Rectangle structure. + The y-coordinate of the lower-right corner of this Rectangle structure. + + + + + + + + + + + + + + + + + + Specifies whether this object contains the same members as the specified Object. + + The Object to test. + This method returns true if obj is the same type as this object and has the same members as this object. + + + + Compares two Rect objects. The result specifies whether the members of each object are equal. + + A Point to compare. + A Point to compare. + This operator returns true if the members of left and right are equal; otherwise, false. + + + + Compares two Rect objects. The result specifies whether the members of each object are unequal. + + A Point to compare. + A Point to compare. + This operator returns true if the members of left and right are unequal; otherwise, false. + + + + Shifts rectangle by a certain offset + + + + + + + + Shifts rectangle by a certain offset + + + + + + + + Expands or shrinks rectangle by a certain amount + + + + + + + + Expands or shrinks rectangle by a certain amount + + + + + + + + Determines the Rect structure that represents the intersection of two rectangles. + + A rectangle to intersect. + A rectangle to intersect. + + + + + Gets a Rect structure that contains the union of two Rect structures. + + A rectangle to union. + A rectangle to union. + + + + + Gets the y-coordinate of the top edge of this Rect structure. + + + + + Gets the y-coordinate that is the sum of the Y and Height property values of this Rect structure. + + + + + Gets the x-coordinate of the left edge of this Rect structure. + + + + + Gets the x-coordinate that is the sum of X and Width property values of this Rect structure. + + + + + Coordinate of the left-most rectangle corner [Point(X, Y)] + + + + + Size of the rectangle [CvSize(Width, Height)] + + + + + Coordinate of the left-most rectangle corner [Point(X, Y)] + + + + + Coordinate of the right-most rectangle corner [Point(X+Width, Y+Height)] + + + + + Determines if the specified point is contained within the rectangular region defined by this Rectangle. + + x-coordinate of the point + y-coordinate of the point + + + + + Determines if the specified point is contained within the rectangular region defined by this Rectangle. + + point + + + + + Determines if the specified rectangle is contained within the rectangular region defined by this Rectangle. + + rectangle + + + + + Inflates this Rect by the specified amount. + + The amount to inflate this Rectangle horizontally. + The amount to inflate this Rectangle vertically. + + + + Inflates this Rect by the specified amount. + + The amount to inflate this rectangle. + + + + Creates and returns an inflated copy of the specified Rect structure. + + The Rectangle with which to start. This rectangle is not modified. + The amount to inflate this Rectangle horizontally. + The amount to inflate this Rectangle vertically. + + + + + Determines the Rect structure that represents the intersection of two rectangles. + + A rectangle to intersect. + A rectangle to intersect. + + + + + Determines the Rect structure that represents the intersection of two rectangles. + + A rectangle to intersect. + + + + + Determines if this rectangle intersects with rect. + + Rectangle + + + + + Gets a Rect structure that contains the union of two Rect structures. + + A rectangle to union. + + + + + Gets a Rect structure that contains the union of two Rect structures. + + A rectangle to union. + A rectangle to union. + + + + + Specifies whether this object contains the same members as the specified Object. + + The Object to test. + This method returns true if obj is the same type as this object and has the same members as this object. + + + + Returns a hash code for this object. + + An integer value that specifies a hash value for this object. + + + + Converts this object to a human readable string. + + A string that represents this object. + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Specifies whether this object contains the same members as the specified Object. + + The Object to test. + This method returns true if obj is the same type as this object and has the same members as this object. + + + + Returns a hash code for this object. + + An integer value that specifies a hash value for this object. + + + + Converts this object to a human readable string. + + A string that represents this object. + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + #F0F8FF + + + + + #FAEBD7 + + + + + #00FFFF + + + + + #7FFFD4 + + + + + #F0FFFF + + + + + #F5F5DC + + + + + #FFE4C4 + + + + + #000000 + + + + + #FFEBCD + + + + + #0000FF + + + + + #8A2BE2 + + + + + #A52A2A + + + + + #DEB887 + + + + + #5F9EA0 + + + + + #7FFF00 + + + + + #D2691E + + + + + #FF7F50 + + + + + #6495ED + + + + + #FFF8DC + + + + + #DC143C + + + + + #00FFFF + + + + + #00008B + + + + + #008B8B + + + + + #B8860B + + + + + #A9A9A9 + + + + + #006400 + + + + + #BDB76B + + + + + #8B008B + + + + + #556B2F + + + + + #FF8C00 + + + + + #9932CC + + + + + #8B0000 + + + + + #E9967A + + + + + #8FBC8F + + + + + #483D8B + + + + + #2F4F4F + + + + + #00CED1 + + + + + #9400D3 + + + + + #FF1493 + + + + + #00BFFF + + + + + #696969 + + + + + #1E90FF + + + + + #B22222 + + + + + #FFFAF0 + + + + + #228B22 + + + + + #FF00FF + + + + + #DCDCDC + + + + + #F8F8FF + + + + + #FFD700 + + + + + #DAA520 + + + + + #808080 + + + + + #008000 + + + + + #ADFF2F + + + + + #F0FFF0 + + + + + #FF69B4 + + + + + #CD5C5C + + + + + #4B0082 + + + + + #FFFFF0 + + + + + #F0E68C + + + + + #E6E6FA + + + + + #FFF0F5 + + + + + #7CFC00 + + + + + #FFFACD + + + + + #ADD8E6 + + + + + #F08080 + + + + + #E0FFFF + + + + + #FAFAD2 + + + + + #D3D3D3 + + + + + #90EE90 + + + + + #FFB6C1 + + + + + #FFA07A + + + + + #20B2AA + + + + + #87CEFA + + + + + #778899 + + + + + #B0C4DE + + + + + #FFFFE0 + + + + + #00FF00 + + + + + #32CD32 + + + + + #FAF0E6 + + + + + #FF00FF + + + + + #800000 + + + + + #66CDAA + + + + + #0000CD + + + + + #BA55D3 + + + + + #9370DB + + + + + #3CB371 + + + + + #7B68EE + + + + + #00FA9A + + + + + #48D1CC + + + + + #C71585 + + + + + #191970 + + + + + #F5FFFA + + + + + #FFE4E1 + + + + + #FFE4B5 + + + + + #FFDEAD + + + + + #000080 + + + + + #FDF5E6 + + + + + #808000 + + + + + #6B8E23 + + + + + #FFA500 + + + + + #FF4500 + + + + + #DA70D6 + + + + + #EEE8AA + + + + + #98FB98 + + + + + #AFEEEE + + + + + #DB7093 + + + + + #FFEFD5 + + + + + #FFDAB9 + + + + + #CD853F + + + + + #FFC0CB + + + + + #DDA0DD + + + + + #B0E0E6 + + + + + #800080 + + + + + #FF0000 + + + + + #BC8F8F + + + + + #4169E1 + + + + + #8B4513 + + + + + #FA8072 + + + + + #F4A460 + + + + + #2E8B57 + + + + + #FFF5EE + + + + + #A0522D + + + + + #C0C0C0 + + + + + #87CEEB + + + + + #6A5ACD + + + + + #708090 + + + + + #FFFAFA + + + + + #00FF7F + + + + + #4682B4 + + + + + #D2B48C + + + + + #008080 + + + + + #D8BFD8 + + + + + #FF6347 + + + + + #40E0D0 + + + + + #EE82EE + + + + + #F5DEB3 + + + + + #FFFFFF + + + + + #F5F5F5 + + + + + #FFFF00 + + + + + #9ACD32 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Specifies whether this object contains the same members as the specified Object. + + The Object to test. + This method returns true if obj is the same type as this object and has the same members as this object. + + + + Compares two CvPoint objects. The result specifies whether the members of each object are equal. + + A Point to compare. + A Point to compare. + This operator returns true if the members of left and right are equal; otherwise, false. + + + + Compares two CvPoint objects. The result specifies whether the members of each object are unequal. + + A Point to compare. + A Point to compare. + This operator returns true if the members of left and right are unequal; otherwise, false. + + + + Specifies whether this object contains the same members as the specified Object. + + The Object to test. + This method returns true if obj is the same type as this object and has the same members as this object. + + + + Returns a hash code for this object. + + An integer value that specifies a hash value for this object. + + + + Converts this object to a human readable string. + + A string that represents this object. + + + + 2-Tuple of float (System.Single) + + + + + The value of the first component of this object. + + + + + The value of the second component of this object. + + + + + Initializer + + + + + + + Indexer + + + + + + + 3-Tuple of float (System.Single) + + + + + The value of the first component of this object. + + + + + The value of the second component of this object. + + + + + The value of the third component of this object. + + + + + Initializer + + + + + + + + Indexer + + + + + + + 4-Tuple of float (System.Single) + + + + + The value of the first component of this object. + + + + + The value of the second component of this object. + + + + + The value of the third component of this object. + + + + + The value of the fourth component of this object. + + + + + Initializer + + + + + + + + + Indexer + + + + + + + 6-Tuple of float (System.Single) + + + + + The value of the first component of this object. + + + + + The value of the second component of this object. + + + + + The value of the third component of this object. + + + + + The value of the fourth component of this object. + + + + + The value of the fifth component of this object. + + + + + The value of the sixth component of this object. + + + + + Initializer + + + + + + + + + + + Indexer + + + + + + + 2-Tuple of short (System.Int16) + + + + + The value of the first component of this object. + + + + + The value of the second component of this object. + + + + + Initializer + + + + + + + Indexer + + + + + + + 3-Tuple of short (System.Int16) + + + + + The value of the first component of this object. + + + + + The value of the second component of this object. + + + + + The value of the third component of this object. + + + + + Initializer + + + + + + + + Indexer + + + + + + + 4-Tuple of short (System.Int16) + + + + + The value of the first component of this object. + + + + + The value of the second component of this object. + + + + + The value of the third component of this object. + + + + + The value of the fourth component of this object. + + + + + Initializer + + + + + + + + + Indexer + + + + + + + 6-Tuple of short (System.Int16) + + + + + The value of the first component of this object. + + + + + The value of the second component of this object. + + + + + The value of the third component of this object. + + + + + The value of the fourth component of this object. + + + + + The value of the fifth component of this object. + + + + + The value of the sixth component of this object. + + + + + Initializer + + + + + + + + + + + Indexer + + + + + + + 2-Tuple of ushort (System.UInt16) + + + + + The value of the first component of this object. + + + + + The value of the second component of this object. + + + + + Initializer + + + + + + + Indexer + + + + + + + 3-Tuple of ushort (System.UInt16) + + + + + The value of the first component of this object. + + + + + The value of the second component of this object. + + + + + The value of the third component of this object. + + + + + Initializer + + + + + + + + Indexer + + + + + + + 4-Tuple of ushort (System.UInt16) + + + + + The value of the first component of this object. + + + + + The value of the second component of this object. + + + + + The value of the third component of this object. + + + + + The value of the fourth component of this object. + + + + + Initializer + + + + + + + + + Indexer + + + + + + + 4-Tuple of ushort (System.UInt16) + + + + + The value of the first component of this object. + + + + + The value of the second component of this object. + + + + + The value of the third component of this object. + + + + + The value of the fourth component of this object. + + + + + The value of the fifth component of this object. + + + + + The value of the sixth component of this object. + + + + + Initializer + + + + + + + + + + + Indexer + + + + + + + 2-Tuple of double (System.Double) + + + + + The value of the first component of this object. + + + + + The value of the second component of this object. + + + + + Initializer + + + + + + + Indexer + + + + + + + 3-Tuple of double (System.Double) + + + + + The value of the first component of this object. + + + + + The value of the second component of this object. + + + + + The value of the third component of this object. + + + + + Initializer + + + + + + + + Indexer + + + + + + + 4-Tuple of double (System.Double) + + + + + The value of the first component of this object. + + + + + The value of the second component of this object. + + + + + The value of the third component of this object. + + + + + The value of the fourth component of this object. + + + + + Initializer + + + + + + + + + Indexer + + + + + + + 6-Tuple of double (System.Double) + + + + + The value of the first component of this object. + + + + + The value of the second component of this object. + + + + + The value of the third component of this object. + + + + + The value of the fourth component of this object. + + + + + The value of the fifth component of this object. + + + + + The value of the sixth component of this object. + + + + + Initializer + + + + + + + + + + + Indexer + + + + + + + A matrix whose element is 8UC3 (cv::Mat_<cv::Vec3b>) + + + + + Creates empty Mat + + + + + Creates from native cv::Mat* pointer + + + + + + Initializes by Mat object + + Managed Mat object + + + + constructs 2D matrix of the specified size and type + + Number of rows in a 2D array. + Number of columns in a 2D array. + + + + constructs 2D matrix of the specified size and type + + 2D array size: Size(cols, rows) . In the Size() constructor, + the number of rows and the number of columns go in the reverse order. + + + + constucts 2D matrix and fills it with the specified Scalar value. + + Number of rows in a 2D array. + Number of columns in a 2D array. + An optional value to initialize each matrix element with. + To set all the matrix elements to the particular value after the construction, use SetTo(Scalar s) method . + + + + constucts 2D matrix and fills it with the specified Scalar value. + + 2D array size: Size(cols, rows) . In the Size() constructor, + the number of rows and the number of columns go in the reverse order. + An optional value to initialize each matrix element with. + To set all the matrix elements to the particular value after the construction, use SetTo(Scalar s) method . + + + + creates a matrix header for a part of the bigger matrix + + Array that (as a whole or partly) is assigned to the constructed matrix. + No data is copied by these constructors. Instead, the header pointing to m data or its sub-array + is constructed and associated with it. The reference counter, if any, is incremented. + So, when you modify the matrix formed using such a constructor, you also modify the corresponding elements of m . + If you want to have an independent copy of the sub-array, use Mat::clone() . + Range of the m rows to take. As usual, the range start is inclusive and the range end is exclusive. + Use Range.All to take all the rows. + Range of the m columns to take. Use Range.All to take all the columns. + + + + creates a matrix header for a part of the bigger matrix + + Array that (as a whole or partly) is assigned to the constructed matrix. + No data is copied by these constructors. Instead, the header pointing to m data or its sub-array + is constructed and associated with it. The reference counter, if any, is incremented. + So, when you modify the matrix formed using such a constructor, you also modify the corresponding elements of m . + If you want to have an independent copy of the sub-array, use Mat.Clone() . + Array of selected ranges of m along each dimensionality. + + + + creates a matrix header for a part of the bigger matrix + + Array that (as a whole or partly) is assigned to the constructed matrix. + No data is copied by these constructors. Instead, the header pointing to m data or its sub-array + is constructed and associated with it. The reference counter, if any, is incremented. + So, when you modify the matrix formed using such a constructor, you also modify the corresponding elements of m . + If you want to have an independent copy of the sub-array, use Mat.Clone() . + Region of interest. + + + + constructor for matrix headers pointing to user-allocated data + + Number of rows in a 2D array. + Number of columns in a 2D array. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Number of bytes each matrix row occupies. The value should include the padding bytes at the end of each row, if any. + If the parameter is missing (set to AUTO_STEP ), no padding is assumed and the actual step is calculated as cols*elemSize() . + + + + constructor for matrix headers pointing to user-allocated data + + Number of rows in a 2D array. + Number of columns in a 2D array. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Number of bytes each matrix row occupies. The value should include the padding bytes at the end of each row, if any. + If the parameter is missing (set to AUTO_STEP ), no padding is assumed and the actual step is calculated as cols*elemSize() . + + + + constructor for matrix headers pointing to user-allocated data + + Number of rows in a 2D array. + Number of columns in a 2D array. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Number of bytes each matrix row occupies. The value should include the padding bytes at the end of each row, if any. + If the parameter is missing (set to AUTO_STEP ), no padding is assumed and the actual step is calculated as cols*elemSize() . + + + + constructor for matrix headers pointing to user-allocated data + + Array of integers specifying an n-dimensional array shape. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Array of ndims-1 steps in case of a multi-dimensional array (the last step is always set to the element size). + If not specified, the matrix is assumed to be continuous. + + + + constructor for matrix headers pointing to user-allocated data + + Array of integers specifying an n-dimensional array shape. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Array of ndims-1 steps in case of a multi-dimensional array (the last step is always set to the element size). + If not specified, the matrix is assumed to be continuous. + + + + constructor for matrix headers pointing to user-allocated data + + Array of integers specifying an n-dimensional array shape. + Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. + Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. + This operation is very efficient and can be used to process external data using OpenCV functions. + The external data is not automatically deallocated, so you should take care of it. + Array of ndims-1 steps in case of a multi-dimensional array (the last step is always set to the element size). + If not specified, the matrix is assumed to be continuous. + + + + constructs n-dimensional matrix + + Array of integers specifying an n-dimensional array shape. + + + + constructs n-dimensional matrix + + Array of integers specifying an n-dimensional array shape. + An optional value to initialize each matrix element with. + To set all the matrix elements to the particular value after the construction, use SetTo(Scalar s) method . + + + + converts old-style CvMat to the new matrix; the data is not copied by default + + Old style CvMat object + Flag to specify whether the underlying data of the the old-style CvMat should be + copied to (true) or shared with (false) the newly constructed matrix. When the data is copied, + the allocated buffer is managed using Mat reference counting mechanism. While the data is shared, + the reference counter is NULL, and you should not deallocate the data until the matrix is not destructed. + + + + converts old-style IplImage to the new matrix; the data is not copied by default + + Old style IplImage object + Flag to specify whether the underlying data of the the old-style IplImage should be + copied to (true) or shared with (false) the newly constructed matrix. When the data is copied, + the allocated buffer is managed using Mat reference counting mechanism. While the data is shared, + the reference counter is NULL, and you should not deallocate the data until the matrix is not destructed. + + + + Matrix indexer + + + + + 1-dimensional indexer + + Index along the dimension 0 + A value to the specified array element. + + + + 2-dimensional indexer + + Index along the dimension 0 + Index along the dimension 1 + A value to the specified array element. + + + + 3-dimensional indexer + + Index along the dimension 0 + Index along the dimension 1 + Index along the dimension 2 + A value to the specified array element. + + + + n-dimensional indexer + + Array of Mat::dims indices. + A value to the specified array element. + + + + + + + + + + Initializes as N x 1 matrix and copys array data to this + + Source array data to be copied to this + + + + Initializes as M x N matrix and copys array data to this + + Source array data to be copied to this + + + + Initializes as N x 1 matrix and copys array data to this + + Source array data to be copied to this + + + + Convert this mat to managed array + + + + + + + + + + + + Convert this mat to managed rectangular array + + + + + + + + + + + + Adds elements to the bottom of the matrix. (Mat::push_back) + + Added element(s) + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Proxy datatype for passing Mat's and vector<>'s as input parameters + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Creates a proxy class of the specified Mat + + + + + + + Creates a proxy class of the specified MatExpr + + + + + + + Creates a proxy class of the specified Scalar + + + + + + + Creates a proxy class of the specified double + + + + + + + Creates a proxy class of the specified GpuMat + + + + + + + Creates a proxy class of the specified array of Mat + + + + + + + Creates a proxy class of the specified list + + Array object + + + + + Creates a proxy class of the specified list + + Array object + Matrix depth and channels for converting array to cv::Mat + + + + + Creates a proxy class of the specified list + + Array object + + + + + Creates a proxy class of the specified list + + Array object + Matrix depth and channels for converting array to cv::Mat + + + + + Creates a proxy class of the specified list + + Array object + + + + + Creates a proxy class of the specified list + + Array object + Matrix depth and channels for converting array to cv::Mat + + + + + + + + + + + + Proxy datatype for passing Mat's and List<>'s as output parameters + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Creates a proxy class of the specified matrix + + + + + + + Creates a proxy class of the specified matrix + + + + + + + Creates a proxy class of the specified list + + + + + + + + Creates a proxy class of the specified list + + + + + + + Represents std::vector + + + + + vector.size() + + + + + &vector[0] + + + + + Convert std::vector<T> to managed array T[] + + + + + + + + + + + Track whether Dispose has been called + + + + + + + + + + + + + + + + + + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + vector.size() + + + + + &vector[0] + + + + + Converts std::vector to managed array + + + + + + + + + + + Track whether Dispose has been called + + + + + + + + + + + + + + + + + + + + + + + + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + vector.size() + + + + + &vector[0] + + + + + Converts std::vector to managed array + + + + + + Converts std::vector to managed array + + structure that has four int members (ex. CvLineSegmentPoint, CvRect) + + + + + + + + + + Track whether Dispose has been called + + + + + + + + + + + + + + + + + + + + + + + + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + vector.size() + + + + + &vector[0] + + + + + Converts std::vector to managed array + + + + + + Converts std::vector to managed array + + structure that has four int members (ex. CvLineSegmentPoint, CvRect) + + + + + + + + + + Track whether Dispose has been called + + + + + + + + + + + + + + + + + + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + vector.size() + + + + + vector[i].size() + + + + + &vector[0] + + + + + Converts std::vector to managed array + + + + + + + + + + + Track whether Dispose has been called + + + + + + + + + + + + + + + + + + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + vector.size() + + + + + vector[i].size() + + + + + &vector[0] + + + + + Converts std::vector to managed array + + + + + + + + + + + Track whether Dispose has been called + + + + + + + + + + + + + + + + + + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + vector.size() + + + + + &vector[0] + + + + + Converts std::vector to managed array + + + + + + The Base Class for Background/Foreground Segmentation. + The class is only used to define the common interface for + the whole family of background/foreground segmentation algorithms. + + + + + the default constructor + + + + + the full constructor that takes the length of the history, the number of gaussian mixtures, the background ratio parameter and the noise strength + + + + + + + + + Creates instance from cv::Ptr<T> . + ptr is disposed when the wrapper disposes. + + + + + + Creates instance from raw T* + + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + the update operator + + + + + + + + re-initiaization method + + + + + + + Pointer to algorithm information (cv::AlgorithmInfo*) + + + + + + + + + + + + [HOGDescriptor::L2Hys] + + + + + + + + + + Track whether Dispose has been called + + + + + + + + + + + + + + + + + + + + + + + + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + vector.size() + + + + + &vector[0] + + + + + Converts std::vector to managed array + + + + + + + + + + + Track whether Dispose has been called + + + + + + + + + + + + + + + + + + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + vector.size() + + + + + &vector[0] + + + + + Converts std::vector to managed array + + + + + + + + + + + Track whether Dispose has been called + + + + + + + + + + + + + + + + + + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + vector.size() + + + + + &vector[0] + + + + + Converts std::vector to managed array + + + + + + + + + + + Track whether Dispose has been called + + + + + + + + + + + + + + + + + + + + + + + + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + vector.size() + + + + + &vector[0] + + + + + Converts std::vector to managed array + + + + + + + + + + + Track whether Dispose has been called + + + + + + + + + + + + + + + + + + + + + + + + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + vector.size() + + + + + &vector[0] + + + + + Converts std::vector to managed array + + + + + + + + + + + Track whether Dispose has been called + + + + + + + + + + + + + + + + + + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + vector.size() + + + + + &vector[0] + + + + + Converts std::vector to managed array + + + + + + Converts std::vector to managed array + + structure that has two float members (ex. CvLineSegmentPolar, CvPoint2D32f, PointF) + + + + + + + + + + Track whether Dispose has been called + + + + + + + + + + + + + + + + + + + + + + + + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + vector.size() + + + + + &vector[0] + + + + + Converts std::vector to managed array + + + + + + Converts std::vector to managed array + + structure that has four int members (ex. CvLineSegmentPoint, CvRect) + + + + + + + + + + Track whether Dispose has been called + + + + + + + + + + + + + + + + + + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + vector.size() + + + + + &vector[0] + + + + + Converts std::vector to managed array + + + + + + Converts std::vector to managed array + + structure that has two float members (ex. CvLineSegmentPolar, CvPoint2D32f, PointF) + + + + + + + + + + Track whether Dispose has been called + + + + + + + + + + + + + + + + + + + + + + + + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + vector.size() + + + + + &vector[0] + + + + + Converts std::vector to managed array + + + + + + Converts std::vector to managed array + + + + + + 各要素の参照カウントを1追加する + + + + diff --git a/OpenCV/Libs/OpenCvSharp.Extensions.dll b/OpenCV/Libs/OpenCvSharp.Extensions.dll new file mode 100644 index 0000000..cfa55a6 Binary files /dev/null and b/OpenCV/Libs/OpenCvSharp.Extensions.dll differ diff --git a/OpenCV/Libs/OpenCvSharp.Extensions.xml b/OpenCV/Libs/OpenCvSharp.Extensions.xml new file mode 100644 index 0000000..5f0250f --- /dev/null +++ b/OpenCV/Libs/OpenCvSharp.Extensions.xml @@ -0,0 +1,474 @@ + + + + OpenCvSharp.Extensions + + + + + Various binarization methods (ATTENTION : The methods of this class is not implemented in OpenCV) + + + + + Binarizes by Niblack's method + + Input image + Output image + Window size + Adequate coefficient + + + + Binarizes by Niblack's method (This is faster but memory-hogging) + + Input image + Output image + Window size + Adequate coefficient + + + + Binarizes by Sauvola's method + + Input image + Output image + Window size + Adequate coefficient + Adequate coefficient + + + + Binarizes by Sauvola's method (This is faster but memory-hogging) + + Input image + Output image + Window size + Adequate coefficient + Adequate coefficient + + + + Binarizes by Bernsen's method + + Input image + Output image + Window size + Adequate coefficient + Adequate coefficient + + + + Binarizes by Nick's method + + Input image + Output image + Window size + Adequate coefficient + + + + 注目画素の周辺画素の平均値と標準偏差を求める + + 画像の画素データ + x座標 + y座標 + 周辺画素の探索サイズ。奇数でなければならない + 出力される平均 + 出力される標準偏差 + + + + 注目画素の周辺画素の最大値と最小値を求める + + 画像の画素データ + x座標 + y座標 + 周辺画素の探索サイズ。奇数でなければならない + 出力される最小値 + 出力される最大値 + + + + static class which provides conversion between System.Drawing.Bitmap and IplImage/Mat + + + + + Converts System.Drawing.Bitmap to IplImage + + System.Drawing.Bitmap object to be converted + An IplImage object which is converted from System.Drawing.Bitmap + + + + Converts System.Drawing.Bitmap to IplImage + + System.Drawing.Bitmap object to be converted + An IplImage object which is converted from System.Drawing.Bitmap + + + + Copies pixel data from System.Drawing.Bitmap to IplImage instance + + + + + + + + Converts IplImage to System.Drawing.Bitmap + + Mat + + + + + Converts IplImage to System.Drawing.Bitmap + + Mat + Pixel Depth + + + + + Converts IplImage to System.Drawing.Bitmap + + Mat + IplImage + Author: shimat, Gummo (ROI support) + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Converts System.Drawing.Bitmap to Mat + + System.Drawing.Bitmap object to be converted + A Mat object which is converted from System.Drawing.Bitmap + + + + Converts System.Drawing.Bitmap to Mat + + System.Drawing.Bitmap object to be converted + A Mat object which is converted from System.Drawing.Bitmap + + + + Converts Mat to System.Drawing.Bitmap + + Mat + + + + + Converts Mat to System.Drawing.Bitmap + + Mat + Pixel Depth + + + + + Converts Mat to System.Drawing.Bitmap + + Mat + Mat + Author: shimat, Gummo (ROI support) + + + + + + + + + + + + + + + + + + + + + + + Task Parallel Library for .NET 2.0 + + + + + Number of Threads + + + + + Executes a for loop in which iterations may run in parallel. + + The start index, inclusive. + The end index, exclusive. + The delegate that is invoked once per iteration. + + + + + + + + + + + + + + Provides information for the platform which the user is using + + + + + OS type + + + + + Runtime type + + + + + A static class which provides conversion between System.Windows.Media.Imaging.WriteableBitmap and IplImage + + + + + Converts Mat to WriteableBitmap. + The arguments of this method corresponds the consructor of WriteableBitmap. + + Input Mat + Horizontal dots per inch + Vertical dots per inch + Pixel format of output WriteableBitmap + Bitmap pallette + WriteableBitmap + + + + Converts Mat to WriteableBitmap (dpi=96, BitmapPalette=null) + + Input Mat + Pixel format of output WriteableBitmap + WriteableBitmap + + + + Converts Mat to WriteableBitmap (dpi=96, BitmapPalette=null) + + Input Mat + WriteableBitmap + + + + Converts Mat to WriteableBitmap. + This method is more efficient because new instance of WriteableBitmap is not allocated. + + Input Mat + Output WriteableBitmap + + + + + + + + + 指定したPixelFormatに適合するIplImageのビット深度を返す + + + + + + + 指定したPixelFormatに適合するIplImageのチャンネル数を返す + + + + + + + 指定したPixelFormatに適合するMatTypeを返す + + + + + + + Converts WriteableBitmap to IplImage + + Input WriteableBitmap + IplImage + + + + Converts WriteableBitmap to IplImage + + Input WriteableBitmap + Output IplImage + + + + Copies pixel data from System.Windows.Media.Imaging.WriteableBitmap to IplImage instance + + + + + + + + 指定したIplImageのビット深度・チャンネル数に適合するPixelFormatを返す + + + + + + + + 指定したIplImageのビット深度・チャンネル数に適合するPixelFormatを返す + + + + + + + Converts IplImage to WriteableBitmap. + The arguments of this method corresponds the consructor of WriteableBitmap. + + Input IplImage + Horizontal dots per inch + Vertical dots per inch + Pixel format of output WriteableBitmap + Bitmap pallette + WriteableBitmap + + + + Converts IplImage to WriteableBitmap (dpi=96, BitmapPalette=null) + + Input IplImage + Pixel format of output WriteableBitmap + WriteableBitmap + + + + Converts IplImage to WriteableBitmap (dpi=96, BitmapPalette=null) + + Input IplImage + WriteableBitmap + + + + Converts IplImage to WriteableBitmap. + This method is more efficient because new instance of WriteableBitmap is not allocated. + + Input IplImage + Output WriteableBitmap + + + + Static class which provides conversion between System.Windows.Media.Imaging.BitmapSource and IplImage + + + + + Converts Mat to BitmapSource. + + Input IplImage + BitmapSource + + + + Converts Mat to BitmapSource. + + Input IplImage + + + + + BitmapSource + + + + Converts System.Drawing.Bitmap to BitmapSource. + + Input System.Drawing.Bitmap + http://www.codeproject.com/Articles/104929/Bitmap-to-BitmapSource + BitmapSource + + + + Converts BitmapSource to Mat + + Input BitmapSource + IplImage + + + + Converts BitmapSource to Mat + + Input BitmapSource + Output Mat + + + + Copies pixel data from System.Windows.Media.Imaging.BitmapSource to IplImage instance + + + + + + + diff --git a/OpenCV/Libs/OpenCvSharp.UserInterface.dll b/OpenCV/Libs/OpenCvSharp.UserInterface.dll new file mode 100644 index 0000000..fc4aac5 Binary files /dev/null and b/OpenCV/Libs/OpenCvSharp.UserInterface.dll differ diff --git a/OpenCV/Libs/OpenCvSharp.dll b/OpenCV/Libs/OpenCvSharp.dll new file mode 100644 index 0000000..7baa4a4 Binary files /dev/null and b/OpenCV/Libs/OpenCvSharp.dll differ diff --git a/OpenCV/Libs/OpenCvSharp.dll.config b/OpenCV/Libs/OpenCvSharp.dll.config new file mode 100644 index 0000000..e2d2e42 --- /dev/null +++ b/OpenCV/Libs/OpenCvSharp.dll.config @@ -0,0 +1,21 @@ + + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/OpenCV/Libs/OpenCvSharp.xml b/OpenCV/Libs/OpenCvSharp.xml new file mode 100644 index 0000000..689709b --- /dev/null +++ b/OpenCV/Libs/OpenCvSharp.xml @@ -0,0 +1,33730 @@ + + + + OpenCvSharp + + + + + + + + + + The X component of the normalized vector collinear to the line + + + + + The Y component of the normalized vector collinear to the line + + + + + X-coordinate of some point on the line + + + + + Y-coordinate of some point on the line + + + + + Initializes this object + + The X component of the normalized vector collinear to the line + The Y component of the normalized vector collinear to the line + Z-coordinate of some point on the line + Z-coordinate of some point on the line + + + + Initializes by cvFitLine output + + The returned value from cvFitLineparam> + + + + + + + + + + + + + + + + Returns the distance between this line and the specified point + + + + + + Returns the distance between this line and the specified point + + + + + + Returns the distance between this line and the specified point + + + + + + Returns the distance between this line and the specified point + + + + + + + Fits this line to the specified size (for drawing) + + Width of fit size + Height of fit size + 1st edge point of fitted line + 2nd edge point of fitted line + + + + A 3-dimensional line object + + + + + The X component of the normalized vector collinear to the line + + + + + The Y component of the normalized vector collinear to the line + + + + + The Z component of the normalized vector collinear to the line + + + + + X-coordinate of some point on the line + + + + + Y-coordinate of some point on the line + + + + + Z-coordinate of some point on the line + + + + + Initializes this object + + The X component of the normalized vector collinear to the line + The Y component of the normalized vector collinear to the line + The Z component of the normalized vector collinear to the line + Z-coordinate of some point on the line + Z-coordinate of some point on the line + Z-coordinate of some point on the line + + + + Initializes by cvFitLine output + + The returned value from cvFitLineparam> + + + + + + + + + + + + + + + + Returns the distance between this line and the specified point + + + + + + + + Returns the distance between this line and the specified point + + + + + + Returns the distance between this line and the specified point + + + + + + Returns the distance between this line and the specified point + + + + + + + + ベクトルの外積 + + + + + + + + ベクトルの長さ(原点からの距離) + + + + + + + 2点間(2ベクトル)の距離 + + + + + + + + Various SURF algorithm parameters + + + + + Field data + + + + + + + + + + false means basic descriptors (64 elements each), + true means _extended descriptors (128 elements each) + + + + + Only features with keypoint.hessian larger than that are extracted. + good default value is ~300-500 (can depend on the average + local contrast and sharpness of the image). + user can further filter out some features based on their hessian values + and other characteristics + + + + + The number of octaves to be used for extraction. + With each next octave the feature size is doubled (3 by default) + + + + + The number of layers within each octave (4 by default) + + + + + Creates SURF default parameters + + Only features with keypoint.hessian larger than that are extracted. + false means basic descriptors (64 elements each), true means _extended descriptors (128 elements each) + + + + Creates a new object that is a copy of the current instance. + + A new object that is a copy of this instance. + + + + tree node + + + + + Default constructor + + + + + Initializes from native pointer + + struct CvTreeNode* + + + + Initializes from native pointer + + struct CvTreeNode* + + + + sizeof(CvTreeNode) + + + + + miscellaneous flags + + + + + size of sequence header + + + + + previous sequence + + + + + next sequence + + + + + 2nd previous sequence + + + + + 2nd next sequence + + + + + Adds new node to the tree + + The parent node that is already in the tree. + The top level node. If parent and frame are the same, v_prev field of node is set to null rather than parent. + + + + Removes node from tree + + The top level node. If node->v_prev = null and node->h_prev is null (i.e. if node is the first child of frame), + frame->v_next is set to node->h_next (i.e. the first child or frame is changed). + + + + Gathers all node pointers to the single sequence + + Header size of the created sequence (sizeof(CvSeq) is the most used value). + Container for the sequence. + + + + + Type information + + + + + Default constructor + + + + + Initializes from native pointer + + struct CvTypeInfo* + + + + sizeof(CvTypeInfo) + + + + + not used + + + + + not used + + + + + previous registered type in the list + + + + + next registered type in the list + + + + + type name, written to file storage + + + + + checks if the passed object belongs to the type + + + + + releases object (memory etc.) + + + + + reads object from file storage + + + + + writes object to file storage + + + + + creates a copy of the object + + + + + Registers new type + + + + + Locality Sensitive Hash (LSH) table + + + + + Track whether Dispose has been called + + + + + Construct a Locality Sensitive Hash (LSH) table, for indexing d-dimensional vectors of + given type. Vectors will be hashed L times with k-dimensional p-stable (p=2) functions. + + (not supported argument on OpenCvSharp) + + + + + Construct a Locality Sensitive Hash (LSH) table, for indexing d-dimensional vectors of + given type. Vectors will be hashed L times with k-dimensional p-stable (p=2) functions. + + (not supported argument on OpenCvSharp) + + + + + + Construct a Locality Sensitive Hash (LSH) table, for indexing d-dimensional vectors of + given type. Vectors will be hashed L times with k-dimensional p-stable (p=2) functions. + + (not supported argument on OpenCvSharp) + + + + + + + Construct a Locality Sensitive Hash (LSH) table, for indexing d-dimensional vectors of + given type. Vectors will be hashed L times with k-dimensional p-stable (p=2) functions. + + (not supported argument on OpenCvSharp) + + + + + + + + Construct a Locality Sensitive Hash (LSH) table, for indexing d-dimensional vectors of + given type. Vectors will be hashed L times with k-dimensional p-stable (p=2) functions. + + (not supported argument on OpenCvSharp) + + + + + + + + + Construct a Locality Sensitive Hash (LSH) table, for indexing d-dimensional vectors of + given type. Vectors will be hashed L times with k-dimensional p-stable (p=2) functions. + + (not supported argument on OpenCvSharp) + + + + + + + + + + Construct a Locality Sensitive Hash (LSH) table, for indexing d-dimensional vectors of + given type. Vectors will be hashed L times with k-dimensional p-stable (p=2) functions. + + (not supported argument on OpenCvSharp) + + + + + + Construct a Locality Sensitive Hash (LSH) table, for indexing d-dimensional vectors of + given type. Vectors will be hashed L times with k-dimensional p-stable (p=2) functions. + + (not supported argument on OpenCvSharp) + + + + + + + Construct a Locality Sensitive Hash (LSH) table, for indexing d-dimensional vectors of + given type. Vectors will be hashed L times with k-dimensional p-stable (p=2) functions. + + (not supported argument on OpenCvSharp) + + + + + + + + Construct a Locality Sensitive Hash (LSH) table, for indexing d-dimensional vectors of + given type. Vectors will be hashed L times with k-dimensional p-stable (p=2) functions. + + (not supported argument on OpenCvSharp) + + + + + + + + + Construct a Locality Sensitive Hash (LSH) table, for indexing d-dimensional vectors of + given type. Vectors will be hashed L times with k-dimensional p-stable (p=2) functions. + + (not supported argument on OpenCvSharp) + + + + + + + + + + Construct a Locality Sensitive Hash (LSH) table, for indexing d-dimensional vectors of + given type. Vectors will be hashed L times with k-dimensional p-stable (p=2) functions. + + (not supported argument on OpenCvSharp) + + + + + + + + + + + Construct in-memory LSH table, with n bins. + + + + + + + Construct in-memory LSH table, with n bins. + + + + + + + + Construct in-memory LSH table, with n bins. + + + + + + + + + Construct in-memory LSH table, with n bins. + + + + + + + + + + Construct in-memory LSH table, with n bins. + + + + + + + + + + + Construct in-memory LSH table, with n bins. + + + + + + + + + + + + Construct in-memory LSH table, with n bins. + + + + + + + + Construct in-memory LSH table, with n bins. + + + + + + + + + Construct in-memory LSH table, with n bins. + + + + + + + + + + Construct in-memory LSH table, with n bins. + + + + + + + + + + + Construct in-memory LSH table, with n bins. + + + + + + + + + + + + Construct in-memory LSH table, with n bins. + + + + + + + + + + + + + Initializes from pointer + + struct CvLSH* + + + + Initializes from pointer + + struct CvLSH* + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + Add vectors to the LSH structure, optionally returning indices. + + + + + + Add vectors to the LSH structure, optionally returning indices. + + + + + + + Query the LSH n times for at most k nearest points; data is n x d, + indices and dist are n x k. At most emax stored points will be accessed. + + + + + + + + + + Free the given LSH structure. + + + + + Remove vectors from LSH, as addressed by given indices. + + + + + + Return the number of vectors in the LSH. + + number of vectors + + + + + + + + + field data + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Constructor + + + + + Constructor + + + + + + Constructor + + + + + + + Constructor + + + + + + + + Constructor + + + + + + + + + Constructor + + + + + + + + + + Specifies whether this object contains the same members as the specified Object. + + The Object to test. + This method returns true if obj is the same type as this object and has the same members as this object. + + + + Compares two CvPoint objects. The result specifies whether the members of each object are equal. + + A Point to compare. + A Point to compare. + This operator returns true if the members of left and right are equal; otherwise, false. + + + + Compares two CvPoint objects. The result specifies whether the members of each object are unequal. + + A Point to compare. + A Point to compare. + This operator returns true if the members of left and right are unequal; otherwise, false. + + + + Specifies whether this object contains the same members as the specified Object. + + The Object to test. + This method returns true if obj is the same type as this object and has the same members as this object. + + + + Returns a hash code for this object. + + An integer value that specifies a hash value for this object. + + + + Converts this object to a human readable string. + + A string that represents this object. + + + + Creates a new object that is a copy of the current instance. + + A new object that is a copy of this instance. + + + + CvBGCodeBookModel + + + + + Track whether Dispose has been called + + + + + Initialize from pointer + + struct CvBGCodeBookModel* + + + + Allocates BGCodeBookModel structure + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + sizeof(CvBGCodeBookModel) + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + CvBGCodeBookElem + + + + + Initialize from pointer + + CvBGCodeBookElem* + + + + sizeof(CvBGCodeBookElem) + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + CvLevMarq + + + + + Track whether Dispose has been called + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + CvLevMarq + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Track whether Dispose has been called + + + + + CV_NUM_FACE_ELEMENTS + + + + + + + + + + + + + Initialize from pointer + + struct CvFaceTracker* + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + + + + + + + + + + + structure contains the bounding box and confidence level for detected object + + + + + Track whether Dispose has been called + + + + + load trained detector from a file + + + + + + Initializes from pointer + + struct CvLatentSvmDetector* + + + + Initializes from pointer + + struct CvLSH* + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + find rectangular regions in the given image that are likely + to contain objects and corresponding confidence levels + + image to detect objects in + memory storage to store the resultant sequence of the object candidate rectangles + + + + + find rectangular regions in the given image that are likely + to contain objects and corresponding confidence levels + + image to detect objects in + memory storage to store the resultant sequence of the object candidate rectangles + threshold for the non-maximum suppression algorithm + = 0.5f [here will be the reference to original paper] + + + + + find rectangular regions in the given image that are likely + to contain objects and corresponding confidence levels + + image to detect objects in + memory storage to store the resultant sequence of the object candidate rectangles + threshold for the non-maximum suppression algorithm + = 0.5f [here will be the reference to original paper] + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Qt Font structure + + + + + Create the font to be used to draw text on an image + + Name of the font. The name should match the name of a system font (such as ``Times’‘). If the font is not found, a default one will be used. + + + + Create the font to be used to draw text on an image + + Name of the font. The name should match the name of a system font (such as ``Times’‘). If the font is not found, a default one will be used. + Size of the font. If not specified, equal zero or negative, the point size of the font is set to a system-dependent default value. Generally, this is 12 points. + + + + Create the font to be used to draw text on an image + + Name of the font. The name should match the name of a system font (such as ``Times’‘). If the font is not found, a default one will be used. + Size of the font. If not specified, equal zero or negative, the point size of the font is set to a system-dependent default value. Generally, this is 12 points. + Color of the font in BGRA – A = 255 is fully transparent. Use the macro CV _ RGB for simplicity. + + + + Create the font to be used to draw text on an image + + Name of the font. The name should match the name of a system font (such as ``Times’‘). If the font is not found, a default one will be used. + Size of the font. If not specified, equal zero or negative, the point size of the font is set to a system-dependent default value. Generally, this is 12 points. + Color of the font in BGRA – A = 255 is fully transparent. Use the macro CV _ RGB for simplicity. + The operation flags + + + + Create the font to be used to draw text on an image + + Name of the font. The name should match the name of a system font (such as ``Times’‘). If the font is not found, a default one will be used. + Size of the font. If not specified, equal zero or negative, the point size of the font is set to a system-dependent default value. Generally, this is 12 points. + Color of the font in BGRA – A = 255 is fully transparent. Use the macro CV _ RGB for simplicity. + The operation flags + The operation flags + + + + Create the font to be used to draw text on an image + + Name of the font. The name should match the name of a system font (such as ``Times’‘). If the font is not found, a default one will be used. + Size of the font. If not specified, equal zero or negative, the point size of the font is set to a system-dependent default value. Generally, this is 12 points. + Color of the font in BGRA – A = 255 is fully transparent. Use the macro CV _ RGB for simplicity. + The operation flags + The operation flags + Spacing between characters. Can be negative or positive. + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + Managed wrapper of all OpenCV functions + + + + + Reconstructs the original vectors from the projection coefficients + + The input data; in the same format as result in cvProjectPCA. + The mean (average) vector. If it is a single-row vector, it means that the output vectors are stored as rows of result; otherwise, it should be a single-column vector, then the vectors are stored as columns of result. + The eigenvectors (principal components); one vector per row. + The output matrix of reconstructed vectors. + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Calculates up-right bounding rectangle of point set. + + Either a 2D point set, represented as a sequence (CvSeq, CvContour) or vector (CvMat) of points, + or 8-bit single-channel mask image (CvMat, IplImage), in which non-zero pixels are considered. + + + + + Calculates up-right bounding rectangle of point set. + + Either a 2D point set, represented as a sequence (CvSeq, CvContour) or vector (CvMat) of points, + or 8-bit single-channel mask image (CvMat, IplImage), in which non-zero pixels are considered. + The update flag + + + + + Calculates up-right bounding rectangle of point set. + + An IEnumerable<CvPoint> object (ex. CvPoint[], List<CvPoint>, ....) + + + + + Finds box vertices + + Box + Array of vertices + + + + Modification of a previous sparse optical flow algorithm to calculate affine flow + + + + + + + + + + + + + + + + + + + Calculates the histogram of one single-channel image. + The elements of a tuple that is used to increment a histogram bin are taken at the same location from the corresponding input images. + + A Source image (though, you may pass CvMat** as well). + Reference to the histogram. + + + + Calculates the histogram of one single-channel image. + The elements of a tuple that is used to increment a histogram bin are taken at the same location from the corresponding input images. + + A Source image (though, you may pass CvMat** as well). + Reference to the histogram. + Accumulation flag. If it is set, the histogram is not cleared in the beginning. This feature allows user to compute a single histogram from several images, or to update the histogram online. + + + + Calculates the histogram of one single-channel image. + The elements of a tuple that is used to increment a histogram bin are taken at the same location from the corresponding input images. + + A Source image (though, you may pass CvMat** as well). + Reference to the histogram. + Accumulation flag. If it is set, the histogram is not cleared in the beginning. This feature allows user to compute a single histogram from several images, or to update the histogram online. + The operation mask, determines what pixels of the source images are counted. + + + + Calculates the histogram of single-channel images. + The elements of a tuple that is used to increment a histogram bin are taken at the same location from the corresponding input images. + + Source images (though, you may pass CvMat** as well), all are of the same size and type. + Reference to the histogram. + + + + Calculates the histogram of single-channel images. + The elements of a tuple that is used to increment a histogram bin are taken at the same location from the corresponding input images. + + Source images (though, you may pass CvMat** as well), all are of the same size and type. + Reference to the histogram. + Accumulation flag. If it is set, the histogram is not cleared in the beginning. This feature allows user to compute a single histogram from several images, or to update the histogram online. + + + + Calculates the histogram of single-channel images. + The elements of a tuple that is used to increment a histogram bin are taken at the same location from the corresponding input images. + + Source images (though, you may pass CvMat** as well), all are of the same size and type. + Reference to the histogram. + Accumulation flag. If it is set, the histogram is not cleared in the beginning. This feature allows user to compute a single histogram from several images, or to update the histogram online. + The operation mask, determines what pixels of the source images are counted. + + + + Calculates back projection + + Source images (though you may pass CvMat** as well), all are of the same size and type + Destination back projection image of the same type as the source images. + Histogram. + + + + + Calculates back projection + + Source images (though you may pass CvMat** as well), all are of the same size and type + Destination back projection image of the same type as the source images. + Histogram. + + + + + Locates a template within image by histogram comparison + + Source images (though you may pass CvMat** as well), all are of the same size and type + Destination image. + Size of patch slid though the source images. + Histogram. + Compasion method, passed to cvCompareHist (see description of that function). + + + + + Locates a template within image by histogram comparison + + Source images (though you may pass CvMat** as well), all are of the same size and type + Destination image. + Size of patch slid though the source images. + Histogram. + Compasion method, passed to cvCompareHist (see description of that function). + Normalization factor for histograms, will affect normalization scale of destination image, pass 1. if unsure. + + + + + Locates a template within image by histogram comparison + + Source images (though you may pass CvMat** as well), all are of the same size and type + Destination image. + Size of patch slid though the source images. + Histogram. + Compasion method, passed to cvCompareHist (see description of that function). + + + + + Locates a template within image by histogram comparison + + Source images (though you may pass CvMat** as well), all are of the same size and type + Destination image. + Size of patch slid though the source images. + Histogram. + Compasion method, passed to cvCompareHist (see description of that function). + Normalization factor for histograms, will affect normalization scale of destination image, pass 1. if unsure. + + + + + Calculates bayesian probabilistic histograms + + + + + + + Calculates covariation matrix of the set of vectors + + The input vectors. They all must have the same type and the same size. The vectors do not have to be 1D, they can be 2D (e.g. images) etc. + The output covariation matrix that should be floating-point and square. + The input or output (depending on the flags) array - the mean (average) vector of the input vectors. + The operation flags + + + + Calculates the covariance matrix for a group of input objects. + + Number of source objects. + Pointer to the read callback function. + Input/output flags. + Input/output buffer size. + Pointer to the input/output buffer. + Pointer to the structure that contains all necessary data for the callback functions. + Averaged object. + Covariance matrix. An output parameter; must be allocated before the call. + + + + Calculates the covariance matrix for a group of input objects. (ioFlags = CV_EIGOBJ_NO_CALLBACK) + + Array of IplImage input objects. + Averaged object. + Covariance matrix. An output parameter; must be allocated before the call. + + + + Calculates the decomposition coefficient of an input object. + + Input object. + Eigen object. + Averaged object. + decomposition coefficient + + + + Calculates the orthonormal eigen basis and the averaged object for group a of input objects. (ioFlags = CV_EIGOBJ_NO_CALLBACK) + + Pointer to the array of IplImage input objects. + Pointer to the array of eigen objects. + Input/output buffer size in bytes. The size is zero if unknown. + Criteria that determine when to stop the calculation of eigen objects. + Averaged object. + Pointer to the eigenvalues array in the descending order; may be null. + + + + Calculates the orthonormal eigen basis and the averaged object for group a of input objects. (ioFlags = CV_EIGOBJ_OUTPUT_CALLBACK) + + nObjects – Number of source objects. + Pointer to the array of IplImage input objects. + Pointer to the write callback function. + Input/output buffer size in bytes. The size is zero if unknown. + Pointer to the structure that contains all of the necessary data for the callback functions. + Criteria that determine when to stop the calculation of eigen objects. + Averaged object. + Pointer to the eigenvalues array in the descending order; may be null. + + + + Calculates the orthonormal eigen basis and the averaged object for group a of input objects. (ioFlags = CV_EIGOBJ_INPUT_CALLBACK) + + nObjects – Number of source objects. + Pointer to the read callback function. + Pointer to the array of eigen objects. + Input/output buffer size in bytes. The size is zero if unknown. + Pointer to the structure that contains all of the necessary data for the callback functions. + Criteria that determine when to stop the calculation of eigen objects. + Averaged object. + Pointer to the eigenvalues array in the descending order; may be null. + + + + Calculates the orthonormal eigen basis and the averaged object for group a of input objects. + + nObjects – Number of source objects. + Pointer to the read callback function. + Pointer to the write callback function. + Input/output flags. + Input/output buffer size in bytes. The size is zero if unknown. + Pointer to the structure that contains all of the necessary data for the callback functions. + Criteria that determine when to stop the calculation of eigen objects. + Averaged object. + Pointer to the eigenvalues array in the descending order; may be null. + + + + Computes "minimal work" distance between two weighted point configurations. + + First signature, size1×dims+1 floating-point matrix. Each row stores the point weight followed by the point coordinates. The matrix is allowed to have a single column (weights only) if the user-defined cost matrix is used. + Second signature of the same format as signature1, though the number of rows may be different. The total weights may be different, in this case an extra "dummy" point is added to either signature1 or signature2. + Metrics used + + + + + Computes "minimal work" distance between two weighted point configurations. + + First signature, size1×dims+1 floating-point matrix. Each row stores the point weight followed by the point coordinates. The matrix is allowed to have a single column (weights only) if the user-defined cost matrix is used. + Second signature of the same format as signature1, though the number of rows may be different. The total weights may be different, in this case an extra "dummy" point is added to either signature1 or signature2. + Metrics used + The user-defined distance function. It takes coordinates of two points and returns the distance between the points. + + + + + Computes "minimal work" distance between two weighted point configurations. + + First signature, size1×dims+1 floating-point matrix. Each row stores the point weight followed by the point coordinates. The matrix is allowed to have a single column (weights only) if the user-defined cost matrix is used. + Second signature of the same format as signature1, though the number of rows may be different. The total weights may be different, in this case an extra "dummy" point is added to either signature1 or signature2. + Metrics used + The user-defined distance function. It takes coordinates of two points and returns the distance between the points. + The user-defined size1×size2 cost matrix. At least one of cost_matrix and distance_func must be NULL. Also, if a cost matrix is used, lower boundary (see below) can not be calculated, because it needs a metric function. + + + + + Computes "minimal work" distance between two weighted point configurations. + + First signature, size1×dims+1 floating-point matrix. Each row stores the point weight followed by the point coordinates. The matrix is allowed to have a single column (weights only) if the user-defined cost matrix is used. + Second signature of the same format as signature1, though the number of rows may be different. The total weights may be different, in this case an extra "dummy" point is added to either signature1 or signature2. + Metrics used + The user-defined distance function. It takes coordinates of two points and returns the distance between the points. + The user-defined size1×size2 cost matrix. At least one of cost_matrix and distance_func must be NULL. Also, if a cost matrix is used, lower boundary (see below) can not be calculated, because it needs a metric function. + The resultant size1×size2 flow matrix: flowij is a flow from i-th point of signature1 to j-th point of signature2 + + + + + Computes "minimal work" distance between two weighted point configurations. + + First signature, size1×dims+1 floating-point matrix. Each row stores the point weight followed by the point coordinates. The matrix is allowed to have a single column (weights only) if the user-defined cost matrix is used. + Second signature of the same format as signature1, though the number of rows may be different. The total weights may be different, in this case an extra "dummy" point is added to either signature1 or signature2. + Metrics used + The user-defined distance function. It takes coordinates of two points and returns the distance between the points. + The user-defined size1×size2 cost matrix. At least one of cost_matrix and distance_func must be NULL. Also, if a cost matrix is used, lower boundary (see below) can not be calculated, because it needs a metric function. + The resultant size1×size2 flow matrix: flowij is a flow from i-th point of signature1 to j-th point of signature2 + Optional input/output parameter. + + + + + Calculates global motion orientation of some selected region + + Motion gradient orientation image; calculated by the function cvCalcMotionGradient. + Mask image. It may be a conjunction of valid gradient mask, obtained with cvCalcMotionGradient and mask of the region, whose direction needs to be calculated. + Motion history image + Current time in milliseconds or other units, it is better to store time passed to cvUpdateMotionHistory before and reuse it here, because running cvUpdateMotionHistory and cvCalcMotionGradient on large images may take some time. + Maximal duration of motion track in milliseconds, the same as in cvUpdateMotionHistory. + + + + Calculates homography matrix for oblong planar object (e.g. arm) + + The main object axis direction (vector (dx,dy,dz)). + Object center ((cx,cy,cz)). + Intrinsic camera parameters (3x3 matrix). + Output homography matrix (3x3). + + + + + Calculates the histogram of one single-channel image. + The elements of a tuple that is used to increment a histogram bin are taken at the same location from the corresponding input images. + + Source image. + Reference to the histogram. + + + + Calculates the histogram of one single-channel image. + The elements of a tuple that is used to increment a histogram bin are taken at the same location from the corresponding input images. + + Source image. + Reference to the histogram. + Accumulation flag. If it is set, the histogram is not cleared in the beginning. This feature allows user to compute a single histogram from several images, or to update the histogram online. + + + + Calculates the histogram of one single-channel image. + The elements of a tuple that is used to increment a histogram bin are taken at the same location from the corresponding input images. + + Source image. + Reference to the histogram. + Accumulation flag. If it is set, the histogram is not cleared in the beginning. This feature allows user to compute a single histogram from several images, or to update the histogram online. + The operation mask, determines what pixels of the source images are counted. + + + + Calculates the histogram of single-channel images. + The elements of a tuple that is used to increment a histogram bin are taken at the same location from the corresponding input images. + + Source images, all are of the same size and type. + Reference to the histogram. + + + + Calculates the histogram of single-channel images. + The elements of a tuple that is used to increment a histogram bin are taken at the same location from the corresponding input images. + + Source images, all are of the same size and type. + Reference to the histogram. + Accumulation flag. If it is set, the histogram is not cleared in the beginning. This feature allows user to compute a single histogram from several images, or to update the histogram online. + + + + Calculates the histogram of single-channel images. + The elements of a tuple that is used to increment a histogram bin are taken at the same location from the corresponding input images. + + Source images, all are of the same size and type. + Reference to the histogram. + Accumulation flag. If it is set, the histogram is not cleared in the beginning. This feature allows user to compute a single histogram from several images, or to update the histogram online. + The operation mask, determines what pixels of the source images are counted. + + + + Computes d(AB)/dA and d(AB)/dB + + + + + + + + + Calculates gradient orientation of motion history image + + Motion history image + Mask image; marks pixels where motion gradient data is correct. Output parameter. + Motion gradient orientation image; contains angles from 0 to ~360°. + The function finds minimum (m(x,y)) and maximum (M(x,y)) mhi values over each pixel (x,y) neihborhood and assumes the gradient is valid only if min(delta1,delta2) <= M(x,y)-m(x,y) <= max(delta1,delta2). + The function finds minimum (m(x,y)) and maximum (M(x,y)) mhi values over each pixel (x,y) neihborhood and assumes the gradient is valid only if min(delta1,delta2) <= M(x,y)-m(x,y) <= max(delta1,delta2). + + + + Calculates gradient orientation of motion history image + + Motion history image + Mask image; marks pixels where motion gradient data is correct. Output parameter. + Motion gradient orientation image; contains angles from 0 to ~360°. + The function finds minimum (m(x,y)) and maximum (M(x,y)) mhi values over each pixel (x,y) neihborhood and assumes the gradient is valid only if min(delta1,delta2) <= M(x,y)-m(x,y) <= max(delta1,delta2). + The function finds minimum (m(x,y)) and maximum (M(x,y)) mhi values over each pixel (x,y) neihborhood and assumes the gradient is valid only if min(delta1,delta2) <= M(x,y)-m(x,y) <= max(delta1,delta2). + Aperture size of derivative operators used by the function: CV_SCHARR, 1, 3, 5 or 7 (see cvSobel). + + + + Calculates optical flow for two images by block matching method + + First image, 8-bit, single-channel. + Second image, 8-bit, single-channel. + Size of basic blocks that are compared. + Block coordinate increments. + Size of the scanned neighborhood in pixels around block. + Uses previous (input) velocity field. + Horizontal component of the optical flow of floor((prev->width - block_size.width)/shiftSize.width) × floor((prev->height - block_size.height)/shiftSize.height) size, 32-bit floating-point, single-channel. + Vertical component of the optical flow of the same size velx, 32-bit floating-point, single-channel. + + + + Estimate optical flow for each pixel using the two-frame G. Farneback algorithm + + + + + + + + + + + + + + + Computes flow for every pixel of the first input image using Horn & Schunck algorithm + + First image, 8-bit, single-channel. + Second image, 8-bit, single-channel. + Uses previous (input) velocity field. + Horizontal component of the optical flow of the same size as input images, 32-bit floating-point, single-channel. + Vertical component of the optical flow of the same size as input images, 32-bit floating-point, single-channel. + Lagrangian multiplier. + Criteria of termination of velocity computing. + + + + Computes flow for every pixel of the first input image using Lucas & Kanade algorithm + + First image, 8-bit, single-channel. + Second image, 8-bit, single-channel. + Size of the averaging window used for grouping pixels. + Horizontal component of the optical flow of the same size as input images, 32-bit floating-point, single-channel. + Vertical component of the optical flow of the same size as input images, 32-bit floating-point, single-channel. + + + + Calculates optical flow for a sparse feature set using iterative Lucas-Kanade method in pyramids + + First frame, at time t. + Second frame, at time t + dt . + Buffer for the pyramid for the first frame. If the pointer is not null , the buffer must have a sufficient size to store the pyramid from level 1 to level #level ; the total size of (image_width+8)*image_height/3 bytes is sufficient. + Similar to prev_pyr, used for the second frame. + Array of points for which the flow needs to be found. + Array of 2D points containing calculated new positions of input features in the second image. + Size of the search window of each pyramid level. + Maximal pyramid level number. If 0 , pyramids are not used (single level), if 1 , two levels are used, etc. + Array. Every element of the array is set to 1 if the flow for the corresponding feature has been found, 0 otherwise. + Specifies when the iteration process of finding the flow for each point on each pyramid level should be stopped. + Miscellaneous flags + + + + Calculates optical flow for a sparse feature set using iterative Lucas-Kanade method in pyramids + + First frame, at time t. + Second frame, at time t + dt . + Buffer for the pyramid for the first frame. If the pointer is not null , the buffer must have a sufficient size to store the pyramid from level 1 to level #level ; the total size of (image_width+8)*image_height/3 bytes is sufficient. + Similar to prev_pyr, used for the second frame. + Array of points for which the flow needs to be found. + Array of 2D points containing calculated new positions of input features in the second image. + Size of the search window of each pyramid level. + Maximal pyramid level number. If 0 , pyramids are not used (single level), if 1 , two levels are used, etc. + Array. Every element of the array is set to 1 if the flow for the corresponding feature has been found, 0 otherwise. + Array of double numbers containing difference between patches around the original and moved points. Optional parameter; can be NULL . + Specifies when the iteration process of finding the flow for each point on each pyramid level should be stopped. + Miscellaneous flags + + + + Performs Principal Component Analysis of a vector set + + The input data; each vector is either a single row (CV_PCA_DATA_AS_ROW) or a single column (CV_PCA_DATA_AS_COL). + The mean (average) vector, computed inside the function or provided by user. + The output eigenvalues of covariation matrix. + The output eigenvectors of covariation matrix (i.e. principal components); one vector per row. + The operation flags + + + + + Calculates pair-wise geometrical histogram for contour + + Input contour. Currently, only integer point coordinates are allowed. + Calculated histogram; must be two-dimensional. + + + + Divides one histogram by another. + + first histogram (the divisor). + second histogram. + destination histogram. + + + + Divides one histogram by another. + + first histogram (the divisor). + second histogram. + destination histogram. + scale factor for the destination histogram. + + + + Calculates coordinates of Voronoi diagram cells. + + Delaunay subdivision, where all the points are added already. + + + + Finds intrinsic and extrinsic camera parameters using calibration pattern + + The joint matrix of object points, 3xN or Nx3, where N is the total number of points in all views. + The joint matrix of corresponding image points, 2xN or Nx2, where N is the total number of points in all views. + Vector containing numbers of points in each particular view, 1xM or Mx1, where M is the number of a scene views. + Size of the image, used only to initialize intrinsic camera matrix. + The output camera matrix (A) [fx 0 cx; 0 fy cy; 0 0 1]. If CV_CALIB_USE_INTRINSIC_GUESS and/or CV_CALIB_FIX_ASPECT_RATION are specified, some or all of fx, fy, cx, cy must be initialized. + The output 4x1 or 1x4 vector of distortion coefficients [k1, k2, p1, p2]. + + + + Finds intrinsic and extrinsic camera parameters using calibration pattern + + The joint matrix of object points, 3xN or Nx3, where N is the total number of points in all views. + The joint matrix of corresponding image points, 2xN or Nx2, where N is the total number of points in all views. + Vector containing numbers of points in each particular view, 1xM or Mx1, where M is the number of a scene views. + Size of the image, used only to initialize intrinsic camera matrix. + The output camera matrix (A) [fx 0 cx; 0 fy cy; 0 0 1]. If CV_CALIB_USE_INTRINSIC_GUESS and/or CV_CALIB_FIX_ASPECT_RATION are specified, some or all of fx, fy, cx, cy must be initialized. + The output 4x1 or 1x4 vector of distortion coefficients [k1, k2, p1, p2]. + The output 3xM or Mx3 array of rotation vectors (compact representation of rotation matrices, see cvRodrigues2). + The output 3xM or Mx3 array of translation vectors. + + + + Finds intrinsic and extrinsic camera parameters using calibration pattern + + The joint matrix of object points, 3xN or Nx3, where N is the total number of points in all views. + The joint matrix of corresponding image points, 2xN or Nx2, where N is the total number of points in all views. + Vector containing numbers of points in each particular view, 1xM or Mx1, where M is the number of a scene views. + Size of the image, used only to initialize intrinsic camera matrix. + The output camera matrix (A) [fx 0 cx; 0 fy cy; 0 0 1]. If CV_CALIB_USE_INTRINSIC_GUESS and/or CV_CALIB_FIX_ASPECT_RATION are specified, some or all of fx, fy, cx, cy must be initialized. + The output 4x1 or 1x4 vector of distortion coefficients [k1, k2, p1, p2]. + The output 3xM or Mx3 array of rotation vectors (compact representation of rotation matrices, see cvRodrigues2). + The output 3xM or Mx3 array of translation vectors. + Different flags + + + + Finds intrinsic and extrinsic camera parameters using calibration pattern + + The joint matrix of object points, 3xN or Nx3, where N is the total number of points in all views. + The joint matrix of corresponding image points, 2xN or Nx2, where N is the total number of points in all views. + Vector containing numbers of points in each particular view, 1xM or Mx1, where M is the number of a scene views. + Size of the image, used only to initialize intrinsic camera matrix. + The output camera matrix (A) [fx 0 cx; 0 fy cy; 0 0 1]. If CV_CALIB_USE_INTRINSIC_GUESS and/or CV_CALIB_FIX_ASPECT_RATION are specified, some or all of fx, fy, cx, cy must be initialized. + The output 4x1 or 1x4 vector of distortion coefficients [k1, k2, p1, p2]. + The output 3xM or Mx3 array of rotation vectors (compact representation of rotation matrices, see cvRodrigues2). + The output 3xM or Mx3 array of translation vectors. + Different flags + The function outputs the final re-projection error. + + + + Finds intrinsic and extrinsic camera parameters using calibration pattern + + The matrix of intrinsic parameters, e.g. computed by cvCalibrateCamera2 + Image size in pixels + + + + Finds intrinsic and extrinsic camera parameters using calibration pattern + + The matrix of intrinsic parameters, e.g. computed by cvCalibrateCamera2 + Image size in pixels + Aperture width in realworld units + Aperture width in realworld units + + + + Finds intrinsic and extrinsic camera parameters using calibration pattern + + The matrix of intrinsic parameters, e.g. computed by cvCalibrateCamera2 + Image size in pixels + Aperture width in realworld units + Aperture width in realworld units + Field of view angle in x direction in degrees + Field of view angle in y direction in degrees + + + + Finds intrinsic and extrinsic camera parameters using calibration pattern + + The matrix of intrinsic parameters, e.g. computed by cvCalibrateCamera2 + Image size in pixels + Aperture width in realworld units + Aperture width in realworld units + Field of view angle in x direction in degrees + Field of view angle in y direction in degrees + Focal length in realworld units + + + + Finds intrinsic and extrinsic camera parameters using calibration pattern + + The matrix of intrinsic parameters, e.g. computed by cvCalibrateCamera2 + Image size in pixels + Aperture width in realworld units + Aperture width in realworld units + Field of view angle in x direction in degrees + Field of view angle in y direction in degrees + Focal length in realworld units + The principal point in realworld units + + + + Finds intrinsic and extrinsic camera parameters using calibration pattern + + The matrix of intrinsic parameters, e.g. computed by cvCalibrateCamera2 + Image size in pixels + Aperture width in realworld units + Aperture width in realworld units + Field of view angle in x direction in degrees + Field of view angle in y direction in degrees + Focal length in realworld units + The principal point in realworld units + The pixel aspect ratio ~ fy/fx + + + + Finds object center, size, and orientation + + Back projection of object histogram (see cvCalcBackProject). + Initial search window. + Criteria applied to determine when the window search should be finished. + The function returns number of iterations made within cvMeanShift. + + + + Finds object center, size, and orientation + + Back projection of object histogram (see cvCalcBackProject). + Initial search window. + Criteria applied to determine when the window search should be finished. + Resultant structure that contains converged search window coordinates (comp->rect field) and sum of all pixels inside the window (comp->area field). + The function returns number of iterations made within cvMeanShift. + + + + Finds object center, size, and orientation + + Back projection of object histogram (see cvCalcBackProject). + Initial search window. + Criteria applied to determine when the window search should be finished. + Resultant structure that contains converged search window coordinates (comp->rect field) and sum of all pixels inside the window (comp->area field). + Circumscribed box for the object. If not NULL, contains object size and orientation. + The function returns number of iterations made within cvMeanShift. + + + + Finds the edges on the input image image and marks them in the output image edges using the Canny algorithm. + The smallest of threshold1 and threshold2 is used for edge linking, the largest - to find initial segments of strong edges. + + Input image. + Image to store the edges found by the function. + The first threshold. + The second threshold. + + + + Finds the edges on the input image image and marks them in the output image edges using the Canny algorithm. + The smallest of threshold1 and threshold2 is used for edge linking, the largest - to find initial segments of strong edges. + + Input image. + Image to store the edges found by the function. + The first threshold. + The second threshold. + Aperture parameter for Sobel operator. + + + + Calculates magnitude and/or angle of 2d vectors + + The array of x-coordinates + The array of y-coordinates + The destination array of magnitudes, may be set to null if it is not needed + + + + Calculates magnitude and/or angle of 2d vectors + + The array of x-coordinates + The array of y-coordinates + The destination array of magnitudes, may be set to null if it is not needed + The destination array of angles, may be set to null if it is not needed. The angles are measured in radians (0..2π) or in degrees (0..360°). + + + + Calculates magnitude and/or angle of 2d vectors + + The array of x-coordinates + The array of y-coordinates + The destination array of magnitudes, may be set to null if it is not needed + The destination array of angles, may be set to null if it is not needed. The angles are measured in radians (0..2π) or in degrees (0..360°). + The flag indicating whether the angles are measured in radians, which is default mode, or in degrees. + + + + Calculates cubic root + + The input floating-point value + + + + + Returns the minimum integer value that is not smaller than the argument. + + The input floating-point value + + + + + Checks every element of input array for invalid values + + returns nonzero if the check succeeded, i.e. all elements are valid and within the range, and zero otherwise. + + + + Checks every element of input array for invalid values + + The array to check. + The operation flags + returns nonzero if the check succeeded, i.e. all elements are valid and within the range, and zero otherwise. + + + + Checks every element of input array for invalid values + + The array to check. + The operation flags + The inclusive lower boundary of valid values range. It is used only if CV_CHECK_RANGE is set. + The exclusive upper boundary of valid values range. It is used only if CV_CHECK_RANGE is set. + returns nonzero if the check succeeded, i.e. all elements are valid and within the range, and zero otherwise. + + + + Checks every element of input array for invalid values + + The array to check. + returns nonzero if the check succeeded, i.e. all elements are valid and within the range, and zero otherwise. + + + + Checks every element of input array for invalid values + + The array to check. + The operation flags + returns nonzero if the check succeeded, i.e. all elements are valid and within the range, and zero otherwise. + + + + Checks every element of input array for invalid values + + The array to check. + The operation flags + The inclusive lower boundary of valid values range. It is used only if CV_CHECK_RANGE is set. + The exclusive upper boundary of valid values range. It is used only if CV_CHECK_RANGE is set. + returns nonzero if the check succeeded, i.e. all elements are valid and within the range, and zero otherwise. + + + + Performs a fast check if a chessboard is in the input image. + This is a workaround to a problem of cvFindChessboardCorners being slow on images with no chessboard + + input image + chessboard size + Returns 1 if a chessboard can be in this image and findChessboardCorners should be called, + 0 if there is no chessboard, -1 in case of error + + + + Tests contour convexity. + + Tested contour (sequence or array of points) + + + + + Check termination criteria and transform it so that type=CriteriaType.Iteration | CriteriaType.Epsilon, + and both max_iter and epsilon are valid + + Termination criteria + Default epsilon + Default maximum number of iteration + + + + + Draws a circle + + Image where the circle is drawn. + X-coordinate of the center of the circle. + Y-coordinate of the center of the circle. + Radius of the circle. + Circle color. + + + + Draws a circle + + Image where the circle is drawn. + X-coordinate of the center of the circle. + Y-coordinate of the center of the circle. + Radius of the circle. + Circle color. + Thickness of the circle outline if positive, otherwise indicates that a filled circle has to be drawn. + + + + Draws a circle + + Image where the circle is drawn. + X-coordinate of the center of the circle. + Y-coordinate of the center of the circle. + Radius of the circle. + Circle color. + Thickness of the circle outline if positive, otherwise indicates that a filled circle has to be drawn. + Type of the circle boundary. + + + + Draws a circle + + Image where the circle is drawn. + X-coordinate of the center of the circle. + Y-coordinate of the center of the circle. + Radius of the circle. + Circle color. + Thickness of the circle outline if positive, otherwise indicates that a filled circle has to be drawn. + Type of the circle boundary. + Number of fractional bits in the center coordinates and radius value. + + + + Draws a circle + + Image where the circle is drawn. + Center of the circle. + Radius of the circle. + Circle color. + + + + Draws a circle + + Image where the circle is drawn. + Center of the circle. + Radius of the circle. + Circle color. + Thickness of the circle outline if positive, otherwise indicates that a filled circle has to be drawn. + + + + Draws a circle + + Image where the circle is drawn. + Center of the circle. + Radius of the circle. + Circle color. + Thickness of the circle outline if positive, otherwise indicates that a filled circle has to be drawn. + Type of the circle boundary. + + + + Draws a circle + + Image where the circle is drawn. + Center of the circle. + Radius of the circle. + Circle color. + Thickness of the circle outline if positive, otherwise indicates that a filled circle has to be drawn. + Type of the circle boundary. + Number of fractional bits in the center coordinates and radius value. + + + + Draws a circle + + Image where the circle is drawn. + X-coordinate of the center of the circle. + Y-coordinate of the center of the circle. + Radius of the circle. + Circle color. + + + + Draws a circle + + Image where the circle is drawn. + X-coordinate of the center of the circle. + Y-coordinate of the center of the circle. + Radius of the circle. + Circle color. + Thickness of the circle outline if positive, otherwise indicates that a filled circle has to be drawn. + + + + Draws a circle + + Image where the circle is drawn. + X-coordinate of the center of the circle. + Y-coordinate of the center of the circle. + Radius of the circle. + Circle color. + Thickness of the circle outline if positive, otherwise indicates that a filled circle has to be drawn. + Type of the circle boundary. + + + + Draws a circle + + Image where the circle is drawn. + X-coordinate of the center of the circle. + Y-coordinate of the center of the circle. + Radius of the circle. + Circle color. + Thickness of the circle outline if positive, otherwise indicates that a filled circle has to be drawn. + Type of the circle boundary. + Number of fractional bits in the center coordinates and radius value. + + + + Draws a circle + + Image where the circle is drawn. + Center of the circle. + Radius of the circle. + Circle color. + + + + Draws a circle + + Image where the circle is drawn. + Center of the circle. + Radius of the circle. + Circle color. + Thickness of the circle outline if positive, otherwise indicates that a filled circle has to be drawn. + + + + Draws a circle + + Image where the circle is drawn. + Center of the circle. + Radius of the circle. + Circle color. + Thickness of the circle outline if positive, otherwise indicates that a filled circle has to be drawn. + Type of the circle boundary. + + + + Draws a circle + + Image where the circle is drawn. + Center of the circle. + Radius of the circle. + Circle color. + Thickness of the circle outline if positive, otherwise indicates that a filled circle has to be drawn. + Type of the circle boundary. + Number of fractional bits in the center coordinates and radius value. + + + + Returns index of graph vertex + + Graph. + The function cvClearGraph removes all vertices and edges from the graph. The function has O(1) time complexity. + + + + Sets all histogram bins to 0 in case of dense histogram and removes all histogram bins in case of sparse array. + + Histogram. + + + + Clears memory storage + + Memory storage. + + + + Clears the particular array element + + Input array. + Array of the element indices + + + + Clears sequence + + Sequence. + + + + Clears set + + Cleared set. + The function cvClearSet removes all elements from set. It has O(1) time complexity. + + + + Removes all virtual points + + Delaunay subdivision. + + + + Clips the line against the image rectangle + + Size of the image. + First ending point of the line segment. It is modified by the function. + Second ending point of the line segment. It is modified by the function. + The function cvClipLine calculates a part of the line segment which is entirely in the image. It returns 0 if the line segment is completely outside the image and 1 otherwise. + + + + Makes a clone of the object + + The object to clone. + + + + + Makes a clone of the object + + The object to clone. + + + + + Clone graph + + Graph. + Container for the copy. + The function cvCloneGraph creates full copy of the graph. If the graph vertices or edges have pointers to some external data, it still be shared between the copies. The vertex and edge indices in the new graph may be different from the original, because the function defragments the vertex and edge sets. + + + + Makes a full copy of image + + Original image. + + + + + Creates matrix copy + + Input matrix + a copy of input array + + + + Creates full copy of multi-dimensional array + + Input array + a copy of input array + + + + Creates a copy of sequence + + Sequence. + + + + + Creates a copy of sequence + + Sequence. + The destination storage to keep the new sequence header and the copied data if any. If it is null, the function uses the storage containing the input sequence. + + + + + Creates a copy of sequence + + Element type + Sequence. + + + + + Creates a copy of sequence + + Element type + Sequence. + The destination storage to keep the new sequence header and the copied data if any. If it is null, the function uses the storage containing the input sequence. + + + + + Creates full copy of sparse array + + Input array + a copy of input array + + + + Performs per-element comparison of two arrays + + The first source array. + The second source array. Both source array must have a single channel. + The destination array, must have 8u or 8s type. + The flag specifying the relation between the elements to be checked + + + + Performs per-element comparison of array and scalar + + The source array, must have a single channel. + The scalar value to compare each array element with. + The destination array, must have 8u or 8s type. + The flag specifying the relation between the elements to be checked + + + + Initializes sample set for ConDensation algorithm + + Structure to be initialized. + Vector of the lower boundary for each dimension. + Vector of the upper boundary for each dimension. + + + + Estimates subsequent model state + + Structure to be updated. + + + + Completes the symmetric matrix from the lower part + + + + + + Completes the symmetric matrix from the lower (LtoR=0) or from the upper (LtoR!=0) part + + + + + + + Compares two dense histograms. + + The first dense histogram. + The second dense histogram. + Comparison method. + + + + + Computes r3 = rodrigues(rodrigues(r2)*rodrigues(r1)), + t3 = rodrigues(r2)*t1 + t2 and the respective derivatives + + + + + + + + + + + + + + + + + + + For points in one image of stereo pair computes the corresponding epilines in the other image + + The input points. 2xN, Nx2, 3xN or Nx3 array (where N number of points). Multi-channel 1xN or Nx1 array is also acceptable. + Index of the image (1 or 2) that contains the points + Fundamental matrix + Computed epilines, 3xN or Nx3 array + + + + Calculates area of the whole contour or contour section. + + Contour (sequence or array of vertices). + + + + + Calculates area of the whole contour or contour section. + + Contour (sequence or array of vertices). + Starting and ending points of the contour section of interest, by default area of the whole contour is calculated. + + + + + Restores contour from tree. + + Contour tree. + Container for the reconstructed contour. + Criteria, where to stop reconstruction. + + + + + Alias for Moments with CvSeq contours + + Contours + Moments + + + + Alias for cvArcLength(curve,Whole_Seq,1) + + Contours + + + + + Converts one image to another and flips the result vertically if required. + + Source image. + Destination image. Must be single-channel or 3-channel 8-bit image. + The operation flags + + + + Converts mapx & mapy from floating-point to integer formats for cvRemap + + + + + + + + + Convert points to/from homogeneous coordinates + + The input point array, 2xN, Nx2, 3xN, Nx3, 4xN or Nx4 (where N is the number of points). Multi-channel 1xN or Nx1 array is also acceptable. + The output point array, must contain the same number of points as the input; The dimensionality must be the same, 1 less or 1 more than the input, and also within 2..4. + + + + Convert points to/from homogeneous coordinates + + The input point array, 2xN, Nx2, 3xN, Nx3, 4xN or Nx4 (where N is the number of points). Multi-channel 1xN or Nx1 array is also acceptable. + The output point array, must contain the same number of points as the input; The dimensionality must be the same, 1 less or 1 more than the input, and also within 2..4. + + + + Converts one array to another with optional linear transformation + + Source array. + Destination array. + + + + Converts one array to another with optional linear transformation + + Source array. + Destination array. + Scale factor. + + + + Converts one array to another with optional linear transformation + + Source array. + Destination array. + Scale factor. + Value added to the scaled source array elements. + + + + Converts one array to another with optional linear transformation + + Source array. + Destination array. + + + + Converts one array to another with optional linear transformation + + Source array. + Destination array. + Scale factor. + + + + Converts one array to another with optional linear transformation + + Source array. + Destination array. + Scale factor. + Value added to the scaled source array elements. + + + + Converts one array to another with optional linear transformation + + Source array. + Destination array. + + + + Converts one array to another with optional linear transformation + + Source array. + Destination array. + Scale factor. + + + + Converts one array to another with optional linear transformation + + Source array. + Destination array. + Scale factor. + Value added to the scaled source array elements. + + + + Converts one array to another with optional linear transformation + + Source array. + Destination array. + + + + Converts input array elements to 8-bit unsigned integer another with optional linear transformation + + Source array. + Destination array (should have 8u depth). + + + + Converts input array elements to 8-bit unsigned integer another with optional linear transformation + + Source array. + Destination array (should have 8u depth). + ScaleAbs factor. + + + + Converts input array elements to 8-bit unsigned integer another with optional linear transformation + + Source array. + Destination array (should have 8u depth). + ScaleAbs factor. + Value added to the scaled source array elements. + + + + Converts input array elements to 8-bit unsigned integer another with optional linear transformation + + Source array. + Destination array (should have 8u depth). + + + + Converts input array elements to 8-bit unsigned integer another with optional linear transformation + + Source array. + Destination array (should have 8u depth). + ScaleAbs factor. + + + + Converts input array elements to 8-bit unsigned integer another with optional linear transformation + + Source array. + Destination array (should have 8u depth). + ScaleAbs factor. + Value added to the scaled source array elements. + + + + Finds convex hull of point set + + Array of 2D points with 32-bit integer or floating-point coordinates. + Vector of 0-based point indices of the hull points in the original array. + Desired orientation of convex hull: CV_CLOCKWISE or CV_COUNTER_CLOCKWISE. + + + + Finds convex hull of point set + + Array of 2D points with 32-bit integer coordinates. + Vector of 0-based point indices of the hull points in the original array. + Desired orientation of convex hull: CV_CLOCKWISE or CV_COUNTER_CLOCKWISE. + + + + Finds convex hull of point set + + Array of 2D points with 32-bit floating-point coordinates. + Vector of 0-based point indices of the hull points in the original array. + Desired orientation of convex hull: CV_CLOCKWISE or CV_COUNTER_CLOCKWISE. + + + + Finds convex hull of point set + + Array of 2D points with 32-bit integer or floating-point coordinates. + The output convex hull. It is either a vector of points that form the hull. + Desired orientation of convex hull: CV_CLOCKWISE or CV_COUNTER_CLOCKWISE. + + + + Finds convex hull of point set + + Array of 2D points with 32-bit integer or floating-point coordinates. + The output convex hull. It is either a vector of points that form the hull. + Desired orientation of convex hull: CV_CLOCKWISE or CV_COUNTER_CLOCKWISE. + + + + Finds convex hull of point set + + Array of 2D points with 32-bit integer coordinates. + The output convex hull. It is either a vector of points that form the hull. + Desired orientation of convex hull: CV_CLOCKWISE or CV_COUNTER_CLOCKWISE. + + + + Finds convex hull of point set + + Array of 2D points with 32-bit floating-point coordinates. + The output convex hull. It is either a vector of points that form the hull. + Desired orientation of convex hull: CV_CLOCKWISE or CV_COUNTER_CLOCKWISE. + + + + Finds convexity defects of contour + + Input contour. + Convex hull obtained using cvConvexHull2 that should contain pointers or indices to the contour points, not the hull points themselves, i.e. return_points parameter in cvConvexHull2 should be 0. + + + + Finds convexity defects of contour + + Input contour. + Convex hull obtained using cvConvexHull2 that should contain pointers or indices to the contour points, not the hull points themselves, i.e. return_points parameter in cvConvexHull2 should be 0. + Container for output sequence of convexity defects. If it is null, contour or hull (in that order) storage is used. + + + + Finds convexity defects of contour + + Input contour. + Convex hull obtained using cvConvexHull2 that should contain indices to the contour points + + + + Copies one array to another + + The source array. + The destination array. + + + + Copies one array to another + + The source array. + The destination array. + Operation mask, 8-bit single channel array; specifies elements of destination array to be changed. + + + + The function cvCopyHist makes a copy of the histogram. + If the second histogram pointer dst is null, a new histogram of the same size as src is created. + Otherwise, both histograms must have equal types and sizes. + Then the function copies the source histogram bins values to destination histogram and sets the same bin values ranges as in src. + + Source histogram. + Reference to destination histogram. + + + + Copies image and makes border around it. + + The source image. + The destination image. + Coordinates of the top-left corner (or bottom-left in case of images with bottom-left origin) of the destination image rectangle where the source image (or its ROI) is copied. Size of the rectanlge matches the source image size/ROI size. + Type of the border to create around the copied source image rectangle. + + + + Copies image and makes border around it. + + The source image. + The destination image. + Coordinates of the top-left corner (or bottom-left in case of images with bottom-left origin) of the destination image rectangle where the source image (or its ROI) is copied. Size of the rectanlge matches the source image size/ROI size. + Type of the border to create around the copied source image rectangle. + Value of the border pixels if bordertype=IPL_BORDER_CONSTANT. + + + + Calculates eigenvalues and eigenvectors of image blocks for corner detection + + Input image. + Image to store the results. It must be 6 times wider than the input image. + Neighborhood size. + + + + Calculates eigenvalues and eigenvectors of image blocks for corner detection + + Input image. + Image to store the results. It must be 6 times wider than the input image. + Neighborhood size. + Aperture parameter for Sobel operator + + + + Runs the Harris edge detector on image. + Similarly to cvCornerMinEigenVal and cvCornerEigenValsAndVecs, + for each pixel it calculates 2x2 gradient covariation matrix M over block_size×block_size neighborhood. + + Input image. + Image to store the Harris detector responces. Should have the same size as image. + Neighborhood size. + + + + Runs the Harris edge detector on image. + Similarly to cvCornerMinEigenVal and cvCornerEigenValsAndVecs, + for each pixel it calculates 2x2 gradient covariation matrix M over block_size×block_size neighborhood. + + Input image. + Image to store the Harris detector responces. Should have the same size as image. + Neighborhood size. + Aperture parameter for Sobel operator (see cvSobel). format. In the case of floating-point input format this parameter is the number of the fixed float filter used for differencing. + + + + Runs the Harris edge detector on image. + Similarly to cvCornerMinEigenVal and cvCornerEigenValsAndVecs, + for each pixel it calculates 2x2 gradient covariation matrix M over block_size×block_size neighborhood. + + Input image. + Image to store the Harris detector responces. Should have the same size as image. + Neighborhood size. + Aperture parameter for Sobel operator (see cvSobel). format. In the case of floating-point input format this parameter is the number of the fixed float filter used for differencing. + Harris detector free parameter. + + + + Calculates minimal eigenvalue of gradient matrices for corner detection + + Input image. + Image to store the minimal eigen values. Should have the same size as image + Neighborhood size. + + + + Calculates minimal eigenvalue of gradient matrices for corner detection + + Input image. + Image to store the minimal eigen values. Should have the same size as image + Neighborhood size. + Aperture parameter for Sobel operator (see cvSobel). format. In the case of floating-point input format this parameter is the number of the fixed float filter used for differencing. + + + + The Optimal Triangulation Method + + 3x3 fundamental matrix + 2xN matrix containing the first set of points + 2xN matrix containing the second set of points + the optimized points1_. if this is null, the corrected points are placed back in points1_ + the optimized points2_. if this is null, the corrected points are placed back in points2_ + + + + Counts non-zero array elements + + The array, must be single-channel array or multi-channel image with COI set. + the number of non-zero elements in arr + + + + + + + + + + Create a button on the control panel + + + + + Create a button on the control panel + + Name of the button ( if null, the name will be “button <number of boutton>”) + + + + Create a button on the control panel + + Name of the button ( if null, the name will be “button <number of boutton>”) + Pointer to the function to be called every time the button changed its state. + + + + Create a button on the control panel + + Name of the button ( if null, the name will be “button <number of boutton>”) + Pointer to the function to be called every time the button changed its state. + object passed to the callback function. + + + + Create a button on the control panel + + Name of the button ( if null, the name will be “button <number of boutton>”) + Pointer to the function to be called every time the button changed its state. + object passed to the callback function. + button type + + + + Create a button on the control panel + + Name of the button ( if null, the name will be “button <number of boutton>”) + Pointer to the function to be called every time the button changed its state. + object passed to the callback function. + button type + Default state of the button. Use for checkbox and radiobox, its value could be 0 or 1. + + + + Allocates and initialized the CvCapture structure for reading a video stream from the camera. + Currently two camera interfaces can be used on Windows: Video for Windows (VFW) and Matrox Imaging Library (MIL); and two on Linux: V4L and FireWire (IEEE1394). + + Index of the camera to be used. If there is only one camera or it does not matter what camera to use -1 may be passed. + + + + + Allocates and initialized the CvCapture structure for reading a video stream from the camera. + Currently two camera interfaces can be used on Windows: Video for Windows (VFW) and Matrox Imaging Library (MIL); and two on Linux: V4L and FireWire (IEEE1394). + + Device type + + + + + Creates child memory storage + + Parent memory storage. + + + + + Allocates ConDensation filter structure + + Dimension of the state vector. + Dimension of the measurement vector. + Number of samples. + + + + Creates hierarchical representation of contour + + Input contour. + Container for output tree. + Approximation accuracy. + + + + + Allocates array data. + + Array header. + + + + Constructs a tree of feature vectors + + n x d matrix of n d-dimensional feature vectors (CV_32FC1 or CV_64FC1). + + + + + Allocates and initialized the CvCapture structure for reading the video stream from the specified file. + After the allocated structure is not used any more it should be released by cvReleaseCapture function. + + Name of the video file. + + + + + Creates a histogram of the specified size and returns the pointer to the created histogram. + + Number of histogram dimensions. + Histogram representation format. + + + + + Creates a histogram of the specified size and returns the pointer to the created histogram. + + Number of histogram dimensions. + Histogram representation format. + Array of ranges for histogram bins. Its meaning depends on the uniform parameter value. The ranges are used for when histogram is calculated or backprojected to determine, which histogram bin corresponds to which value/tuple of values from the input image[s]. + + + + + Creates a histogram of the specified size and returns the pointer to the created histogram. + + Number of histogram dimensions. + Histogram representation format. + Array of ranges for histogram bins. Its meaning depends on the uniform parameter value. The ranges are used for when histogram is calculated or backprojected to determine, which histogram bin corresponds to which value/tuple of values from the input image[s]. + Uniformity flag. + + + + + Creates empty graph + + Type of the created graph. Usually, it is either CV_SEQ_KIND_GRAPH for generic unoriented graphs and CV_SEQ_KIND_GRAPH | CV_GRAPH_FLAG_ORIENTED for generic oriented graphs. + Graph vertex size; the custom vertex structure must start with CvGraphVtx (use CV_GRAPH_VERTEX_FIELDS()) + Graph edge size; the custom edge structure must start with CvGraphEdge (use CV_GRAPH_EDGE_FIELDS()) + The graph container. + The function cvCreateGraph creates an empty graph and returns it. + + + + Creates empty graph + + Type of the created graph. Usually, it is either CV_SEQ_KIND_GRAPH for generic unoriented graphs and CV_SEQ_KIND_GRAPH | CV_GRAPH_FLAG_ORIENTED for generic oriented graphs. + Graph header size; may not be less than sizeof(CvGraph). + Graph vertex size; the custom vertex structure must start with CvGraphVtx (use CV_GRAPH_VERTEX_FIELDS()) + Graph edge size; the custom edge structure must start with CvGraphEdge (use CV_GRAPH_EDGE_FIELDS()) + The graph container. + The function cvCreateGraph creates an empty graph and returns it. + + + + Creates structure for depth-first graph traversal + + Graph. + + + + Creates structure for depth-first graph traversal + + Graph. + Initial vertex to start from. If NULL, the traversal starts from the first vertex (a vertex with the minimal index in the sequence of vertices). + + + + Creates structure for depth-first graph traversal + + Graph. + Initial vertex to start from. If NULL, the traversal starts from the first vertex (a vertex with the minimal index in the sequence of vertices). + Event mask indicating which events are interesting to the user (where cvNextGraphItem function returns control to the user) It can be CV_GRAPH_ALL_ITEMS (all events are interesting) or combination of the following flags: +
* CV_GRAPH_VERTEX - stop at the graph vertices visited for the first time +
* CV_GRAPH_TREE_EDGE - stop at tree edges (tree edge is the edge connecting the last visited vertex and the vertex to be visited next) +
* CV_GRAPH_BACK_EDGE - stop at back edges (back edge is an edge connecting the last visited vertex with some of its ancestors in the search tree) +
* CV_GRAPH_FORWARD_EDGE - stop at forward edges (forward edge is an edge conecting the last visited vertex with some of its descendants in the search tree). The forward edges are only possible during oriented graph traversal) +
* CV_GRAPH_CROSS_EDGE - stop at cross edges (cross edge is an edge connecting different search trees or branches of the same tree. The cross edges are only possible during oriented graphs traversal) +
* CV_GRAPH_ANY_EDGE - stop and any edge (tree, back, forward and cross edges) +
* CV_GRAPH_NEW_TREE - stop in the beginning of every new search tree. When the traversal procedure visits all vertices and edges reachible from the initial vertex (the visited vertices together with tree edges make up a tree), it searches for some unvisited vertex in the graph and resumes the traversal process from that vertex. Before starting a new tree (including the very first tree when cvNextGraphItem is called for the first time) it generates CV_GRAPH_NEW_TREE event. +
For unoriented graphs each search tree corresponds to a connected component of the graph. +
* CV_GRAPH_BACKTRACKING - stop at every already visited vertex during backtracking - returning to already visited vertexes of the traversal tree. + + + + Creates header and allocates data + + Image width and height. + Bit depth of image elements. + Number of channels per element(pixel). + Reference to image header + + + + Allocates, initializes, and returns structure IplImage + + Image width and height. + Image depth. + Number of channels. + Reference to image header + + + + Allocates Kalman filter structure + + dimensionality of the state vector + dimensionality of the measurement vector + Kalman structure + + + + Allocates Kalman filter structure + + dimensionality of the state vector + dimensionality of the measurement vector + dimensionality of the control vector + + + + + Constructs kd-tree from set of feature descriptors + + + + + + + Construct a Locality Sensitive Hash (LSH) table, for indexing d-dimensional vectors of + given type. Vectors will be hashed L times with k-dimensional p-stable (p=2) functions. + + (not supported argument on OpenCvSharp) + + + + + + Construct a Locality Sensitive Hash (LSH) table, for indexing d-dimensional vectors of + given type. Vectors will be hashed L times with k-dimensional p-stable (p=2) functions. + + (not supported argument on OpenCvSharp) + + + + + + + Construct a Locality Sensitive Hash (LSH) table, for indexing d-dimensional vectors of + given type. Vectors will be hashed L times with k-dimensional p-stable (p=2) functions. + + (not supported argument on OpenCvSharp) + + + + + + + + Construct a Locality Sensitive Hash (LSH) table, for indexing d-dimensional vectors of + given type. Vectors will be hashed L times with k-dimensional p-stable (p=2) functions. + + (not supported argument on OpenCvSharp) + + + + + + + + + Construct a Locality Sensitive Hash (LSH) table, for indexing d-dimensional vectors of + given type. Vectors will be hashed L times with k-dimensional p-stable (p=2) functions. + + (not supported argument on OpenCvSharp) + + + + + + + + + + Construct a Locality Sensitive Hash (LSH) table, for indexing d-dimensional vectors of + given type. Vectors will be hashed L times with k-dimensional p-stable (p=2) functions. + + (not supported argument on OpenCvSharp) + + + + + + + + + + + Allocates header for the new matrix and underlying data, and returns a pointer to the created matrix. + + Number of rows in the matrix. + Number of columns in the matrix. + Type of the matrix elements. + + + + + allocates new matrix header and returns pointer to it. + The matrix data can further be allocated using cvCreateData or set explicitly to user-allocated data via cvSetData. + + Number of rows in the matrix. + Number of columns in the matrix. + Type of the matrix elements. + + + + + Allocates header for multi-dimensional dense array and the underlying data, and returns pointer to the created array. + + Number of array dimensions. It must not exceed CV_MAX_DIM (=32 by default, though it may be changed at build time) + Array of dimension sizes. + Type of array elements. + + + + + Allocates header for multi-dimensional dense array. + The array data can further be allocated using cvCreateData or set explicitly to user-allocated data via cvSetData. + + Number of array dimensions. + Array of dimension sizes. + Type of array elements. + + + + + Construct in-memory LSH table, with n bins. + + + + + + + + Construct in-memory LSH table, with n bins. + + + + + + + + + Construct in-memory LSH table, with n bins. + + + + + + + + + + Construct in-memory LSH table, with n bins. + + + + + + + + + + + Construct in-memory LSH table, with n bins. + + + + + + + + + + + + Construct in-memory LSH table, with n bins. + + + + + + + + + + + + + Creates memory storage + + + + + + Creates memory storage + + Size of the storage blocks in bytes. If it is 0, the block size is set to default value - currently it is ≈64K. + + + + + Initializes structure containing object information + + Array of points of the 3D object model. + + + + + Initializes structure containing object information + + Array of points of the 3D object model. + Number of object points. + + + + + Builds pyramid for an image + + + + + + + + + + + + + Constructs spill-tree from set of feature descriptors + + + + + + + Constructs spill-tree from set of feature descriptors + + + + + + + + Constructs spill-tree from set of feature descriptors + + + + + + + + + Constructs spill-tree from set of feature descriptors + + + + + + + + + + Creates sequence + + Flags of the created sequence. If the sequence is not passed to any function working with a specific type of sequences, the sequence value may be set to 0, otherwise the appropriate type must be selected from the list of predefined sequence types. + Size of the sequence header; must be greater or equal to sizeof(CvSeq). If a specific type or its extension is indicated, this type must fit the base type header. + Size of the sequence elements in bytes. The size must be consistent with the sequence type. For example, for a sequence of points to be created, the element type CV_SEQ_ELTYPE_POINT should be specified and the parameter elemSize must be equal to sizeof(CvPoint). + Sequence location. + + + + + Creates sequence + + Element type (ex. int, CvPoint) + Flags of the created sequence. If the sequence is not passed to any function working with a specific type of sequences, the sequence value may be set to 0, otherwise the appropriate type must be selected from the list of predefined sequence types. + Size of the sequence header; must be greater or equal to sizeof(CvSeq). If a specific type or its extension is indicated, this type must fit the base type header. + Sequence location. + + + + + + + + + + + Creates empty set + + Type of the created set. + Set header size; may not be less than sizeof(CvSet). + Set element size; may not be less than CvSetElem. + Container for the set. + + + + + Creates sparse array + + Number of array dimensions. As opposite to the dense matrix, the number of dimensions is practically unlimited (up to 2^16). + Array of dimension sizes. + Type of array elements. + + + + + Creates block matching stereo correspondence structure + + stereo correspondence structure + + + + Creates block matching stereo correspondence structure + + ID of one of the pre-defined parameter sets. Any of the parameters can be overridden after creating the structure. + stereo correspondence structure + + + + Creates block matching stereo correspondence structure + + ID of one of the pre-defined parameter sets. Any of the parameters can be overridden after creating the structure. + The number of disparities. If the parameter is 0, it is taken from the preset, otherwise the supplied value overrides the one from preset. + stereo correspondence structure + + + + Creates the state of graph cut-based stereo correspondence algorithm + + The number of disparities. The disparity search range will be state->minDisparity ≤ disparity < state->minDisparity + state->numberOfDisparities + Maximum number of iterations. On each iteration all possible (or reasonable) alpha-expansions are tried. The algorithm may terminate earlier if it could not find an alpha-expansion that decreases the overall cost function value. + stereo correspondence structure + + + + Allocates and fills the structure IplConvKernel, which can be used as a structuring element in the morphological operations. + + Number of columns in the structuring element. + Number of rows in the structuring element. + Relative horizontal offset of the anchor point. + Relative vertical offset of the anchor point. + Shape of the structuring element. + + + + + Allocates and fills the structure IplConvKernel, which can be used as a structuring element in the morphological operations. + + Number of columns in the structuring element. + Number of rows in the structuring element. + Relative horizontal offset of the anchor point. + Relative vertical offset of the anchor point. + Shape of the structuring element. + Pointer to the structuring element data, a plane array, representing row-by-row scanning of the element matrix. + Non-zero values indicate points that belong to the element. If the pointer is null, then all values are considered non-zero, + that is, the element is of a rectangular shape. This parameter is considered only if the shape is CV_SHAPE_CUSTOM . + + + + + Creates empty Delaunay triangulation. + The users must initialize the returned value by cvInitSubdivDelaunay2D. + + + + + + + + + + + Creates empty Delaunay triangulation + + Rectangle that includes all the 2d points that are to be added to subdivision. + Container for subdivision. + + + + + Creates the trackbar (a.k.a. slider or range control) with the specified name and range, + assigns the variable to be syncronized with trackbar position and specifies callback function to be called on trackbar position change. + The created trackbar is displayed on top of given window. + + Name of created trackbar. + Name of the window which will e used as a parent for created trackbar. + Ref of int value + Maximal position of the slider. Minimal position is always 0. + Reference to the function to be called every time the slider changes the position. + This function should be prototyped as void Foo(int);Can be null if callback is not required. + + + + + Creates the trackbar (a.k.a. slider or range control) with the specified name and range, + assigns the variable to be syncronized with trackbar position and specifies callback function to be called on trackbar position change. + The created trackbar is displayed on top of given window. + + Name of created trackbar. + Name of the window which will e used as a parent for created trackbar. + Initial position of the slider. + Maximal position of the slider. Minimal position is always 0. + Reference to the function to be called every time the slider changes the position. + This function should be prototyped as void Foo(int);Can be null if callback is not required. + + + + + Creates the trackbar (a.k.a. slider or range control) with the specified name and range, + assigns the variable to be syncronized with trackbar position and specifies callback function to be called on trackbar position change. + The created trackbar is displayed on top of given window. + + Name of created trackbar. + Name of the window which will e used as a parent for created trackbar. + Initial position of the slider. + Maximal position of the slider. Minimal position is always 0. + Reference to the function to be called every time the slider changes the position. + This function should be prototyped as void Foo(int);Can be null if callback is not required. + + + + + + Creates video writer structure. + + Name of the output video file. + 4-character code of codec used to compress the frames. For example, "PIM1" is MPEG-1 codec, "MJPG" is motion-jpeg codec etc. + Under Win32 it is possible to pass null in order to choose compression method and additional compression parameters from dialog. + Framerate of the created video stream. + Size of video frames. + + + + + Creates video writer structure. + + Name of the output video file. + 4-character code of codec used to compress the frames. For example, "PIM1" is MPEG-1 codec, "MJPG" is motion-jpeg codec etc. + Under Win32 it is possible to pass null in order to choose compression method and additional compression parameters from dialog. + Framerate of the created video stream. + Size of video frames. + If it is true, the encoder will expect and encode color frames, otherwise it will work with grayscale frames (the flag is currently supported on Windows only). + + + + + Calculates cross product of two 3D vectors + + The first source vector. + The second source vector. + The destination vector. + + + + Converts image from one color space to another. + + The source 8-bit (8u), 16-bit (16u) or single-precision floating-point (32f) image. + The destination image of the same data type as the source one. The number of channels may be different. + Color conversion operation that can be specifed using CV_<src_color_space>2<dst_color_space> constants (see below). + + + + Copies sequence to one continuous block of memory + + + Sequence. + destination array that must be large enough. It should be a pointer to data, not a matrix header. + + + + + Copies sequence to one continuous block of memory + + + Sequence. + destination array that must be large enough. It should be a pointer to data, not a matrix header. + The sequence part to copy to the array. + + + + + Calculates angle of 2D vector + + y-coordinate of 2D vector + x-coordinate of 2D vector + + + + + Fills convex polygon + + Image. + Array of pointers to a single polygon. + Polygon color. + + + + Fills convex polygon + + Image. + Array of pointers to a single polygon. + Polygon color. + Type of the polygon boundaries. + + + + Fills convex polygon + + Image. + Array of pointers to a single polygon. + Polygon color. + Type of the polygon boundaries. + Number of fractional bits in the vertex coordinates. + + + + Fills polygons interior + + Image. + Array of pointers to polygons. + Polygon color. + + + + Fills polygons interior + + Image. + Array of pointers to polygons. + Polygon color. + ype of the polygon boundaries. + + + + Fills polygons interior + + Image. + Array of pointers to polygons. + Polygon color. + ype of the polygon boundaries. + Number of fractional bits in the vertex coordinates. + + + + Applies arbitrary linear filter to the image. In-place operation is supported. + When the aperture is partially outside the image, the function interpolates outlier pixel values from the nearest pixels that is inside the image. + + The source image. + The destination image. + Convolution kernel, single-channel floating point matrix. If you want to apply different kernels to different channels, split the image using cvSplit into separate color planes and process them individually. + + + + Applies arbitrary linear filter to the image. In-place operation is supported. + When the aperture is partially outside the image, the function interpolates outlier pixel values from the nearest pixels that is inside the image. + + The source image. + The destination image. + Convolution kernel, single-channel floating point matrix. If you want to apply different kernels to different channels, split the image using cvSplit into separate color planes and process them individually. + The anchor of the kernel that indicates the relative position of a filtered point within the kernel. The anchor shoud lie within the kernel. The special default value (-1,-1) means that it is at the kernel center. + + + + Finds positions of internal corners of the chessboard + + Source chessboard view; it must be 8-bit grayscale or color image. + The number of inner corners per chessboard row and column. + The output array of corners detected. + returns true if all the corners have been found and they have been placed in a certain order (row by row, left to right in every row), otherwise, if the function fails to find all the corners or reorder them, it returns false. + + + + Finds positions of internal corners of the chessboard + + Source chessboard view; it must be 8-bit grayscale or color image. + The number of inner corners per chessboard row and column. + The output array of corners detected. + The output corner counter. If it is not null, the function stores there the number of corners found. + returns true if all the corners have been found and they have been placed in a certain order (row by row, left to right in every row), otherwise, if the function fails to find all the corners or reorder them, it returns false. + + + + Finds positions of internal corners of the chessboard + + Source chessboard view; it must be 8-bit grayscale or color image. + The number of inner corners per chessboard row and column. + The output array of corners detected. + The output corner counter. If it is not null, the function stores there the number of corners found. + Various operation flags + returns true if all the corners have been found and they have been placed in a certain order (row by row, left to right in every row), otherwise, if the function fails to find all the corners or reorder them, it returns false. + + + + Retrieves contours from the binary image and returns the number of retrieved contours. + + The source 8-bit single channel image. Non-zero pixels are treated as 1’s, zero pixels remain 0’s - that is image treated as binary. + To get such a binary image from grayscale, one may use cvThreshold, cvAdaptiveThreshold or cvCanny. The function modifies the source image content. + Container of the retrieved contours. + Output parameter, will contain the pointer to the first outer contour. + The number of retrieved contours. + + + + Retrieves contours from the binary image and returns the number of retrieved contours. + + The source 8-bit single channel image. Non-zero pixels are treated as 1’s, zero pixels remain 0’s - that is image treated as binary. + To get such a binary image from grayscale, one may use cvThreshold, cvAdaptiveThreshold or cvCanny. The function modifies the source image content. + Container of the retrieved contours. + Output parameter, will contain the pointer to the first outer contour. + Size of the sequence header, >=sizeof(CvChain) if method=CV_CHAIN_CODE, and >=sizeof(CvContour) otherwise. + The number of retrieved contours. + + + + Retrieves contours from the binary image and returns the number of retrieved contours. + + The source 8-bit single channel image. Non-zero pixels are treated as 1’s, zero pixels remain 0’s - that is image treated as binary. + To get such a binary image from grayscale, one may use cvThreshold, cvAdaptiveThreshold or cvCanny. The function modifies the source image content. + Container of the retrieved contours. + Output parameter, will contain the pointer to the first outer contour. + Size of the sequence header, >=sizeof(CvChain) if method=CV_CHAIN_CODE, and >=sizeof(CvContour) otherwise. + Retrieval mode. + The number of retrieved contours. + + + + Retrieves contours from the binary image and returns the number of retrieved contours. + + The source 8-bit single channel image. Non-zero pixels are treated as 1’s, zero pixels remain 0’s - that is image treated as binary. + To get such a binary image from grayscale, one may use cvThreshold, cvAdaptiveThreshold or cvCanny. The function modifies the source image content. + Container of the retrieved contours. + Output parameter, will contain the pointer to the first outer contour. + Size of the sequence header, >=sizeof(CvChain) if method=CV_CHAIN_CODE, and >=sizeof(CvContour) otherwise. + Retrieval mode. + Approximation method. + The number of retrieved contours. + + + + Retrieves contours from the binary image and returns the number of retrieved contours. + + The source 8-bit single channel image. Non-zero pixels are treated as 1’s, zero pixels remain 0’s - that is image treated as binary. + To get such a binary image from grayscale, one may use cvThreshold, cvAdaptiveThreshold or cvCanny. The function modifies the source image content. + Container of the retrieved contours. + Output parameter, will contain the pointer to the first outer contour. + Size of the sequence header, >=sizeof(CvChain) if method=CV_CHAIN_CODE, and >=sizeof(CvContour) otherwise. + Retrieval mode. + Approximation method. + Offset, by which every contour point is shifted. This is useful if the contours are extracted from the image ROI and then they should be analyzed in the whole image context. + The number of retrieved contours. + + + + Iterates to find the sub-pixel accurate location of corners, or radial saddle points. + + Input image. + Initial coordinates of the input corners and refined coordinates on output. + Number of corners. + Half sizes of the search window. + Half size of the dead region in the middle of the search zone over which the summation in formulae below is not done. It is used sometimes to avoid possible singularities of the autocorrelation matrix. The value of (-1,-1) indicates that there is no such size. + Criteria for termination of the iterative process of corner refinement. That is, the process of corner position refinement stops either after certain number of iteration or when a required accuracy is achieved. The criteria may specify either of or both the maximum number of iteration and the required accuracy. + + + + Finds high-curvature points of the contour + + pointer to input contour object. + memory storage + + for IPAN algorithm - minimal distance + for IPAN algorithm - maximal distance + for IPAN algorithm - neighborhood distance (must be not greater than dmaximal distance) + for IPAN algorithm - maximal possible angle of curvature + array of dominant points indices + + + + Finds extrinsic camera parameters for particular view + + The array of object points, 3xN or Nx3, where N is the number of points in the view. + The array of corresponding image points, 2xN or Nx2, where N is the number of points in the view. + The camera matrix (A) [fx 0 cx; 0 fy cy; 0 0 1]. + The vector of distortion coefficients, 4x1 or 1x4 [k1, k2, p1, p2]. If it is null, all distortion coefficients are considered 0's. + The output 3x1 or 1x3 rotation vector (compact representation of a rotation matrix, see cvRodrigues2). + The output 3x1 or 1x3 translation vector. + + + + Finds extrinsic camera parameters for particular view + + The array of object points, 3xN or Nx3, where N is the number of points in the view. + The array of corresponding image points, 2xN or Nx2, where N is the number of points in the view. + The camera matrix (A) [fx 0 cx; 0 fy cy; 0 0 1]. + The vector of distortion coefficients, 4x1 or 1x4 [k1, k2, p1, p2]. If it is NULL, all distortion coefficients are considered 0's. + The output 3x1 or 1x3 rotation vector (compact representation of a rotation matrix, see cvRodrigues2). + The output 3x1 or 1x3 translation vector. + + + + + + + + + + + + + Finds approximate k nearest neighbors of given vectors using best-bin-first search. + + pointer to kd-tree index of reference vectors. + m x d matrix of (row-)vectors to find the nearest neighbors of. + m x k set of row indices of matching vectors (referring to matrix passed to cvCreateFeatureTree). Contains -1 in some columns if fewer than k neighbors found. + m x k matrix of distances to k nearest neighbors. + + + + Finds approximate k nearest neighbors of given vectors using best-bin-first search. + + pointer to kd-tree index of reference vectors. + m x d matrix of (row-)vectors to find the nearest neighbors of. + m x k set of row indices of matching vectors (referring to matrix passed to cvCreateFeatureTree). Contains -1 in some columns if fewer than k neighbors found. + m x k matrix of distances to k nearest neighbors. + The number of neighbors to find. + + + + Finds approximate k nearest neighbors of given vectors using best-bin-first search. + + pointer to kd-tree index of reference vectors. + m x d matrix of (row-)vectors to find the nearest neighbors of. + m x k set of row indices of matching vectors (referring to matrix passed to cvCreateFeatureTree). Contains -1 in some columns if fewer than k neighbors found. + m x k matrix of distances to k nearest neighbors. + The number of neighbors to find. + The maximum number of leaves to visit. + + + + Performs orthogonal range seaching on the given kd-tree. + + Pointer to kd-tree index of reference vectors. + 1 x d or d x 1 vector (CV_32FC1 or CV_64FC1) giving minimum value for each dimension. + 1 x d or d x 1 vector (CV_32FC1 or CV_64FC1) giving maximum value for each dimension. + 1 x m or m x 1 vector (CV_32SC1) to contain output row indices (referring to matrix passed to cvCreateFeatureTree). + the number of such vectors found. + + + + Calculates fundamental matrix from corresponding points in two images + + Array of the first image points of 2xN, Nx2, 3xN or Nx3 size (where N is number of points). Multi-channel 1xN or Nx1 array is also acceptable. The point coordinates should be floating-point (single or double precision) + Array of the second image points of the same size and format as points1 + The output fundamental matrix or matrices. The size should be 3x3 or 9x3 (7-point method may return up to 3 matrices). + + + + + Calculates fundamental matrix from corresponding points in two images + + Array of the first image points of 2xN, Nx2, 3xN or Nx3 size (where N is number of points). Multi-channel 1xN or Nx1 array is also acceptable. The point coordinates should be floating-point (single or double precision) + Array of the second image points of the same size and format as points1 + The output fundamental matrix or matrices. The size should be 3x3 or 9x3 (7-point method may return up to 3 matrices). + Method for computing the fundamental matrix + + + + + Calculates fundamental matrix from corresponding points in two images + + Array of the first image points of 2xN, Nx2, 3xN or Nx3 size (where N is number of points). Multi-channel 1xN or Nx1 array is also acceptable. The point coordinates should be floating-point (single or double precision) + Array of the second image points of the same size and format as points1 + The output fundamental matrix or matrices. The size should be 3x3 or 9x3 (7-point method may return up to 3 matrices). + Method for computing the fundamental matrix + The parameter is used for RANSAC method only. It is the maximum distance from point to epipolar line in pixels, beyond which the point is considered an outlier and is not used for computing the final fundamental matrix. Usually it is set somewhere from 1 to 3. + The parameter is used for RANSAC or LMedS methods only. It denotes the desirable level of confidence of the fundamental matrix estimate. + + + + + Calculates fundamental matrix from corresponding points in two images + + Array of the first image points of 2xN, Nx2, 3xN or Nx3 size (where N is number of points). Multi-channel 1xN or Nx1 array is also acceptable. The point coordinates should be floating-point (single or double precision) + Array of the second image points of the same size and format as points1 + The output fundamental matrix or matrices. The size should be 3x3 or 9x3 (7-point method may return up to 3 matrices). + Method for computing the fundamental matrix + The parameter is used for RANSAC method only. It is the maximum distance from point to epipolar line in pixels, beyond which the point is considered an outlier and is not used for computing the final fundamental matrix. Usually it is set somewhere from 1 to 3. + The parameter is used for RANSAC or LMedS methods only. It denotes the desirable level of confidence of the fundamental matrix estimate. + The optional output array of N elements, every element of which is set to 0 for outliers and to 1 for the "inliers", i.e. points that comply well with the estimated epipolar geometry. The array is computed only in RANSAC and LMedS methods. For other methods it is set to all 1’s. + + + + + Finds edge in graph + + Graph. + Index of the starting vertex of the edge. + Index of the ending vertex of the edge. For unoriented graph the order of the vertex parameters does not matter. + The function cvFindGraphEdge finds the graph edge connecting two specified vertices and returns pointer to it or NULL if the edge does not exists. + + + + Finds edge in graph + + Graph. + Index of the starting vertex of the edge. + Index of the ending vertex of the edge. For unoriented graph the order of the vertex parameters does not matter. + The function cvFindGraphEdge finds the graph edge connecting two specified vertices and returns pointer to it or NULL if the edge does not exists. + + + + Finds edge in graph + + Graph. + Starting vertex of the edge. + Ending vertex of the edge. For unoriented graph the order of the vertex parameters does not matter. + The function cvFindGraphEdge finds the graph edge connecting two specified vertices and returns pointer to it or NULL if the edge does not exists. + + + + Finds edge in graph + + Graph. + Starting vertex of the edge. + Ending vertex of the edge. For unoriented graph the order of the vertex parameters does not matter. + The function cvFindGraphEdge finds the graph edge connecting two specified vertices and returns pointer to it or NULL if the edge does not exists. + + + + Finds perspective transformation between two planes + + Point coordinates in the original plane, 2xN, Nx2, 3xN or Nx3 array (the latter two are for representation in homogenious coordinates), where N is the number of points. + Point coordinates in the destination plane, 2xN, Nx2, 3xN or Nx3 array (the latter two are for representation in homogenious coordinates) + Output 3x3 homography matrix. + + + + + Finds perspective transformation between two planes + + Point coordinates in the original plane, 2xN, Nx2, 3xN or Nx3 array (the latter two are for representation in homogenious coordinates), where N is the number of points. + Point coordinates in the destination plane, 2xN, Nx2, 3xN or Nx3 array (the latter two are for representation in homogenious coordinates) + Output 3x3 homography matrix. + + + + + + Finds perspective transformation between two planes + + Point coordinates in the original plane, 2xN, Nx2, 3xN or Nx3 array (the latter two are for representation in homogenious coordinates), where N is the number of points. + Point coordinates in the destination plane, 2xN, Nx2, 3xN or Nx3 array (the latter two are for representation in homogenious coordinates) + Output 3x3 homography matrix. + + + + + + + Finds perspective transformation between two planes + + Point coordinates in the original plane, 2xN, Nx2, 3xN or Nx3 array (the latter two are for representation in homogenious coordinates), where N is the number of points. + Point coordinates in the destination plane, 2xN, Nx2, 3xN or Nx3 array (the latter two are for representation in homogenious coordinates) + Output 3x3 homography matrix. + + + + + + + + Finds the closest subdivision vertex to given point + + Delaunay or another subdivision. + Input point. + + + + + Finds next contour in the image + + Contour scanner initialized by The function cvStartFindContours + + + + Calculates disparity for stereo-pair + + Left image of stereo pair, rectified grayscale 8-bit image + Right image of stereo pair, rectified grayscale 8-bit image + Algorithm used to find a disparity (now only CV_DISPARITY_BIRCHFIELD is supported) + Destination depth image, grayscale 8-bit image that codes the scaled disparity, so that the zero disparity (corresponding to the points that are very far from the cameras) maps to 0, maximum disparity maps to 255. + Maximum possible disparity. The closer the objects to the cameras, the larger value should be specified here. Too big values slow down the process significantly. + + + + Calculates disparity for stereo-pair + + Left image of stereo pair, rectified grayscale 8-bit image + Right image of stereo pair, rectified grayscale 8-bit image + Algorithm used to find a disparity (now only CV_DISPARITY_BIRCHFIELD is supported) + Destination depth image, grayscale 8-bit image that codes the scaled disparity, so that the zero disparity (corresponding to the points that are very far from the cameras) maps to 0, maximum disparity maps to 255. + Maximum possible disparity. The closer the objects to the cameras, the larger value should be specified here. Too big values slow down the process significantly. + Constant occlusion penalty, default=25 + Constant match reward, default=5 + Defines a highly reliable region (set of contiguous pixels whose reliability is at least param3), default=12 + Defines a moderately reliable region, default=15 + Defines a slightly reliable region, default=25 + + + + Computes the disparity map using block matching algorithm + + The left single-channel, 8-bit image. + The right image of the same size and the same type. + The output single-channel 16-bit signed disparity map of the same size as input images. Its elements will be the computed disparities, multiplied by 16 and rounded to integer's. + Stereo correspondence structure. + + + + Computes the disparity map using graph cut-based algorithm + + The left single-channel, 8-bit image. + The right image of the same size and the same type. + The optional output single-channel 16-bit signed left disparity map of the same size as input images. + The optional output single-channel 16-bit signed right disparity map of the same size as input images. + Stereo correspondence structure. + + + + Computes the disparity map using graph cut-based algorithm + + The left single-channel, 8-bit image. + The right image of the same size and the same type. + The optional output single-channel 16-bit signed left disparity map of the same size as input images. + The optional output single-channel 16-bit signed right disparity map of the same size as input images. + Stereo correspondence structure. + If the parameter is not zero, the algorithm will start with pre-defined disparity maps. Both dispLeft and dispRight should be valid disparity maps. Otherwise, the function starts with blank disparity maps (all pixels are marked as occlusions). + + + + Finds type by its name + + Type name. + + + + + Returns the beginning of type list + + the first type of the list of registered types. + + + + Fits ellipse to set of 2D points + + Array or sequence of the points. + ellipse that fits best (in least-squares sense) to a set of 2D points. + + + + Fits ellipse to set of 2D points + + Array of the points. + ellipse that fits best (in least-squares sense) to a set of 2D points. + + + + Fits line to 2D or 3D point set + + Sequence or array of 2D or 3D points with 32-bit integer or floating-point coordinates. + The distance used for fitting (see the discussion). + Numerical parameter (C) for some types of distances, if 0 then some optimal value is chosen. + Sufficient accuracy for radius (distance between the coordinate origin and the line) and angle, respectively, 0.01 would be a good defaults for both. + Sufficient accuracy for radius (distance between the coordinate origin and the line) and angle, respectively, 0.01 would be a good defaults for both. + The output line parameters. In case of 2d fitting it is array of 4 floats (vx, vy, x0, y0) where (vx, vy) is a normalized vector collinear to the line and (x0, y0) is some point on the line. In case of 3D fitting it is array of 6 floats (vx, vy, vz, x0, y0, z0) where (vx, vy, vz) is a normalized vector collinear to the line and (x0, y0, z0) is some point on the line. + + + + Fits line to 2D point set + + Sequence or array of 2D points with 32-bit integer coordinates. + The distance used for fitting (see the discussion). + Numerical parameter (C) for some types of distances, if 0 then some optimal value is chosen. + Sufficient accuracy for radius (distance between the coordinate origin and the line) and angle, respectively, 0.01 would be a good defaults for both. + Sufficient accuracy for radius (distance between the coordinate origin and the line) and angle, respectively, 0.01 would be a good defaults for both. + The output line parameters. (vx, vy) is a normalized vector collinear to the line and + (x0, y0) is some point on the line. + + + + Fits line to 2D point set + + Sequence or array of 2D points with floating-point coordinates. + The distance used for fitting (see the discussion). + Numerical parameter (C) for some types of distances, if 0 then some optimal value is chosen. + Sufficient accuracy for radius (distance between the coordinate origin and the line) and angle, respectively, 0.01 would be a good defaults for both. + Sufficient accuracy for radius (distance between the coordinate origin and the line) and angle, respectively, 0.01 would be a good defaults for both. + The output line parameters. (vx, vy) is a normalized vector collinear to the line and + (x0, y0) is some point on the line. + + + + Fits line to 3D point set + + Sequence or array of 3D points with floating-point coordinates. + The distance used for fitting (see the discussion). + Numerical parameter (C) for some types of distances, if 0 then some optimal value is chosen. + Sufficient accuracy for radius (distance between the coordinate origin and the line) and angle, respectively, 0.01 would be a good defaults for both. + Sufficient accuracy for radius (distance between the coordinate origin and the line) and angle, respectively, 0.01 would be a good defaults for both. + The output line parameters. (vx, vy, vz) is a normalized vector collinear to the line and + (x0, y0, z0) is some point on the line. + + + + Flip a 2D array around vertical, horizontal or both axises + + Source array. + + + + Flip a 2D array around vertical, horizontal or both axises + + Source array. + Destination array. If dst = null the flipping is done in-place. + + + + Flip a 2D array around vertical, horizontal or both axises + + Source array. + Destination array. If dst = null the flipping is done in-place. + Specifies how to flip the array. + + + + Flip a 2D array around vertical, horizontal or both axises + + Source array. + + + + Flip a 2D array around vertical, horizontal or both axises + + Source array. + Destination array. If dst = null the flipping is done in-place. + + + + Flip a 2D array around vertical, horizontal or both axises + + Source array. + Destination array. If dst = null the flipping is done in-place. + Specifies how to flip the array. + + + + Fills a connected component with given color. + + Input 1- or 3-channel, 8-bit or floating-point image. It is modified by the function unless CV_FLOODFILL_MASK_ONLY flag is set. + The starting point. + New value of repainted domain pixels. + + + + Fills a connected component with given color. + + Input 1- or 3-channel, 8-bit or floating-point image. It is modified by the function unless CV_FLOODFILL_MASK_ONLY flag is set. + The starting point. + New value of repainted domain pixels. + Maximal lower brightness/color difference between the currently observed pixel and one of its neighbor belong to the component or seed pixel to add the pixel to component. In case of 8-bit color images it is packed value. + + + + Fills a connected component with given color. + + Input 1- or 3-channel, 8-bit or floating-point image. It is modified by the function unless CV_FLOODFILL_MASK_ONLY flag is set. + The starting point. + New value of repainted domain pixels. + Maximal lower brightness/color difference between the currently observed pixel and one of its neighbor belong to the component or seed pixel to add the pixel to component. In case of 8-bit color images it is packed value. + Maximal upper brightness/color difference between the currently observed pixel and one of its neighbor belong to the component or seed pixel to add the pixel to component. In case of 8-bit color images it is packed value. + + + + Fills a connected component with given color. + + Input 1- or 3-channel, 8-bit or floating-point image. It is modified by the function unless CV_FLOODFILL_MASK_ONLY flag is set. + The starting point. + New value of repainted domain pixels. + Maximal lower brightness/color difference between the currently observed pixel and one of its neighbor belong to the component or seed pixel to add the pixel to component. In case of 8-bit color images it is packed value. + Maximal upper brightness/color difference between the currently observed pixel and one of its neighbor belong to the component or seed pixel to add the pixel to component. In case of 8-bit color images it is packed value. + Pointer to structure the function fills with the information about the repainted domain. + + + + Fills a connected component with given color. + + Input 1- or 3-channel, 8-bit or floating-point image. It is modified by the function unless CV_FLOODFILL_MASK_ONLY flag is set. + The starting point. + New value of repainted domain pixels. + Maximal lower brightness/color difference between the currently observed pixel and one of its neighbor belong to the component or seed pixel to add the pixel to component. In case of 8-bit color images it is packed value. + Maximal upper brightness/color difference between the currently observed pixel and one of its neighbor belong to the component or seed pixel to add the pixel to component. In case of 8-bit color images it is packed value. + Pointer to structure the function fills with the information about the repainted domain. + The operation flags. Lower bits contain connectivity value, 4 (by default) or 8, used within the function. Connectivity determines which neighbors of a pixel are considered. Upper bits can be 0 or combination of the flags + + + + Fills a connected component with given color. + + Input 1- or 3-channel, 8-bit or floating-point image. It is modified by the function unless CV_FLOODFILL_MASK_ONLY flag is set. + The starting point. + New value of repainted domain pixels. + Maximal lower brightness/color difference between the currently observed pixel and one of its neighbor belong to the component or seed pixel to add the pixel to component. In case of 8-bit color images it is packed value. + Maximal upper brightness/color difference between the currently observed pixel and one of its neighbor belong to the component or seed pixel to add the pixel to component. In case of 8-bit color images it is packed value. + Pointer to structure the function fills with the information about the repainted domain. + The operation flags. Lower bits contain connectivity value, 4 (by default) or 8, used within the function. Connectivity determines which neighbors of a pixel are considered. Upper bits can be 0 or combination of the flags + Operation mask + + + + Returns the maximum integer value that is not larger than the argument. + + The input floating-point value + + + + + Updates sequence headers from the writer state + + Writer state + + + + Create the font to be used to draw text on an image + + Name of the font. The name should match the name of a system font (such as ``Times’‘). If the font is not found, a default one will be used. + + + + Create the font to be used to draw text on an image + + Name of the font. The name should match the name of a system font (such as ``Times’‘). If the font is not found, a default one will be used. + Size of the font. If not specified, equal zero or negative, the point size of the font is set to a system-dependent default value. Generally, this is 12 points. + + + + Create the font to be used to draw text on an image + + Name of the font. The name should match the name of a system font (such as ``Times’‘). If the font is not found, a default one will be used. + Size of the font. If not specified, equal zero or negative, the point size of the font is set to a system-dependent default value. Generally, this is 12 points. + Color of the font in BGRA – A = 255 is fully transparent. Use the macro CV _ RGB for simplicity. + + + + Create the font to be used to draw text on an image + + Name of the font. The name should match the name of a system font (such as ``Times’‘). If the font is not found, a default one will be used. + Size of the font. If not specified, equal zero or negative, the point size of the font is set to a system-dependent default value. Generally, this is 12 points. + Color of the font in BGRA – A = 255 is fully transparent. Use the macro CV _ RGB for simplicity. + The operation flags + + + + Create the font to be used to draw text on an image + + Name of the font. The name should match the name of a system font (such as ``Times’‘). If the font is not found, a default one will be used. + Size of the font. If not specified, equal zero or negative, the point size of the font is set to a system-dependent default value. Generally, this is 12 points. + Color of the font in BGRA – A = 255 is fully transparent. Use the macro CV _ RGB for simplicity. + The operation flags + The operation flags + + + + Create the font to be used to draw text on an image + + Name of the font. The name should match the name of a system font (such as ``Times’‘). If the font is not found, a default one will be used. + Size of the font. If not specified, equal zero or negative, the point size of the font is set to a system-dependent default value. Generally, this is 12 points. + Color of the font in BGRA – A = 255 is fully transparent. Use the macro CV _ RGB for simplicity. + The operation flags + The operation flags + Spacing between characters. Can be negative or positive. + + + + Deallocates memory buffer + + Double pointer to released buffer. + + + + Performs generalized matrix multiplication + + The first source array. + The second source array. + Scale factor + The third source array (shift). Can be null, if there is no shift. + Scale factor + The destination array. + + + + Performs generalized matrix multiplication + + The first source array. + The second source array. + Scale factor + The third source array (shift). Can be null, if there is no shift. + Scale factor + The destination array. + The operation flags + + + + Performs generalized matrix multiplication + + The first source array. + The second source array. + The destination array. + + + + Performs generalized matrix multiplication + + The first source array. + The second source array. + The third source array (shift). Can be null, if there is no shift. + The destination array. + + + + Performs generalized matrix multiplication + + The first source array. + The second source array. + Scale factor + The third source array (shift). Can be null, if there is no shift. + Scale factor + The destination array. + + + + Performs generalized matrix multiplication + + The first source array. + The second source array. + Scale factor + The third source array (shift). Can be null, if there is no shift. + Scale factor + The destination array. + The operation flags + + + + Return the particular array element + + Input array. + The first zero-based component of the element index + + + + + Return the particular array element + + Input array. + The first zero-based component of the element index + The second zero-based component of the element index + + + + + Return the particular array element + + Input array. + The first zero-based component of the element index + The second zero-based component of the element index + The third zero-based component of the element index + + + + + Return the particular array element + + Input array. + Array of the element indices + the particular array element + + + + Calculates affine transform from 3 corresponding points. + + Coordinates of 3 triangle vertices in the source image. + Coordinates of the 3 corresponding triangle vertices in the destination image. + + + + + Calculates affine transform from 3 corresponding points. + + Coordinates of 3 triangle vertices in the source image. + Coordinates of the 3 corresponding triangle vertices in the destination image. + Pointer to the destination 2×3 matrix. + + + + + Retrieves the specified property of camera or video file. + + video capturing structure. + property identifier. + property value + + + + Retrieves the specified property of camera or video file. + + video capturing structure. + property identifier. + property value + + + + Retrieves central moment from moment state structure + + Moment state structure + x order of the retrieved moment, x_order >= 0 + y order of the retrieved moment, y_order >= 0 and x_order + y_order <= 3 + Central moment + + + + Returns array column + + Input array. + Reference to the resulting sub-array header. + Zero-based index of the selected column. + + + + + Returns array column span + + Input array. + Reference to the resulting sub-array header. + Zero-based index of the starting column (inclusive) of the span. + Zero-based index of the ending column (exclusive) of the span. + + + + + Returns one of array diagonals + + Input array. + Reference to the resulting sub-array header. + + + + + Returns one of array diagonals + + Input array. + Reference to the resulting sub-array header. + Array diagonal. Zero corresponds to the main diagonal, -1 corresponds to the diagonal above the main etc., 1 corresponds to the diagonal below the main etc. + + + + + Return number of array dimensions and their sizes + + Input array. + number of array dimensions. + + + + Return number of array dimensions and their sizes + + Input array. + Optional output vector of the array dimension sizes. For 2d arrays the number of rows (height) goes first, number of columns (width) next. + number of array dimensions. + + + + Return the size of particular dimension + + Input array. + Zero-based dimension index (for matrices 0 means number of rows, 1 means number of columns; for images 0 means height, 1 means width). + the particular dimension size (number of elements per that dimension). + + + + Returns type of array elements + + Input array. + type of the array elements + + + + Returns the current error mode + + the current error mode + + + + Returns the current error status + + the current error status + + + + Finds node in the map or file storage + + File storage. + The parent map. If it is null, the function searches a top-level node. If both map and key are nulls, the function returns the root file node - a map that contains top-level nodes. + Unique pointer to the node name, retrieved with cvGetHashedKey. + + + + + Finds node in the map or file storage + + File storage. + The parent map. If it is null, the function searches a top-level node. If both map and key are nulls, the function returns the root file node - a map that contains top-level nodes. + Unique pointer to the node name, retrieved with cvGetHashedKey. + Flag that specifies, whether an absent node should be added to the map, or not. + + + + + Returns name of file node + + File node. + name of the file node or null + + + + Finds node in the map or file storage + + File storage. + The parent map. If it is null, the function searches in all the top-level nodes (streams), starting from the first one. + The file node name. + + + + + Finds graph vertex by index + + Graph. + Index of the vertex. + The function cvGetGraphVtx finds the graph vertex by index and returns the pointer to it or null if the vertex does not belong to the graph. + + + + Returns a unique pointer for given name + + File storage. + Literal node name. + The unique pointer for each particular file node name. + + + + Returns a unique pointer for given name + + File storage. + Literal node name. + Length of the name (if it is known a priori), or -1 if it needs to be calculated. + The unique pointer for each particular file node name. + + + + Returns pointer to histogram bin. + + Histogram. + 1st index of the bin. + + + + + Returns pointer to histogram bin. + + Histogram. + 1st index of the bin. + 2rd index of the bin. + + + + + Returns pointer to histogram bin. + + Histogram. + 1st index of the bin. + 2nd index of the bin. + 3rd index of the bin. + + + + + Returns pointer to histogram bin. + + Histogram. + Indices of the bin. + + + + + Calculates seven Hu invariants + + Moment state structure + Pointer to Hu moments structure + + + + Returns image header for arbitrary array + + Input array. + returns the image header for the input array that can be a matrix + + + + Returns image header for arbitrary array + + Input array. + IplImage structure used as a temporary buffer. + returns the image header for the input array that can be a matrix + + + + Returns index of channel of interest + + Image header. + channel of interest of the image (it returns 0 if all the channels are selected) + + + + Returns image ROI coordinates. + The rectangle cvRect(0,0,image.Width,image.Height) is returned if there is no ROI. + + Image header. + + + + + Returns matrix header for arbitrary array + + Input array. + returns a matrix header for the input array that can be a matrix + + + + Returns matrix header for arbitrary array + + Input array. + Pointer to CvMat structure used as a temporary buffer. + returns a matrix header for the input array that can be a matrix + + + + Returns matrix header for arbitrary array + + Input array. + Pointer to CvMat structure used as a temporary buffer. + Optional output parameter for storing COI. + returns a matrix header for the input array that can be a matrix + + + + Returns matrix header for arbitrary array + + Input array. + Pointer to CvMat structure used as a temporary buffer. + Optional output parameter for storing COI. + If true, the function accepts multi-dimensional dense arrays (CvMatND*) and returns 2D (if CvMatND has two dimensions) or 1D matrix (when CvMatND has 1 dimension or more than 2 dimensions). The array must be continuous. + returns a matrix header for the input array that can be a matrix + + + + Moves iterator to the next sparse matrix element and returns pointer to it. + + Sparse array iterator. + + + + + Finds minimum and maximum histogram bins. + + Histogram. + The minimum value of the histogram. + The maximum value of the histogram. + + + + Finds minimum and maximum histogram bins. + + Histogram. + The minimum value of the histogram. + The maximum value of the histogram. + The array of coordinates for minimum. + The array of coordinates for maximum. + + + + Retrieves information about the registered module(s) and plugins + + Name of the module of interest, or null, which means all the modules. + The output parameter. Information about the module(s), including version. + The list of names and versions of the optimized plugins that CXCORE was able to find and load. + + + + Retrieves normalized central moment from moment state structure + + Moment state structure + x order of the retrieved moment, x_order >= 0 + y order of the retrieved moment, y_order >= 0 and x_order + y_order <= 3 + Central moment + + + + Returns the current number of threads that are used by parallelized (via OpenMP) OpenCV functions. + + the current number of threads used + + + + Returns optimal DFT size for given vector size + + Vector size. + optimal DFT size for given vector size + + + + Returns the new camera matrix based on the free scaling parameter + + The input camera matrix + The input 4x1, 1x4, 5x1 or 1x5 vector of distortion coefficients (k_1, k_2, p_1, p_2[, k_3]) + The original image size + The free scaling parameter between 0 (when all the pixels in the undistorted image will be valid) and 1 (when all the source image pixels will be retained in the undistorted image); + The output new camera matrix. + + + + Returns the new camera matrix based on the free scaling parameter + + The input camera matrix + The input 4x1, 1x4, 5x1 or 1x5 vector of distortion coefficients (k_1, k_2, p_1, p_2[, k_3]) + The original image size + The free scaling parameter between 0 (when all the pixels in the undistorted image will be valid) and 1 (when all the source image pixels will be retained in the undistorted image); + The output new camera matrix. + The image size after rectification. By default it will be set to imageSize . + + + + Returns the new camera matrix based on the free scaling parameter + + The input camera matrix + The input 4x1, 1x4, 5x1 or 1x5 vector of distortion coefficients (k_1, k_2, p_1, p_2[, k_3]) + The original image size + The free scaling parameter between 0 (when all the pixels in the undistorted image will be valid) and 1 (when all the source image pixels will be retained in the undistorted image); + The output new camera matrix. + The image size after rectification. By default it will be set to imageSize . + The optional output rectangle that will outline all-good-pixels region in the undistorted image. + + + + Calculates perspective transform from 4 corresponding points. + + Coordinates of 4 quadrangle vertices in the source image. + Coordinates of the 4 corresponding quadrangle vertices in the destination image. + + + + + Calculates perspective transform from 4 corresponding points. + + Coordinates of 4 quadrangle vertices in the source image. + Coordinates of the 4 corresponding quadrangle vertices in the destination image. + Pointer to the destination 3×3 matrix. + + + + + Calculates perspective transform from 4 corresponding points. + + Coordinates of 4 quadrangle vertices in the source image. + Coordinates of the 4 corresponding quadrangle vertices in the destination image. + + + + + Calculates perspective transform from 4 corresponding points. + + Coordinates of 4 quadrangle vertices in the source image. + Coordinates of the 4 corresponding quadrangle vertices in the destination image. + Pointer to the destination 3×3 matrix. + + + + + Retrieves pixel quadrangle from image with sub-pixel accuracy. + + Source image. + Extracted quadrangle. + The transformation 2 × 3 matrix [A|b]. + + + + Retrieves low-level information about the array + + Array header. + Output pointer to the whole image origin or ROI origin if ROI is set. + + + + Retrieves low-level information about the array + + Array header. + Output pointer to the whole image origin or ROI origin if ROI is set. + Output full row length in bytes. + + + + Retrieves low-level information about the array + + Array header. + Output pointer to the whole image origin or ROI origin if ROI is set. + Output full row length in bytes. + Output ROI size. + + + + Return the particular element of single-channel array + + Input array. Must have a single channel. + The first zero-based component of the element index + the particular element of single-channel array. + + + + Return the particular element of single-channel array + + Input array. Must have a single channel. + The first zero-based component of the element index + The second zero-based component of the element index + the particular element of single-channel array. + + + + Return the particular element of single-channel array + + Input array. Must have a single channel. + The first zero-based component of the element index + The second zero-based component of the element index + The third zero-based component of the element index + the particular element of single-channel array. + + + + Return the particular element of single-channel array + + Input array. Must have a single channel. + Array of the element indices + the particular element of single-channel array. + + + + Retrieves pixel rectangle from image with sub-pixel accuracy. + + Source image. + Extracted rectangle. + Floating point coordinates of the extracted rectangle center within the source image. The center must be inside the image. + + + + Retrieves one of top-level nodes of the file storage + + File storage. + One of top-level file nodes + + + + Retrieves one of top-level nodes of the file storage + + File storage. + Zero-based index of the stream. In most cases, there is only one stream in the file, however there can be several. + One of top-level file nodes + + + + Calculates affine matrix of 2d rotation. + + Center of the rotation in the source image. + The rotation angle in degrees. Positive values mean couter-clockwise rotation (the coordiate origin is assumed at top-left corner). + Isotropic scale factor. + + + + + Calculates affine matrix of 2d rotation. + + Center of the rotation in the source image. + The rotation angle in degrees. Positive values mean couter-clockwise rotation (the coordiate origin is assumed at top-left corner). + Isotropic scale factor. + + + + + Calculates affine matrix of 2d rotation. + + Center of the rotation in the source image. + The rotation angle in degrees. Positive values mean couter-clockwise rotation (the coordiate origin is assumed at top-left corner). + Isotropic scale factor. + Pointer to the destination 2×3 matrix. + The transformation maps the rotation center to itself. If this is not the purpose, the shift should be adjusted. + + + + Returns array row + + Input array. + Reference to the resulting sub-array header. + Zero-based index of the selected row. + + + + + Returns array row span + + Input array. + Reference to the resulting sub-array header. + Zero-based index of the starting row (inclusive) of the span. + Zero-based index of the ending row (exclusive) of the span. + + + + + Returns array row span + + Input array. + Reference to the resulting sub-array header. + Zero-based index of the starting row (inclusive) of the span. + Zero-based index of the ending row (exclusive) of the span. + Index step in the row span. That is, the function extracts every delta_row-th row from start_row and up to (but not including) end_row. + + + + + Returns pointer to sequence element by its index + + Element type + Sequence. + Index of element. + + + + + Returns pointer to sequence element by its index + + Element type + Sequence. + Index of element. + + + + + Returns the current reader position + + Reader state. + the current reader position + + + + Finds set element by its index + + Set. + Index of the set element within a sequence. + the pointer to it or null if the index is invalid or the corresponding node is free. + + + + Returns size of matrix or image ROI + + array header. + + + + + Retrieves spatial moment from moment state structure + + The moment state, calculated by cvMoments + x order of the retrieved moment, x_order >= 0 + y order of the retrieved moment, y_order >= 0 and x_order + y_order <= 3 + Spatial moments + + + + Retrieves keypoints using the StarDetector algorithm. + + The input 8-bit grayscale image + Memory storage where the keypoints will be stored + + + + + Retrieves keypoints using the StarDetector algorithm. + + The input 8-bit grayscale image + Memory storage where the keypoints will be stored + Various algorithm parameters given to the structure CvStarDetectorParams + + + + + Returns matrix header corresponding to the rectangular sub-array of input image or matrix + + Input array. + Reference to the resultant sub-array header. + Zero-based coordinates of the rectangle of interest. + Reference to the header, corresponding to a specified rectangle of the input array. + + + + Returns matrix header corresponding to the rectangular sub-array of input image or matrix + + Input array. + Reference to the resultant sub-array header. + Zero-based coordinates of the rectangle of interest. + Reference to the header, corresponding to a specified rectangle of the input array. + + + + Retrieves width and height of text string + + Input string. + Reference to the font structure. + Resultant size of the text string. Height of the text does not include the height of character parts that are below the baseline. + y-coordinate of the baseline relatively to the bottom-most text point. + + + + Returns number of tics starting from some platform-dependent event (number of CPU ticks from the startup, number of milliseconds from 1970th year etc.). + + Number of tics + + + + Returns number of tics per microsecond + + number of tics per microsecond. + + + + Returns index of the current thread + + + + + + Returns the current position of the specified trackbar. + + Name of trackbar. + Name of the window which is the parent of trackbar. + the current position of the specified trackbar. + + + + + + + + + + + + + + + Returns native window handle (HWND in case of Win32 and GtkWidget in case of GTK+). + + Name of the window. + HWND in case of Win32 and GtkWidget in case of GTK+ + + + + Returns the name of window given its native handle (HWND in case of Win32 and GtkWidget in case of GTK+). + + Handle of the window. + Window name + + + + Get Property of the window + + Window name + Property identifier + Value of the specified property + + + + Determines strong corners on image + + The source 8-bit or floating-point 32-bit, single-channel image. + Temporary floating-point 32-bit image of the same size as image. + Another temporary image of the same size and same format as eig_image. + Output parameter. Detected corners. + Output parameter. Number of detected corners. + Multiplier for the maxmin eigenvalue; specifies minimal accepted quality of image corners. + Limit, specifying minimum possible distance between returned corners; Euclidian distance is used. + + + + Determines strong corners on image + + The source 8-bit or floating-point 32-bit, single-channel image. + Temporary floating-point 32-bit image of the same size as image. + Another temporary image of the same size and same format as eig_image. + Output parameter. Detected corners. + Output parameter. Number of detected corners. + Multiplier for the maxmin eigenvalue; specifies minimal accepted quality of image corners. + Limit, specifying minimum possible distance between returned corners; Euclidian distance is used. + Region of interest. The function selects points either in the specified region or in the whole image if the mask is null. + + + + Determines strong corners on image + + The source 8-bit or floating-point 32-bit, single-channel image. + Temporary floating-point 32-bit image of the same size as image. + Another temporary image of the same size and same format as eig_image. + Output parameter. Detected corners. + Output parameter. Number of detected corners. + Multiplier for the maxmin eigenvalue; specifies minimal accepted quality of image corners. + Limit, specifying minimum possible distance between returned corners; Euclidian distance is used. + Region of interest. The function selects points either in the specified region or in the whole image if the mask is null. + Size of the averaging block, passed to underlying cvCornerMinEigenVal or cvCornerHarris used by the function. + + + + Determines strong corners on image + + The source 8-bit or floating-point 32-bit, single-channel image. + Temporary floating-point 32-bit image of the same size as image. + Another temporary image of the same size and same format as eig_image. + Output parameter. Detected corners. + Output parameter. Number of detected corners. + Multiplier for the maxmin eigenvalue; specifies minimal accepted quality of image corners. + Limit, specifying minimum possible distance between returned corners; Euclidian distance is used. + Region of interest. The function selects points either in the specified region or in the whole image if the mask is null. + Size of the averaging block, passed to underlying cvCornerMinEigenVal or cvCornerHarris used by the function. + If true, Harris operator (cvCornerHarris) is used instead of default cvCornerMinEigenVal. + + + + Determines strong corners on image + + The source 8-bit or floating-point 32-bit, single-channel image. + Temporary floating-point 32-bit image of the same size as image. + Another temporary image of the same size and same format as eig_image. + Output parameter. Detected corners. + Output parameter. Number of detected corners. + Multiplier for the maxmin eigenvalue; specifies minimal accepted quality of image corners. + Limit, specifying minimum possible distance between returned corners; Euclidian distance is used. + Region of interest. The function selects points either in the specified region or in the whole image if the mask is null. + Size of the averaging block, passed to underlying cvCornerMinEigenVal or cvCornerHarris used by the function. + If true, Harris operator (cvCornerHarris) is used instead of default cvCornerMinEigenVal. + Free parameter of Harris detector; used only if use_harris is true. + + + + Grabs the frame from camera or file. The grabbed frame is stored internally. + The purpose of this function is to grab frame fast that is important for syncronization in case of reading from several cameras simultaneously. + The grabbed frames are not exposed because they may be stored in compressed format (as defined by camera/driver). + To retrieve the grabbed frame, cvRetrieveFrame should be used. + + video capturing structure. + + + + + Adds vertex to graph + + Graph. + The function cvGraphAddVtx adds a vertex to the graph and returns the vertex index. + + + + Adds vertex to graph + + Graph. + Optional input argument used to initialize the added vertex (only user-defined fields beyond sizeof(CvGraphVtx) are copied). + The function cvGraphAddVtx adds a vertex to the graph and returns the vertex index. + + + + Adds vertex to graph + + Graph. + Optional input argument used to initialize the added vertex (only user-defined fields beyond sizeof(CvGraphVtx) are copied). + The address of the new vertex is written there. + The function cvGraphAddVtx adds a vertex to the graph and returns the vertex index. + + + + Adds edge to graph + + Graph. + Index of the starting vertex of the edge. + Index of the ending vertex of the edge. For unoriented graph the order of the vertex parameters does not matter. + The function cvGraphAddEdge connects two specified vertices. The function returns 1 if the edge has been added successfully, 0 if the edge connecting the two vertices exists already and -1 if either of the vertices was not found, the starting and the ending vertex are the same or there is some other critical situation. In the latter case (i.e. when the result is negative) the function also reports an error by default. + + + + Adds edge to graph + + Graph. + Index of the starting vertex of the edge. + Index of the ending vertex of the edge. For unoriented graph the order of the vertex parameters does not matter. + Optional input parameter, initialization data for the edge. + The function cvGraphAddEdge connects two specified vertices. The function returns 1 if the edge has been added successfully, 0 if the edge connecting the two vertices exists already and -1 if either of the vertices was not found, the starting and the ending vertex are the same or there is some other critical situation. In the latter case (i.e. when the result is negative) the function also reports an error by default. + + + + Adds edge to graph + + Graph. + Index of the starting vertex of the edge. + Index of the ending vertex of the edge. For unoriented graph the order of the vertex parameters does not matter. + Optional input parameter, initialization data for the edge. + Optional output parameter to contain the address of the inserted edge. + The function cvGraphAddEdge connects two specified vertices. The function returns 1 if the edge has been added successfully, 0 if the edge connecting the two vertices exists already and -1 if either of the vertices was not found, the starting and the ending vertex are the same or there is some other critical situation. In the latter case (i.e. when the result is negative) the function also reports an error by default. + + + + Adds edge to graph + + Graph. + Starting vertex of the edge. + Ending vertex of the edge. For unoriented graph the order of the vertex parameters does not matter. + The function cvGraphAddEdge connects two specified vertices. The function returns 1 if the edge has been added successfully, 0 if the edge connecting the two vertices exists already and -1 if either of the vertices was not found, the starting and the ending vertex are the same or there is some other critical situation. In the latter case (i.e. when the result is negative) the function also reports an error by default. + + + + Adds edge to graph + + Graph. + Starting vertex of the edge. + Ending vertex of the edge. For unoriented graph the order of the vertex parameters does not matter. + Optional input parameter, initialization data for the edge. + The function cvGraphAddEdge connects two specified vertices. The function returns 1 if the edge has been added successfully, 0 if the edge connecting the two vertices exists already and -1 if either of the vertices was not found, the starting and the ending vertex are the same or there is some other critical situation. In the latter case (i.e. when the result is negative) the function also reports an error by default. + + + + Adds edge to graph + + Graph. + Starting vertex of the edge. + Ending vertex of the edge. For unoriented graph the order of the vertex parameters does not matter. + Optional input parameter, initialization data for the edge. + Optional output parameter to contain the address of the inserted edge. + The function cvGraphAddEdge connects two specified vertices. The function returns 1 if the edge has been added successfully, 0 if the edge connecting the two vertices exists already and -1 if either of the vertices was not found, the starting and the ending vertex are the same or there is some other critical situation. In the latter case (i.e. when the result is negative) the function also reports an error by default. + + + + Returns index of graph edge + + Graph. + Graph edge. + The function cvGraphEdgeIdx returns index of the graph edge. + + + + Returns count of edges + + Graph. + + + + + Returns count of vertex + + Graph. + + + + + Removes edge from graph + + Graph. + Index of the starting vertex of the edge. + Index of the ending vertex of the edge. For unoriented graph the order of the vertex parameters does not matter. + The function cvGraphRemoveEdge removes the edge connecting two specified vertices. If the vertices are not connected [in that order], the function does nothing. + + + + Removes edge from graph + + Graph. + Starting vertex of the edge. + Ending vertex of the edge. For unoriented graph the order of the vertex parameters does not matter. + The function cvGraphRemoveEdgeByPtr removes the edge connecting two specified vertices. If the vertices are not connected [in that order], the function does nothing. + + + + Removes vertex from graph + + Graph. + Index of the removed vertex. + The function cvGraphRemoveAddVtx removes a vertex from the graph together with all the edges incident to it. The function reports an error, if the input vertex does not belong to the graph. The return value is number of edges deleted, or -1 if the vertex does not belong to the graph. + + + + Removes vertex from graph + + Graph. + Vertex to remove + The function cvGraphRemoveVtxByPtr removes a vertex from the graph together with all the edges incident to it. The function reports an error, if the vertex does not belong to the graph. The return value is number of edges deleted, or -1 if the vertex does not belong to the graph. + + + + Counts edges indicent to the vertex + + Graph. + Index of the graph vertex. + The function cvGraphVtxDegree returns the number of edges incident to the specified vertex, both incoming and outcoming. + + + + Counts edges indicent to the vertex + + Graph. + Index of the graph vertex. + The function cvGraphVtxDegree returns the number of edges incident to the specified vertex, both incoming and outcoming. + + + + Returns index of graph vertex + + Graph. + Graph vertex. + The function cvGraphVtxIdx returns index of the graph vertex. + + + + Calculates all of the decomposition coefficients for an input object. (ioFlags = CV_EIGOBJ_NO_CALLBACK) + + Input object. + Pointer to the array of IplImage input objects. + Averaged object. + Calculated coefficients; an output parameter. + + + + Calculates all of the decomposition coefficients for an input object. + + Input object. + Number of eigen objects. + ointer to the read callback function. + Input/output flags. + Pointer to the structure that contains all of the necessary data for the callback functions. + Averaged object. + Calculated coefficients; an output parameter. + + + + Calculates the object projection into the eigen sub-space. (ioFlags = CV_EIGOBJ_NO_CALLBACK) + + Pointer to an array of IplImage input objects. + Number of eigenvectors. + Previously calculated decomposition coefficients. + Average vector + Projection to the eigen sub-space. + + + + Calculates the object projection into the eigen sub-space. + + Pointer to to a callback function, depending on io_flags. + Number of eigenvectors. + Input/output flags + Pointer to the structure that contains all of the necessary data for the callback functions. + Previously calculated decomposition coefficients. + Average vector + Projection to the eigen sub-space. + + + + Computes eigenvalues and eigenvectors of symmetric matrix + + The input symmetric square matrix. It is modified during the processing. + The output matrix of eigenvectors, stored as a subsequent rows. + The output vector of eigenvalues, stored in the descending order (order of eigenvalues and eigenvectors is synchronized, of course). + + + + Computes eigenvalues and eigenvectors of symmetric matrix + + The input symmetric square matrix. It is modified during the processing. + The output matrix of eigenvectors, stored as a subsequent rows. + The output vector of eigenvalues, stored in the descending order (order of eigenvalues and eigenvectors is synchronized, of course). + Accuracy of diagonalization (typically, DBL_EPSILON=≈10-15 is enough). + + + + Computes eigenvalues and eigenvectors of symmetric matrix + + The input symmetric square matrix. It is modified during the processing. + The output matrix of eigenvectors, stored as a subsequent rows. + The output vector of eigenvalues, stored in the descending order (order of eigenvalues and eigenvectors is synchronized, of course). + Accuracy of diagonalization (typically, DBL_EPSILON=≈10-15 is enough). + Optional index of largest eigenvalue/-vector to calculate. + + + + Computes eigenvalues and eigenvectors of symmetric matrix + + The input symmetric square matrix. It is modified during the processing. + The output matrix of eigenvectors, stored as a subsequent rows. + The output vector of eigenvalues, stored in the descending order (order of eigenvalues and eigenvectors is synchronized, of course). + Accuracy of diagonalization (typically, DBL_EPSILON=≈10-15 is enough). + Optional index of largest eigenvalue/-vector to calculate. + Optional index of smallest eigenvalue/-vector to calculate. + + + + Draws simple or thick elliptic arc or fills ellipse sector + + Image. + Center of the ellipse. + Length of the ellipse axes. + Rotation angle. + Starting angle of the elliptic arc. + Ending angle of the elliptic arc. + Ellipse color. + + + + Draws simple or thick elliptic arc or fills ellipse sector + + Image. + Center of the ellipse. + Length of the ellipse axes. + Rotation angle. + Starting angle of the elliptic arc. + Ending angle of the elliptic arc. + Ellipse color. + Thickness of the ellipse arc. + + + + Draws simple or thick elliptic arc or fills ellipse sector + + Image. + Center of the ellipse. + Length of the ellipse axes. + Rotation angle. + Starting angle of the elliptic arc. + Ending angle of the elliptic arc. + Ellipse color. + Thickness of the ellipse arc. + Type of the ellipse boundary. + + + + Draws simple or thick elliptic arc or fills ellipse sector + + Image. + Center of the ellipse. + Length of the ellipse axes. + Rotation angle. + Starting angle of the elliptic arc. + Ending angle of the elliptic arc. + Ellipse color. + Thickness of the ellipse arc. + Type of the ellipse boundary. + Number of fractional bits in the center coordinates and axes' values. + + + + Draws simple or thick elliptic arc or fills ellipse sector + + Image. + Center of the ellipse. + Length of the ellipse axes. + Rotation angle. + Starting angle of the elliptic arc. + Ending angle of the elliptic arc. + Ellipse color. + + + + Draws simple or thick elliptic arc or fills ellipse sector + + Image. + Center of the ellipse. + Length of the ellipse axes. + Rotation angle. + Starting angle of the elliptic arc. + Ending angle of the elliptic arc. + Ellipse color. + Thickness of the ellipse arc. + + + + Draws simple or thick elliptic arc or fills ellipse sector + + Image. + Center of the ellipse. + Length of the ellipse axes. + Rotation angle. + Starting angle of the elliptic arc. + Ending angle of the elliptic arc. + Ellipse color. + Thickness of the ellipse arc. + Type of the ellipse boundary. + + + + Draws simple or thick elliptic arc or fills ellipse sector + + Image. + Center of the ellipse. + Length of the ellipse axes. + Rotation angle. + Starting angle of the elliptic arc. + Ending angle of the elliptic arc. + Ellipse color. + Thickness of the ellipse arc. + Type of the ellipse boundary. + Number of fractional bits in the center coordinates and axes' values. + + + + Draws simple or thick elliptic arc or fills ellipse sector + + Image. + The enclosing box of the ellipse drawn + Ellipse color. + + + + Draws simple or thick elliptic arc or fills ellipse sector + + Image. + The enclosing box of the ellipse drawn + Ellipse color. + Thickness of the ellipse boundary. + + + + Draws simple or thick elliptic arc or fills ellipse sector + + Image. + The enclosing box of the ellipse drawn + Ellipse color. + Thickness of the ellipse boundary. + Type of the ellipse boundary + + + + Draws simple or thick elliptic arc or fills ellipse sector + + Image. + The enclosing box of the ellipse drawn + Ellipse color. + Thickness of the ellipse boundary. + Type of the ellipse boundary + Number of fractional bits in the box vertex coordinates. + + + + Approximates elliptic arc with polyline + + Center of the arc. + Half-sizes of the arc. See cvEllipse. + Rotation angle of the ellipse in degrees. See cvEllipse. + Starting angle of the elliptic arc. + Ending angle of the elliptic arc. + The array of points, filled by the function. + Angle between the subsequent polyline vertices, approximation accuracy. So, the total number of output points will ceil((end_angle - start_angle)/delta) + 1 at max. + The function cvEllipse2Poly computes vertices of the polyline that approximates the specified elliptic arc. It is used by cvEllipse. It returns the numbers of output points. + + + + Encode image and store the result as a byte vector (single-row 8uC1 matrix) + + The file extension that defines the output format + The image to be written + The format-specific parameters + + + + + Encode image and store the result as a byte vector (single-row 8uC1 matrix) + + The file extension that defines the output format + The image to be written + The format-specific parameters + + + + + Finishes scanning process + + Contour scanner. + + + + + Finishes process of writing sequence + + Writer state + the pointer to the written sequence. + + + + Ends writing a structure + + File storage. + + + + Equalizes histogram of grayscale image. + + The input 8-bit single-channel image. + The output image of the same size and the same data type as src. + + + + Erodes image by using arbitrary structuring element. + + Source image. + Destination image. + + + + Erodes image by using arbitrary structuring element. + + Source image. + Destination image. + Structuring element used for erosion. If it is null, a 3x3 rectangular structuring element is used. + + + + Erodes image by using arbitrary structuring element. + + Source image. + Destination image. + Structuring element used for erosion. If it is null, a 3x3 rectangular structuring element is used. + Number of times erosion is applied. + + + + Raises an error + + The error status. + Name of the function where the error occurred. + Additional information/diagnostics about the error. + Name of the file where the error occurred. + Line number, where the error occurred. + + + + Returns textual description of error status code + + The error status. + The textual description for the specified error status code. + + + + Estimate rigid transformation between 2 images or 2 point sets + + + + + + + + + + Calculates exponent of every array element + + The source array. + The destination array, it should have double type or the same type as the source. + + + + Extracts the contours of Maximally Stable Extremal Regions + + + + + + + + + + Extracts Speeded Up Robust Features from image + + The input 8-bit grayscale image. + The optional input 8-bit mask. The features are only found in the areas that contain more than 50% of non-zero mask pixels. + The output parameter; double pointer to the sequence of keypoints. This will be the sequence of CvSURFPoint structures. + The optional output parameter; double pointer to the sequence of descriptors; Depending on the params.extended value, each element of the sequence will be either 64-element or 128-element floating-point (CV_32F) vector. If the parameter is null, the descriptors are not computed. + Memory storage where keypoints and descriptors will be stored. + Various algorithm parameters put to the structure CvSURFParams + + + + Extracts Speeded Up Robust Features from image + + The input 8-bit grayscale image. + The optional input 8-bit mask. The features are only found in the areas that contain more than 50% of non-zero mask pixels. + The output parameter; double pointer to the sequence of keypoints. This will be the sequence of CvSURFPoint structures. + The optional output parameter; double pointer to the sequence of descriptors; Depending on the params.extended value, each element of the sequence will be either 64-element or 128-element floating-point (CV_32F) vector. If the parameter is null, the descriptors are not computed. + Memory storage where keypoints and descriptors will be stored. + Various algorithm parameters put to the structure CvSURFParams + If useProvidedKeyPts!=0, keypoints are not detected, but descriptors are computed at the locations provided in keypoints (a CvSeq of CvSURFPoint). + + + + Extracts Speeded Up Robust Features from image + + The input 8-bit grayscale image. + The optional input 8-bit mask. The features are only found in the areas that contain more than 50% of non-zero mask pixels. + The output parameter; double pointer to the sequence of keypoints. This will be the sequence of CvSURFPoint structures. + The optional output parameter; double pointer to the sequence of descriptors; Depending on the params.extended value, each element of the sequence will be either 64-element or 128-element floating-point (CV_32F) vector. If the parameter is null, the descriptors are not computed. + Various algorithm parameters put to the structure CvSURFParams + + + + Extracts Speeded Up Robust Features from image + + The input 8-bit grayscale image. + The optional input 8-bit mask. The features are only found in the areas that contain more than 50% of non-zero mask pixels. + The output parameter; double pointer to the sequence of keypoints. This will be the sequence of CvSURFPoint structures. + The optional output parameter; double pointer to the sequence of descriptors; Depending on the params.extended value, each element of the sequence will be either 64-element or 128-element floating-point (CV_32F) vector. If the parameter is null, the descriptors are not computed. + Various algorithm parameters put to the structure CvSURFParams + If useProvidedKeyPts!=0, keypoints are not detected, but descriptors are computed at the locations provided in keypoints (a CvSeq of CvSURFPoint). + + + + Increments array data reference counter + + Array header. + The function cvIncRefData increments CvMat or CvMatND data reference counter and returns the new counter value if the reference counter pointer is not NULL, otherwise it returns zero. + + + + + + + + + + + + Initializes font structure + + font structure initialized by the function. + Font name identifier. Only a subset of Hershey fonts are supported now. + Horizontal scale. If equal to 1.0f, the characters have the original width depending on the font type. If equal to 0.5f, the characters are of half the original width. + Vertical scale. If equal to 1.0f, the characters have the original height depending on the font type. If equal to 0.5f, the characters are of half the original height. + + + + Initializes font structure + + font structure initialized by the function. + Font name identifier. Only a subset of Hershey fonts are supported now. + Horizontal scale. If equal to 1.0f, the characters have the original width depending on the font type. If equal to 0.5f, the characters are of half the original width. + Vertical scale. If equal to 1.0f, the characters have the original height depending on the font type. If equal to 0.5f, the characters are of half the original height. + Approximate tangent of the character slope relative to the vertical line. Zero value means a non-italic font, 1.0f means ≈45° slope, etc. thickness Thickness of lines composing letters outlines. The function cvLine is used for drawing letters. + + + + Initializes font structure + + font structure initialized by the function. + Font name identifier. Only a subset of Hershey fonts are supported now. + Horizontal scale. If equal to 1.0f, the characters have the original width depending on the font type. If equal to 0.5f, the characters are of half the original width. + Vertical scale. If equal to 1.0f, the characters have the original height depending on the font type. If equal to 0.5f, the characters are of half the original height. + Approximate tangent of the character slope relative to the vertical line. Zero value means a non-italic font, 1.0f means ≈45° slope, etc. thickness Thickness of lines composing letters outlines. The function cvLine is used for drawing letters. + Thickness of the text strokes. + + + + Initializes font structure + + font structure initialized by the function. + Font name identifier. Only a subset of Hershey fonts are supported now. + Horizontal scale. If equal to 1.0f, the characters have the original width depending on the font type. If equal to 0.5f, the characters are of half the original width. + Vertical scale. If equal to 1.0f, the characters have the original height depending on the font type. If equal to 0.5f, the characters are of half the original height. + Approximate tangent of the character slope relative to the vertical line. Zero value means a non-italic font, 1.0f means ≈45° slope, etc. thickness Thickness of lines composing letters outlines. The function cvLine is used for drawing letters. + Thickness of the text strokes. + Type of the strokes, see cvLine description. + + + + Initializes allocated by user image header + + Image header to initialise. + Image width and height. + Image depth. + Number of channels. + Initialzed IplImage header + + + + Initializes allocated by user image header + + Image header to initialise. + Image width and height. + Image depth. + Number of channels. + Origin of image + Initialzed IplImage header + + + + Initializes allocated by user image header + + Image header to initialise. + Image width and height. + Image depth. + Number of channels. + Origin of image + Alignment for image rows, typically 4 or 8 bytes. + Initialzed IplImage header + + + + Finds the initial camera matrix from the 3D-2D point correspondences + + The joint array of object points + The joint array of object point projections + The array of point counts + The image size in pixels + The output camera matrix + + + + Finds the initial camera matrix from the 3D-2D point correspondences + + The joint array of object points + The joint array of object point projections + The array of point counts + The image size in pixels + The output camera matrix + If it is zero or negative, both f_x and f_y are estimated independently. Otherwise f_x = f_y * aspectRatio + + + + Initializes line iterator + + Image to sample the line from. + First ending point of the line segment. + Second ending point of the line segment. + Line iterator state structure to be generated. + The function cvInitLineIterator initializes the line iterator and returns the number of pixels between two end points. Both points must be inside the image. After the iterator has been initialized, all the points on the raster line that connects the two ending points may be retrieved by successive calls of NextLinePoint point. The points on the line are calculated one by one using 4-connected or 8-connected Bresenham algorithm. + + + + Initializes line iterator + + Image to sample the line from. + First ending point of the line segment. + Second ending point of the line segment. + Line iterator state structure to be generated. + The scanned line connectivity, 4 or 8. + The function cvInitLineIterator initializes the line iterator and returns the number of pixels between two end points. Both points must be inside the image. After the iterator has been initialized, all the points on the raster line that connects the two ending points may be retrieved by successive calls of NextLinePoint point. The points on the line are calculated one by one using 4-connected or 8-connected Bresenham algorithm. + + + + Initializes line iterator + + Image to sample the line from. + First ending point of the line segment. + Second ending point of the line segment. + Line iterator state structure to be generated. + The scanned line connectivity, 4 or 8. + The flag, indicating whether the line should be always scanned from the left-most point to the right-most out of pt1 and pt2 (left_to_right=true), or it is scanned in the specified order, from pt1 to pt2 (left_to_right=false). + The function cvInitLineIterator initializes the line iterator and returns the number of pixels between two end points. Both points must be inside the image. After the iterator has been initialized, all the points on the raster line that connects the two ending points may be retrieved by successive calls of NextLinePoint point. The points on the line are calculated one by one using 4-connected or 8-connected Bresenham algorithm. + + + + Initializes matrix header. + + Reference to the matrix header to be initialized. + Number of rows in the matrix. + Number of columns in the matrix. + Type of the matrix elements. + + + + + Initializes matrix header. + + + Reference to the matrix header to be initialized. + Number of rows in the matrix. + Number of columns in the matrix. + Type of the matrix elements. + Optional data pointer assigned to the matrix header. + + + + + Initializes matrix header. + + + Reference to the matrix header to be initialized. + Number of rows in the matrix. + Number of columns in the matrix. + Type of the matrix elements. + Optional data pointer assigned to the matrix header. + Full row width in bytes of the data assigned. By default, the minimal possible step is used, i.e., no gaps is assumed between subsequent rows of the matrix. + + + + + Initializes multi-dimensional array header. + + Reference to the array header to be initialized. + Number of array dimensions. + Array of dimension sizes. + Type of array elements. The same as for CvMat. + + + + + Initializes multi-dimensional array header. + + + Reference to the array header to be initialized. + Number of array dimensions. + Array of dimension sizes. + Type of array elements. The same as for CvMat. + Optional data pointer assigned to the matrix header. + + + + + Initializes sparse array elements iterator + + Input array + Initialized iterator + the first sparse matrix element + + + + CvSubdiv2Dの初期化 + + + + + + + Initializes tree node iterator + + Tree iterator initialized by the function. + The initial node to start traversing from. + The maximal level of the tree (first node assumed to be at the first level) to traverse up to. For example, 1 means that only nodes at the same level as first should be visited, 2 means that the nodes on the same level as first and their direct children should be visited etc. + + + + Pre-computes the undistortion map - coordinates of the corresponding pixel in the distorted image for every pixel in the corrected image. + + The camera matrix (A) [fx 0 cx; 0 fy cy; 0 0 1]. + The vector of distortion coefficients, 4x1 or 1x4 [k1, k2, p1, p2]. + The output array of x-coordinates of the map. + The output array of y-coordinates of the map. + + + + Computes undistortion+rectification transformation map a head of stereo camera + + The camera matrix A=[fx 0 cx; 0 fy cy; 0 0 1]. + The vector of distortion coefficients, 4x1, 1x4, 5x1 or 1x5. + The rectification transformation in object space (3x3 matrix). R1 or R2, computed by cvStereoRectify can be passed here. If the parameter is null, the identity matrix is used. + The new camera matrix A'=[fx' 0 cx'; 0 fy' cy'; 0 0 1]. + The output array of x-coordinates of the map. + The output array of y-coordinates of the map. + + + + Inpaints the selected region in the image. + + The input 8-bit 1-channel or 3-channel image. + The inpainting mask, 8-bit 1-channel image. Non-zero pixels indicate the area that needs to be inpainted. + The output image of the same format and the same size as input. + The radius of circlular neighborhood of each point inpainted that is considered by the algorithm. + The inpainting method. + + + + Checks that array elements lie between elements of two other arrays + + The first source array. + The inclusive lower boundary array. + The exclusive upper boundary array. + The destination array, must have 8u or 8s type. + + + + Checks that array elements lie between two scalars + + The first source array. + The inclusive lower boundary. + The exclusive upper boundary. + The destination array, must have 8u or 8s type. + + + + Adds new node to the tree + + + The inserted node. + The parent node that is already in the tree. + The top level node. If parent and frame are the same, v_prev field of node is set to null rather than parent. + + + + Calculates integral images. + + The source image, WxH, 8-bit or floating-point (32f or 64f) image. + The integral image, W+1xH+1, 32-bit integer or double precision floating-point (64f). + + + + Calculates integral images. + + The source image, WxH, 8-bit or floating-point (32f or 64f) image. + The integral image, W+1xH+1, 32-bit integer or double precision floating-point (64f). + The integral image for squared pixel values, W+1xH+1, double precision floating-point (64f). + + + + Calculates integral images. + + The source image, WxH, 8-bit or floating-point (32f or 64f) image. + The integral image, W+1xH+1, 32-bit integer or double precision floating-point (64f). + The integral image for squared pixel values, W+1xH+1, double precision floating-point (64f). + The integral for the image rotated by 45 degrees, W+1xH+1, the same data type as sum. + + + + Finds inverse or pseudo-inverse of matrix + + The source matrix. + The destination matrix. + In case of LU method the function returns src1 determinant (src1 must be square). + If it is 0, the matrix is not inverted and src2 is filled with zeros. + In case of SVD methods the function returns the inverted condition number of src1 + + + + Finds inverse or pseudo-inverse of matrix + + The source matrix. + The destination matrix. + Inversion method + In case of LU method the function returns src1 determinant (src1 must be square). + If it is 0, the matrix is not inverted and src2 is filled with zeros. + In case of SVD methods the function returns the inverted condition number of src1 + + + + Finds inverse or pseudo-inverse of matrix + + The source matrix. + The destination matrix. + In case of LU method the function returns src1 determinant (src1 must be square). + If it is 0, the matrix is not inverted and src2 is filled with zeros. + In case of SVD methods the function returns the inverted condition number of src1 + + + + Finds inverse or pseudo-inverse of matrix + + The source matrix. + The destination matrix. + Inversion method + In case of LU method the function returns src1 determinant (src1 must be square). + If it is 0, the matrix is not inverted and src2 is filled with zeros. + In case of SVD methods the function returns the inverted condition number of src1 + + + + Calculates inverse square root + + The input floating-point value + + + + + + + + + + + + Determines if the argument is Infinity + + The input floating-point value + + + + + Determines if the argument is Not A Number + + The input floating-point value + + + + + Adjusts model state + + Kalman filter + CvMat containing the measurement vector. + The function stores adjusted state at kalman->state_post and returns it on output. + + + + Adjusts model state + + Kalman filter + CvMat containing the measurement vector. + The function stores adjusted state at kalman->state_post and returns it on output. + + + + Estimates subsequent model state + + Kalman filter state. + The function returns the estimated state. + + + + Estimates subsequent model state + + Kalman filter state. + Control vector (uk), should be null iff there is no external control (control_params=0). + The function returns the estimated state. + + + + Estimates subsequent model state + + Kalman filter state. + The function returns the estimated state. + + + + Estimates subsequent model state + + Kalman filter state. + Control vector (uk), should be null iff there is no external control (control_params=0). + The function returns the estimated state. + + + + Splits set of vectors by given number of clusters + + Floating-point matrix of input samples, one row per sample. + Number of clusters to split the set by. + Output integer vector storing cluster indices for every sample. + Specifies maximum number of iterations and/or accuracy (distance the centers move by between the subsequent iterations). + + + + + Splits set of vectors by given number of clusters + + Floating-point matrix of input samples, one row per sample. + Number of clusters to split the set by. + Output integer vector storing cluster indices for every sample. + Specifies maximum number of iterations and/or accuracy (distance the centers move by between the subsequent iterations). + + + + + + Splits set of vectors by given number of clusters + + Floating-point matrix of input samples, one row per sample. + Number of clusters to split the set by. + Output integer vector storing cluster indices for every sample. + Specifies maximum number of iterations and/or accuracy (distance the centers move by between the subsequent iterations). + + + + + + + + Splits set of vectors by given number of clusters + + Floating-point matrix of input samples, one row per sample. + Number of clusters to split the set by. + Output integer vector storing cluster indices for every sample. + Specifies maximum number of iterations and/or accuracy (distance the centers move by between the subsequent iterations). + + + + + + + + + Splits set of vectors by given number of clusters + + Floating-point matrix of input samples, one row per sample. + Number of clusters to split the set by. + Output integer vector storing cluster indices for every sample. + Specifies maximum number of iterations and/or accuracy (distance the centers move by between the subsequent iterations). + + + + + + + + + + Splits set of vectors by given number of clusters + + Floating-point matrix of input samples, one row per sample. + + Number of clusters to split the set by. + Output integer vector storing cluster indices for every sample. + Specifies maximum number of iterations and/or accuracy (distance the centers move by between the subsequent iterations). + + + + + Splits set of vectors by given number of clusters + + Floating-point matrix of input samples, one row per sample. + + Number of clusters to split the set by. + Output integer vector storing cluster indices for every sample. + Specifies maximum number of iterations and/or accuracy (distance the centers move by between the subsequent iterations). + + + + + + + + Splits set of vectors by given number of clusters + + Floating-point matrix of input samples, one row per sample. + + Number of clusters to split the set by. + Output integer vector storing cluster indices for every sample. + Specifies maximum number of iterations and/or accuracy (distance the centers move by between the subsequent iterations). + + + + + + + + + Splits set of vectors by given number of clusters + + Floating-point matrix of input samples, one row per sample. + + Number of clusters to split the set by. + Output integer vector storing cluster indices for every sample. + Specifies maximum number of iterations and/or accuracy (distance the centers move by between the subsequent iterations). + + + + + + + + + + Calculates Laplacian of the source image by summing second x- and y- derivatives calculated using Sobel operator. + + Source image. + Destination image. + + + + Calculates Laplacian of the source image by summing second x- and y- derivatives calculated using Sobel operator. + + Source image. + Destination image. + Aperture size (it has the same meaning as in cvSobel). + + + + find rectangular regions in the given image that are likely + to contain objects and corresponding confidence levels + + image to detect objects in + Latent SVM detector in internal representation + memory storage to store the resultant sequence of the object candidate rectangles + + + + + find rectangular regions in the given image that are likely + to contain objects and corresponding confidence levels + + image to detect objects in + Latent SVM detector in internal representation + memory storage to store the resultant sequence of the object candidate rectangles + threshold for the non-maximum suppression algorithm + = 0.5f [here will be the reference to original paper] + + + + + find rectangular regions in the given image that are likely + to contain objects and corresponding confidence levels + + image to detect objects in + Latent SVM detector in internal representation + memory storage to store the resultant sequence of the object candidate rectangles + threshold for the non-maximum suppression algorithm + = 0.5f [here will be the reference to original paper] + + + + + + Draws a line segment connecting two points + + The image. + First point's x-coordinate of the line segment. + First point's y-coordinate of the line segment. + Second point's x-coordinate of the line segment. + Second point's y-coordinate of the line segment. + Line color. + + + + Draws a line segment connecting two points + + The image. + First point's x-coordinate of the line segment. + First point's y-coordinate of the line segment. + Second point's x-coordinate of the line segment. + Second point's y-coordinate of the line segment. + Line color. + Line thickness. + + + + Draws a line segment connecting two points + + The image. + First point's x-coordinate of the line segment. + First point's y-coordinate of the line segment. + Second point's x-coordinate of the line segment. + Second point's y-coordinate of the line segment. + Line color. + Line thickness. + Type of the line. + + + + Draws a line segment connecting two points + + The image. + First point's x-coordinate of the line segment. + First point's y-coordinate of the line segment. + Second point's x-coordinate of the line segment. + Second point's y-coordinate of the line segment. + Line color. + Line thickness. + Type of the line. + Number of fractional bits in the point coordinates. + + + + Draws a line segment connecting two points + + The image. + First point of the line segment. + Second point of the line segment. + Line color. + + + + Draws a line segment connecting two points + + The image. + First point of the line segment. + Second point of the line segment. + Line color. + Line thickness. + + + + Draws a line segment connecting two points + + The image. + First point of the line segment. + Second point of the line segment. + Line color. + Line thickness. + Type of the line. + + + + Draws a line segment connecting two points + + The image. + First point of the line segment. + Second point of the line segment. + Line color. + Line thickness. + Type of the line. + Number of fractional bits in the point coordinates. + + + + Draws a line segment connecting two points + + The image. + First point's x-coordinate of the line segment. + First point's y-coordinate of the line segment. + Second point's x-coordinate of the line segment. + Second point's y-coordinate of the line segment. + Line color. + + + + Draws a line segment connecting two points + + The image. + First point's x-coordinate of the line segment. + First point's y-coordinate of the line segment. + Second point's x-coordinate of the line segment. + Second point's y-coordinate of the line segment. + Line color. + Line thickness. + + + + Draws a line segment connecting two points + + The image. + First point's x-coordinate of the line segment. + First point's y-coordinate of the line segment. + Second point's x-coordinate of the line segment. + Second point's y-coordinate of the line segment. + Line color. + Line thickness. + Type of the line. + + + + Draws a line segment connecting two points + + The image. + First point's x-coordinate of the line segment. + First point's y-coordinate of the line segment. + Second point's x-coordinate of the line segment. + Second point's y-coordinate of the line segment. + Line color. + Line thickness. + Type of the line. + Number of fractional bits in the point coordinates. + + + + Draws a line segment connecting two points + + The image. + First point of the line segment. + Second point of the line segment. + Line color. + + + + Draws a line segment connecting two points + + The image. + First point of the line segment. + Second point of the line segment. + Line color. + Line thickness. + + + + Draws a line segment connecting two points + + The image. + First point of the line segment. + Second point of the line segment. + Line color. + Line thickness. + Type of the line. + + + + Draws a line segment connecting two points + + The image. + First point of the line segment. + Second point of the line segment. + Line color. + Line thickness. + Type of the line. + Number of fractional bits in the point coordinates. + + + + Performs forward or inverse linear-polar image transform + + + + + + + + + Performs forward or inverse linear-polar image transform + + + + + + + + + + Loads object from file + + Object type to load + File name. + The function cvLoad loads object from file. + + + + Loads object from file + + Object type to load + File name. + Memory storage for dynamic structures, such as CvSeq or CvGraph. It is not used for matrices or images. + The function cvLoad loads object from file. + + + + Loads object from file + + Object type to load + File name. + Memory storage for dynamic structures, such as CvSeq or CvGraph. It is not used for matrices or images. + Optional object name. If it is NULL, the first top-level object in the storage will be loaded. + The function cvLoad loads object from file. + + + + Loads object from file + + Object type to load + File name. + Memory storage for dynamic structures, such as CvSeq or CvGraph. It is not used for matrices or images. + Optional object name. If it is NULL, the first top-level object in the storage will be loaded. + Optional output parameter that will contain name of the loaded object (useful if name=NULL). + The function cvLoad loads object from file. + + + + Loads a trained cascade classifier from file or the classifier database embedded in OpenCV + + Name of directory containing the description of a trained cascade classifier. + Original size of objects the cascade has been trained on. Note that it is not stored in the cascade and therefore must be specified separately. + + The function is obsolete. Nowadays object detection classifiers are stored in XML or YAML files, rather than in directories. To load cascade from a file, use cvLoad function. + + + + Loads an image from the specified file and returns the reference to the loaded image. + + Name of file to be loaded. + the reference to the loaded image. + + + + Loads an image from the specified file and returns the reference to the loaded image. + + Name of file to be loaded. + Specifies colorness and Depth of the loaded image. + the reference to the loaded image. + + + + Loads an image from the specified file and returns the reference to the loaded image as CvMat. + + Name of file to be loaded. + the reference to the loaded image. + + + + Loads an image from the specified file and returns the reference to the loaded image as CvMat. + + Name of file to be loaded. + Specifies colorness and Depth of the loaded image. + the reference to the loaded image. + + + + load trained detector from a file + + Name of file to be loaded. + + + + + Load parameters of the window. + + Name of the window + + + + Calculates natural logarithm of every array element absolute value + + The source array. + The destination array, it should have double type or the same type as the source. + + + + Remaps image to log-polar space. + The function emulates the human "foveal" vision and can be used for fast scale and rotation-invariant template matching, for object tracking etc. + + Source image. + Destination image. + The transformation center, where the output precision is maximal. + Magnitude scale parameter. See below. + + + + Remaps image to log-polar space. + The function emulates the human "foveal" vision and can be used for fast scale and rotation-invariant template matching, for object tracking etc. + + Source image. + Destination image. + The transformation center, where the output precision is maximal. + Magnitude scale parameter. See below. + A combination of interpolation method and the optional flags. + + + + Add vectors to the LSH structure, optionally returning indices. + + + + + + + Add vectors to the LSH structure, optionally returning indices. + + + + + + + + Query the LSH n times for at most k nearest points; data is n x d, + indices and dist are n x k. At most emax stored points will be accessed. + + + + + + + + + + + Remove vectors from LSH, as addressed by given indices. + + + + + + + Return the number of vectors in the LSH. + + + number of vectors + + + + Performs look-up table transform of array + + Source array of 8-bit elements. + Destination array of arbitrary depth and of the same number of channels as the source array. + Look-up table of 256 elements; should have the same depth as the destination array. In case of multi-channel source and destination arrays, the table should either have a single-channel (in this case the same table is used for all channels), or the same number of channels as the source/destination array. + + + + Performs look-up table transform of array + + Source array of 8-bit elements. + Destination array of arbitrary depth and of the same number of channels as the source array. + Look-up table of 256 elements; should have the same depth as the destination array. + + + + Performs look-up table transform of array + + Source array of 8-bit elements. + Destination array of arbitrary depth and of the same number of channels as the source array. + Look-up table of 256 elements; should have the same depth as the destination array. + + + + Performs look-up table transform of array + + Source array of 8-bit elements. + Destination array of arbitrary depth and of the same number of channels as the source array. + Look-up table of 256 elements; should have the same depth as the destination array. + + + + Performs look-up table transform of array + + Source array of 8-bit elements. + Destination array of arbitrary depth and of the same number of channels as the source array. + Look-up table of 256 elements; should have the same depth as the destination array. + + + + Performs look-up table transform of array + + Source array of 8-bit elements. + Destination array of arbitrary depth and of the same number of channels as the source array. + Look-up table of 256 elements; should have the same depth as the destination array. + + + + Calculates Mahalanobis distance between two vectors + + The first 1D source vector. + The second 1D source vector. + The inverse covariation matrix. + Mahalanobis distance + + + + Calculates Mahalonobis distance between two vectors + + The first 1D source vector. + The second 1D source vector. + The inverse covariation matrix. + Mahalonobis distance + + + + Makes a histogram out of array + + Number of histogram dimensions. + Array of histogram dimension sizes. + The histogram header initialized by the function. + Array that will be used to store histogram bins. + + + + Makes a histogram out of array + + Number of histogram dimensions. + Array of histogram dimension sizes. + The histogram header initialized by the function. + Array that will be used to store histogram bins. + Histogram bin ranges, see CreateHist. + + + + Makes a histogram out of array + + Number of histogram dimensions. + Array of histogram dimension sizes. + The histogram header initialized by the function. + Array that will be used to store histogram bins. + Histogram bin ranges, see CreateHist. + Uniformity flag, see CreateHist. + + + + Calculates scanlines coordinates for two cameras by fundamental matrix + + Fundamental matrix. + Size of the image. + Array of calculated scanlines of the first image. + Array of calculated scanlines of the second image. + Array of calculated lengths (in pixels) of the first image scanlines. + Array of calculated lengths (in pixels) of the second image scanlines. + Variable that stores the number of scanlines. + + + + Constructs sequence from array + + + Type of the created sequence. + Size of the header of the sequence. Parameter sequence must point to the structure of that size or greater size. + Size of the sequence element. + Elements that will form a sequence. + Pointer to the local variable that is used as the sequence header. + Pointer to the local variable that is the header of the single sequence block. + + + + + Initializes matrix header (light-weight variant) + + Number of rows in the matrix. + Number of columns in the matrix. + Type of the matrix elements (see CreateMat). + The function cvMat is a fast inline substitution for cvInitMatHeader. + + + + Initializes matrix header (light-weight variant) + + Number of rows in the matrix. + Number of columns in the matrix. + Type of the matrix elements (see CreateMat). + Optional data pointer assigned to the matrix header. + The function cvMat is a fast inline substitution for cvInitMatHeader. + + + + Compares two contours using their tree representations. + + First contour tree. + Second contour tree. + Similarity measure, only I1 is supported. + Similarity threshold. + + + + + Compares two shapes. + + First contour or grayscale image. + Second contour or grayscale image. + Comparison method. + + + + + Compares two shapes. + + First contour or grayscale image. + Second contour or grayscale image. + Comparison method. + Method-specific parameter (is not used now). + + + + + Compares template against overlapped image regions. + + Image where the search is running. It should be 8-bit or 32-bit floating-point. + Searched template; must be not greater than the source image and the same data type as the image. + A map of comparison results; single-channel 32-bit floating-point. If image is W×H and templ is w×h then result must be W-w+1×H-h+1. + Specifies the way the template must be compared with image regions. + + + + Finds per-element maximum of two arrays + + The first source array. + The second source array. + The destination array. + + + + Finds bounding rectangle for two given rectangles + + First rectangle + Second rectangle + + + + Finds per-element maximum of array and scalar + + The first source array. + The scalar value. + The destination array. + + + + Finds object center on back projection + + Back projection of object histogram (see cvCalcBackProject). + Initial search window. + Criteria applied to determine when the window search should be finished. + Resultant structure that contains converged search window coordinates (comp->rect field) and sum of all pixels inside the window (comp->area field). + The function returns number of iterations made within cvMeanShift. + + + + Allocates memory buffer in the storage + + Memory storage. + Buffer size. + + + + + Allocates text string in the storage + + Memory storage + The string + + + + + Composes multi-channel array from several single-channel arrays or inserts a single channel into the array + + Input channel 0 + Input channel 1 + Input channel 2 + Input channel 3 + Destination array. + + + + Composes multi-channel array from several single-channel arrays or inserts a single channel into the array + + Input channel 0 + Input channel 1 + Input channel 2 + Input channel 3 + Destination array. + + + + Return the particular element of single-channel floating-point matrix + + Input matrix. + The zero-based index of row. + The zero-based index of column. + + + + + Finds per-element minimum of two arrays + + The first source array. + The second source array. + The destination array. + + + + Finds global minimum and maximum in array or subarray + + The source array, single-channel or multi-channel with COI set. + Pointer to returned minimum value. + Pointer to returned maximum value. + + + + Finds global minimum and maximum in array or subarray + + The source array, single-channel or multi-channel with COI set. + Pointer to returned minimum value. + Pointer to returned maximum value. + The optional mask that is used to select a subarray. + + + + Finds global minimum and maximum in array or subarray + + The source array, single-channel or multi-channel with COI set. + Pointer to returned minimum location. + Pointer to returned maximum location. + + + + Finds global minimum and maximum in array or subarray + + The source array, single-channel or multi-channel with COI set. + Pointer to returned minimum location. + Pointer to returned maximum location. + The optional mask that is used to select a subarray. + + + + Finds global minimum and maximum in array or subarray + + The source array, single-channel or multi-channel with COI set. + Pointer to returned minimum value. + Pointer to returned maximum value. + Pointer to returned minimum location. + Pointer to returned maximum location. + + + + Finds global minimum and maximum in array or subarray + + The source array, single-channel or multi-channel with COI set. + Pointer to returned minimum value. + Pointer to returned maximum value. + Pointer to returned minimum location. + Pointer to returned maximum location. + The optional mask that is used to select a subarray. + + + + Finds circumscribed rectangle of minimal area for given 2D point set + + Sequence or array of points. + The function cvMinAreaRect2 finds a circumscribed rectangle of the minimal area for 2D point set by building convex hull for the set and applying rotating calipers technique to the hull. + + + + Finds circumscribed rectangle of minimal area for given 2D point set + + Sequence or array of points. + The point tested against the contour. + The function cvMinAreaRect2 finds a circumscribed rectangle of the minimal area for 2D point set by building convex hull for the set and applying rotating calipers technique to the hull. + + + + Finds circumscribed rectangle of minimal area for given 2D point set + + Sequence or array of 2D points. + Output parameter. The center of the enclosing circle. + Output parameter. The radius of the enclosing circle. + The function cvMinEnclosingCircle finds the minimal circumscribed circle for 2D point set using iterative algorithm. + It returns true if the resultant circle contains all the input points and false otherwise (i.e. algorithm failed). + + + + Finds circumscribed rectangle of minimal area for given 2D point set + + Sequence or array of 2D points. + Output parameter. The center of the enclosing circle. + Output parameter. The radius of the enclosing circle. + The function cvMinEnclosingCircle finds the minimal circumscribed circle for 2D point set using iterative algorithm. + It returns true if the resultant circle contains all the input points and false otherwise (i.e. algorithm failed). + + + + Finds circumscribed rectangle of minimal area for given 2D point set + + Sequence or array of 2D points. + Output parameter. The center of the enclosing circle. + Output parameter. The radius of the enclosing circle. + The function cvMinEnclosingCircle finds the minimal circumscribed circle for 2D point set using iterative algorithm. + It returns true if the resultant circle contains all the input points and false otherwise (i.e. algorithm failed). + + + + Finds per-element minimum of array and scalar + + The first source array. + The scalar value. + The destination array. + + + + Copies several channels from input arrays to certain channels of output arrays + + The array of input arrays. + The array of output arrays. + The array of pairs of indices of the planes copied. from_to[k*2] is the 0-based index of the input plane, and from_to[k*2+1] is the index of the output plane, where the continuous numbering of the planes over all the input and over all the output arrays is used. When from_to[k*2] is negative, the corresponding output plane is filled with 0's. + + + + Moments + + Image (1-channel or 3-channel with COI set) or polygon (CvSeq of points or a vector of points) + Returned moment state structure + (For images only) If the flag is non-zero, all the zero pixel values are treated as zeroes, all the others are treated as 1’s + + + + Performs advanced morphological transformations using erosion and dilation as basic operations. + + Source image. + Destination image. + Temporary image, required in some cases. + Structuring element. + Type of morphological operation. + + + + Performs advanced morphological transformations using erosion and dilation as basic operations. + + Source image. + Destination image. + Temporary image, required in some cases. + Structuring element. + Type of morphological operation. + Number of times erosion and dilation are applied. + + + + Changes position of the window. + + Name of the window to be resized. + New x coordinate of top-left corner + New y coordinate of top-left corner + + + + Creates MSER parameters + + + + + Creates MSER parameters + + delta, in the code, it compares (size_{i}-size_{i-delta})/size_{i-delta} + prune the area which smaller than min_area + prune the area which bigger than max_area + prune the area have simliar size to its children + trace back to cut off mser with diversity < min_diversity + for color image, the evolution steps + the area threshold to cause re-initialize + ignore too small margin + the aperture size for edge blur + + + + Return the particular element of single-channel floating-point matrix + + The matrix. + The zero-based index of row. + The zero-based index of column. + The new value of the matrix element + + + + Calculates per-element product of two arrays + + The first source array. + The second source array. + The destination array. + + + + Calculates per-element product of two arrays + + The first source array. + The second source array. + The destination array. + Optional scale factor + + + + Performs per-element multiplication of two Fourier spectrums + + The first source array. + The second source array. + The destination array of the same type and the same size of the sources. + + + + + Adds product of two input images to accumulator + + First input image, 1- or 3-channel, 8-bit or 32-bit floating point (each channel of multi-channel image is processed independently). + Second input image, the same format as the first one. + Accumulator of the same number of channels as input images, 32-bit or 64-bit floating-point. + + + + Adds product of two input images to accumulator + + First input image, 1- or 3-channel, 8-bit or 32-bit floating point (each channel of multi-channel image is processed independently). + Second input image, the same format as the first one. + Accumulator of the same number of channels as input images, 32-bit or 64-bit floating-point. + Optional operation mask. + + + + Calculates product of array and transposed array + + The source matrix. + The destination matrix. + Order of multipliers. + + + + Calculates product of array and transposed array + + The source matrix. + The destination matrix. + Order of multipliers. + An optional array, subtracted from src before multiplication. + + + + Calculates product of array and transposed array + + The source matrix. + The destination matrix. + Order of multipliers. + An optional array, subtracted from src before multiplication. + + + + + Creates a window which can be used as a placeholder for images and trackbars. Created windows are reffered by their names. + + Name of the window which is used as window identifier and appears in the window caption. + + + + + Creates a window which can be used as a placeholder for images and trackbars. Created windows are reffered by their names. + + Name of the window which is used as window identifier and appears in the window caption. + Flags of the window. Currently the only supported flag is WindowMode.AutoSize. + If it is set, window size is automatically adjusted to fit the displayed image (see cvShowImage), while user can not change the window size manually. + + + + + Returns index of graph vertex + + Graph traversal state. It is updated by the function. + The function cvNextGraphItem traverses through the graph until an event interesting to the user (that is, an event, specified in the mask in cvCreateGraphScanner call) is met or the traversal is over. In the first case it returns one of the events, listed in the description of mask parameter above and with the next call it resumes the traversal. In the latter case it returns CV_GRAPH_OVER (-1). When the event is CV_GRAPH_VERTEX, or CV_GRAPH_BACKTRACKING or CV_GRAPH_NEW_TREE, the currently observed vertex is stored in scanner->vtx. And if the event is edge-related, the edge itself is stored at scanner->edge, the previously visited vertex - at scanner->vtx and the other ending vertex of the edge - at scanner->dst. + + + + Moves iterator to the next line point + + LineIterator object + + + + + Returns the currently observed node and moves iterator toward the next node + + Tree iterator initialized by the function. + + + + + Returns the currently observed node and moves iterator toward the next node + + + Tree iterator initialized by the function. + + + + + Returns the currently observed node and moves iterator toward the next node + + + Tree iterator initialized by the function. + + + + + Calculates absolute array norm, absolute difference norm or relative difference norm + + The first source image. + + + + + Calculates absolute array norm, absolute difference norm or relative difference norm + + The first source image. + The second source image. If it is null, the absolute norm of arr1 is calculated, otherwise absolute or relative norm of arr1-arr2 is calculated. + + + + + Calculates absolute array norm, absolute difference norm or relative difference norm + + The first source image. + The second source image. If it is null, the absolute norm of arr1 is calculated, otherwise absolute or relative norm of arr1-arr2 is calculated. + Type of norm + + + + + Calculates absolute array norm, absolute difference norm or relative difference norm + + The first source image. + The second source image. If it is null, the absolute norm of arr1 is calculated, otherwise absolute or relative norm of arr1-arr2 is calculated. + Type of norm + The optional operation mask. + + + + + Normalizes array to a certain norm or value range + + The input array. + The output array; in-place operation is supported. + + + + Normalizes array to a certain norm or value range + + The input array. + The output array; in-place operation is supported. + The minimum/maximum value of the output array or the norm of output array. + The maximum/minimum value of the output array. + + + + Normalizes array to a certain norm or value range + + The input array. + The output array; in-place operation is supported. + The minimum/maximum value of the output array or the norm of output array. + The maximum/minimum value of the output array. + The normalization type. + + + + Normalizes array to a certain norm or value range + + The input array. + The output array; in-place operation is supported. + The minimum/maximum value of the output array or the norm of output array. + The maximum/minimum value of the output array. + The normalization type. + The operation mask. Makes the function consider and normalize only certain array elements. + + + + Normalizes the histogram bins by scaling them, such that the sum of the bins becomes equal to factor. + + Reference to the histogram. + Threshold level. + + + + Performs per-element bit-wise inversion of array elements + + The source array. + The destination array. + + + + Opens file storage for reading or writing data + + Name of the file associated with the storage. + Memory storage used for temporary data and for storing dynamic structures, such as CvSeq or CvGraph. If it is null, a temporary memory storage is created and used. + + pointer to CvFileStorage structure. + + + + Opens file storage for reading or writing data + + Name of the file associated with the storage. + Memory storage used for temporary data and for storing dynamic structures, such as CvSeq or CvGraph. If it is null, a temporary memory storage is created and used. + + + pointer to CvFileStorage structure. + + + + Calculates per-element bit-wise disjunction of two arrays + + The first source array. + The second source array. + The destination array. + + + + Calculates per-element bit-wise disjunction of two arrays + + The first source array. + The second source array. + The destination array. + Operation mask, 8-bit single channel array; specifies elements of destination array to be changed. + + + + Calculates per-element bit-wise disjunction of array and scalar + + The source array. + Scalar to use in the operation. + The destination array. + + + + Calculates per-element bit-wise disjunction of array and scalar + + The source array. + Scalar to use in the operation. + The destination array. + Operation mask, 8-bit single channel array; specifies elements of destination array to be changed. + + + + Performs perspective matrix transform of vector array + + The source three-channel floating-point array. + The destination three-channel floating-point array. + 3×3 or 4×4 transformation matrix. + + + + Creates 2D point with integer coordinates + + x-coordinate, usually zero-based + y-coordinate, usually zero-based + + + + + Creates 2D point with floating-point coordinates + + x-coordinate, usually zero-based + y-coordinate, usually zero-based + + + + + Creates 2D point with double precision floating-point coordinates + + x-coordinate, usually zero-based + y-coordinate, usually zero-based + + + + + Creates3D point with floating-point coordinates + + x-coordinate, usually zero-based + y-coordinate, usually zero-based + z-coordinate, usually zero-based + + + + + Creates 3D point with double precision floating-point coordinates + + x-coordinate, usually zero-based + y-coordinate, usually zero-based + z-coordinate, usually zero-based + + + + + Point in contour test + + Input contour. + The point tested against the contour. + If it is true, the function estimates distance from the point to the nearest contour edge. + The function cvPointPolygonTest determines whether the point is inside contour, + outside, or lies on an edge (or coinsides with a vertex). + It returns positive, negative or zero value, correspondingly. + When measureDist=0, the return value is +1, -1 and 0, respectively. + When measureDist≠0, it is a signed distance between the point and the nearest contour edge. + + + + Initializes point sequence header from a point vector + + Type of the point sequence. + Input matrix. It should be continuous 1-dimensional vector of points, that is, it should have type CV_32SC2 or CV_32FC2. + Contour header, initialized by the function. + Sequence block header, initialized by the function. + + + + Calculates cartesian coordinates of 2d vectors represented in polar form + + The array of magnitudes. If it is null, the magnitudes are assumed all 1’s. + The array of angles, whether in radians or degrees. + The destination array of x-coordinates, may be set to null if it is not needed. + The destination array of y-coordinates, mau be set to null if it is not needed. + + + + Calculates cartesian coordinates of 2d vectors represented in polar form + + The array of magnitudes. If it is null, the magnitudes are assumed all 1’s. + The array of angles, whether in radians or degrees. + The destination array of x-coordinates, may be set to null if it is not needed. + The destination array of y-coordinates, mau be set to null if it is not needed. + The flag indicating whether the angles are measured in radians, which is default mode, or in degrees. + + + + Draws simple or thick polygons + + Image. + Array of pointers to polylines. + Indicates whether the polylines must be drawn closed. If closed, the function draws the line from the last vertex of every contour to the first vertex. + Polyline color. + + + + Draws simple or thick polygons + + Image. + Array of pointers to polylines. + Indicates whether the polylines must be drawn closed. If closed, the function draws the line from the last vertex of every contour to the first vertex. + Polyline color. + Thickness of the polyline edges. + + + + Draws simple or thick polygons + + Image. + Array of pointers to polylines. + Indicates whether the polylines must be drawn closed. If closed, the function draws the line from the last vertex of every contour to the first vertex. + Polyline color. + Thickness of the polyline edges. + Type of the line segments. + + + + Draws simple or thick polygons + + Image. + Array of pointers to polylines. + Indicates whether the polylines must be drawn closed. If closed, the function draws the line from the last vertex of every contour to the first vertex. + Polyline color. + Thickness of the polyline edges. + Type of the line segments. + Number of fractional bits in the vertex coordinates. + + + + Draws simple or thick polygons + + Image. + Array of pointers to polylines. + Indicates whether the polylines must be drawn closed. If closed, the function draws the line from the last vertex of every contour to the first vertex. + Polyline color. + + + + Draws simple or thick polygons + + Image. + Array of pointers to polylines. + Indicates whether the polylines must be drawn closed. If closed, the function draws the line from the last vertex of every contour to the first vertex. + Polyline color. + Thickness of the polyline edges. + + + + Draws simple or thick polygons + + Image. + Array of pointers to polylines. + Indicates whether the polylines must be drawn closed. If closed, the function draws the line from the last vertex of every contour to the first vertex. + Polyline color. + Thickness of the polyline edges. + Type of the line segments. + + + + Draws simple or thick polygons + + Image. + Array of pointers to polylines. + Indicates whether the polylines must be drawn closed. If closed, the function draws the line from the last vertex of every contour to the first vertex. + Polyline color. + Thickness of the polyline edges. + Type of the line segments. + Number of fractional bits in the vertex coordinates. + + + + Implements POSIT algorithm + + Posit object structure. + Object points projections on the 2D image plane. + Focal length of the camera used. + Termination criteria of the iterative POSIT algorithm. + Matrix of rotations. + Translation vector. + + + + + + + + + + + + Raises every array element to power + + The source array. + The destination array, should be the same type as the source. + The exponent of power. + + + + Calculates feature map for corner detection + + Input image. + Image to store the corner candidates. + + + + Calculates feature map for corner detection + + Input image. + Image to store the corner candidates. + Aperture parameter for Sobel operator. + + + + Returns the currently observed node and moves iterator toward the previous node + + Tree iterator initialized by the function. + + + + + Returns the currently observed node and moves iterator toward the previous node + + Tree iterator initialized by the function. + + + + + Returns the currently observed node and moves iterator toward the previous node + + Tree iterator initialized by the function. + + + + + Projects vectors to the specified subspace + + The input data; each vector is either a single row or a single column. + The mean (average) vector. If it is a single-row vector, it means that the output vectors are stored as rows of result; otherwise, it should be a single-column vector, then the vectors are stored as columns of result. + The eigenvectors (principal components); one vector per row. + The output matrix of decomposition coefficients. The number of rows must be the same as the number of vectors, the number of columns must be less than or equal to the number of rows in eigenvectors. That it is less, the input vectors are projected into subspace of the first cols(result) principal components. + + + + + Computes projections of 3D points to the image plane given intrinsic and extrinsic camera parameters. + Optionally, the function computes jacobians - matrices of partial derivatives of image points as functions of all the input parameters w.r.t. the particular parameters, intrinsic and/or extrinsic. + + + Note, that with intrinsic and/or extrinsic parameters set to special values, + the function can be used to compute just extrinsic transformation or just intrinsic transformation (i.e. distortion of a sparse set of points). + + The array of object points, 3xN or Nx3, where N is the number of points in the view. + The rotation vector, 1x3 or 3x1. + The translation vector, 1x3 or 3x1. + The camera matrix (A) [fx 0 cx; 0 fy cy; 0 0 1]. + The vector of distortion coefficients, 4x1 or 1x4 [k1, k2, p1, p2]. If it is null, all distortion coefficients are considered 0's. + The output array of image points, 2xN or Nx2, where N is the total number of points in the view. + + + + Computes projections of 3D points to the image plane given intrinsic and extrinsic camera parameters. + Optionally, the function computes jacobians - matrices of partial derivatives of image points as functions of all the input parameters w.r.t. the particular parameters, intrinsic and/or extrinsic. + + + Note, that with intrinsic and/or extrinsic parameters set to special values, + the function can be used to compute just extrinsic transformation or just intrinsic transformation (i.e. distortion of a sparse set of points). + + The array of object points, 3xN or Nx3, where N is the number of points in the view. + The rotation vector, 1x3 or 3x1. + The translation vector, 1x3 or 3x1. + The camera matrix (A) [fx 0 cx; 0 fy cy; 0 0 1]. + The vector of distortion coefficients, 4x1 or 1x4 [k1, k2, p1, p2]. If it is null, all distortion coefficients are considered 0's. + The output array of image points, 2xN or Nx2, where N is the total number of points in the view. + Optional Nx3 matrix of derivatives of image points with respect to components of the rotation vector. + Optional Nx3 matrix of derivatives of image points w.r.t. components of the translation vector. + Optional Nx2 matrix of derivatives of image points w.r.t. fx and fy. + Optional Nx2 matrix of derivatives of image points w.r.t. cx and cy. + Optional Nx4 matrix of derivatives of image points w.r.t. distortion coefficients. + + + + Computes projections of 3D points to the image plane given intrinsic and extrinsic camera parameters. + Optionally, the function computes jacobians - matrices of partial derivatives of image points as functions of all the input parameters w.r.t. the particular parameters, intrinsic and/or extrinsic. + + + Note, that with intrinsic and/or extrinsic parameters set to special values, + the function can be used to compute just extrinsic transformation or just intrinsic transformation (i.e. distortion of a sparse set of points). + + The array of object points, 3xN or Nx3, where N is the number of points in the view. + The rotation vector, 1x3 or 3x1. + The translation vector, 1x3 or 3x1. + The camera matrix (A) [fx 0 cx; 0 fy cy; 0 0 1]. + The vector of distortion coefficients, 4x1 or 1x4 [k1, k2, p1, p2]. If it is null, all distortion coefficients are considered 0's. + The output array of image points, 2xN or Nx2, where N is the total number of points in the view. + Optional Nx3 matrix of derivatives of image points with respect to components of the rotation vector. + Optional Nx3 matrix of derivatives of image points w.r.t. components of the translation vector. + Optional Nx2 matrix of derivatives of image points w.r.t. fx and fy. + Optional Nx2 matrix of derivatives of image points w.r.t. cx and cy. + Optional Nx4 matrix of derivatives of image points w.r.t. distortion coefficients. + + + + + Return pointer to the particular array element + + Input array. + The first zero-based component of the element index + pointer to the particular array element + + + + Return pointer to the particular array element + + Input array. + The first zero-based component of the element index + Type of matrix elements + pointer to the particular array element + + + + Return pointer to the particular array element + + Input array. + The first zero-based component of the element index + The second zero-based component of the element index + pointer to the particular array element + + + + Return pointer to the particular array element + + Input array. + The first zero-based component of the element index + The second zero-based component of the element index + Type of matrix elements + pointer to the particular array element + + + + Return pointer to the particular array element + + Input array. + The first zero-based component of the element index + The second zero-based component of the element index + The third zero-based component of the element index + pointer to the particular array element + + + + Return pointer to the particular array element + + Input array. + The first zero-based component of the element index + The second zero-based component of the element index + The third zero-based component of the element index + Type of matrix elements + pointer to the particular array element + + + + Return pointer to the particular array element + + Input array. + Array of the element indices + pointer to the particular array element + + + + Return pointer to the particular array element + + Input array. + Array of the element indices + Type of matrix elements + pointer to the particular array element + + + + Return pointer to the particular array element + + Input array. + Array of the element indices + Type of matrix elements + Optional input parameter for sparse matrices. Non-zero value of the parameter means that the requested element is created if it does not exist already. + pointer to the particular array element + + + + Return pointer to the particular array element + + Input array. + Array of the element indices + Type of matrix elements + Optional input parameter for sparse matrices. Non-zero value of the parameter means that the requested element is created if it does not exist already. + Optional input parameter for sparse matrices. If the pointer is not NULL, the function does not recalculate the node hash value, but takes it from the specified location. It is useful for speeding up pair-wise operations + pointer to the particular array element + + + + Draws text string + + Input image. + String to print. + Coordinates of the bottom-left corner of the first letter. + Pointer to the font structure. + Text color. + + + + Downsamples image. + + The source image. + The destination image, should have 2x smaller width and height than the source. + + + + Downsamples image. + + The source image. + The destination image, should have 2x smaller width and height than the source. + Type of the filter used for convolution; only CV_GAUSSIAN_5x5 is currently supported. + + + + Does meanshift image segmentation. + + The source 8-bit 3-channel image. + The destination image of the same format and the same size as the source. + The spatial window radius. + The color window radius. + + + + Does meanshift image segmentation. + + The source 8-bit 3-channel image. + The destination image of the same format and the same size as the source. + The spatial window radius. + The color window radius. + Maximum level of the pyramid for the segmentation. + + + + Does meanshift image segmentation. + + The source 8-bit 3-channel image. + The destination image of the same format and the same size as the source. + The spatial window radius. + The color window radius. + Maximum level of the pyramid for the segmentation. + Termination criteria: when to stop meanshift iterations. + + + + Does image segmentation by pyramids. + + The source image. + The destination image. + + + + + + + Does image segmentation by pyramids. + + The source image. + The destination image. + Storage; stores the resulting sequence of connected components. + Pointer to the output sequence of the segmented components. + Maximum level of the pyramid for the segmentation. + Error threshold for establishing the links. + Error threshold for the segments clustering. + + + + Upsamples image. + + The source image. + The destination image, should have 2x smaller width and height than the source. + + + + Upsamples image. + + The source image. + The destination image, should have 2x smaller width and height than the source. + Type of the filter used for convolution; only CV_GAUSSIAN_5x5 is currently supported. + + + + Grabs a frame from camera or video file, decompresses and returns it. + This function is just a combination of cvGrabFrame and cvRetrieveFrame in one call. + The returned image should not be released or modified by user. + + video capturing structure. + + + + + Queries value of histogram bin. + + Histogram. + 1st index of the bin. + + + + + Queries value of histogram bin. + + Histogram. + 1st index of the bin. + 2nd index of the bin. + + + + + Queries value of histogram bin. + + Histogram. + 1st index of the bin. + 2nd index of the bin. + 3rd index of the bin. + + + + + Queries value of histogram bin. + + 1st index of the bin. + Array of indices. + + + + + Implements a particular case of application of line iterators. + The function reads all the image points lying on the line between pt1 and pt2, including the ending points, and stores them into the buffer. + + Image to sample the line from. + Starting the line point. + Ending the line point. + Buffer to store the line points. + The line connectivity, 4 or 8. + + + + + Saves object to file + + File name. + Object to save. + + + + Saves object to file + + File name. + Object to save. + Optional object name. If it is null, the name will be formed from filename. + + + + Saves object to file + + File name. + Object to save. + Optional object name. If it is null, the name will be formed from filename. + Optional comment to put in the beginning of the file. + + + + Saves object to file + + File name. + Object to save. + Optional object name. If it is null, the name will be formed from filename. + Optional comment to put in the beginning of the file. + Optional attributes passed to cvWrite. + + + + Saves object to file + + Object to save. + File name. + + + + Saves object to file + + Object to save. + File name. + Optional object name. If it is null, the name will be formed from filename. + + + + Saves object to file + + Object to save. + File name. + Optional object name. If it is null, the name will be formed from filename. + Optional comment to put in the beginning of the file. + + + + Saves object to file + + Object to save. + File name. + Optional object name. If it is null, the name will be formed from filename. + Optional comment to put in the beginning of the file. + Optional attributes passed to cvWrite. + + + + Saves the image to the specified file. The image format is chosen depending on the filename extension, see cvLoadImage. + Only 8-bit single-channel or 3-channel (with 'BGR' channel order) images can be saved using this function. + + Name of the file. + Image to be saved. + + + + + + Saves the image to the specified file. The image format is chosen depending on the filename extension, see cvLoadImage. + Only 8-bit single-channel or 3-channel (with 'BGR' channel order) images can be saved using this function. + + Name of the file. + Image to be saved. + + + + + + Saves memory storage position + + Memory storage. + The output position of the storage top. + + + + Save parameters of the window. + + Name of the window + + + + Initializes val[0]...val[3] with val0123 + + + + + + + Calculates sum of scaled array and another array + + The first source array. + Scale factor for the first array. + The second source array. + The destination array + + + + Calculates sum of scaled array and another array + + The first source array. + Scale factor for the first array. + The second source array. + The destination array + + + + cvScaleAdd(A, cvRealScalar(real_scalar), B, C) + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Segments whole motion into separate moving parts + + Motion history image. + Image where the mask found should be stored, single-channel, 32-bit floating-point. + Memory storage that will contain a sequence of motion connected components. + Current time in milliseconds or other units. + Segmentation threshold; recommended to be equal to the interval between motion history "steps" or greater. + + + + Returns index of concrete sequence element + + Element type + Sequence. + the element within the sequence. + the index of a sequence element or a negative number if the element is not found. + + + + Returns index of concrete sequence element + + Element type + Sequence. + the element within the sequence. + the address of the sequence block that contains the element is stored in this location. + the index of a sequence element or a negative number if the element is not found. + + + + Inserts element in sequence middle + + Element type + Sequence. + Index before which the element is inserted. Inserting before 0 (the minimal allowed value of the parameter) is equal to cvSeqPushFront and inserting before seq->total (the maximal allowed value of the parameter) is equal to cvSeqPush. + Inserted element. + Inserted element. + + + + Inserts array in the middle of sequence + + Sequence. + The part of the sequence to remove. + The array to take elements from. + + + + Reverses the order of sequence elements + + Sequence. + + + + Removes element from sequence middle + + Sequence. + Index of removed element. + + + + Removes sequence slice + + Sequence. + The part of the sequence to remove. + + + + Splits sequence into equivalence classes + + The sequence to partition. + The storage to store the sequence of equivalence classes. If it is null, the function uses seq->storage for output labels. + Output parameter. Double pointer to the sequence of 0-based labels of input sequence elements. + The relation function that should return non-zero if the two particular sequence elements are from the same class, and zero otherwise. The partitioning algorithm uses transitive closure of the relation function as equivalence criteria. + + + + + Splits sequence into equivalence classes + + The sequence to partition. + The storage to store the sequence of equivalence classes. If it is null, the function uses seq->storage for output labels. + Output parameter. Double pointer to the sequence of 0-based labels of input sequence elements. + The relation function that should return non-zero if the two particular sequence elements are from the same class, and zero otherwise. The partitioning algorithm uses transitive closure of the relation function as equivalence criteria. + + + + + Removes element from sequence end + + Sequence. + + + + Removes element from sequence end + + Element type + Sequence. + copied the removed element to this location. + + + + Removes element from sequence beginning + + Sequence. + + + + Removes element from sequence beginning + + Element type + Sequence. + copied the removed element to this location. + + + + Removes several elements from the either end of sequence + + Element type + Sequence. + Removed elements. + Number of elements to pop. + The flags specifying the modified sequence end + + + + allocates a space for one more element. + + Sequence. + pointer to the allocated element. + + + + Adds element to sequence end + + Element type + Sequence. + Added element. + pointer to the allocated element. + + + + Adds element to sequence beginning + + Sequence. + pointer to the added element + + + + Adds element to sequence beginning + + Element type + Sequence. + Added element. + pointer to the added element + + + + Pushes several elements to the either end of sequence + + Element type + Sequence. + Added elements. + The flags specifying the modified sequence end + + + + Searches element in sequence + + The sequence + The element to look for + The comparison function that returns negative, zero or positive value depending on the elements relation + Whether the sequence is sorted or not. + Output parameter; index of the found element. + + + + + Searches element in sequence + + Element type + The sequence + The element to look for + The comparison function that returns negative, zero or positive value depending on the elements relation + Whether the sequence is sorted or not. + Output parameter; index of the found element. + + + + + Makes separate header for the sequence slice + + Sequence. + The part of the sequence to extract. + + + + + Makes separate header for the sequence slice + + Sequence. + The part of the sequence to extract. + The destination storage to keep the new sequence header and the copied data if any. If it is null, the function uses the storage containing the input sequence. + + + + + Makes separate header for the sequence slice + + Sequence. + The part of the sequence to extract. + The destination storage to keep the new sequence header and the copied data if any. If it is null, the function uses the storage containing the input sequence. + The flag that indicates whether to copy the elements of the extracted slice (copy_data=true) or not (copy_data=false) + + + + + Makes separate header for the sequence slice + + Element type + Sequence. + The part of the sequence to extract. + + + + + Makes separate header for the sequence slice + + Element type + Sequence. + The part of the sequence to extract. + The destination storage to keep the new sequence header and the copied data if any. If it is null, the function uses the storage containing the input sequence. + + + + + Makes separate header for the sequence slice + + Element type + Sequence. + The part of the sequence to extract. + The destination storage to keep the new sequence header and the copied data if any. If it is null, the function uses the storage containing the input sequence. + The flag that indicates whether to copy the elements of the extracted slice (copy_data=true) or not (copy_data=false) + + + + + Sorts sequence element using the specified comparison function + + The sequence to sort + The comparison function that returns negative, zero or positive value depending on the elements relation (see the above declaration and the example below) - similar function is used by qsort from C runtime except that in the latter userdata is not used + + + + Sorts sequence element using the specified comparison function + + Element type + The sequence to sort + The comparison function that returns negative, zero or positive value depending on the elements relation (see the above declaration and the example below) - similar function is used by qsort from C runtime except that in the latter userdata is not used + + + + Sets every element of array to given value + + The destination array. + Fill value. + + + + Sets every element of array to given value + + The destination array. + Fill value. + Operation mask, 8-bit single channel array; specifies elements of destination array to be changed. + + + + Change the particular array element + + Input array. + The first zero-based component of the element index + The assigned value + + + + Change the particular array element + + Input array. + The first zero-based component of the element index + The second zero-based component of the element index + The assigned value + + + + Change the particular array element + + Input array. + The first zero-based component of the element index + The second zero-based component of the element index + The third zero-based component of the element index + The assigned value + + + + Change the particular array element + + Input array. + The assigned value + Array of the element indices + + + + Occupies a node in the set + + Set. + the index to the node + + + + Occupies a node in the set + + Set. + Optional input argument, inserted element. If not null, the function copies the data to the allocated node (The MSB of the first integer field is cleared after copying). + the index to the node + + + + Occupies a node in the set + + Set. + Optional input argument, inserted element. If not null, the function copies the data to the allocated node (The MSB of the first integer field is cleared after copying). + Optional output argument; the pointer to the allocated cell. + the index to the node + + + + Sets bounds of histogram bins + + Histogram. + Array of bin ranges arrays. + + + + Sets bounds of histogram bins + + Histogram. + Array of bin ranges arrays. + Uniformity flag. + + + + Sets the specified property of video capturing. + + video capturing structure. + property identifier. + value of the property. + + + + + Sets the specified property of video capturing. + + video capturing structure. + property identifier. + value of the property. + + + + + Assigns user data to the array header. + Header should be initialized before using cvCreate*Header, cvInit*Header or cvMat (in case of matrix) function. + + + Array header. + User data. + Full row length in bytes. + + + + Assigns user data to the array header. + Header should be initialized before using cvCreate*Header, cvInit*Header or cvMat (in case of matrix) function. + + Array header. + User data. + Full row length in bytes. + + + + Sets error processing mode, returns previously used mode + + The error mode. + previously used mode + + + + Sets the error status + + The error status. + + + + Initializes scaled identity matrix + + The matrix to initialize (not necessarily square). + + + + Initializes scaled identity matrix + + The matrix to initialize (not necessarily square). + The value to assign to the diagonal elements. + + + + Sets channel of interest to given value. + Value 0 means that all channels are selected, 1 means that the first channel is selected etc. + + Image header. + Channel of interest. + + + + Sets image ROI to given rectangle + + Image header. + ROI rectangle. + + + + Assigns images to the hidden cascade + + Hidden Haar classifier cascade, created by cvCreateHidHaarClassifierCascade. + Integral (sum) single-channel image of 32-bit integer format. This image as well as the two subsequent images are used for fast feature evaluation and brightness/contrast normalization. They all can be retrieved from input 8-bit or floating point single-channel image using The function cvIntegral. + Square sum single-channel image of 64-bit floating-point format. + Tilted sum single-channel image of 32-bit integer format. + Window scale for the cascade. If scale=1, original window size is used (objects of that size are searched) - the same size as specified in cvLoadHaarClassifierCascade (24x24 in case of "<default_face_cascade>"), if scale=2, a two times larger window is used (48x48 in case of default face cascade). While this will speed-up search about four times, faces smaller than 48x48 cannot be detected. + + + + Sets the callback function for mouse events occuting within the specified window. + + Name of the window. + Reference to the function to be called every time mouse event occurs in the specified window. + + + + Adds element to set (fast variant) + + Set. + pointer to a new node + + + + Sets the number of threads. + + + + + Sets the number of threads. + + The number of threads. + When the argument is zero or negative, and at the beginning of the program, the number of threads is set to the number of processors in the system, as returned by the function omp_get_num_procs() from OpenMP runtime. + + + + + + + + + + + + + + + + Change the particular array element + + Input array. + The first zero-based component of the element index + The assigned value + + + + Change the particular array element + + Input array. + The first zero-based component of the element index + The second zero-based component of the element index + The assigned value + + + + Change the particular array element + + Input array. + The first zero-based component of the element index + The second zero-based component of the element index + The third zero-based component of the element index + The assigned value + + + + Change the particular array element + + Input array. + The assigned value + Array of the element indices + + + + Removes element from set + + Set. + Index of the removed element. + + + + Removes set element given its pointer + + Set. + Removed element. + + + + Sets up sequence block size + + Sequence. + Desirable sequence block size in elements. + + + + Moves the reader to specified position + + Reader state. + The destination position. If the positioning mode is used (see the next parameter) the actual position will be index mod reader->seq->total. + + + + Moves the reader to specified position + + Reader state. + The destination position. If the positioning mode is used (see the next parameter) the actual position will be index mod reader->seq->total. + If it is true, then index is a relative to the current position. + + + + Sets the position of the specified trackbar. + + Name of trackbar. + Name of the window which is the parent of trackbar. + New position. + + + + Set Property of the window + + Window name + Property identifier + New value of the specified property + + + + Clears the array + + array to be cleared. + + + + Clears the array + + array to be cleared. + + + + Shows the image in the specified window. + If the window was created with CV_WINDOW_AUTOSIZE flag then the image is shown with its original size, otherwise the image is scaled to fit the window. + + Name of the window. + Image to be shown. + + + + Create CVSize structure and initializes it + + Width + Height + + + + + Calculates the sequence slice length + + Slice to measure + Sequence + + + + + Smooths the image in one of several ways. + + The source image. + The destination image. + + + + Smooths the image in one of several ways. + + The source image. + The destination image. + Type of the smoothing. + + + + Smooths the image in one of several ways. + + The source image. + The destination image. + Type of the smoothing. + The first parameter of smoothing operation. + + + + Smooths the image in one of several ways. + + The source image. + The destination image. + Type of the smoothing. + The first parameter of smoothing operation. + The second parameter of smoothing operation. In case of simple scaled/non-scaled and Gaussian blur if param2 is zero, it is set to param1. + + + + Smooths the image in one of several ways. + + The source image. + The destination image. + Type of the smoothing. + The first parameter of smoothing operation. + The second parameter of smoothing operation. In case of simple scaled/non-scaled and Gaussian blur if param2 is zero, it is set to param1. + In case of Gaussian kernel this parameter may specify Gaussian sigma (standard deviation). If it is zero, it is calculated from the kernel size. + + + + Smooths the image in one of several ways. + + The source image. + The destination image. + Type of the smoothing. + The first parameter of smoothing operation. + The second parameter of smoothing operation. In case of simple scaled/non-scaled and Gaussian blur if param2 is zero, it is set to param1. + In case of Gaussian kernel this parameter may specify Gaussian sigma (standard deviation). If it is zero, it is calculated from the kernel size. + In case of non-square Gaussian kernel the parameter may be used to specify a different (from param3) sigma in the vertical direction. + + + + Changes contour position to minimize its energy + + The source image or external energy field. + Contour points (snake). + Weight of continuity energy, single float or array of length floats, one per each contour point. + Weight of curvature energy, similar to alpha. + Weight of image energy, similar to alpha. + Size of neighborhood of every point used to search the minimum, both win.width and win.height must be odd. + Termination criteria. + + + + Changes contour position to minimize its energy + + The source image or external energy field. + Contour points (snake). + Weight of continuity energy, single float or array of length floats, one per each contour point. + Weight of curvature energy, similar to alpha. + Weight of image energy, similar to alpha. + Size of neighborhood of every point used to search the minimum, both win.width and win.height must be odd. + Termination criteria. + Gradient flag. If true, the function calculates gradient magnitude for every image pixel and consideres it as the energy field, otherwise the input image itself is considered. + + + + Changes contour position to minimize its energy + + The source image or external energy field. + Contour points (snake). + Weights of continuity energy, single float or array of length floats, one per each contour point. + Weights of curvature energy, similar to alpha. + Weights of image energy, similar to alpha. + Size of neighborhood of every point used to search the minimum, both win.width and win.height must be odd. + Termination criteria. + + + + Changes contour position to minimize its energy + + The source image or external energy field. + Contour points (snake). + Weights of continuity energy, single float or array of length floats, one per each contour point. + Weights of curvature energy, similar to alpha. + Weights of image energy, similar to alpha. + Size of neighborhood of every point used to search the minimum, both win.width and win.height must be odd. + Termination criteria. + Gradient flag. If true, the function calculates gradient magnitude for every image pixel and consideres it as the energy field, otherwise the input image itself is considered. + + + + Calculates first, second, third or mixed image derivatives using _extended Sobel operator + + Source image. + Destination image. + Order of the derivative x. + Order of the derivative y. + + + + Calculates first, second, third or mixed image derivatives using extended Sobel operator + + Source image. + Destination image. + Order of the derivative x. + Order of the derivative y. + Size of the extended Sobel kernel. + + + + Solves linear system or least-squares problem + + The source matrix. + The right-hand part of the linear system. + The output solution. + If CV_LU method is used, the function returns true if src1 is non-singular and false otherwise, in the latter case dst is not valid + + + + Solves linear system or least-squares problem + + The source matrix. + The right-hand part of the linear system. + The output solution. + The solution (matrix inversion) method + If CV_LU method is used, the function returns true if src1 is non-singular and false otherwise, in the latter case dst is not valid + + + + Finds real roots of a cubic equation + + The equation coefficients, array of 3 or 4 elements. + The output array of real roots. Should have 3 elements. + the number of real roots found. + + + + Finds real and complex roots of a polynomial equation with real coefficients + + The (degree + 1)-length array of equation coefficients (CV_32FC1 or CV_64FC1). + The degree-length output array of real or complex roots (CV_32FC2 or CV_64FC2). + + + + Finds real and complex roots of a polynomial equation with real coefficients + + The (degree + 1)-length array of equation coefficients (CV_32FC1 or CV_64FC1). + The degree-length output array of real or complex roots (CV_32FC2 or CV_64FC2). + The maximum number of iterations. + + + + Finds real and complex roots of a polynomial equation with real coefficients + + The (degree + 1)-length array of equation coefficients (CV_32FC1 or CV_64FC1). + The degree-length output array of real or complex roots (CV_32FC2 or CV_64FC2). + The maximum number of iterations. + The required figures of precision required. + + + + Sorts the rows/cols of an array ascending/descending + + Source array to sort + + + + Sorts the rows/cols of an array ascending/descending + + Source array to sort + Optional destination array + + + + Sorts the rows/cols of an array ascending/descending + + Source array to sort + Optional destination array + Index matrix + + + + Sorts the rows/cols of an array ascending/descending + + Source array to sort + Optional destination array + Index matrix + Sorting parameter + + + + Divides multi-channel array into several single-channel arrays or extracts a single channel from the array + + Source array. + Destination channel 0 + Destination channel 1 + Destination channel 2 + Destination channel 3 + + + + Divides multi-channel array into several single-channel arrays or extracts a single channel from the array + + Source array. + Destination channel 0 + Destination channel 1 + Destination channel 2 + Destination channel 3 + + + + Calculates square root + + The input floating-point value + + + + + Adds the square of source image to accumulator + + Input image, 1- or 3-channel, 8-bit or 32-bit floating point (each channel of multi-channel image is processed independently). + Accumulator of the same number of channels as input image, 32-bit or 64-bit floating-point. + + + + Adds the square of source image to accumulator + + Input image, 1- or 3-channel, 8-bit or 32-bit floating point (each channel of multi-channel image is processed independently). + Accumulator of the same number of channels as input image, 32-bit or 64-bit floating-point. + Optional operation mask. + + + + Constructor + + + + + Constructor + + + + + + Constructor + + + + + + + Constructor + + + + + + + + Constructor + + + + + + + + + Constructor + + + + + + + + + + Constructor + + + + + + + + Initializes process of writing data to sequence + + Pointer to the sequence. + Writer state; initialized by the function. + + + + Initializes contour scanning process + + The source 8-bit single channel binary image. + Container of the retrieved contours. + CvContourScanner + + + + Initializes contour scanning process + + The source 8-bit single channel binary image. + Container of the retrieved contours. + Size of the sequence header, >=sizeof(CvChain) if method=CV_CHAIN_CODE, and >=sizeof(CvContour) otherwise. + CvContourScanner + + + + Initializes contour scanning process + + The source 8-bit single channel binary image. + Container of the retrieved contours. + Size of the sequence header, >=sizeof(CvChain) if method=CV_CHAIN_CODE, and >=sizeof(CvContour) otherwise. + Retrieval mode; see cvFindContours. + CvContourScanner + + + + Initializes contour scanning process + + The source 8-bit single channel binary image. + Container of the retrieved contours. + Size of the sequence header, >=sizeof(CvChain) if method=CV_CHAIN_CODE, and >=sizeof(CvContour) otherwise. + Retrieval mode; see cvFindContours. + Approximation method. It has the same meaning as in cvFindContours, but CV_LINK_RUNS can not be used here. + CvContourScanner + + + + Initializes contour scanning process + + The source 8-bit single channel binary image. + Container of the retrieved contours. + Size of the sequence header, >=sizeof(CvChain) if method=CV_CHAIN_CODE, and >=sizeof(CvContour) otherwise. + Retrieval mode; see cvFindContours. + Approximation method. It has the same meaning as in cvFindContours, but CV_LINK_RUNS can not be used here. + ROI offset; see cvFindContours. + CvContourScanner + + + + Starts the next stream + + File storage. + + + + + + Pointer to chain. + Chain reader state. + + + + Initializes file node sequence reader + + File storage. + The file node (a sequence) to read numbers from. + Output reference to the sequence reader. + + + + Initializes process of sequential reading from sequence + + Sequence. + Reader state; initialized by the function. + + + + Initializes process of sequential reading from sequence + + Sequence. + Reader state; initialized by the function. + Determines the direction of the sequence traversal. If reverse is false, the reader is positioned at the first sequence element, otherwise it is positioned at the last element. + + + + For MacOS or Linux, tries to start thread to hande a window automatically (resizing, updating). Returns 0 if not supported + + + + + + Creates new sequence and initializes writer for it + + Flags of the created sequence. If the sequence is not passed to any function working with a specific type of sequences, the sequence value may be equal to 0, otherwise the appropriate type must be selected from the list of predefined sequence types. + Size of the sequence header. The parameter value may not be less than sizeof(CvSeq). If a certain type or extension is specified, it must fit the base type header. + Size of the sequence elements in bytes; must be consistent with the sequence type. For example, if the sequence of points is created (element type CV_SEQ_ELTYPE_POINT ), then the parameter elem_size must be equal to sizeof(CvPoint). + Sequence location. + Writer state; initialized by the function. + + + + Starts writing a new structure + + File storage. + Name of the written structure. The structure can be accessed by this name when the storage is read. + A combination one of the NodeType flags + + + + Starts writing a new structure + + File storage. + Name of the written structure. The structure can be accessed by this name when the storage is read. + A combination one of the NodeType flags + Optional parameter - the object type name. + In case of XML it is written as type_id attribute of the structure opening tag. + In case of YAML it is written after a colon following the structure name. Mainly it comes with user objects. + When the storage is read, the encoded type name is used to determine the object type. + + + + Calibrates stereo camera + + The joint matrix of object points, 3xN or Nx3, where N is the total number of points in all views. + The joint matrix of corresponding image points in the views from the 1st camera, 2xN or Nx2, where N is the total number of points in all views. + The joint matrix of corresponding image points in the views from the 2nd camera, 2xN or Nx2, where N is the total number of points in all views. + Vector containing numbers of points in each view, 1xM or Mx1, where M is the number of views. + The input/output camera matrix [fxk 0 cxk; 0 fyk cyk; 0 0 1]. If CV_CALIB_USE_INTRINSIC_GUESS or CV_CALIB_FIX_ASPECT_RATIO are specified, some or all of the elements of the matrices must be initialized. + The input/output vector of distortion coefficients for each camera, 4x1, 1x4, 5x1 or 1x5. + The input/output camera matrix [fxk 0 cxk; 0 fyk cyk; 0 0 1]. If CV_CALIB_USE_INTRINSIC_GUESS or CV_CALIB_FIX_ASPECT_RATIO are specified, some or all of the elements of the matrices must be initialized. + The input/output vector of distortion coefficients for each camera, 4x1, 1x4, 5x1 or 1x5. + Size of the image, used only to initialize intrinsic camera matrix. + The rotation matrix between the 1st and the 2nd cameras' coordinate systems + The translation vector between the cameras' coordinate systems. + + + + Calibrates stereo camera + + The joint matrix of object points, 3xN or Nx3, where N is the total number of points in all views. + The joint matrix of corresponding image points in the views from the 1st camera, 2xN or Nx2, where N is the total number of points in all views. + The joint matrix of corresponding image points in the views from the 2nd camera, 2xN or Nx2, where N is the total number of points in all views. + Vector containing numbers of points in each view, 1xM or Mx1, where M is the number of views. + The input/output camera matrix [fxk 0 cxk; 0 fyk cyk; 0 0 1]. If CV_CALIB_USE_INTRINSIC_GUESS or CV_CALIB_FIX_ASPECT_RATIO are specified, some or all of the elements of the matrices must be initialized. + The input/output vector of distortion coefficients for each camera, 4x1, 1x4, 5x1 or 1x5. + The input/output camera matrix [fxk 0 cxk; 0 fyk cyk; 0 0 1]. If CV_CALIB_USE_INTRINSIC_GUESS or CV_CALIB_FIX_ASPECT_RATIO are specified, some or all of the elements of the matrices must be initialized. + The input/output vector of distortion coefficients for each camera, 4x1, 1x4, 5x1 or 1x5. + Size of the image, used only to initialize intrinsic camera matrix. + The rotation matrix between the 1st and the 2nd cameras' coordinate systems + The translation vector between the cameras' coordinate systems. + The optional output essential matrix + + + + Calibrates stereo camera + + The joint matrix of object points, 3xN or Nx3, where N is the total number of points in all views. + The joint matrix of corresponding image points in the views from the 1st camera, 2xN or Nx2, where N is the total number of points in all views. + The joint matrix of corresponding image points in the views from the 2nd camera, 2xN or Nx2, where N is the total number of points in all views. + Vector containing numbers of points in each view, 1xM or Mx1, where M is the number of views. + The input/output camera matrix [fxk 0 cxk; 0 fyk cyk; 0 0 1]. If CV_CALIB_USE_INTRINSIC_GUESS or CV_CALIB_FIX_ASPECT_RATIO are specified, some or all of the elements of the matrices must be initialized. + The input/output vector of distortion coefficients for each camera, 4x1, 1x4, 5x1 or 1x5. + The input/output camera matrix [fxk 0 cxk; 0 fyk cyk; 0 0 1]. If CV_CALIB_USE_INTRINSIC_GUESS or CV_CALIB_FIX_ASPECT_RATIO are specified, some or all of the elements of the matrices must be initialized. + The input/output vector of distortion coefficients for each camera, 4x1, 1x4, 5x1 or 1x5. + Size of the image, used only to initialize intrinsic camera matrix. + The rotation matrix between the 1st and the 2nd cameras' coordinate systems + The translation vector between the cameras' coordinate systems. + The optional output essential matrix + The optional output fundamental matrix + + + + Calibrates stereo camera + + The joint matrix of object points, 3xN or Nx3, where N is the total number of points in all views. + The joint matrix of corresponding image points in the views from the 1st camera, 2xN or Nx2, where N is the total number of points in all views. + The joint matrix of corresponding image points in the views from the 2nd camera, 2xN or Nx2, where N is the total number of points in all views. + Vector containing numbers of points in each view, 1xM or Mx1, where M is the number of views. + The input/output camera matrix [fxk 0 cxk; 0 fyk cyk; 0 0 1]. If CV_CALIB_USE_INTRINSIC_GUESS or CV_CALIB_FIX_ASPECT_RATIO are specified, some or all of the elements of the matrices must be initialized. + The input/output vector of distortion coefficients for each camera, 4x1, 1x4, 5x1 or 1x5. + The input/output camera matrix [fxk 0 cxk; 0 fyk cyk; 0 0 1]. If CV_CALIB_USE_INTRINSIC_GUESS or CV_CALIB_FIX_ASPECT_RATIO are specified, some or all of the elements of the matrices must be initialized. + The input/output vector of distortion coefficients for each camera, 4x1, 1x4, 5x1 or 1x5. + Size of the image, used only to initialize intrinsic camera matrix. + The rotation matrix between the 1st and the 2nd cameras' coordinate systems + The translation vector between the cameras' coordinate systems. + The optional output essential matrix + The optional output fundamental matrix + Termination criteria for the iterative optimiziation algorithm. + + + + Calibrates stereo camera + + The joint matrix of object points, 3xN or Nx3, where N is the total number of points in all views. + The joint matrix of corresponding image points in the views from the 1st camera, 2xN or Nx2, where N is the total number of points in all views. + The joint matrix of corresponding image points in the views from the 2nd camera, 2xN or Nx2, where N is the total number of points in all views. + Vector containing numbers of points in each view, 1xM or Mx1, where M is the number of views. + The input/output camera matrix [fxk 0 cxk; 0 fyk cyk; 0 0 1]. If CV_CALIB_USE_INTRINSIC_GUESS or CV_CALIB_FIX_ASPECT_RATIO are specified, some or all of the elements of the matrices must be initialized. + The input/output vector of distortion coefficients for each camera, 4x1, 1x4, 5x1 or 1x5. + The input/output camera matrix [fxk 0 cxk; 0 fyk cyk; 0 0 1]. If CV_CALIB_USE_INTRINSIC_GUESS or CV_CALIB_FIX_ASPECT_RATIO are specified, some or all of the elements of the matrices must be initialized. + The input/output vector of distortion coefficients for each camera, 4x1, 1x4, 5x1 or 1x5. + Size of the image, used only to initialize intrinsic camera matrix. + The rotation matrix between the 1st and the 2nd cameras' coordinate systems + The translation vector between the cameras' coordinate systems. + The optional output essential matrix + The optional output fundamental matrix + Termination criteria for the iterative optimiziation algorithm. + Different flags + + + + Computes rectification transform for stereo camera + + The camera matrix [fxk 0 cxk; 0 fyk cyk; 0 0 1]. + The camera matrix [fxk 0 cxk; 0 fyk cyk; 0 0 1]. + The vector of distortion coefficients for camera1, 4x1, 1x4, 5x1 or 1x5. + The vector of distortion coefficients for camera2, 4x1, 1x4, 5x1 or 1x5. + Size of the image used for stereo calibration. + The rotation matrix between the 1st and the 2nd cameras' coordinate systems + The translation vector between the cameras' coordinate systems. + 3x3 Rectification transforms (rotation matrices) for the first and the second cameras, respectively + 3x3 Rectification transforms (rotation matrices) for the first and the second cameras, respectively + 3x4 Projection matrices in the new (rectified) coordinate systems + 3x4 Projection matrices in the new (rectified) coordinate systems + + + + Computes rectification transform for stereo camera + + The camera matrix [fxk 0 cxk; 0 fyk cyk; 0 0 1]. + The camera matrix [fxk 0 cxk; 0 fyk cyk; 0 0 1]. + The vector of distortion coefficients for camera1, 4x1, 1x4, 5x1 or 1x5. + The vector of distortion coefficients for camera2, 4x1, 1x4, 5x1 or 1x5. + Size of the image used for stereo calibration. + The rotation matrix between the 1st and the 2nd cameras' coordinate systems + The translation vector between the cameras' coordinate systems. + 3x3 Rectification transforms (rotation matrices) for the first and the second cameras, respectively + 3x3 Rectification transforms (rotation matrices) for the first and the second cameras, respectively + 3x4 Projection matrices in the new (rectified) coordinate systems + 3x4 Projection matrices in the new (rectified) coordinate systems + The optional output disparity-to-depth mapping matrix, 4x4 + + + + Computes rectification transform for stereo camera + + The camera matrix [fxk 0 cxk; 0 fyk cyk; 0 0 1]. + The camera matrix [fxk 0 cxk; 0 fyk cyk; 0 0 1]. + The vector of distortion coefficients for camera1, 4x1, 1x4, 5x1 or 1x5. + The vector of distortion coefficients for camera2, 4x1, 1x4, 5x1 or 1x5. + Size of the image used for stereo calibration. + The rotation matrix between the 1st and the 2nd cameras' coordinate systems + The translation vector between the cameras' coordinate systems. + 3x3 Rectification transforms (rotation matrices) for the first and the second cameras, respectively + 3x3 Rectification transforms (rotation matrices) for the first and the second cameras, respectively + 3x4 Projection matrices in the new (rectified) coordinate systems + 3x4 Projection matrices in the new (rectified) coordinate systems + The optional output disparity-to-depth mapping matrix, 4x4 + The operation flags + + + + Computes rectification transform for stereo camera + + The camera matrix [fxk 0 cxk; 0 fyk cyk; 0 0 1]. + The camera matrix [fxk 0 cxk; 0 fyk cyk; 0 0 1]. + The vector of distortion coefficients for camera1, 4x1, 1x4, 5x1 or 1x5. + The vector of distortion coefficients for camera2, 4x1, 1x4, 5x1 or 1x5. + Size of the image used for stereo calibration. + The rotation matrix between the 1st and the 2nd cameras' coordinate systems + The translation vector between the cameras' coordinate systems. + 3x3 Rectification transforms (rotation matrices) for the first and the second cameras, respectively + 3x3 Rectification transforms (rotation matrices) for the first and the second cameras, respectively + 3x4 Projection matrices in the new (rectified) coordinate systems + 3x4 Projection matrices in the new (rectified) coordinate systems + The optional output disparity-to-depth mapping matrix, 4x4 + The operation flags + + + + + Computes rectification transform for stereo camera + + The camera matrix [fxk 0 cxk; 0 fyk cyk; 0 0 1]. + The camera matrix [fxk 0 cxk; 0 fyk cyk; 0 0 1]. + The vector of distortion coefficients for camera1, 4x1, 1x4, 5x1 or 1x5. + The vector of distortion coefficients for camera2, 4x1, 1x4, 5x1 or 1x5. + Size of the image used for stereo calibration. + The rotation matrix between the 1st and the 2nd cameras' coordinate systems + The translation vector between the cameras' coordinate systems. + 3x3 Rectification transforms (rotation matrices) for the first and the second cameras, respectively + 3x3 Rectification transforms (rotation matrices) for the first and the second cameras, respectively + 3x4 Projection matrices in the new (rectified) coordinate systems + 3x4 Projection matrices in the new (rectified) coordinate systems + The optional output disparity-to-depth mapping matrix, 4x4 + The operation flags + + + + + + Computes rectification transform for stereo camera + + The camera matrix [fxk 0 cxk; 0 fyk cyk; 0 0 1]. + The camera matrix [fxk 0 cxk; 0 fyk cyk; 0 0 1]. + The vector of distortion coefficients for camera1, 4x1, 1x4, 5x1 or 1x5. + The vector of distortion coefficients for camera2, 4x1, 1x4, 5x1 or 1x5. + Size of the image used for stereo calibration. + The rotation matrix between the 1st and the 2nd cameras' coordinate systems + The translation vector between the cameras' coordinate systems. + 3x3 Rectification transforms (rotation matrices) for the first and the second cameras, respectively + 3x3 Rectification transforms (rotation matrices) for the first and the second cameras, respectively + 3x4 Projection matrices in the new (rectified) coordinate systems + 3x4 Projection matrices in the new (rectified) coordinate systems + The optional output disparity-to-depth mapping matrix, 4x4 + The operation flags + + + + + + + + Computes rectification transform for uncalibrated stereo camera + + The 2 arrays of corresponding 2D points. + The 2 arrays of corresponding 2D points. + Fundamental matrix. It can be computed using the same set of point pairs points1 and points2 using cvFindFundamentalMat + Size of the image. + The rectification homography matrices for the first and for the second images. + The rectification homography matrices for the first and for the second images. + + + + + Computes rectification transform for uncalibrated stereo camera + + The 2 arrays of corresponding 2D points. + The 2 arrays of corresponding 2D points. + Fundamental matrix. It can be computed using the same set of point pairs points1 and points2 using cvFindFundamentalMat + Size of the image. + The rectification homography matrices for the first and for the second images. + The rectification homography matrices for the first and for the second images. + Optional threshold used to filter out the outliers. If the parameter is greater than zero, then all the point pairs that do not comply the epipolar geometry well enough (that is, the points for which fabs(points2[i]T*F*points1[i])>threshold) are rejected prior to computing the homographies. + + + + + Computes per-element difference between two arrays + + The first source array. + The second source array. + The destination array. + + + + Computes per-element difference between two arrays + + The first source array. + The second source array. + The destination array. + Operation mask, 8-bit single channel array; specifies elements of destination array to be changed. + + + + Computes difference between array and scalar + + The source array. + Subtracted scalar. + The destination array. + + + + Computes difference between array and scalar + + The source array. + Subtracted scalar. + The destination array. + Operation mask, 8-bit single channel array; specifies elements of destination array to be changed. + + + + Computes difference between scalar and array + + The first source array. + Scalar to subtract from. + The destination array. + + + + Computes difference between scalar and array + + The first source array. + Scalar to subtract from. + The destination array. + Operation mask, 8-bit single channel array; specifies elements of destination array to be changed. + + + + Summarizes array elements + + The array. + sum S of array elements, independently for each channel + + + + Returns edge destination. + + Subdivision edge (not a quad-edge) + The edge destination. If the edge is from dual subdivision and the virtual point coordinates are not calculated yet, the returned pointer may be null. + + + + Returns edge origin. + + Subdivision edge (not a quad-edge) + The edge origin. If the edge is from dual subdivision and the virtual point coordinates are not calculated yet, the returned pointer may be null. + + + + Returns one of edges related to given. + + Subdivision edge (not a quad-edge) + Specifies, which of related edges to return + one the edges related to the input edge + + + + Inserts a single point to Delaunay triangulation + + Delaunay or another subdivision. + The point to locate. + The output edge the point falls onto or right to. + + + + + Inserts a single point to Delaunay triangulation + + Delaunay or another subdivision. + The point to locate. + The output edge the point falls onto or right to. + Optional output vertex double pointer the input point coinsides with. + + + + + + + + + + + + Returns another edge of the same quad-edge + + Subdivision edge (not a quad-edge) + Specifies, which of edges of the same quad-edge as the input one to return + one the edges of the same quad-edge as the input edge. + + + + + + + + + + + Inserts a single point to Delaunay triangulation + + Delaunay subdivision created by function cvCreateSubdivDelaunay2D. + Inserted point. + + + + + Replaces retrieved contour + + Contour scanner initialized by the function cvStartFindContours . + Substituting contour. + + + + Creates SURF default parameters + + Only features with keypoint.hessian larger than that are extracted. + false means basic descriptors (64 elements each), true means _extended descriptors (128 elements each) + default parameters + + + + Performs singular value back substitution + + Matrix or vector of singular values. + Left orthogonal matrix (transposed, perhaps) + Right orthogonal matrix (transposed, perhaps) + The matrix to multiply the pseudo-inverse of the original matrix A by. This is the optional parameter. If it is omitted then it is assumed to be an identity matrix of an appropriate size (So X will be the reconstructed pseudo-inverse of A). + The destination matrix: result of back substitution. + Operation flags, should match exactly to the flags passed to cvSVD. + + + + Performs singular value decomposition of real floating-point matrix + + Source M×N matrix. + Resulting singular value matrix (M×N or N×N) or vector (N×1). + + + + Performs singular value decomposition of real floating-point matrix + + Source M×N matrix. + Resulting singular value matrix (M×N or N×N) or vector (N×1). + Optional left orthogonal matrix (M×M or M×N). If CV_SVD_U_T is specified, the number of rows and columns in the sentence above should be swapped. + + + + Performs singular value decomposition of real floating-point matrix + + Source M×N matrix. + Resulting singular value matrix (M×N or N×N) or vector (N×1). + Optional left orthogonal matrix (M×M or M×N). If CV_SVD_U_T is specified, the number of rows and columns in the sentence above should be swapped. + Optional right orthogonal matrix (N×N) + + + + Performs singular value decomposition of real floating-point matrix + + Source M×N matrix. + Resulting singular value matrix (M×N or N×N) or vector (N×1). + Optional left orthogonal matrix (M×M or M×N). If CV_SVD_U_T is specified, the number of rows and columns in the sentence above should be swapped. + Optional right orthogonal matrix (N×N) + Operation flags + + + + Creates termination criteria for iterative algorithms. + + A combination of Iteration and Epsilon + Maximum number of iterations + Required accuracy + + + + + Clears histogram bins that are below the specified threshold. + + Reference to the histogram. + Threshold level. + + + + Applies fixed-level threshold to array elements. + + Source array (single-channel, 8-bit of 32-bit floating point). + Destination array; must be either the same type as src or 8-bit. + Threshold value. + Maximum value to use with CV_THRESH_BINARY and CV_THRESH_BINARY_INV thresholding types. + Thresholding type. + + + + Returns trace of matrix + + The source matrix. + sum of diagonal elements of the matrix src1 + + + + + + + + + + + + + + + Performs matrix transform of every array element + + The first source array. + The destination array. + Transformation matrix. + + + + Performs matrix transform of every array element + + The first source array. + The destination array. + Transformation matrix. + Optional shift vector. + + + + Performs matrix transform of every array element + + The first source array. + The destination array. + Transformation matrix. + + + + Performs matrix transform of every array element + + The first source array. + The destination array. + Transformation matrix. + Optional shift vector. + + + + Transposes matrix + + The source matrix. + The destination matrix. + + + + Transposes matrix + + The source matrix. + The destination matrix. + + + + Gathers all node pointers to the single sequence + + + The initial tree node. + Header size of the created sequence (sizeof(CvSeq) is the most used value). + Container for the sequence. + + + + + + + + + + + + + + + Returns type of the object + + The object pointer. + + + + + Returns type of the object + + The OpenCV object. + + + + + Transforms image to compensate lens distortion. + + The input (distorted) image. + The output (corrected) image. + The camera matrix (A) [fx 0 cx; 0 fy cy; 0 0 1]. + The vector of distortion coefficients, 4x1 or 1x4 [k1, k2, p1, p2]. + + + + Transforms image to compensate lens distortion. + + The input (distorted) image. + The output (corrected) image. + The camera matrix (A) [fx 0 cx; 0 fy cy; 0 0 1]. + The vector of distortion coefficients, 4x1 or 1x4 [k1, k2, p1, p2]. + + + + + Computes the ideal point coordinates from the observed point coordinates + + The observed point coordinates. + The ideal point coordinates, after undistortion and reverse perspective transformation. + The camera matrix A=[fx 0 cx; 0 fy cy; 0 0 1]. + The vector of distortion coefficients, 4x1, 1x4, 5x1 or 1x5. + The rectification transformation in object space (3x3 matrix). R1 or R2, computed by cvStereoRectify can be passed here. If the parameter is null, the identity matrix is used. + The new camera matrix (3x3) or the new projection matrix (3x4). P1 or P2, computed by cvStereoRectify can be passed here. If the parameter is null, the identity matrix is used. + + + + Unregisters the type + + Name of the unregistered type. + + + + Updates motion history image by moving silhouette + + Silhouette mask that has non-zero pixels where the motion occurs. + Motion history image, that is updated by the function (single-channel, 32-bit floating-point) + Current time in milliseconds or other units. + Maximal duration of motion track in the same units as timestamp. + + + + Switches between optimized/non-optimized modes + + Use optimized (true) or not (false). + the number of optimized functions loaded + + + + + + + + + + + + + + + + + + + + + + + Waits for key event infinitely (delay<=0) or for "delay" milliseconds. + Returns the code of the pressed key or -1 if no key were pressed until the specified timeout has elapsed. + + key code + + + + Waits for key event infinitely (delay<=0) or for "delay" milliseconds. + Returns the code of the pressed key or -1 if no key were pressed until the specified timeout has elapsed. + + Delay in milliseconds. + key code + + + + Applies affine transformation to the image. + + Source image. + Destination image. + 2x3 transformation matrix. + + + + Applies affine transformation to the image. + + Source image. + Destination image. + 2x3 transformation matrix. + A combination of interpolation method and the optional flags. + + + + Applies affine transformation to the image. + + Source image. + Destination image. + 2x3 transformation matrix. + A combination of interpolation method and the optional flags. + A value used to fill outliers. + + + + Applies perspective transformation to the image. + + Source image. + Destination image. + 3x3 transformation matrix. + + + + Applies perspective transformation to the image. + + Source image. + Destination image. + 3x3 transformation matrix. + A combination of interpolation method and the optional flags. + + + + Applies perspective transformation to the image. + + Source image. + Destination image. + 3x3 transformation matrix. + A combination of interpolation method and the optional flags. + A value used to fill outliers. + + + + Does watershed segmentation. + + The input 8-bit 3-channel image. + The input/output 32-bit single-channel image (map) of markers. + + + + Writes user object + + File storage. + Name, of the written object. Should be null if and only if the parent structure is a sequence. + Pointer to the object. + + + + Writes user object + + File storage. + Name, of the written object. Should be null if and only if the parent structure is a sequence. + Pointer to the object. + The attributes of the object. They are specific for each particular type. + + + + Writes comment + + File storage. + The written comment, single-line or multi-line. + + + + Writes comment + + File storage. + The written comment, single-line or multi-line. + If true, the function tries to put the comment in the end of current line. + If the flag is false, if the comment is multi-line, or if it does not fit in the end of the current line, the comment starts from a new line. + + + + Writes file node to another file storage + + Destination file storage. + New name of the file node in the destination file storage. To keep the existing name, use cvGetFileNodeName(node). + The written node + If the written node is a collection and this parameter is true, no extra level of hierarchy is created. + Instead, all the elements of node are written into the currently written structure. + Of course, map elements may be written only to map, and sequence elements may be written only to sequence. + + + + Writes/appends one frame to video file. + + video writer structure. + the written frame. + + + + + Writes an integer value + + File storage. + Name of the written value. Should be NULL if and only if the parent structure is a sequence. + The written value. + + + + Writes multiple numbers + + Type of the elements in src + File storage. + Written array + Format + + + + Writes a floating-point value + + File storage. + Name of the written value. Should be null if and only if the parent structure is a sequence. + The written value. + + + + Writes a text string + + File storage. + Name of the written string. Should be null if and only if the parent structure is a sequence. + The written text string. + + + + Writes a text string + + File storage. + Name of the written string. Should be null if and only if the parent structure is a sequence. + The written text string. + If true, the written string is put in quotes, regardless of whether they are required or not. + Otherwise, if the flag is false, quotes are used only when they are required (e.g. when the string starts with a digit or contains spaces). + + + + Performs per-element bit-wise "exclusive or" operation on two arrays + + The first source array. + The second source array. + The destination array. am> + + + + Performs per-element bit-wise "exclusive or" operation on two arrays + + The first source array. + The second source array. + The destination array. + Operation mask, 8-bit single channel array; specifies elements of destination array to be changed. + + + + Performs per-element bit-wise "exclusive or" operation on array and scalar + + The source array. + Scalar to use in the operation. + The destination array. + + + + Performs per-element bit-wise "exclusive or" operation on array and scalar + + The source array. + Scalar to use in the operation. + The destination array. + Operation mask, 8-bit single channel array; specifies elements of destination array to be changed. + + + + Decrements array data reference counter． + + Input array. + + + + Returns determinant of matrix + + The source matrix. + determinant of the square matrix mat + + + + Performs forward or inverse Discrete Cosine transform of 1D or 2D floating-point array + + Source array, real 1D or 2D array. + Destination array of the same size and same type as the source. + Transformation flags. + + + + Decode image stored in the buffer + + The input array of vector of bytes + Specifies color type of the loaded image + + + + + Decode image stored in the buffer + + The input array of vector of bytes + Specifies color type of the loaded image + + + + + Computes projection matrix decomposition + + The 3x4 input projection matrix P + The output 3x3 internal calibration matrix K + The output 3x3 external rotation matrix R + The output 4x1 external homogenious position vector C + + + + Computes projection matrix decomposition + + The 3x4 input projection matrix P + The output 3x3 internal calibration matrix K + The output 3x3 external rotation matrix R + The output 4x1 external homogenious position vector C + Optional 3x3 rotation matrix around x-axis + Optional 3x3 rotation matrix around y-axis + Optional 3x3 rotation matrix around z-axis + + + + Computes projection matrix decomposition + + The 3x4 input projection matrix P + The output 3x3 internal calibration matrix K + The output 3x3 external rotation matrix R + The output 4x1 external homogenious position vector C + Optional 3x3 rotation matrix around x-axis + Optional 3x3 rotation matrix around y-axis + Optional 3x3 rotation matrix around z-axis + Optional 3 points containing the three Euler angles of rotation + + + + Deletes moire in given image + + Image. + + + + Destroys all the opened HighGUI windows. + + + + + Destroys the window with a given name. + + Name of the window to be destroyed. + + + + Performs forward or inverse Discrete Fourier transform of 1D or 2D floating-point array + + Source array, real or complex. + Destination array of the same size and same type as the source. + Transformation flags + + + + Performs forward or inverse Discrete Fourier transform of 1D or 2D floating-point array + + Source array, real or complex. + Destination array of the same size and same type as the source. + Transformation flags + Number of nonzero rows to in the source array (in case of forward 2d transform), or a number of rows of interest in the destination array (in case of inverse 2d transform). If the value is negative, zero, or greater than the total number of rows, it is ignored. The parameter can be used to speed up 2d convolution/correlation when computing them via DFT. + + + + Performs forward or inverse Discrete Fourier transform of 1D or 2D floating-point array + + Source array, real or complex. + Destination array of the same size and same type as the source. + Transformation flags + + + + Performs forward or inverse Discrete Fourier transform of 1D or 2D floating-point array + + Source array, real or complex. + Destination array of the same size and same type as the source. + Transformation flags + Number of nonzero rows to in the source array (in case of forward 2d transform), or a number of rows of interest in the destination array (in case of inverse 2d transform). If the value is negative, zero, or greater than the total number of rows, it is ignored. The parameter can be used to speed up 2d convolution/correlation when computing them via DFT. + + + + Dilates image by using arbitrary structuring element. + + Source image. + Destination image. + + + + Dilates image by using arbitrary structuring element. + + Source image. + Destination image. + Structuring element used for erosion. If it is null, a 3x3 rectangular structuring element is used. + + + + Dilates image by using arbitrary structuring element. + + Source image. + Destination image. + Structuring element used for erosion. If it is null, a 3x3 rectangular structuring element is used. + Number of times erosion is applied. + + + + Display text on the window's image as an overlay for delay milliseconds. This is not editing the image's data. The text is display on the top of the image. + + Name of the window + Overlay text to write on the window’s image + Delay to display the overlay text. If this function is called before the previous overlay text time out, the timer is restarted and the text updated. . If this value is zero, the text never disapers. + + + + + + Name of the window + Text to write on the window’s statusbar + Delay to display the text. If this function is called before the previous text time out, the timer is restarted and the text updated. If this value is zero, the text never disapers. + + + + Calculates distance to closest zero pixel for all non-zero pixels of source image. + + Source 8-bit single-channel (binary) image. + Output image with calculated distances (32-bit floating-point, single-channel). + + + + Calculates distance to closest zero pixel for all non-zero pixels of source image. + + Source 8-bit single-channel (binary) image. + Output image with calculated distances (32-bit floating-point, single-channel). + Type of distance. + + + + Calculates distance to closest zero pixel for all non-zero pixels of source image. + + Source 8-bit single-channel (binary) image. + Output image with calculated distances (32-bit floating-point, single-channel). + Type of distance. + Size of distance transform mask; can be 3, 5 or 0. In case of CV_DIST_L1 or CV_DIST_C the parameter is forced to 3, because 3×3 mask gives the same result as 5x5 yet it is faster. When mask_size==0, a different non-approximate algorithm is used to calculate distances. + + + + Calculates distance to closest zero pixel for all non-zero pixels of source image. + + Source 8-bit single-channel (binary) image. + Output image with calculated distances (32-bit floating-point, single-channel). + Type of distance. + Size of distance transform mask; can be 3, 5 or 0. In case of CV_DIST_L1 or CV_DIST_C the parameter is forced to 3, because 3×3 mask gives the same result as 5x5 yet it is faster. When mask_size==0, a different non-approximate algorithm is used to calculate distances. + User-defined mask in case of user-defined distance, it consists of 2 numbers (horizontal/vertical shift cost, diagonal shift cost) in case of 3x3 mask and 3 numbers (horizontal/vertical shift cost, diagonal shift cost, knight’s move cost) in case of 5x5 mask. + + + + Calculates distance to closest zero pixel for all non-zero pixels of source image. + + Source 8-bit single-channel (binary) image. + Output image with calculated distances (32-bit floating-point, single-channel). + Type of distance. + Size of distance transform mask; can be 3, 5 or 0. In case of CV_DIST_L1 or CV_DIST_C the parameter is forced to 3, because 3×3 mask gives the same result as 5x5 yet it is faster. When mask_size==0, a different non-approximate algorithm is used to calculate distances. + User-defined mask in case of user-defined distance, it consists of 2 numbers (horizontal/vertical shift cost, diagonal shift cost) in case of 3x3 mask and 3 numbers (horizontal/vertical shift cost, diagonal shift cost, knight’s move cost) in case of 5x5 mask. + The optional output 2d array of labels of integer type and the same size as src and dst, can now be used only with mask_size==3 or 5. + + + + Calculates distance to closest zero pixel for all non-zero pixels of source image. + + Source 8-bit single-channel (binary) image. + Output image with calculated distances (32-bit floating-point, single-channel). + Type of distance. + Size of distance transform mask; can be 3, 5 or 0. In case of CV_DIST_L1 or CV_DIST_C the parameter is forced to 3, because 3×3 mask gives the same result as 5x5 yet it is faster. When mask_size==0, a different non-approximate algorithm is used to calculate distances. + User-defined mask in case of user-defined distance, it consists of 2 numbers (horizontal/vertical shift cost, diagonal shift cost) in case of 3x3 mask and 3 numbers (horizontal/vertical shift cost, diagonal shift cost, knight’s move cost) in case of 5x5 mask. + The optional output 2d array of labels of integer type and the same size as src and dst, can now be used only with mask_size==3 or 5. + + + + + Performs per-element division of two arrays + + The first source array. If the pointer is NULL, the array is assumed to be all 1’s. + The second source array. + The destination array. + + + + Performs per-element division of two arrays + + The first source array. If the pointer is NULL, the array is assumed to be all 1’s. + The second source array. + The destination array. + Optional scale factor + + + + Calculates dot product of two arrays in Euclidean metrics + + The first source array. + The second source array. + + + + + Draws the individual chessboard corners detected (as red circles) in case if the board was not found (pattern_was_found=0) or the colored corners connected with lines when the board was found (pattern_was_found≠0). + + The destination image; it must be 8-bit color image. + The number of inner corners per chessboard row and column. + The array of corners detected. + Indicates whether the complete board was found (≠0) or not (=0). One may just pass the return value cvFindChessboardCorners here. + + + + Draws contour outlines or interiors in the image + + Image where the contours are to be drawn. Like in any other drawing function, the contours are clipped with the ROI. + Reference to the first contour. + Color of the external contours. + Color of internal contours (holes). + Maximal level for drawn contours. If 0, only contour is drawn. If 1, the contour and all contours after it on the same level are drawn. If 2, all contours after and all contours one level below the contours are drawn, etc. If the value is negative, the function does not draw the contours following after contour but draws child contours of contour up to abs(max_level)-1 level. + + + + Draws contour outlines or interiors in the image + + Image where the contours are to be drawn. Like in any other drawing function, the contours are clipped with the ROI. + Reference to the first contour. + Color of the external contours. + Color of internal contours (holes). + Maximal level for drawn contours. If 0, only contour is drawn. If 1, the contour and all contours after it on the same level are drawn. If 2, all contours after and all contours one level below the contours are drawn, etc. If the value is negative, the function does not draw the contours following after contour but draws child contours of contour up to abs(max_level)-1 level. + Thickness of lines the contours are drawn with. If it is negative (e.g. =CV_FILLED), the contour interiors are drawn. + + + + Draws contour outlines or interiors in the image + + Image where the contours are to be drawn. Like in any other drawing function, the contours are clipped with the ROI. + Reference to the first contour. + Color of the external contours. + Color of internal contours (holes). + Maximal level for drawn contours. If 0, only contour is drawn. If 1, the contour and all contours after it on the same level are drawn. If 2, all contours after and all contours one level below the contours are drawn, etc. If the value is negative, the function does not draw the contours following after contour but draws child contours of contour up to abs(max_level)-1 level. + Thickness of lines the contours are drawn with. If it is negative (e.g. =CV_FILLED), the contour interiors are drawn. + Type of the contour segments. + + + + Draws contour outlines or interiors in the image + + Image where the contours are to be drawn. Like in any other drawing function, the contours are clipped with the ROI. + Reference to the first contour. + Color of the external contours. + Color of internal contours (holes). + Maximal level for drawn contours. If 0, only contour is drawn. If 1, the contour and all contours after it on the same level are drawn. If 2, all contours after and all contours one level below the contours are drawn, etc. If the value is negative, the function does not draw the contours following after contour but draws child contours of contour up to abs(max_level)-1 level. + Thickness of lines the contours are drawn with. If it is negative (e.g. =CV_FILLED), the contour interiors are drawn. + Type of the contour segments. + Shift all the point coordinates by the specified value. It is useful in case if the contours retrieved in some image ROI and then the ROI offset needs to be taken into account during the rendering. + + + + Calculates absolute difference between two arrays + + The first source array. + The second source array. + The destination array. + + + + Calculates absolute difference between array and scalar + + The source array. + The destination array. + + + + Calculates absolute difference between array and scalar + + The source array. + The destination array. + The scalar. + + + + Adds frame to accumulator + + Input image, 1- or 3-channel, 8-bit or 32-bit floating point. (each channel of multi-channel image is processed independently). + Accumulator of the same number of channels as input image, 32-bit or 64-bit floating-point. + + + + Adds frame to accumulator + + Input image, 1- or 3-channel, 8-bit or 32-bit floating point. (each channel of multi-channel image is processed independently). + Accumulator of the same number of channels as input image, 32-bit or 64-bit floating-point. + Optional operation mask. + + + + Applies adaptive threshold to array. + + Source image. + Destination image. + Maximum value that is used with Binary and BinaryInv. + + + + Applies adaptive threshold to array. + + Source image. + Destination image. + Maximum value that is used with Binary and BinaryInv. + Adaptive thresholding algorithm to use: MeanC or GaussianC. + + + + Applies adaptive threshold to array. + + Source image. + Destination image. + Maximum value that is used with Binary and BinaryInv. + Adaptive thresholding algorithm to use: MeanC or GaussianC. + Thresholding type. + + + + Applies adaptive threshold to array. + + Source image. + Destination image. + Maximum value that is used with Binary and BinaryInv. + Adaptive thresholding algorithm to use: MeanC or GaussianC. + Thresholding type. + The size of a pixel neighborhood that is used to calculate a threshold value for the pixel: 3, 5, 7, ... + + + + Applies adaptive threshold to array. + + Source image. + Destination image. + Maximum value that is used with Binary and BinaryInv. + Adaptive thresholding algorithm to use: MeanC or GaussianC. + Thresholding type. + The size of a pixel neighborhood that is used to calculate a threshold value for the pixel: 3, 5, 7, ... + The method-dependent parameter. For the methods MeanC and GaussianC it is a constant subtracted from mean or weighted mean (see the discussion), though it may be negative. + + + + Computes per-element sum of two arrays + + The first source array. + The second source array. + The destination array. + + + + Computes per-element sum of two arrays + + The first source array. + The second source array. + The destination array. + Operation mask, 8-bit single channel array; specifies elements of destination array to be changed. + + + + Computes sum of array and scalar + + The source array. + Added scalar. + The destination array. + + + + Computes sum of array and scalar + + The source array. + Added scalar. + The destination array. + Operation mask, 8-bit single channel array; specifies elements of destination array to be changed. + + + + Create the font to be used to draw text on an image + + Image where the text should be drawn + Text to write on the image + Point(x,y) where the text should start on the image + Font to use to draw the text + + + + Computes weighted sum of two arrays + + The first source array. + Weight of the first array elements. + The second source array. + Weight of the second array elements. + Scalar, added to each sum. + The destination array. + + + + Allocates memory buffer + + Buffer size in bytes. + + + + + Calculates per-element bit-wise conjunction of two arrays + + The first source array. + The second source array. + The destination array. + + + + Calculates per-element bit-wise conjunction of two arrays + + The first source array. + The second source array. + The destination array. + Operation mask, 8-bit single channel array; specifies elements of destination array to be changed. + + + + Calculates per-element bit-wise conjunction of array and scalar + + The source array. + Scalar to use in the operation. + The destination array. + + + + Calculates per-element bit-wise conjunction of array and scalar + + The source array. + Scalar to use in the operation. + The destination array. + Operation mask, 8-bit single channel array; specifies elements of destination array to be changed. + + + + Approximates Freeman chain(s) with polygonal curve + + Freeman chain(s) + Storage location for the resulting polylines. + + + + + Approximates Freeman chain(s) with polygonal curve + + Freeman chain(s) + Storage location for the resulting polylines. + Approximation method. + /// + + + + Approximates Freeman chain(s) with polygonal curve + + Freeman chain(s) + Storage location for the resulting polylines. + Approximation method. + Method parameter (not used now). + + + + + Approximates Freeman chain(s) with polygonal curve + + Freeman chain(s) + Storage location for the resulting polylines. + Approximation method. + Method parameter (not used now). + Approximates only those contours whose perimeters are not less than minimal_perimeter. Other chains are removed from the resulting structure. + + + + + Approximates Freeman chain(s) with polygonal curve + + Freeman chain(s) + Storage location for the resulting polylines. + Approximation method. + Method parameter (not used now). + Approximates only those contours whose perimeters are not less than minimal_perimeter. Other chains are removed from the resulting structure. + If true, the function approximates all chains that access can be obtained to from src_seq by h_next or v_next links. If false, the single chain is approximated. + + + + + Approximates polygonal curve(s) with desired precision. + + Sequence of array of points. + Header size of approximated curve[s]. + Container for approximated contours. If it is null, the input sequences' storage is used. + Approximation method; only ApproxPolyMethod.DP is supported, that corresponds to Douglas-Peucker algorithm. + Method-specific parameter; in case of CV_POLY_APPROX_DP it is a desired approximation accuracy. + + + + + Approximates polygonal curve(s) with desired precision. + + Sequence of array of points. + Header size of approximated curve[s]. + Container for approximated contours. If it is null, the input sequences' storage is used. + Approximation method; only ApproxPolyMethod.DP is supported, that corresponds to Douglas-Peucker algorithm. + Method-specific parameter; in case of CV_POLY_APPROX_DP it is a desired approximation accuracy. + If case if src_seq is sequence it means whether the single sequence should be approximated + or all sequences on the same level or below src_seq (see cvFindContours for description of hierarchical contour structures). + And if src_seq is array (CvMat*) of points, the parameter specifies whether the curve is closed (parameter2==true) or not (parameter2==false). + + + + + Calculates contour perimeter or curve length + + Sequence or array of the curve points. + + + + + Calculates contour perimeter or curve length + + Sequence or array of the curve points. + Starting and ending points of the curve, by default the whole curve length is calculated. + + + + + Calculates contour perimeter or curve length + + Sequence or array of the curve points. + Starting and ending points of the curve, by default the whole curve length is calculated. + Indicates whether the curve is closed or not. There are 3 cases: + * is_closed=0 - the curve is assumed to be unclosed. + * is_closed>0 - the curve is assumed to be closed. + * is_closed<0 - if curve is sequence, the flag CV_SEQ_FLAG_CLOSED of ((CvSeq*)curve)->flags is checked to determine if the curve is closed or not, otherwise (curve is represented by array (CvMat*) of points) it is assumed to be unclosed. + + + + + initializes CvAttrList structure + + + + + + initializes CvAttrList structure + + array of (attribute_name,attribute_value) pairs + + + + + initializes CvAttrList structure + + array of (attribute_name,attribute_value) pairs + pointer to next chunk of the attributes list + + + + + Calculates average (mean) of array elements + + The array. + + + + + Calculates average (mean) of array elements + + The array. + The optional operation mask. + + + + + Calculates average (mean) of array elements + + The array. + Pointer to the mean value, may be null if it is not needed. + Pointer to the standard deviation. + + + + Calculates average (mean) of array elements + + The array. + Pointer to the mean value, may be null if it is not needed. + Pointer to the standard deviation. + The optional operation mask. + + + + Finds rectangular regions in the given image that are likely to contain objects the cascade has been trained for and returns those regions as a sequence of rectangles. + + Image to detect objects in. + Haar classifier cascade in internal representation. + Memory storage to store the resultant sequence of the object candidate rectangles. + + + + + Finds rectangular regions in the given image that are likely to contain objects the cascade has been trained for and returns those regions as a sequence of rectangles. + + Image to detect objects in. + Haar classifier cascade in internal representation. + Memory storage to store the resultant sequence of the object candidate rectangles. + The factor by which the search window is scaled between the subsequent scans, for example, 1.1 means increasing window by 10%. + + + + + Finds rectangular regions in the given image that are likely to contain objects the cascade has been trained for and returns those regions as a sequence of rectangles. + + Image to detect objects in. + Haar classifier cascade in internal representation. + Memory storage to store the resultant sequence of the object candidate rectangles. + The factor by which the search window is scaled between the subsequent scans, for example, 1.1 means increasing window by 10%. + Minimum number (minus 1) of neighbor rectangles that makes up an object. All the groups of a smaller number of rectangles than min_neighbors-1 are rejected. If min_neighbors is 0, the function does not any grouping at all and returns all the detected candidate rectangles, which may be useful if the user wants to apply a customized grouping procedure. + + + + + Finds rectangular regions in the given image that are likely to contain objects the cascade has been trained for and returns those regions as a sequence of rectangles. + + Image to detect objects in. + Haar classifier cascade in internal representation. + Memory storage to store the resultant sequence of the object candidate rectangles. + The factor by which the search window is scaled between the subsequent scans, for example, 1.1 means increasing window by 10%. + Minimum number (minus 1) of neighbor rectangles that makes up an object. All the groups of a smaller number of rectangles than min_neighbors-1 are rejected. If min_neighbors is 0, the function does not any grouping at all and returns all the detected candidate rectangles, which may be useful if the user wants to apply a customized grouping procedure. + Mode of operation. Currently the only flag that may be specified is CV_HAAR_DO_CANNY_PRUNING. If it is set, the function uses Canny edge detector to reject some image regions that contain too few or too much edges and thus can not contain the searched object. The particular threshold values are tuned for face detection and in this case the pruning speeds up the processing. + + + + + Finds rectangular regions in the given image that are likely to contain objects the cascade has been trained for and returns those regions as a sequence of rectangles. + + Image to detect objects in. + Haar classifier cascade in internal representation. + Memory storage to store the resultant sequence of the object candidate rectangles. + The factor by which the search window is scaled between the subsequent scans, for example, 1.1 means increasing window by 10%. + Minimum number (minus 1) of neighbor rectangles that makes up an object. All the groups of a smaller number of rectangles than min_neighbors-1 are rejected. If min_neighbors is 0, the function does not any grouping at all and returns all the detected candidate rectangles, which may be useful if the user wants to apply a customized grouping procedure. + Mode of operation. Currently the only flag that may be specified is CV_HAAR_DO_CANNY_PRUNING. If it is set, the function uses Canny edge detector to reject some image regions that contain too few or too much edges and thus can not contain the searched object. The particular threshold values are tuned for face detection and in this case the pruning speeds up the processing. + Minimum window size. By default, it is set to the size of samples the classifier has been trained on (~20×20 for face detection). + Minimum window size. By default, it is set to the Size(0,0) + + + + + Finds circles in grayscale image using Hough transform. + + The input 8-bit single-channel grayscale image. + The storage for the circles detected. It can be a memory storage or single row/single column matrix (CvMat*) of type CV_32FC3, to which the circles' parameters are written. + Currently, the only implemented method is CV_HOUGH_GRADIENT, which is basically 21HT + Resolution of the accumulator used to detect centers of the circles. For example, if it is 1, the accumulator will have the same resolution as the input image, if it is 2 - accumulator will have twice smaller width and height, etc. + Minimum distance between centers of the detected circles. If the parameter is too small, multiple neighbor circles may be falsely detected in addition to a true one. If it is too large, some circles may be missed. + + + + + Finds circles in grayscale image using Hough transform. + + The input 8-bit single-channel grayscale image. + The storage for the circles detected. It can be a memory storage or single row/single column matrix (CvMat*) of type CV_32FC3, to which the circles' parameters are written. + Currently, the only implemented method is CV_HOUGH_GRADIENT, which is basically 21HT + Resolution of the accumulator used to detect centers of the circles. For example, if it is 1, the accumulator will have the same resolution as the input image, if it is 2 - accumulator will have twice smaller width and height, etc. + Minimum distance between centers of the detected circles. If the parameter is too small, multiple neighbor circles may be falsely detected in addition to a true one. If it is too large, some circles may be missed. + The first method-specific parameter. In case of CV_HOUGH_GRADIENT it is the higher threshold of the two passed to Canny edge detector (the lower one will be twice smaller). + + + + + Finds circles in grayscale image using Hough transform. + + The input 8-bit single-channel grayscale image. + The storage for the circles detected. It can be a memory storage or single row/single column matrix (CvMat*) of type CV_32FC3, to which the circles' parameters are written. + Currently, the only implemented method is CV_HOUGH_GRADIENT, which is basically 21HT + Resolution of the accumulator used to detect centers of the circles. For example, if it is 1, the accumulator will have the same resolution as the input image, if it is 2 - accumulator will have twice smaller width and height, etc. + Minimum distance between centers of the detected circles. If the parameter is too small, multiple neighbor circles may be falsely detected in addition to a true one. If it is too large, some circles may be missed. + The first method-specific parameter. In case of CV_HOUGH_GRADIENT it is the higher threshold of the two passed to Canny edge detector (the lower one will be twice smaller). + The second method-specific parameter. In case of CV_HOUGH_GRADIENT it is accumulator threshold at the center detection stage. The smaller it is, the more false circles may be detected. Circles, corresponding to the larger accumulator values, will be returned first. + + + + + Finds circles in grayscale image using Hough transform. + + The input 8-bit single-channel grayscale image. + The storage for the circles detected. It can be a memory storage or single row/single column matrix (CvMat*) of type CV_32FC3, to which the circles' parameters are written. + Currently, the only implemented method is CV_HOUGH_GRADIENT, which is basically 21HT + Resolution of the accumulator used to detect centers of the circles. For example, if it is 1, the accumulator will have the same resolution as the input image, if it is 2 - accumulator will have twice smaller width and height, etc. + Minimum distance between centers of the detected circles. If the parameter is too small, multiple neighbor circles may be falsely detected in addition to a true one. If it is too large, some circles may be missed. + The first method-specific parameter. In case of CV_HOUGH_GRADIENT it is the higher threshold of the two passed to Canny edge detector (the lower one will be twice smaller). + The second method-specific parameter. In case of CV_HOUGH_GRADIENT it is accumulator threshold at the center detection stage. The smaller it is, the more false circles may be detected. Circles, corresponding to the larger accumulator values, will be returned first. + Minimal radius of the circles to search for. + + + + + Finds circles in grayscale image using Hough transform. + + The input 8-bit single-channel grayscale image. + The storage for the circles detected. It can be a memory storage or single row/single column matrix (CvMat*) of type CV_32FC3, to which the circles' parameters are written. + Currently, the only implemented method is CV_HOUGH_GRADIENT, which is basically 21HT + Resolution of the accumulator used to detect centers of the circles. For example, if it is 1, the accumulator will have the same resolution as the input image, if it is 2 - accumulator will have twice smaller width and height, etc. + Minimum distance between centers of the detected circles. If the parameter is too small, multiple neighbor circles may be falsely detected in addition to a true one. If it is too large, some circles may be missed. + The first method-specific parameter. In case of CV_HOUGH_GRADIENT it is the higher threshold of the two passed to Canny edge detector (the lower one will be twice smaller). + The second method-specific parameter. In case of CV_HOUGH_GRADIENT it is accumulator threshold at the center detection stage. The smaller it is, the more false circles may be detected. Circles, corresponding to the larger accumulator values, will be returned first. + Minimal radius of the circles to search for. + Maximal radius of the circles to search for. By default the maximal radius is set to max(image_width, image_height). + + + + + Finds circles in grayscale image using Hough transform. + + The input 8-bit single-channel grayscale image. + The storage for the circles detected. It can be a memory storage or single row/single column matrix (CvMat*) of type CV_32FC3, to which the circles' parameters are written. + Currently, the only implemented method is CV_HOUGH_GRADIENT, which is basically 21HT + Resolution of the accumulator used to detect centers of the circles. For example, if it is 1, the accumulator will have the same resolution as the input image, if it is 2 - accumulator will have twice smaller width and height, etc. + Minimum distance between centers of the detected circles. If the parameter is too small, multiple neighbor circles may be falsely detected in addition to a true one. If it is too large, some circles may be missed. + + + + + Finds circles in grayscale image using Hough transform. + + The input 8-bit single-channel grayscale image. + The storage for the circles detected. It can be a memory storage or single row/single column matrix (CvMat*) of type CV_32FC3, to which the circles' parameters are written. + Currently, the only implemented method is CV_HOUGH_GRADIENT, which is basically 21HT + Resolution of the accumulator used to detect centers of the circles. For example, if it is 1, the accumulator will have the same resolution as the input image, if it is 2 - accumulator will have twice smaller width and height, etc. + Minimum distance between centers of the detected circles. If the parameter is too small, multiple neighbor circles may be falsely detected in addition to a true one. If it is too large, some circles may be missed. + The first method-specific parameter. In case of CV_HOUGH_GRADIENT it is the higher threshold of the two passed to Canny edge detector (the lower one will be twice smaller). + + + + + Finds circles in grayscale image using Hough transform. + + The input 8-bit single-channel grayscale image. + The storage for the circles detected. It can be a memory storage or single row/single column matrix (CvMat*) of type CV_32FC3, to which the circles' parameters are written. + Currently, the only implemented method is CV_HOUGH_GRADIENT, which is basically 21HT + Resolution of the accumulator used to detect centers of the circles. For example, if it is 1, the accumulator will have the same resolution as the input image, if it is 2 - accumulator will have twice smaller width and height, etc. + Minimum distance between centers of the detected circles. If the parameter is too small, multiple neighbor circles may be falsely detected in addition to a true one. If it is too large, some circles may be missed. + The first method-specific parameter. In case of CV_HOUGH_GRADIENT it is the higher threshold of the two passed to Canny edge detector (the lower one will be twice smaller). + The second method-specific parameter. In case of CV_HOUGH_GRADIENT it is accumulator threshold at the center detection stage. The smaller it is, the more false circles may be detected. Circles, corresponding to the larger accumulator values, will be returned first. + + + + + Finds circles in grayscale image using Hough transform. + + The input 8-bit single-channel grayscale image. + The storage for the circles detected. It can be a memory storage or single row/single column matrix (CvMat*) of type CV_32FC3, to which the circles' parameters are written. + Currently, the only implemented method is CV_HOUGH_GRADIENT, which is basically 21HT + Resolution of the accumulator used to detect centers of the circles. For example, if it is 1, the accumulator will have the same resolution as the input image, if it is 2 - accumulator will have twice smaller width and height, etc. + Minimum distance between centers of the detected circles. If the parameter is too small, multiple neighbor circles may be falsely detected in addition to a true one. If it is too large, some circles may be missed. + The first method-specific parameter. In case of CV_HOUGH_GRADIENT it is the higher threshold of the two passed to Canny edge detector (the lower one will be twice smaller). + The second method-specific parameter. In case of CV_HOUGH_GRADIENT it is accumulator threshold at the center detection stage. The smaller it is, the more false circles may be detected. Circles, corresponding to the larger accumulator values, will be returned first. + Minimal radius of the circles to search for. + + + + + Finds circles in grayscale image using Hough transform. + + The input 8-bit single-channel grayscale image. + The storage for the circles detected. It can be a memory storage or single row/single column matrix (CvMat*) of type CV_32FC3, to which the circles' parameters are written. + Currently, the only implemented method is CV_HOUGH_GRADIENT, which is basically 21HT + Resolution of the accumulator used to detect centers of the circles. For example, if it is 1, the accumulator will have the same resolution as the input image, if it is 2 - accumulator will have twice smaller width and height, etc. + Minimum distance between centers of the detected circles. If the parameter is too small, multiple neighbor circles may be falsely detected in addition to a true one. If it is too large, some circles may be missed. + The first method-specific parameter. In case of CV_HOUGH_GRADIENT it is the higher threshold of the two passed to Canny edge detector (the lower one will be twice smaller). + The second method-specific parameter. In case of CV_HOUGH_GRADIENT it is accumulator threshold at the center detection stage. The smaller it is, the more false circles may be detected. Circles, corresponding to the larger accumulator values, will be returned first. + Minimal radius of the circles to search for. + Maximal radius of the circles to search for. By default the maximal radius is set to max(image_width, image_height). + + + + + Finds lines in binary image using Hough transform. + + The input 8-bit single-channel binary image. In case of probabilistic method the image is modified by the function. + The storage for the lines detected. It can be a memory storage or single row/single column matrix (CvMat*) of a particular type to which the lines' parameters are written. + The Hough transform variant. + Distance resolution in pixel-related units. + Angle resolution measured in radians. + Threshold parameter. A line is returned by the function if the corresponding accumulator value is greater than threshold. + + + + + Finds lines in binary image using Hough transform. + + The input 8-bit single-channel binary image. In case of probabilistic method the image is modified by the function. + The storage for the lines detected. It can be a memory storage or single row/single column matrix (CvMat*) of a particular type to which the lines' parameters are written. + The Hough transform variant. + Distance resolution in pixel-related units. + Angle resolution measured in radians. + Threshold parameter. A line is returned by the function if the corresponding accumulator value is greater than threshold. + The first method-dependent parameter. + The second method-dependent parameter. + + + + + Finds lines in binary image using Hough transform. + + The input 8-bit single-channel binary image. In case of probabilistic method the image is modified by the function. + The storage for the lines detected. It can be a memory storage or single row/single column matrix (CvMat*) of a particular type to which the lines' parameters are written. + The Hough transform variant. + Distance resolution in pixel-related units. + Angle resolution measured in radians. + Threshold parameter. A line is returned by the function if the corresponding accumulator value is greater than threshold. + + + + + Finds lines in binary image using Hough transform. + + The input 8-bit single-channel binary image. In case of probabilistic method the image is modified by the function. + The storage for the lines detected. It can be a memory storage or single row/single column matrix (CvMat*) of a particular type to which the lines' parameters are written. + The Hough transform variant. + Distance resolution in pixel-related units. + Angle resolution measured in radians. + Threshold parameter. A line is returned by the function if the corresponding accumulator value is greater than threshold. + The first method-dependent parameter. + The second method-dependent parameter. + + + + + Fills array with random numbers + + CvRandState Structure + The array to randomize + + + + Fills array with random numbers and updates the RNG state + + RNG state initialized by cvRNG. + The destination array. + Distribution type. + The first parameter of distribution. In case of uniform distribution it is the inclusive lower boundary of random numbers range. In case of normal distribution it is the mean value of random numbers. + The second parameter of distribution. In case of uniform distribution it is the exclusive upper boundary of random numbers range. In case of normal distribution it is the standard deviation of random numbers. + + + + Initialize CvRandState structure + + CvRandState structure to initialize + The first parameter of distribution. In case of uniform distribution it is the inclusive lower boundary of random numbers range. In case of normal distribution it is the mean value of random numbers. + The second parameter of distribution. In case of uniform distribution it is the exclusive upper boundary of random numbers range. In case of normal distribution it is the standard deviation of random numbers. + Seed value + + + + Initialize CvRandState structure + + CvRandState structure to initialize + The first parameter of distribution. In case of uniform distribution it is the inclusive lower boundary of random numbers range. In case of normal distribution it is the mean value of random numbers. + The second parameter of distribution. In case of uniform distribution it is the exclusive upper boundary of random numbers range. In case of normal distribution it is the standard deviation of random numbers. + Seed value + Type of distribution + + + + Returns 32-bit unsigned integer and updates RNG + + RNG state initialized by RandInit and, optionally, customized by RandSetRange (though, the latter function does not affect on the discussed function outcome). + uniformly-distributed random 32-bit unsigned integer + + + + Returns floating-point random number and updates RNG + + RNG state initialized by cvRNG. + uniformly-distributed random floating-point number from 0..1 range (1 is not included). + + + + updates the number of RANSAC iterations + + + + + + + + + + Changes RNG range while preserving RNG state + + CvRandState structure to be opdated + The first parameter of distribution. In case of uniform distribution it is the inclusive lower boundary of random numbers range. In case of normal distribution it is the mean value of random numbers. + The second parameter of distribution. In case of uniform distribution it is the exclusive upper boundary of random numbers range. In case of normal distribution it is the standard deviation of random numbers. + + + + Changes RNG range while preserving RNG state + + CvRandState structure to be opdated + The first parameter of distribution. In case of uniform distribution it is the inclusive lower boundary of random numbers range. In case of normal distribution it is the mean value of random numbers. + The second parameter of distribution. In case of uniform distribution it is the exclusive upper boundary of random numbers range. In case of normal distribution it is the standard deviation of random numbers. + Index dimension to initialize, -1 = all + + + + Randomly shuffles the array elements + + The input/output matrix. It is shuffled in-place. + + + + Randomly shuffles the array elements + + The input/output matrix. It is shuffled in-place. + The Random Number Generator used to shuffle the elements. When the pointer is null, a temporary RNG will be created and used. + + + + Randomly shuffles the array elements + + The input/output matrix. It is shuffled in-place. + The Random Number Generator used to shuffle the elements. When the pointer is null, a temporary RNG will be created and used. + The relative parameter that characterizes intensity of the shuffling performed. + + + + Fills matrix with given range of numbers as following: + arr(i,j) = (end-start) * (i*cols(arr)+j) / (cols(arr)*rows(arr)) + + The matrix to initialize. It should be single-channel 32-bit, integer or floating-point. + The lower inclusive boundary of the range. + The upper exclusive boundary of the range. + + + + Decodes object and returns pointer to it + + + File storage. + The root object node. + + + + + Finds object and decodes it + + + File storage. + The parent map. If it is null, the function searches a top-level node. + The node name. + + + + + Gets next chain point + + Chain reader state. + Current chain point. + + + + Retrieves integer value from file node + + File node. + integer that is represented by the file node. If the file node is null, default_value is returned. + + + + Retrieves integer value from file node + + File node. + The value that is returned if node is null. + integer that is represented by the file node. If the file node is null, default_value is returned. + + + + Finds file node and returns its value + + File storage. + The parent map. If it is null, the function searches a top-level node. + The node name. + + + + + Finds file node and returns its value + + File storage. + The parent map. If it is null, the function searches a top-level node. + The node name. + The value that is returned if the file node is not found. + + + + + Reads multiple numbers + + + File storage. + The file node (a sequence) to read numbers from. + Reference to the destination array. + Specification of each array element. It has the same format as in cvWriteRawData. + + + + Initializes file node sequence reader + + + File storage. + The sequence reader. Initialize it with cvStartReadRawData. + The number of elements to read. + Destination array. + Specification of each array element. It has the same format as in cvWriteRawData. + + + + Retrieves floating-point value from file node + + File node. + returns floating-point value that is represented by the file node. If the file node is null, default_value is returned. + + + + Retrieves floating-point value from file node + + File node. + The value that is returned if node is null. + returns floating-point value that is represented by the file node. If the file node is null, default_value is returned. + + + + Finds file node and returns its value + + File storage. + The parent map. If it is null, the function searches a top-level node. + The node name. + + + + + Finds file node and returns its value + + File storage. + The parent map. If it is null, the function searches a top-level node. + The node name. + The value that is returned if the file node is not found. + + + + + Retrieves text string from file node + + File node. + returns text string that is represented by the file node. If the file node is null, default_value is returned. + + + + Retrieves text string from file node + + File node. + The value that is returned if node is null. + returns text string that is represented by the file node. If the file node is null, default_value is returned. + + + + Finds file node and returns its value + + File storage. + The parent map. If it is null, the function searches a top-level node. + The node name. + + + + + Finds file node and returns its value + + File storage. + The parent map. If it is null, the function searches a top-level node. + The node name. + The value that is returned if the file node is not found. + + + + + Initializes val[0] with val0, val[1]...val[3] with zeros + + + + + + + Draws simple, thick or filled rectangle + + Image. + X-coordinate of the one of the rectangle vertices. + Y-coordinate of the one of the rectangle vertices. + X-coordinate of the opposite rectangle vertex. + Y-coordinate of the opposite rectangle vertex. + Line color (RGB) or brightness (grayscale image). + + + + Draws simple, thick or filled rectangle + + Image. + X-coordinate of the one of the rectangle vertices. + Y-coordinate of the one of the rectangle vertices. + X-coordinate of the opposite rectangle vertex. + Y-coordinate of the opposite rectangle vertex. + Line color (RGB) or brightness (grayscale image). + Thickness of lines that make up the rectangle. Negative values, e.g. CV_FILLED, make the function to draw a filled rectangle. + + + + Draws simple, thick or filled rectangle + + Image. + X-coordinate of the one of the rectangle vertices. + Y-coordinate of the one of the rectangle vertices. + X-coordinate of the opposite rectangle vertex. + Y-coordinate of the opposite rectangle vertex. + Line color (RGB) or brightness (grayscale image). + Thickness of lines that make up the rectangle. Negative values, e.g. CV_FILLED, make the function to draw a filled rectangle. + Type of the line, see cvLine description. + + + + Draws simple, thick or filled rectangle + + Image. + X-coordinate of the one of the rectangle vertices. + Y-coordinate of the one of the rectangle vertices. + X-coordinate of the opposite rectangle vertex. + Y-coordinate of the opposite rectangle vertex. + Line color (RGB) or brightness (grayscale image). + Thickness of lines that make up the rectangle. Negative values, e.g. CV_FILLED, make the function to draw a filled rectangle. + Type of the line, see cvLine description. + Number of fractional bits in the point coordinates. + + + + Draws simple, thick or filled rectangle + + Image. + One of the rectangle vertices. + Opposite rectangle vertex. + Line color (RGB) or brightness (grayscale image). + + + + Draws simple, thick or filled rectangle + + Image. + One of the rectangle vertices. + Opposite rectangle vertex. + Line color (RGB) or brightness (grayscale image). + Thickness of lines that make up the rectangle. Negative values, e.g. CV_FILLED, make the function to draw a filled rectangle. + + + + Draws simple, thick or filled rectangle + + Image. + One of the rectangle vertices. + Opposite rectangle vertex. + Line color (RGB) or brightness (grayscale image). + Thickness of lines that make up the rectangle. Negative values, e.g. CV_FILLED, make the function to draw a filled rectangle. + Type of the line, see cvLine description. + + + + Draws simple, thick or filled rectangle + + Image. + One of the rectangle vertices. + Opposite rectangle vertex. + Line color (RGB) or brightness (grayscale image). + Thickness of lines that make up the rectangle. Negative values, e.g. CV_FILLED, make the function to draw a filled rectangle. + Type of the line, see cvLine description. + Number of fractional bits in the point coordinates. + + + + Draws simple, thick or filled rectangle + + Image. + Rectangle. + Line color (RGB) or brightness (grayscale image). + + + + Draws simple, thick or filled rectangle + + Image. + Rectangle. + Line color (RGB) or brightness (grayscale image). + Thickness of lines that make up the rectangle. Negative values, e.g. CV_FILLED, make the function to draw a filled rectangle. + + + + Draws simple, thick or filled rectangle + + Image. + Rectangle. + Line color (RGB) or brightness (grayscale image). + Thickness of lines that make up the rectangle. Negative values, e.g. CV_FILLED, make the function to draw a filled rectangle. + Type of the line, see cvLine description. + + + + Draws simple, thick or filled rectangle + + Image. + Rectangle. + Line color (RGB) or brightness (grayscale image). + Thickness of lines that make up the rectangle. Negative values, e.g. CV_FILLED, make the function to draw a filled rectangle. + Type of the line, see cvLine description. + Number of fractional bits in the point coordinates. + + + + Draws simple, thick or filled rectangle + + Image. + X-coordinate of the one of the rectangle vertices. + Y-coordinate of the one of the rectangle vertices. + X-coordinate of the opposite rectangle vertex. + Y-coordinate of the opposite rectangle vertex. + Line color (RGB) or brightness (grayscale image). + + + + Draws simple, thick or filled rectangle + + Image. + X-coordinate of the one of the rectangle vertices. + Y-coordinate of the one of the rectangle vertices. + X-coordinate of the opposite rectangle vertex. + Y-coordinate of the opposite rectangle vertex. + Line color (RGB) or brightness (grayscale image). + Thickness of lines that make up the rectangle. Negative values, e.g. CV_FILLED, make the function to draw a filled rectangle. + + + + Draws simple, thick or filled rectangle + + Image. + X-coordinate of the one of the rectangle vertices. + Y-coordinate of the one of the rectangle vertices. + X-coordinate of the opposite rectangle vertex. + Y-coordinate of the opposite rectangle vertex. + Line color (RGB) or brightness (grayscale image). + Thickness of lines that make up the rectangle. Negative values, e.g. CV_FILLED, make the function to draw a filled rectangle. + Type of the line, see cvLine description. + + + + Draws simple, thick or filled rectangle + + Image. + X-coordinate of the one of the rectangle vertices. + Y-coordinate of the one of the rectangle vertices. + X-coordinate of the opposite rectangle vertex. + Y-coordinate of the opposite rectangle vertex. + Line color (RGB) or brightness (grayscale image). + Thickness of lines that make up the rectangle. Negative values, e.g. CV_FILLED, make the function to draw a filled rectangle. + Type of the line, see cvLine description. + Number of fractional bits in the point coordinates. + + + + Draws simple, thick or filled rectangle + + Image. + One of the rectangle vertices. + Opposite rectangle vertex. + Line color (RGB) or brightness (grayscale image). + + + + Draws simple, thick or filled rectangle + + Image. + One of the rectangle vertices. + Opposite rectangle vertex. + Line color (RGB) or brightness (grayscale image). + Thickness of lines that make up the rectangle. Negative values, e.g. CV_FILLED, make the function to draw a filled rectangle. + + + + Draws simple, thick or filled rectangle + + Image. + One of the rectangle vertices. + Opposite rectangle vertex. + Line color (RGB) or brightness (grayscale image). + Thickness of lines that make up the rectangle. Negative values, e.g. CV_FILLED, make the function to draw a filled rectangle. + Type of the line, see cvLine description. + + + + Draws simple, thick or filled rectangle + + Image. + One of the rectangle vertices. + Opposite rectangle vertex. + Line color (RGB) or brightness (grayscale image). + Thickness of lines that make up the rectangle. Negative values, e.g. CV_FILLED, make the function to draw a filled rectangle. + Type of the line, see cvLine description. + Number of fractional bits in the point coordinates. + + + + Draws simple, thick or filled rectangle + + Image. + Rectangle. + Line color (RGB) or brightness (grayscale image). + + + + Draws simple, thick or filled rectangle + + Image. + Rectangle. + Line color (RGB) or brightness (grayscale image). + Thickness of lines that make up the rectangle. Negative values, e.g. CV_FILLED, make the function to draw a filled rectangle. + + + + Draws simple, thick or filled rectangle + + Image. + Rectangle. + Line color (RGB) or brightness (grayscale image). + Thickness of lines that make up the rectangle. Negative values, e.g. CV_FILLED, make the function to draw a filled rectangle. + Type of the line, see cvLine description. + + + + Draws simple, thick or filled rectangle + + Image. + Rectangle. + Line color (RGB) or brightness (grayscale image). + Thickness of lines that make up the rectangle. Negative values, e.g. CV_FILLED, make the function to draw a filled rectangle. + Type of the line, see cvLine description. + Number of fractional bits in the point coordinates. + + + + Sets a new error handler + + The new error_handler + Current error handler + + + + Sets a new error handler + + The new error_handler + Arbitrary pointer that is transparently passed to the error handler + Pointer to the previously assigned user data pointer + Current error handler + + + + Sets a new error handler + + The new error_handler + Current error handler + + + + Sets a new error handler + + The new error_handler + Arbitrary pointer that is transparently passed to the error handler + Pointer to the previously assigned user data pointer + Current error handler + + + + Reduces matrix to a vector + + The input matrix. + The output single-row/single-column vector that accumulates somehow all the matrix rows/columns. + + + + Reduces matrix to a vector + + The input matrix. + The output single-row/single-column vector that accumulates somehow all the matrix rows/columns. + The dimension index along which the matrix is reduce. 0 means that the matrix is reduced to a single row, 1 means that the matrix is reduced to a single column. -1 means that the dimension is chosen automatically by analysing the dst size. + + + + Reduces matrix to a vector + + The input matrix. + The output single-row/single-column vector that accumulates somehow all the matrix rows/columns. + The dimension index along which the matrix is reduce. 0 means that the matrix is reduced to a single row, 1 means that the matrix is reduced to a single column. -1 means that the dimension is chosen automatically by analysing the dst size. + The reduction operation. + + + + Registers new type + + Type info structure. + + + + Releases the object + + Double pointer to the object. + + + + Releases the object + + Double pointer to the object. + + + + Deallocates BGCodeBookModel structure + + Structure to be released. + + + + Releases the CvCapture structure allocated by cvCreateFileCapture or cvCreateCameraCapture. + + Reference to video capturing structure. + + + + Deallocates ConDensation filter structure + + Structure to be released. + + + + Releases array data. + + Array header. + + + + + + + + + + Destroys a tree of feature vectors + + pointer to tree being destroyed. + + + + Releases file storage + + Reference to the released file storage. + + + + Finishes graph traversal procedure + + Reference to graph traverser. + + + + Releases haar classifier cascade + + Double pointer to the released cascade. + + + + Releases the histogram (header and the data). + + Double pointer to the released histogram. + + + + Releases header and image data + + Reference to the header of the deallocated image. + + + + Releases IplImage header + + Reference to the deallocated header. + + + + Deallocates Kalman filter structure + + Kalman filter structure. + + + + release memory allocated for CvLatentSvmDetector structure + + + + + + Free the given LSH structure. + + + + + + Deallocates matrix. + + Reference to the matrix. + + + + Deallocates multi-dimensional array + + Reference to the array. + + + + Releases memory storage + + Pointer to the released storage. + + + + Deallocates 3D object structure + + Reference to CvPOSIT structure. + + + + Releases pyramid + + + + + + + Deallocates sparse array + + Reference to the array. + + + + Releases block matching stereo correspondence structure + + Reference to the released structure + + + + Releases the state structure of the graph cut-based stereo correspondence algorithm + + Reference to the released structure + + + + Releases the structure IplConvKernel that is no longer needed. + If *element is NULL, the function has no effect. + + Pointer to the deleted structuring element. + + + + Finishes writing to video file and releases the structure. + + Reference to video file writer structure. + + + + Applies generic geometrical transformation to the image. + + Source image. + Destination image. + The map of x-coordinates (32fC1 image). + The map of y-coordinates (32fC1 image). + + + + Applies generic geometrical transformation to the image. + + Source image. + Destination image. + The map of x-coordinates (32fC1 image). + The map of y-coordinates (32fC1 image). + A combination of interpolation method and the optional flag(s). + + + + Applies generic geometrical transformation to the image. + + Source image. + Destination image. + The map of x-coordinates (32fC1 image). + The map of y-coordinates (32fC1 image). + A combination of interpolation method and the optional flag(s). + A value used to fill outliers. + + + + Removes node from tree + + The removed node. + The top level node. If node->v_prev = null and node->h_prev is null (i.e. if node is the first child of frame), + frame->v_next is set to node->h_next (i.e. the first child or frame is changed). + + + + Fill destination array with tiled source array + + Source array, image or matrix. + Destination array, image or matrix. + + + + Reprojects disparity image to 3D space + + Disparity map. + 3-channel, 16-bit integer or 32-bit floating-point image - the output map of 3D points. + The reprojection 4x4 matrix. + + + + Releases image ROI. After that the whole image is considered selected. + + Image header. + + + + Changes shape of matrix/image without copying data + + Input array. + Output header to be filled. + New number of channels. new_cn = 0 means that number of channels remains unchanged. + + + + + Changes shape of matrix/image without copying data + + Input array. + Output header to be filled. + New number of channels. new_cn = 0 means that number of channels remains unchanged. + New number of rows. new_rows = 0 means that number of rows remains unchanged unless it needs to be changed according to new_cn value. destination array to be changed. + + + + + Changes shape of matrix/image without copying data + + Input array. + Output header to be filled. + New number of channels. new_cn = 0 means that number of channels remains unchanged. + + + + + Changes shape of matrix/image without copying data + + Input array. + Output header to be filled. + New number of channels. new_cn = 0 means that number of channels remains unchanged. + New number of rows. new_rows = 0 means that number of rows remains unchanged unless it needs to be changed according to new_cn value. destination array to be changed. + + + + + Changes shape of multi-dimensional array w/o copying data + + + Input array. + Size of output header to distinguish between IplImage, CvMat and CvMatND output headers. + Output header to be filled. + New number of channels. new_cn = 0 means that number of channels remains unchanged. + New number of dimensions. new_dims = 0 means that number of dimensions remains the same. + Array of new dimension sizes. Only new_dims-1 values are used, because the total number of elements must remain the same. Thus, if new_dims = 1, new_sizes array is not used + + + + + Changes shape of multi-dimensional array w/o copying data + + + Input array. + Output header to be filled. + New number of channels. new_cn = 0 means that number of channels remains unchanged. + New number of dimensions. new_dims = 0 means that number of dimensions remains the same. + Array of new dimension sizes. Only new_dims-1 values are used, because the total number of elements must remain the same. Thus, if new_dims = 1, new_sizes array is not used + + + + + Resizes image src so that it fits exactly to dst. + If ROI is set, the function consideres the ROI as supported as usual. + + Source image. + Destination image. + + + + Resizes image src so that it fits exactly to dst. + If ROI is set, the function consideres the ROI as supported as usual. + + Source image. + Destination image. + Interpolation method. + + + + Changes size of the window. + + Name of the window to be resized. + New width. + New height. + + + + Restores memory storage position + + Memory storage + New storage top position + + + + Returns the pointer to the image grabbed with cvGrabFrame function. + The returned image should not be released or modified by user. + + video capturing structure. + + + + + Returns the pointer to the image grabbed with cvGrabFrame function. + The returned image should not be released or modified by user. + + video capturing structure. + non-zero streamIdx is only valid for multi-head camera live streams + + + + + Returns the pointer to the image grabbed with cvGrabFrame function. + The returned image should not be released or modified by user. + + video capturing structure. + non-zero streamIdx is only valid for multi-head camera live streams + + + + + Initializes random number generator state + + + + + + Initializes random number generator state + + 64-bit value used to initiate a random sequence. + + + + + Converts rotation matrix to rotation vector or vice versa + + The input rotation vector (3x1 or 1x3) or rotation matrix (3x3). + The output rotation matrix (3x3) or rotation vector (3x1 or 1x3), respectively. + + + + + Converts rotation matrix to rotation vector or vice versa + + The input rotation vector (3x1 or 1x3) or rotation matrix (3x3). + The output rotation matrix (3x3) or rotation vector (3x1 or 1x3), respectively. + Optional output Jacobian matrix, 3x9 or 9x3 - partial derivatives of the output array components w.r.t the input array components. + + + + + Returns the nearest integer value to the argument. + + The input floating-point value + + + + + Computes RQ decomposition for 3x3 matrices + + The 3x3 input matrix M + The output 3x3 upper-triangular matrix R + The output 3x3 orthogonal matrix Q + + + + Computes RQ decomposition for 3x3 matrices + + The 3x3 input matrix M + The output 3x3 upper-triangular matrix R + The output 3x3 orthogonal matrix Q + Optional 3x3 rotation matrix around x-axis + Optional 3x3 rotation matrix around y-axis + Optional 3x3 rotation matrix around z-axis + + + + Computes RQ decomposition for 3x3 matrices + + The 3x3 input matrix M + The output 3x3 upper-triangular matrix R + The output 3x3 orthogonal matrix Q + Optional 3x3 rotation matrix around x-axis + Optional 3x3 rotation matrix around y-axis + Optional 3x3 rotation matrix around z-axis + Optional 3 points containing the three Euler angles of rotation + + + + Runs cascade of boosted classifier at given image location + + Haar classifier cascade. + Top-left corner of the analyzed region. Size of the region is a original window size scaled by the currenly set scale. The current window size may be retrieved using cvGetHaarClassifierCascadeWindowSize function. + positive value if the analyzed rectangle passed all the classifier stages (it is a candidate) and zero or negative value otherwise. + + + + Runs cascade of boosted classifier at given image location + + Haar classifier cascade. + Top-left corner of the analyzed region. Size of the region is a original window size scaled by the currenly set scale. The current window size may be retrieved using cvGetHaarClassifierCascadeWindowSize function. + Initial zero-based index of the cascade stage to start from. The function assumes that all the previous stages are passed. This feature is used internally by cvHaarDetectObjects for better processor cache utilization. + positive value if the analyzed rectangle passed all the classifier stages (it is a candidate) and zero or negative value otherwise. + + + + Calculates weighted sum of input image image and the accumulator acc so that acc becomes a running average of frame sequence: + acc(x,y)=(1-α)•acc(x,y) + α•image(x,y) if mask(x,y)!=null + + Input image, 1- or 3-channel, 8-bit or 32-bit floating point (each channel of multi-channel image is processed independently). + Accumulator of the same number of channels as input image, 32-bit or 64-bit floating-point. + Weight of input image. + + + + Calculates weighted sum of input image image and the accumulator acc so that acc becomes a running average of frame sequence: + acc(x,y)=(1-α)•acc(x,y) + α•image(x,y) if mask(x,y)!=null + + Input image, 1- or 3-channel, 8-bit or 32-bit floating point (each channel of multi-channel image is processed independently). + Accumulator of the same number of channels as input image, 32-bit or 64-bit floating-point. + Weight of input image. + Optional operation mask. + + + + References the specified object, which makes it ineligible for garbage collection + from the start of the current routine to the point where this method is called. + + + + + + References the specified object, which makes it ineligible for garbage collection + from the start of the current routine to the point where this method is called. + + + + + + + References the specified object, which makes it ineligible for garbage collection + from the start of the current routine to the point where this method is called. + + + + + + + + References the specified object, which makes it ineligible for garbage collection + from the start of the current routine to the point where this method is called. + + + + + + Returns obj.CvPtr if obj != null; otherwise, IntPtr.Zero + + + + + + + Converts IEnumerable to Array + + + + + + + CV_AA + + + + + CV_AUTOSTEP + + + + + CV_FILLED + + + + + CV_LOG2 + + + + + CV_PI + + + + + CV_WHOLE_SEQ_END_INDEX + + + + + CV_WHOLE_SEQ + + + + + if set, the difference between the current pixel and seed pixel is considered, otherwise the difference between neighbor pixels is considered (the range is floating) + + + + + if set, the function does not fill the image (new_val is ignored), but fills the mask (that must be non-null in this case) + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + 4つの文字からFOURCCの整数値を得る + + + + + + + + + + 4つの文字からFOURCCの整数値を得る + + + + + + + + + + 4つの文字からFOURCCの整数値を得る + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + CV_NODE_IDX + + + + + + + + CV_NODE_VAL + + + + + + + + + CV_NODE_VAL + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Constructs a color value + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Error Handler + + The numeric code for error status + The source file name where error is encountered + A description of the error + The source file name where error is encountered + The line number in the souce where error is encountered + Pointer to the user data. Ignored by the standard handlers + + + + Read callback function + + + + + + + + + + + + + + + + Pointer to the function to be called every time the button changed its state. + + + + + + + + Pointer to the function to be called every time the button changed its state. + + + + + + + + IEnumerable<T> extension methods for .NET Framework 2.0 + + + + + Enumerable.Select + + + + + + + + + + Enumerable.Select -> ToArray + + + + + + + + + + Enumerable.Select -> ToArray + + + + + + + + + + Enumerable.Select -> ToArray + + + + + + + Enumerable.Where + + + + + + + + + Enumerable.Where -> ToArray + + + + + + + + + Enumerable.ToArray + + + + + + + + Enumerable.Any + + + + + + + + + Enumerable.Any + + + + + + + + Enumerable.All + + + + + + + + + Enumerable.Count + + + + + + + + + Enumerable.Count + + + + + + + + + + + + + + + + Input/output flags for Eigen Objects (PCA) Functions + + + + + + [CV_EIGOBJ_NO_CALLBACK] + + + + + + [CV_EIGOBJ_INPUT_CALLBACK] + + + + + + [CV_EIGOBJ_OUTPUT_CALLBACK] + + + + + + [CV_EIGOBJ_BOTH_CALLBACK] + + + + + + + + + + + [CV_CPU_NONE] + + + + + + [CV_CPU_MMX] + + + + + + [CV_CPU_SSE] + + + + + + [CV_CPU_SSE2] + + + + + + [CV_CPU_SSE3] + + + + + + [CV_CPU_SSSE3] + + + + + + [CV_CPU_SSE4_1] + + + + + + [CV_CPU_SSE4_2] + + + + + + [CV_CPU_POPCNT] + + + + + + [CV_CPU_AVX] + + + + + + [CV_HARDWARE_MAX_FEATURE] + + + + + Miscellaneous flags for cvKMeans2 + + + + + + [= 0] + + + + + + [KMEANS_RANDOM_CENTERS] + + + + + + [KMEANS_PP_CENTERS] + + + + + + [KMEANS_USE_INITIAL_LABELS] + + + + + Various operation flags for cvFindDominantPoints + + + + + + [CV_DOMINANT_IPAN] + + + + + Marker styles for CvArr.DrawMarker + + + + + A circle polyline + + + + + A filled circle + + + + + A cross + + + + + A tilted cross + + + + + A circle and a cross + + + + + A circle and a tilted cross + + + + + A diamond polyline + + + + + A filled diamond + + + + + A square polyline + + + + + A filledsquare + + + + + The format type IDs for cv::imwrite and cv::inencode + + + + + In the case of JPEG it can be a quality, from 0 to 100 (the higher is the better), 95 by default. + [CV_IMWRITE_JPEG_QUALITY] + + + + + In the case of PNG it can be the compression level, from 0 to 9 (the higher value means smaller size and longer compression time), 3 by default. + [CV_IMWRITE_PNG_COMPRESSION] + + + + + In the case of PPM, PGM or PBM it can a binary format flag, 0 or 1, 1 by default. + [CV_IMWRITE_PXM_BINARY] + + + + + Property identifiers for cvGetWindowProperty/cvSetWindowProperty + + + + + Normal mode + [CV_WND_PROP_AUTOSIZE] + + + + + Fullscreen + [CV_WND_PROP_FULLSCREEN] + + + + + + [CV_WND_PROP_ASPECTRATIO] + + + + + opengl support + [CV_WND_PROP_OPENGL] + + + + + New value of the window property. + + + + + Change the window to normal size or make the window resizable. + [CV_WINDOW_NORMAL] + + + + + Constrain the size by the displayed image. The window is not resizable. + [CV_WINDOW_AUTOSIZE] + + + + + Change the window to fullscreen. + [CV_WINDOW_FULLSCREEN] + + + + + Make the window resizable without any ratio constraints. + [CV_WINDOW_FREERATIO] + + + + + Make the window resizable, but preserve the proportions of the displayed image. + [CV_WINDOW_KEEPRATIO] + + + + + CV_FACE_ELEMENTS + + + + + + [CV_FACE_MOUTH] + + + + + + [CV_FACE_LEFT_EYE] + + + + + + [CV_FACE_RIGHT_EYE] + + + + + The operation flags for cvFontQt + + + + + QFont::Light + + + + + QFont::Normal + + + + + QFont::DemiBold + + + + + QFont::Bold + + + + + QFont::Black + + + + + The operation flags for cvFontQt + + + + + QFont::StyleNormal + + + + + QFont::StyleItalic + + + + + QFont::StyleOblique + + + + + Button type flags (cvCreateButton) + + + + + The button will be a push button. + [CV_PUSH_BUTTON] + + + + + The button will be a checkbox button. + [CV_CHECKBOX] + + + + + The button will be a radiobox button. The radiobox on the same buttonbar (same line) are exclusive; one on can be select at the time. + [CV_RADIOBOX] + + + + + channel indices for multi-head camera live streams + + + + + 0 + + + + + Depth values in mm (CV_16UC1) + [CV_CAP_OPENNI_DEPTH_MAP] + + + + + XYZ in meters (CV_32FC3) + [CV_CAP_OPENNI_POINT_CLOUD_MAP] + + + + + Disparity in pixels (CV_8UC1) + [CV_CAP_OPENNI_DISPARITY_MAP] + + + + + Disparity in pixels (CV_32FC1) + [CV_CAP_OPENNI_DISPARITY_MAP_32F] + + + + + CV_8UC1 + [CV_CAP_OPENNI_VALID_DEPTH_MASK] + + + + + + [CV_CAP_OPENNI_BGR_IMAGE] + + + + + + [CV_CAP_OPENNI_GRAY_IMAGE] + + + + + + [CV_CAP_OPENNI_VGA_30HZ] + + + + + + [CV_CAP_OPENNI_SXGA_15HZ] + + + + + BGR + [CV_CAP_ANDROID_COLOR_FRAME_BGR] + + + + + + [CV_CAP_ANDROID_COLOR_FRAME] + + + + + Y + [CV_CAP_ANDROID_GREY_FRAME] + + + + + + [CV_CAP_ANDROID_COLOR_FRAME_RGB] + + + + + + [CV_CAP_ANDROID_COLOR_FRAME_BGRA] + + + + + + [CV_CAP_ANDROID_COLOR_FRAME_RGBA] + + + + + + + + + + + [CV_DIST_LABEL_CCOMP] + + + + + + [CV_DIST_LABEL_PIXEL] + + + + + floodFill Operation flags. Lower bits contain a connectivity value, 4 (default) or 8, used within the function. Connectivity determines which neighbors of a pixel are considered. Upper bits can be 0 or a combination of the following flags: + + + + + 4-connected line. + [= 4] + + + + + 8-connected line. + [= 8] + + + + + If set, the difference between the current pixel and seed pixel is considered. Otherwise, the difference between neighbor pixels is considered (that is, the range is floating). + [CV_FLOODFILL_FIXED_RANGE] + + + + + If set, the function does not change the image ( newVal is ignored), but fills the mask. The flag can be used for the second variant only. + [CV_FLOODFILL_MASK_ONLY] + + + + + Button that is used on Qt Window + + + + + Track whether Dispose has been called + + + + + + + + + + Constructor + + + + + Constructor + + Name of the button ( if null, the name will be “button <number of boutton>”) + + + + Constructor + + Name of the button ( if null, the name will be “button <number of boutton>”) + Pointer to the function to be called every time the button changed its state. + + + + Constructor + + Name of the button ( if null, the name will be “button <number of boutton>”) + Pointer to the function to be called every time the button changed its state. + object passed to the callback function. + + + + Constructor + + Name of the button ( if null, the name will be “button <number of boutton>”) + Pointer to the function to be called every time the button changed its state. + object passed to the callback function. + button type + + + + Constructor + + Name of the button ( if null, the name will be “button <number of boutton>”) + Pointer to the function to be called every time the button changed its state. + object passed to the callback function. + button type + Default state of the button. Use for checkbox and radiobox, its value could be 0 or 1. + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + Name of this trackbar + + + + + Gets the callback delegate which occurs when the Value property of a track bar changes, either by movement of the scroll box or by manipulation in code. + + + + + All created buttons + + + + + All created buttons + + + + + The format-specific save parameters for cv::imwrite and cv::imencode + + + + + format type ID + + + + + value of parameter + + + + + Constructor + + format type ID + value of parameter + + + + The format-specific save parameters for cv::imwrite and cv::imencode + + + + + Constructor + + value of parameter, from 0 to 100 (the higher is the better), 95 by default. + + + + The format-specific save parameters for cv::imwrite and cv::imencode + + + + + Constructor + + value of parameter, from 0 to 9 (the higher value means smaller size and longer compression time), 3 by default. + + + + The format-specific save parameters for cv::imwrite and cv::imencode + + + + + Constructor + + value of parameter. binary format flag, 0 or 1, 1 by default. + + + + + + + + + Checks whether PInvoke functions can be called + + + + + DllImportの際にDllNotFoundExceptionかBadImageFormatExceptionが発生した際に呼び出されるメソッド。 + エラーメッセージを表示して解決策をユーザに示す。 + + + + + + + + + + + + Class to get address of string array + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Class to get address of specified jagged array + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Name of library to be loaded + + + + + Name of function to be called + + + + + Pointer which retrieved by LoadLibrary + + + + + Pointer which retrieved by GetProcAddress + + + + + Delegate which is converted from function pointer + + + + + Constructor + + Name of library + Name of function + + + + Releases resources + + + + + + Provides information for the platform which the user is using + + + + + OS type + + + + + Runtime type + + + + + Substitute of System.Action + + + + + + + + + + + + + + + + + Class that converts structure into pointer and cleans up resources automatically + + + + + Pointer + + + + + Structure + + + + + Size of allocated memory + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Clean up resources to be used + + + + + Class that converts structure into pointer and cleans up resources automatically (generic version) + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Original GCHandle that implement IDisposable + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Destructor + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + IEnumerable<T>.ToArray of LINQ + + + + + + + + + + + + + OpenCV Constants defined by macro + + + + + Arbitrary array + + + + + Calculates absolute difference between two arrays + + The second source array. + The destination array. + + + + Calculates absolute difference between array and scalar + + The destination array. + + + + Calculates absolute difference between array and scalar + + The destination array. + The scalar. + + + + Adds frame to accumulator + + Accumulator of the same number of channels as input image, 32-bit or 64-bit floating-point. + + + + Adds frame to accumulator + + Accumulator of the same number of channels as input image, 32-bit or 64-bit floating-point. + Optional operation mask. + + + + Applies adaptive threshold to array. + + Destination image. + Maximum value that is used with CV_THRESH_BINARY and CV_THRESH_BINARY_INV. + + + + Applies adaptive threshold to array. + + Destination image. + Maximum value that is used with CV_THRESH_BINARY and CV_THRESH_BINARY_INV. + Adaptive thresholding algorithm to use: CV_ADAPTIVE_THRESH_MEAN_C or CV_ADAPTIVE_THRESH_GAUSSIAN_C. + + + + Applies adaptive threshold to array. + + Destination image. + Maximum value that is used with CV_THRESH_BINARY and CV_THRESH_BINARY_INV. + Adaptive thresholding algorithm to use: CV_ADAPTIVE_THRESH_MEAN_C or CV_ADAPTIVE_THRESH_GAUSSIAN_C. + Thresholding type. + + + + Applies adaptive threshold to array. + + Destination image. + Maximum value that is used with CV_THRESH_BINARY and CV_THRESH_BINARY_INV. + Adaptive thresholding algorithm to use: CV_ADAPTIVE_THRESH_MEAN_C or CV_ADAPTIVE_THRESH_GAUSSIAN_C. + Thresholding type. + The size of a pixel neighborhood that is used to calculate a threshold value for the pixel: 3, 5, 7, ... + + + + Applies adaptive threshold to array. + + Destination image. + Maximum value that is used with CV_THRESH_BINARY and CV_THRESH_BINARY_INV. + Adaptive thresholding algorithm to use: CV_ADAPTIVE_THRESH_MEAN_C or CV_ADAPTIVE_THRESH_GAUSSIAN_C. + Thresholding type. + The size of a pixel neighborhood that is used to calculate a threshold value for the pixel: 3, 5, 7, ... + The method-dependent parameter. For the methods CV_ADAPTIVE_THRESH_MEAN_C and CV_ADAPTIVE_THRESH_GAUSSIAN_C it is a constant subtracted from mean or weighted mean (see the discussion), though it may be negative. + + + + Computes per-element sum of two arrays + + The second source array. + The destination array. + + + + Computes per-element sum of two arrays + + The second source array. + The destination array. + Operation mask, 8-bit single channel array; specifies elements of destination array to be changed. + + + + Computes sum of array and scalar + + Added scalar. + The destination array. + + + + Computes sum of array and scalar + + Added scalar. + The destination array. + Operation mask, 8-bit single channel array; specifies elements of destination array to be changed. + + + + Create the font to be used to draw text on an image + + Text to write on the image + Point(x,y) where the text should start on the image + Font to use to draw the text + + + + Computes weighted sum of two arrays + + Weight of the first array elements. + The second source array. + Weight of the second array elements. + Scalar, added to each sum. + The destination array. + + + + Calculates per-element bit-wise conjunction of two arrays + + The second source array. + The destination array. + + + + Calculates per-element bit-wise conjunction of two arrays + + The second source array. + The destination array. + Operation mask, 8-bit single channel array; specifies elements of destination array to be changed. + + + + Calculates per-element bit-wise conjunction of array and scalar + + Scalar to use in the operation. + The destination array. + + + + Calculates per-element bit-wise conjunction of array and scalar + + Scalar to use in the operation. + The destination array. + Operation mask, 8-bit single channel array; specifies elements of destination array to be changed. + + + + Calculates contour perimeter or curve length + + + + + + Calculates contour perimeter or curve length + + Starting and ending points of the curve, by default the whole curve length is calculated. + + + + + Calculates contour perimeter or curve length + + Starting and ending points of the curve, by default the whole curve length is calculated. + Indicates whether the curve is closed or not. There are 3 cases: + * is_closed=0 - the curve is assumed to be unclosed. + * is_closed>0 - the curve is assumed to be closed. + * is_closed<0 - if curve is sequence, the flag CV_SEQ_FLAG_CLOSED of ((CvSeq*)curve)->flags is checked to determine if the curve is closed or not, otherwise (curve is represented by array (CvMat*) of points) it is assumed to be unclosed. + + + + + Calculates average (mean) of array elements + + + + + + Calculates average (mean) of array elements + + The optional operation mask. + + + + + Calculates average (mean) of array elements + + Pointer to the mean value, may be null if it is not needed. + Pointer to the standard deviation. + + + + Calculates average (mean) of array elements + + Pointer to the mean value, may be null if it is not needed. + Pointer to the standard deviation. + The optional operation mask. + + + + Calculates up-right bounding rectangle of point set. + + + + + + Calculates up-right bounding rectangle of point set. + + The update flag. Here is list of possible combination of the flag values and type of contour: + * points is CvContour*, update=0: the bounding rectangle is not calculated, but it is read from rect field of the contour header. + * points is CvContour*, update=1: the bounding rectangle is calculated and written to rect field of the contour header. For example, this mode is used by cvFindContours. + * points is CvSeq* or CvMat*: update is ignored, the bounding rectangle is calculated and returned. + + + + + Finds the edges on the input image image and marks them in the output image edges using the Canny algorithm. + The smallest of threshold1 and threshold2 is used for edge linking, the largest - to find initial segments of strong edges. + + Image to store the edges found by the function. + The first threshold. + The second threshold. + + + + Finds the edges on the input image image and marks them in the output image edges using the Canny algorithm. + The smallest of threshold1 and threshold2 is used for edge linking, the largest - to find initial segments of strong edges. + + Image to store the edges found by the function. + The first threshold. + The second threshold. + Aperture parameter for Sobel operator. + + + + Checks every element of input array for invalid values + + returns nonzero if the check succeeded, i.e. all elements are valid and within the range, and zero otherwise. + + + + Checks every element of input array for invalid values + + The operation flags + returns nonzero if the check succeeded, i.e. all elements are valid and within the range, and zero otherwise. + + + + Checks every element of input array for invalid values + + The operation flags + The inclusive lower boundary of valid values range. It is used only if CV_CHECK_RANGE is set. + The exclusive upper boundary of valid values range. It is used only if CV_CHECK_RANGE is set. + returns nonzero if the check succeeded, i.e. all elements are valid and within the range, and zero otherwise. + + + + Checks every element of input array for invalid values + + returns nonzero if the check succeeded, i.e. all elements are valid and within the range, and zero otherwise. + + + + Checks every element of input array for invalid values + + The operation flags + returns nonzero if the check succeeded, i.e. all elements are valid and within the range, and zero otherwise. + + + + Checks every element of input array for invalid values + + The operation flags + The inclusive lower boundary of valid values range. It is used only if CV_CHECK_RANGE is set. + The exclusive upper boundary of valid values range. It is used only if CV_CHECK_RANGE is set. + returns nonzero if the check succeeded, i.e. all elements are valid and within the range, and zero otherwise. + + + + Tests contour convexity. + + + + + + Draws a circle + + X-coordinate of the center of the circle. + Y-coordinate of the center of the circle. + Radius of the circle. + Circle color. + + + + Draws a circle + + X-coordinate of the center of the circle. + Y-coordinate of the center of the circle. + Radius of the circle. + Circle color. + Thickness of the circle outline if positive, otherwise indicates that a filled circle has to be drawn. + + + + Draws a circle + + X-coordinate of the center of the circle. + Y-coordinate of the center of the circle. + Radius of the circle. + Circle color. + Thickness of the circle outline if positive, otherwise indicates that a filled circle has to be drawn. + Type of the circle boundary. + + + + Draws a circle + + X-coordinate of the center of the circle. + Y-coordinate of the center of the circle. + Radius of the circle. + Circle color. + Thickness of the circle outline if positive, otherwise indicates that a filled circle has to be drawn. + Type of the circle boundary. + Number of fractional bits in the center coordinates and radius value. + + + + Draws a circle + + Center of the circle. + Radius of the circle. + Circle color. + + + + Draws a circle + + Center of the circle. + Radius of the circle. + Circle color. + Thickness of the circle outline if positive, otherwise indicates that a filled circle has to be drawn. + + + + Draws a circle + + Center of the circle. + Radius of the circle. + Circle color. + Thickness of the circle outline if positive, otherwise indicates that a filled circle has to be drawn. + Type of the circle boundary. + + + + Draws a circle + + Center of the circle. + Radius of the circle. + Circle color. + Thickness of the circle outline if positive, otherwise indicates that a filled circle has to be drawn. + Type of the circle boundary. + Number of fractional bits in the center coordinates and radius value. + + + + Draws a circle + + X-coordinate of the center of the circle. + Y-coordinate of the center of the circle. + Radius of the circle. + Circle color. + + + + Draws a circle + + X-coordinate of the center of the circle. + Y-coordinate of the center of the circle. + Radius of the circle. + Circle color. + Thickness of the circle outline if positive, otherwise indicates that a filled circle has to be drawn. + + + + Draws a circle + + X-coordinate of the center of the circle. + Y-coordinate of the center of the circle. + Radius of the circle. + Circle color. + Thickness of the circle outline if positive, otherwise indicates that a filled circle has to be drawn. + Type of the circle boundary. + + + + Draws a circle + + X-coordinate of the center of the circle. + Y-coordinate of the center of the circle. + Radius of the circle. + Circle color. + Thickness of the circle outline if positive, otherwise indicates that a filled circle has to be drawn. + Type of the circle boundary. + Number of fractional bits in the center coordinates and radius value. + + + + Draws a circle + + Center of the circle. + Radius of the circle. + Circle color. + + + + Draws a circle + + Center of the circle. + Radius of the circle. + Circle color. + Thickness of the circle outline if positive, otherwise indicates that a filled circle has to be drawn. + + + + Draws a circle + + Center of the circle. + Radius of the circle. + Circle color. + Thickness of the circle outline if positive, otherwise indicates that a filled circle has to be drawn. + Type of the circle boundary. + + + + Draws a circle + + Center of the circle. + Radius of the circle. + Circle color. + Thickness of the circle outline if positive, otherwise indicates that a filled circle has to be drawn. + Type of the circle boundary. + Number of fractional bits in the center coordinates and radius value. + + + + Clears the particular array element + + Array of the element indices + + + + Performs per-element comparison of two arrays + + The second source array. Both source array must have a single channel. + The destination array, must have 8u or 8s type. + The flag specifying the relation between the elements to be checked + + + + Performs per-element comparison of array and scalar + + The scalar value to compare each array element with. + The destination array, must have 8u or 8s type. + The flag specifying the relation between the elements to be checked + + + + Calculates area of the whole contour or contour section. + + + + + + Calculates area of the whole contour or contour section. + + Starting and ending points of the contour section of interest, by default area of the whole contour is calculated. + + + + + Alias for cvArcLength(curve,Whole_Seq,1) + + + + + + Converts one array to another with optional linear transformation + + Destination array. + + + + Converts one array to another with optional linear transformation + + Destination array. + Scale factor. + + + + Converts one array to another with optional linear transformation + + Destination array. + Scale factor. + Value added to the scaled source array elements. + + + + Converts one array to another with optional linear transformation + + Destination array. + + + + Converts one array to another with optional linear transformation + + Destination array. + Scale factor. + + + + Converts one array to another with optional linear transformation + + Destination array. + Scale factor. + Value added to the scaled source array elements. + + + + Converts one array to another with optional linear transformation + + Destination array. + + + + Converts one array to another with optional linear transformation + + Destination array. + Scale factor. + + + + Converts one array to another with optional linear transformation + + Destination array. + Scale factor. + Value added to the scaled source array elements. + + + + Converts one array to another with optional linear transformation + + Destination array. + + + + Converts input array elements to 8-bit unsigned integer another with optional linear transformation + + Destination array (should have 8u depth). + + + + Converts input array elements to 8-bit unsigned integer another with optional linear transformation + + Destination array (should have 8u depth). + ScaleAbs factor. + + + + Converts input array elements to 8-bit unsigned integer another with optional linear transformation + + Destination array (should have 8u depth). + ScaleAbs factor. + Value added to the scaled source array elements. + + + + Converts input array elements to 8-bit unsigned integer another with optional linear transformation + + Destination array (should have 8u depth). + + + + Converts input array elements to 8-bit unsigned integer another with optional linear transformation + + Destination array (should have 8u depth). + ScaleAbs factor. + + + + Converts input array elements to 8-bit unsigned integer another with optional linear transformation + + Destination array (should have 8u depth). + ScaleAbs factor. + Value added to the scaled source array elements. + + + + Finds convex hull of point set + + Vector of 0-based point indices of the hull points in the original array. + Desired orientation of convex hull: CV_CLOCKWISE or CV_COUNTER_CLOCKWISE. + + + + Finds convex hull of point set + + The output convex hull. It is either a vector of points that form the hull. + Desired orientation of convex hull: CV_CLOCKWISE or CV_COUNTER_CLOCKWISE. + + + + Finds convex hull of point set + + The output convex hull. It is either a vector of points that form the hull. + Desired orientation of convex hull: CV_CLOCKWISE or CV_COUNTER_CLOCKWISE. + + + + Finds convexity defects of contour + + Convex hull obtained using cvConvexHull2 that should contain pointers or indices to the contour points, not the hull points themselves, i.e. return_points parameter in cvConvexHull2 should be 0. + + + + Finds convexity defects of contour + + Convex hull obtained using cvConvexHull2 that should contain pointers or indices to the contour points, not the hull points themselves, i.e. return_points parameter in cvConvexHull2 should be 0. + Container for output sequence of convexity defects. If it is null, contour or hull (in that order) storage is used. + + + + Finds convexity defects of contour + + Convex hull obtained using cvConvexHull2 that should contain indices to the contour points + + + + Copies one array to another + + The destination array. + + + + Copies one array to another + + The destination array. + Operation mask, 8-bit single channel array; specifies elements of destination array to be changed. + + + + Copies image and makes border around it. + + The destination image. + Coordinates of the top-left corner (or bottom-left in case of images with bottom-left origin) of the destination image rectangle where the source image (or its ROI) is copied. Size of the rectanlge matches the source image size/ROI size. + Type of the border to create around the copied source image rectangle. + + + + Copies image and makes border around it. + + The destination image. + Coordinates of the top-left corner (or bottom-left in case of images with bottom-left origin) of the destination image rectangle where the source image (or its ROI) is copied. Size of the rectanlge matches the source image size/ROI size. + Type of the border to create around the copied source image rectangle. + Value of the border pixels if bordertype=IPL_BORDER_CONSTANT. + + + + Calculates eigenvalues and eigenvectors of image blocks for corner detection + + Image to store the results. It must be 6 times wider than the input image. + Neighborhood size. + + + + Calculates eigenvalues and eigenvectors of image blocks for corner detection + + Image to store the results. It must be 6 times wider than the input image. + Neighborhood size. + Aperture parameter for Sobel operator + + + + Runs the Harris edge detector on image. + Similarly to cvCornerMinEigenVal and cvCornerEigenValsAndVecs, + for each pixel it calculates 2x2 gradient covariation matrix M over block_size×block_size neighborhood. + + Image to store the Harris detector responces. Should have the same size as image. + Neighborhood size. + + + + Runs the Harris edge detector on image. + Similarly to cvCornerMinEigenVal and cvCornerEigenValsAndVecs, + for each pixel it calculates 2x2 gradient covariation matrix M over block_size×block_size neighborhood. + + Image to store the Harris detector responces. Should have the same size as image. + Neighborhood size. + Aperture parameter for Sobel operator (see cvSobel). format. In the case of floating-point input format this parameter is the number of the fixed float filter used for differencing. + + + + Runs the Harris edge detector on image. + Similarly to cvCornerMinEigenVal and cvCornerEigenValsAndVecs, + for each pixel it calculates 2x2 gradient covariation matrix M over block_size×block_size neighborhood. + + Image to store the Harris detector responces. Should have the same size as image. + Neighborhood size. + Aperture parameter for Sobel operator (see cvSobel). format. In the case of floating-point input format this parameter is the number of the fixed float filter used for differencing. + Harris detector free parameter. + + + + Calculates minimal eigenvalue of gradient matrices for corner detection + + Image to store the minimal eigen values. Should have the same size as image + Neighborhood size. + + + + Calculates minimal eigenvalue of gradient matrices for corner detection + + Image to store the minimal eigen values. Should have the same size as image + Neighborhood size. + Aperture parameter for Sobel operator (see cvSobel). format. In the case of floating-point input format this parameter is the number of the fixed float filter used for differencing. + + + + Counts non-zero array elements + + the number of non-zero elements in arr + + + + Allocates array data. + + + + + Builds pyramid for an image + + + + + + + + + + + + Calculates cross product of two 3D vectors + + The second source vector. + The destination vector. + + + + Converts image from one color space to another. + + The destination image of the same data type as the source one. The number of channels may be different. + Color conversion operation that can be specifed using CV_<src_color_space>2<dst_color_space> constants (see below). + + + + Performs forward or inverse Discrete Cosine transform of 1D or 2D floating-point array + + Destination array of the same size and same type as the source. + Transformation flags. + + + + Decrements array data reference counter． + + + + + Returns determinant of matrix + + determinant of the square matrix mat + + + + Performs forward or inverse Discrete Fourier transform of 1D or 2D floating-point array + + Destination array of the same size and same type as the source. + Transformation flags + + + + Performs forward or inverse Discrete Fourier transform of 1D or 2D floating-point array + + Destination array of the same size and same type as the source. + Transformation flags + Number of nonzero rows to in the source array (in case of forward 2d transform), or a number of rows of interest in the destination array (in case of inverse 2d transform). If the value is negative, zero, or greater than the total number of rows, it is ignored. The parameter can be used to speed up 2d convolution/correlation when computing them via DFT. + + + + Performs forward or inverse Discrete Fourier transform of 1D or 2D floating-point array + + Destination array of the same size and same type as the source. + Transformation flags + + + + Performs forward or inverse Discrete Fourier transform of 1D or 2D floating-point array + + Destination array of the same size and same type as the source. + Transformation flags + Number of nonzero rows to in the source array (in case of forward 2d transform), or a number of rows of interest in the destination array (in case of inverse 2d transform). If the value is negative, zero, or greater than the total number of rows, it is ignored. The parameter can be used to speed up 2d convolution/correlation when computing them via DFT. + + + + Dilates image by using arbitrary structuring element. + + Destination image. + + + + Dilates image by using arbitrary structuring element. + + Destination image. + Structuring element used for erosion. If it is null, a 3x3 rectangular structuring element is used. + + + + Dilates image by using arbitrary structuring element. + + Destination image. + Structuring element used for erosion. If it is null, a 3x3 rectangular structuring element is used. + Number of times erosion is applied. + + + + Calculates distance to closest zero pixel for all non-zero pixels of source image. + + Output image with calculated distances (32-bit floating-point, single-channel). + + + + Calculates distance to closest zero pixel for all non-zero pixels of source image. + + Output image with calculated distances (32-bit floating-point, single-channel). + Type of distance. + + + + Calculates distance to closest zero pixel for all non-zero pixels of source image. + + Output image with calculated distances (32-bit floating-point, single-channel). + Type of distance. + Size of distance transform mask; can be 3, 5 or 0. In case of CV_DIST_L1 or CV_DIST_C the parameter is forced to 3, because 3×3 mask gives the same result as 5x5 yet it is faster. When mask_size==0, a different non-approximate algorithm is used to calculate distances. + + + + Calculates distance to closest zero pixel for all non-zero pixels of source image. + + Output image with calculated distances (32-bit floating-point, single-channel). + Type of distance. + Size of distance transform mask; can be 3, 5 or 0. In case of CV_DIST_L1 or CV_DIST_C the parameter is forced to 3, because 3×3 mask gives the same result as 5x5 yet it is faster. When mask_size==0, a different non-approximate algorithm is used to calculate distances. + User-defined mask in case of user-defined distance, it consists of 2 numbers (horizontal/vertical shift cost, diagonal shift cost) in case of 3x3 mask and 3 numbers (horizontal/vertical shift cost, diagonal shift cost, knight’s move cost) in case of 5x5 mask. + + + + Calculates distance to closest zero pixel for all non-zero pixels of source image. + + Output image with calculated distances (32-bit floating-point, single-channel). + Type of distance. + Size of distance transform mask; can be 3, 5 or 0. In case of CV_DIST_L1 or CV_DIST_C the parameter is forced to 3, because 3×3 mask gives the same result as 5x5 yet it is faster. When mask_size==0, a different non-approximate algorithm is used to calculate distances. + User-defined mask in case of user-defined distance, it consists of 2 numbers (horizontal/vertical shift cost, diagonal shift cost) in case of 3x3 mask and 3 numbers (horizontal/vertical shift cost, diagonal shift cost, knight’s move cost) in case of 5x5 mask. + The optional output 2d array of labels of integer type and the same size as src and dst, can now be used only with mask_size==3 or 5. + + + + Performs per-element division of two arrays + + The second source array. + The destination array. + + + + Performs per-element division of two arrays + + The second source array. + The destination array. + Optional scale factor + + + + Draws the individual chessboard corners detected (as red circles) in case if the board was not found (pattern_was_found=0) or the colored corners connected with lines when the board was found (pattern_was_found≠0). + + The number of inner corners per chessboard row and column. + The array of corners detected. + Indicates whether the complete board was found (≠0) or not (=0). One may just pass the return value cvFindChessboardCorners here. + + + + Draws contour outlines or interiors in the image + + Reference to the first contour. + Color of the external contours. + Color of internal contours (holes). + Maximal level for drawn contours. If 0, only contour is drawn. If 1, the contour and all contours after it on the same level are drawn. If 2, all contours after and all contours one level below the contours are drawn, etc. If the value is negative, the function does not draw the contours following after contour but draws child contours of contour up to abs(max_level)-1 level. + + + + Draws contour outlines or interiors in the image + + Reference to the first contour. + Color of the external contours. + Color of internal contours (holes). + Maximal level for drawn contours. If 0, only contour is drawn. If 1, the contour and all contours after it on the same level are drawn. If 2, all contours after and all contours one level below the contours are drawn, etc. If the value is negative, the function does not draw the contours following after contour but draws child contours of contour up to abs(max_level)-1 level. + Thickness of lines the contours are drawn with. If it is negative (e.g. =CV_FILLED), the contour interiors are drawn. + + + + Draws contour outlines or interiors in the image + + Reference to the first contour. + Color of the external contours. + Color of internal contours (holes). + Maximal level for drawn contours. If 0, only contour is drawn. If 1, the contour and all contours after it on the same level are drawn. If 2, all contours after and all contours one level below the contours are drawn, etc. If the value is negative, the function does not draw the contours following after contour but draws child contours of contour up to abs(max_level)-1 level. + Thickness of lines the contours are drawn with. If it is negative (e.g. =CV_FILLED), the contour interiors are drawn. + Type of the contour segments. + + + + Draws contour outlines or interiors in the image + + Reference to the first contour. + Color of the external contours. + Color of internal contours (holes). + Maximal level for drawn contours. If 0, only contour is drawn. If 1, the contour and all contours after it on the same level are drawn. If 2, all contours after and all contours one level below the contours are drawn, etc. If the value is negative, the function does not draw the contours following after contour but draws child contours of contour up to abs(max_level)-1 level. + Thickness of lines the contours are drawn with. If it is negative (e.g. =CV_FILLED), the contour interiors are drawn. + Type of the contour segments. + Shift all the point coordinates by the specified value. It is useful in case if the contours retrieved in some image ROI and then the ROI offset needs to be taken into account during the rendering. + + + + Computes eigenvalues and eigenvectors of symmetric matrix + + The output matrix of eigenvectors, stored as a subsequent rows. + The output vector of eigenvalues, stored in the descending order (order of eigenvalues and eigenvectors is synchronized, of course). + + + + Computes eigenvalues and eigenvectors of symmetric matrix + + The output matrix of eigenvectors, stored as a subsequent rows. + The output vector of eigenvalues, stored in the descending order (order of eigenvalues and eigenvectors is synchronized, of course). + Accuracy of diagonalization (typically, DBL_EPSILON=≈10-15 is enough). + + + + Draws simple or thick elliptic arc or fills ellipse sector + + Center of the ellipse. + Length of the ellipse axes. + Rotation angle. + Starting angle of the elliptic arc. + Ending angle of the elliptic arc. + Ellipse color. + + + + Draws simple or thick elliptic arc or fills ellipse sector + + Center of the ellipse. + Length of the ellipse axes. + Rotation angle. + Starting angle of the elliptic arc. + Ending angle of the elliptic arc. + Ellipse color. + Thickness of the ellipse arc. + + + + Draws simple or thick elliptic arc or fills ellipse sector + + Center of the ellipse. + Length of the ellipse axes. + Rotation angle. + Starting angle of the elliptic arc. + Ending angle of the elliptic arc. + Ellipse color. + Thickness of the ellipse arc. + Type of the ellipse boundary. + + + + Draws simple or thick elliptic arc or fills ellipse sector + + Center of the ellipse. + Length of the ellipse axes. + Rotation angle. + Starting angle of the elliptic arc. + Ending angle of the elliptic arc. + Ellipse color. + Thickness of the ellipse arc. + Type of the ellipse boundary. + Number of fractional bits in the center coordinates and axes' values. + + + + Draws simple or thick elliptic arc or fills ellipse sector + + Center of the ellipse. + Length of the ellipse axes. + Rotation angle. + Starting angle of the elliptic arc. + Ending angle of the elliptic arc. + Ellipse color. + + + + Draws simple or thick elliptic arc or fills ellipse sector + + Center of the ellipse. + Length of the ellipse axes. + Rotation angle. + Starting angle of the elliptic arc. + Ending angle of the elliptic arc. + Ellipse color. + Thickness of the ellipse arc. + + + + Draws simple or thick elliptic arc or fills ellipse sector + + Center of the ellipse. + Length of the ellipse axes. + Rotation angle. + Starting angle of the elliptic arc. + Ending angle of the elliptic arc. + Ellipse color. + Thickness of the ellipse arc. + Type of the ellipse boundary. + + + + Draws simple or thick elliptic arc or fills ellipse sector + + Center of the ellipse. + Length of the ellipse axes. + Rotation angle. + Starting angle of the elliptic arc. + Ending angle of the elliptic arc. + Ellipse color. + Thickness of the ellipse arc. + Type of the ellipse boundary. + Number of fractional bits in the center coordinates and axes' values. + + + + Draws simple or thick elliptic arc or fills ellipse sector + + The enclosing box of the ellipse drawn + Ellipse color. + + + + Draws simple or thick elliptic arc or fills ellipse sector + + The enclosing box of the ellipse drawn + Ellipse color. + Thickness of the ellipse boundary. + + + + Draws simple or thick elliptic arc or fills ellipse sector + + The enclosing box of the ellipse drawn + Ellipse color. + Thickness of the ellipse boundary. + Type of the ellipse boundary + + + + Draws simple or thick elliptic arc or fills ellipse sector + + The enclosing box of the ellipse drawn + Ellipse color. + Thickness of the ellipse boundary. + Type of the ellipse boundary + Number of fractional bits in the box vertex coordinates. + + + + Equalizes histogram of grayscale image. + + The output image of the same size and the same data type as src. + + + + Erodes image by using arbitrary structuring element. + + Destination image. + + + + Erodes image by using arbitrary structuring element. + + Destination image. + Structuring element used for erosion. If it is null, a 3x3 rectangular structuring element is used. + + + + Erodes image by using arbitrary structuring element. + + Destination image. + Structuring element used for erosion. If it is null, a 3x3 rectangular structuring element is used. + Number of times erosion is applied. + + + + Calculates exponent of every array element + + The destination array, it should have double type or the same type as the source. + + + + Extracts the contours of Maximally Stable Extremal Regions + + + + + + + + Extracts Speeded Up Robust Features from image + + The optional input 8-bit mask. The features are only found in the areas that contain more than 50% of non-zero mask pixels. + The output parameter; double pointer to the sequence of keypoints. This will be the sequence of CvSURFPoint structures. + The optional output parameter; double pointer to the sequence of descriptors; Depending on the params.extended value, each element of the sequence will be either 64-element or 128-element floating-point (CV_32F) vector. If the parameter is null, the descriptors are not computed. + Memory storage where keypoints and descriptors will be stored. + Various algorithm parameters put to the structure CvSURFParams + + + + Extracts Speeded Up Robust Features from image + + The optional input 8-bit mask. The features are only found in the areas that contain more than 50% of non-zero mask pixels. + The output parameter; double pointer to the sequence of keypoints. This will be the sequence of CvSURFPoint structures. + The optional output parameter; double pointer to the sequence of descriptors; Depending on the params.extended value, each element of the sequence will be either 64-element or 128-element floating-point (CV_32F) vector. If the parameter is null, the descriptors are not computed. + Memory storage where keypoints and descriptors will be stored. + Various algorithm parameters put to the structure CvSURFParams + If useProvidedKeyPts!=0, keypoints are not detected, but descriptors are computed at the locations provided in keypoints (a CvSeq of CvSURFPoint). + + + + Extracts Speeded Up Robust Features from image + + The optional input 8-bit mask. The features are only found in the areas that contain more than 50% of non-zero mask pixels. + The output parameter; double pointer to the sequence of keypoints. This will be the sequence of CvSURFPoint structures. + The optional output parameter; double pointer to the sequence of descriptors; Depending on the params.extended value, each element of the sequence will be either 64-element or 128-element floating-point (CV_32F) vector. If the parameter is null, the descriptors are not computed. + Various algorithm parameters put to the structure CvSURFParams + + + + Extracts Speeded Up Robust Features from image + + The optional input 8-bit mask. The features are only found in the areas that contain more than 50% of non-zero mask pixels. + The output parameter; double pointer to the sequence of keypoints. This will be the sequence of CvSURFPoint structures. + The optional output parameter; double pointer to the sequence of descriptors; Depending on the params.extended value, each element of the sequence will be either 64-element or 128-element floating-point (CV_32F) vector. If the parameter is null, the descriptors are not computed. + Various algorithm parameters put to the structure CvSURFParams + If useProvidedKeyPts!=0, keypoints are not detected, but descriptors are computed at the locations provided in keypoints (a CvSeq of CvSURFPoint). + + + + Fills convex polygon + + Array of pointers to a single polygon. + Polygon color. + + + + Fills convex polygon + + Array of pointers to a single polygon. + Polygon color. + Type of the polygon boundaries. + + + + Fills convex polygon + + Array of pointers to a single polygon. + Polygon color. + Type of the polygon boundaries. + Number of fractional bits in the vertex coordinates. + + + + Fills polygons interior + + Array of pointers to polygons. + Polygon color. + + + + Fills polygons interior + + Array of pointers to polygons. + Polygon color. + ype of the polygon boundaries. + + + + Fills polygons interior + + Array of pointers to polygons. + Polygon color. + ype of the polygon boundaries. + Number of fractional bits in the vertex coordinates. + + + + Applies arbitrary linear filter to the image. In-place operation is supported. + When the aperture is partially outside the image, the function interpolates outlier pixel values from the nearest pixels that is inside the image. + + The destination image. + Convolution kernel, single-channel floating point matrix. If you want to apply different kernels to different channels, split the image using cvSplit into separate color planes and process them individually. + + + + Applies arbitrary linear filter to the image. In-place operation is supported. + When the aperture is partially outside the image, the function interpolates outlier pixel values from the nearest pixels that is inside the image. + + The destination image. + Convolution kernel, single-channel floating point matrix. If you want to apply different kernels to different channels, split the image using cvSplit into separate color planes and process them individually. + The anchor of the kernel that indicates the relative position of a filtered point within the kernel. The anchor shoud lie within the kernel. The special default value (-1,-1) means that it is at the kernel center. + + + + Finds positions of internal corners of the chessboard + + The number of inner corners per chessboard row and column. + The output array of corners detected. + returns true if all the corners have been found and they have been placed in a certain order (row by row, left to right in every row), otherwise, if the function fails to find all the corners or reorder them, it returns false. + + + + Finds positions of internal corners of the chessboard + + The number of inner corners per chessboard row and column. + The output array of corners detected. + The output corner counter. If it is not null, the function stores there the number of corners found. + returns true if all the corners have been found and they have been placed in a certain order (row by row, left to right in every row), otherwise, if the function fails to find all the corners or reorder them, it returns false. + + + + Finds positions of internal corners of the chessboard + + The number of inner corners per chessboard row and column. + The output array of corners detected. + The output corner counter. If it is not null, the function stores there the number of corners found. + Various operation flags + returns true if all the corners have been found and they have been placed in a certain order (row by row, left to right in every row), otherwise, if the function fails to find all the corners or reorder them, it returns false. + + + + Retrieves contours from the binary image and returns the number of retrieved contours. + + Container of the retrieved contours. + Output parameter, will contain the pointer to the first outer contour. + The number of retrieved contours. + + + + Retrieves contours from the binary image and returns the number of retrieved contours. + + Container of the retrieved contours. + Output parameter, will contain the pointer to the first outer contour. + Size of the sequence header, >=sizeof(CvChain) if method=CV_CHAIN_CODE, and >=sizeof(CvContour) otherwise. + The number of retrieved contours. + + + + Retrieves contours from the binary image and returns the number of retrieved contours. + + Container of the retrieved contours. + Output parameter, will contain the pointer to the first outer contour. + Size of the sequence header, >=sizeof(CvChain) if method=CV_CHAIN_CODE, and >=sizeof(CvContour) otherwise. + Retrieval mode. + The number of retrieved contours. + + + + Retrieves contours from the binary image and returns the number of retrieved contours. + + Container of the retrieved contours. + Output parameter, will contain the pointer to the first outer contour. + Size of the sequence header, >=sizeof(CvChain) if method=CV_CHAIN_CODE, and >=sizeof(CvContour) otherwise. + Retrieval mode. + Approximation method. + The number of retrieved contours. + + + + Retrieves contours from the binary image and returns the number of retrieved contours. + + Container of the retrieved contours. + Output parameter, will contain the pointer to the first outer contour. + Size of the sequence header, >=sizeof(CvChain) if method=CV_CHAIN_CODE, and >=sizeof(CvContour) otherwise. + Retrieval mode. + Approximation method. + Offset, by which every contour point is shifted. This is useful if the contours are extracted from the image ROI and then they should be analyzed in the whole image context. + The number of retrieved contours. + + + + Iterates to find the sub-pixel accurate location of corners, or radial saddle points. + + Initial coordinates of the input corners and refined coordinates on output. + Number of corners. + Half sizes of the search window. + Half size of the dead region in the middle of the search zone over which the summation in formulae below is not done. It is used sometimes to avoid possible singularities of the autocorrelation matrix. The value of (-1,-1) indicates that there is no such size. + Criteria for termination of the iterative process of corner refinement. That is, the process of corner position refinement stops either after certain number of iteration or when a required accuracy is achieved. The criteria may specify either of or both the maximum number of iteration and the required accuracy. + + + + Fits ellipse to set of 2D points + + ellipse that fits best (in least-squares sense) to a set of 2D points. + + + + Fits line to 2D or 3D point set + + The distance used for fitting (see the discussion). + Numerical parameter (C) for some types of distances, if 0 then some optimal value is chosen. + Sufficient accuracy for radius (distance between the coordinate origin and the line) and angle, respectively, 0.01 would be a good defaults for both. + Sufficient accuracy for radius (distance between the coordinate origin and the line) and angle, respectively, 0.01 would be a good defaults for both. + The output line parameters. In case of 2d fitting it is array of 4 floats (vx, vy, x0, y0) where (vx, vy) is a normalized vector collinear to the line and (x0, y0) is some point on the line. In case of 3D fitting it is array of 6 floats (vx, vy, vz, x0, y0, z0) where (vx, vy, vz) is a normalized vector collinear to the line and (x0, y0, z0) is some point on the line. + + + + Flip a 2D array around vertical, horizontal or both axises + + + + + Flip a 2D array around vertical, horizontal or both axises + + Destination array. If dst = null the flipping is done in-place. + + + + Flip a 2D array around vertical, horizontal or both axises + + Destination array. If dst = null the flipping is done in-place. + Specifies how to flip the array. + + + + Flip a 2D array around vertical, horizontal or both axises + + + + + Flip a 2D array around vertical, horizontal or both axises + + Destination array. If dst = null the flipping is done in-place. + + + + Flip a 2D array around vertical, horizontal or both axises + + Destination array. If dst = null the flipping is done in-place. + Specifies how to flip the array. + + + + Fills a connected component with given color. + + The starting point. + New value of repainted domain pixels. + + + + Fills a connected component with given color. + + The starting point. + New value of repainted domain pixels. + Maximal lower brightness/color difference between the currently observed pixel and one of its neighbor belong to the component or seed pixel to add the pixel to component. In case of 8-bit color images it is packed value. + + + + Fills a connected component with given color. + + The starting point. + New value of repainted domain pixels. + Maximal lower brightness/color difference between the currently observed pixel and one of its neighbor belong to the component or seed pixel to add the pixel to component. In case of 8-bit color images it is packed value. + Maximal upper brightness/color difference between the currently observed pixel and one of its neighbor belong to the component or seed pixel to add the pixel to component. In case of 8-bit color images it is packed value. + + + + Fills a connected component with given color. + + The starting point. + New value of repainted domain pixels. + Maximal lower brightness/color difference between the currently observed pixel and one of its neighbor belong to the component or seed pixel to add the pixel to component. In case of 8-bit color images it is packed value. + Maximal upper brightness/color difference between the currently observed pixel and one of its neighbor belong to the component or seed pixel to add the pixel to component. In case of 8-bit color images it is packed value. + Pointer to structure the function fills with the information about the repainted domain. + + + + Fills a connected component with given color. + + The starting point. + New value of repainted domain pixels. + Maximal lower brightness/color difference between the currently observed pixel and one of its neighbor belong to the component or seed pixel to add the pixel to component. In case of 8-bit color images it is packed value. + Maximal upper brightness/color difference between the currently observed pixel and one of its neighbor belong to the component or seed pixel to add the pixel to component. In case of 8-bit color images it is packed value. + Pointer to structure the function fills with the information about the repainted domain. + The operation flags. Lower bits contain connectivity value, 4 (by default) or 8, used within the function. Connectivity determines which neighbors of a pixel are considered. Upper bits can be 0 or combination of the flags + + + + Fills a connected component with given color. + + The starting point. + New value of repainted domain pixels. + Maximal lower brightness/color difference between the currently observed pixel and one of its neighbor belong to the component or seed pixel to add the pixel to component. In case of 8-bit color images it is packed value. + Maximal upper brightness/color difference between the currently observed pixel and one of its neighbor belong to the component or seed pixel to add the pixel to component. In case of 8-bit color images it is packed value. + Pointer to structure the function fills with the information about the repainted domain. + The operation flags. Lower bits contain connectivity value, 4 (by default) or 8, used within the function. Connectivity determines which neighbors of a pixel are considered. Upper bits can be 0 or combination of the flags + Operation mask + + + + Return the particular array element + + The first zero-based component of the element index + + + + + Return the particular array element + + The first zero-based component of the element index + The second zero-based component of the element index + + + + + Return the particular array element + + The first zero-based component of the element index + The second zero-based component of the element index + The third zero-based component of the element index + + + + + Return the particular array element + + Array of the element indices + the particular array element + + + + Returns array column + + Zero-based index of the selected column. + + + + + Returns array column span + + Zero-based index of the starting column (inclusive) of the span. + Zero-based index of the ending column (exclusive) of the span. + + + + + Returns one of array diagonals + + Reference to the resulting sub-array header. + + + + + Returns one of array diagonals + + Reference to the resulting sub-array header. + Array diagonal. Zero corresponds to the main diagonal, -1 corresponds to the diagonal above the main etc., 1 corresponds to the diagonal below the main etc. + + + + + Return number of array dimensions and their sizes + + number of array dimensions. + + + + Return number of array dimensions and their sizes + + Optional output vector of the array dimension sizes. For 2d arrays the number of rows (height) goes first, number of columns (width) next. + number of array dimensions. + + + + Return the size of particular dimension + + Zero-based dimension index (for matrices 0 means number of rows, 1 means number of columns; for images 0 means height, 1 means width). + the particular dimension size (number of elements per that dimension). + + + + Returns type of array elements + + type of the array elements + + + + Retrieves pixel quadrangle from image with sub-pixel accuracy. + + Extracted quadrangle. + The transformation 2 × 3 matrix [A|b]. + + + + Retrieves low-level information about the array + + Output pointer to the whole image origin or ROI origin if ROI is set. + + + + Retrieves low-level information about the array + + Output pointer to the whole image origin or ROI origin if ROI is set. + Output full row length in bytes. + + + + Retrieves low-level information about the array + + Output pointer to the whole image origin or ROI origin if ROI is set. + Output full row length in bytes. + Output ROI size. + + + + Return the particular element of single-channel array + + The first zero-based component of the element index + the particular element of single-channel array. + + + + Return the particular element of single-channel array + + The first zero-based component of the element index + The second zero-based component of the element index + the particular element of single-channel array. + + + + Return the particular element of single-channel array + + The first zero-based component of the element index + The second zero-based component of the element index + The third zero-based component of the element index + the particular element of single-channel array. + + + + Return the particular element of single-channel array + + Array of the element indices + the particular element of single-channel array. + + + + Retrieves pixel rectangle from image with sub-pixel accuracy. + + Extracted rectangle. + Floating point coordinates of the extracted rectangle center within the source image. The center must be inside the image. + + + + Returns array row + + Zero-based index of the selected row. + + + + + Returns array row span + + Zero-based index of the starting row (inclusive) of the span. + Zero-based index of the ending row (exclusive) of the span. + + + + + Returns array row span + + Zero-based index of the starting row (inclusive) of the span. + Zero-based index of the ending row (exclusive) of the span. + Index step in the row span. That is, the function extracts every delta_row-th row from start_row and up to (but not including) end_row. + + + + + Returns size of matrix or image ROI + + + + + + Retrieves keypoints using the StarDetector algorithm. + + Memory storage where the keypoints will be stored + + + + + Retrieves keypoints using the StarDetector algorithm. + + Memory storage where the keypoints will be stored + Various algorithm parameters given to the structure CvStarDetectorParams + + + + + Returns matrix header corresponding to the rectangular sub-array of input image or matrix + + Reference to the resultant sub-array header. + Zero-based coordinates of the rectangle of interest. + Reference to the header, corresponding to a specified rectangle of the input array. + + + + Returns matrix header corresponding to the rectangular sub-array of input image or matrix + + Reference to the resultant sub-array header. + Zero-based coordinates of the rectangle of interest. + Reference to the header, corresponding to a specified rectangle of the input array. + + + + Finds rectangular regions in the given image that are likely to contain objects the cascade has been trained for and returns those regions as a sequence of rectangles. + + Haar classifier cascade in internal representation. + Memory storage to store the resultant sequence of the object candidate rectangles. + + + + + Finds rectangular regions in the given image that are likely to contain objects the cascade has been trained for and returns those regions as a sequence of rectangles. + + Haar classifier cascade in internal representation. + Memory storage to store the resultant sequence of the object candidate rectangles. + The factor by which the search window is scaled between the subsequent scans, for example, 1.1 means increasing window by 10%. + + + + + Finds rectangular regions in the given image that are likely to contain objects the cascade has been trained for and returns those regions as a sequence of rectangles. + + Haar classifier cascade in internal representation. + Memory storage to store the resultant sequence of the object candidate rectangles. + The factor by which the search window is scaled between the subsequent scans, for example, 1.1 means increasing window by 10%. + Minimum number (minus 1) of neighbor rectangles that makes up an object. All the groups of a smaller number of rectangles than min_neighbors-1 are rejected. If min_neighbors is 0, the function does not any grouping at all and returns all the detected candidate rectangles, which may be useful if the user wants to apply a customized grouping procedure. + + + + + Finds rectangular regions in the given image that are likely to contain objects the cascade has been trained for and returns those regions as a sequence of rectangles. + + Haar classifier cascade in internal representation. + Memory storage to store the resultant sequence of the object candidate rectangles. + The factor by which the search window is scaled between the subsequent scans, for example, 1.1 means increasing window by 10%. + Minimum number (minus 1) of neighbor rectangles that makes up an object. All the groups of a smaller number of rectangles than min_neighbors-1 are rejected. If min_neighbors is 0, the function does not any grouping at all and returns all the detected candidate rectangles, which may be useful if the user wants to apply a customized grouping procedure. + Mode of operation. Currently the only flag that may be specified is CV_HAAR_DO_CANNY_PRUNING. If it is set, the function uses Canny edge detector to reject some image regions that contain too few or too much edges and thus can not contain the searched object. The particular threshold values are tuned for face detection and in this case the pruning speeds up the processing. + + + + + Finds rectangular regions in the given image that are likely to contain objects the cascade has been trained for and returns those regions as a sequence of rectangles. + + Haar classifier cascade in internal representation. + Memory storage to store the resultant sequence of the object candidate rectangles. + The factor by which the search window is scaled between the subsequent scans, for example, 1.1 means increasing window by 10%. + Minimum number (minus 1) of neighbor rectangles that makes up an object. All the groups of a smaller number of rectangles than min_neighbors-1 are rejected. If min_neighbors is 0, the function does not any grouping at all and returns all the detected candidate rectangles, which may be useful if the user wants to apply a customized grouping procedure. + Mode of operation. Currently the only flag that may be specified is CV_HAAR_DO_CANNY_PRUNING. If it is set, the function uses Canny edge detector to reject some image regions that contain too few or too much edges and thus can not contain the searched object. The particular threshold values are tuned for face detection and in this case the pruning speeds up the processing. + Minimum window size. By default, it is set to the size of samples the classifier has been trained on (~20×20 for face detection). + Maximum window size. + + + + + Finds circles in grayscale image using Hough transform. + + The storage for the circles detected. It can be a memory storage or single row/single column matrix (CvMat*) of type CV_32FC3, to which the circles' parameters are written. + Currently, the only implemented method is CV_HOUGH_GRADIENT, which is basically 21HT + Resolution of the accumulator used to detect centers of the circles. For example, if it is 1, the accumulator will have the same resolution as the input image, if it is 2 - accumulator will have twice smaller width and height, etc. + Minimum distance between centers of the detected circles. If the parameter is too small, multiple neighbor circles may be falsely detected in addition to a true one. If it is too large, some circles may be missed. + + + + + Finds circles in grayscale image using Hough transform. + + The storage for the circles detected. It can be a memory storage or single row/single column matrix (CvMat*) of type CV_32FC3, to which the circles' parameters are written. + Currently, the only implemented method is CV_HOUGH_GRADIENT, which is basically 21HT + Resolution of the accumulator used to detect centers of the circles. For example, if it is 1, the accumulator will have the same resolution as the input image, if it is 2 - accumulator will have twice smaller width and height, etc. + Minimum distance between centers of the detected circles. If the parameter is too small, multiple neighbor circles may be falsely detected in addition to a true one. If it is too large, some circles may be missed. + The first method-specific parameter. In case of CV_HOUGH_GRADIENT it is the higher threshold of the two passed to Canny edge detector (the lower one will be twice smaller). + + + + + Finds circles in grayscale image using Hough transform. + + The storage for the circles detected. It can be a memory storage or single row/single column matrix (CvMat*) of type CV_32FC3, to which the circles' parameters are written. + Currently, the only implemented method is CV_HOUGH_GRADIENT, which is basically 21HT + Resolution of the accumulator used to detect centers of the circles. For example, if it is 1, the accumulator will have the same resolution as the input image, if it is 2 - accumulator will have twice smaller width and height, etc. + Minimum distance between centers of the detected circles. If the parameter is too small, multiple neighbor circles may be falsely detected in addition to a true one. If it is too large, some circles may be missed. + The first method-specific parameter. In case of CV_HOUGH_GRADIENT it is the higher threshold of the two passed to Canny edge detector (the lower one will be twice smaller). + The second method-specific parameter. In case of CV_HOUGH_GRADIENT it is accumulator threshold at the center detection stage. The smaller it is, the more false circles may be detected. Circles, corresponding to the larger accumulator values, will be returned first. + + + + + Finds circles in grayscale image using Hough transform. + + The storage for the circles detected. It can be a memory storage or single row/single column matrix (CvMat*) of type CV_32FC3, to which the circles' parameters are written. + Currently, the only implemented method is CV_HOUGH_GRADIENT, which is basically 21HT + Resolution of the accumulator used to detect centers of the circles. For example, if it is 1, the accumulator will have the same resolution as the input image, if it is 2 - accumulator will have twice smaller width and height, etc. + Minimum distance between centers of the detected circles. If the parameter is too small, multiple neighbor circles may be falsely detected in addition to a true one. If it is too large, some circles may be missed. + The first method-specific parameter. In case of CV_HOUGH_GRADIENT it is the higher threshold of the two passed to Canny edge detector (the lower one will be twice smaller). + The second method-specific parameter. In case of CV_HOUGH_GRADIENT it is accumulator threshold at the center detection stage. The smaller it is, the more false circles may be detected. Circles, corresponding to the larger accumulator values, will be returned first. + Minimal radius of the circles to search for. + + + + + Finds circles in grayscale image using Hough transform. + + The storage for the circles detected. It can be a memory storage or single row/single column matrix (CvMat*) of type CV_32FC3, to which the circles' parameters are written. + Currently, the only implemented method is CV_HOUGH_GRADIENT, which is basically 21HT + Resolution of the accumulator used to detect centers of the circles. For example, if it is 1, the accumulator will have the same resolution as the input image, if it is 2 - accumulator will have twice smaller width and height, etc. + Minimum distance between centers of the detected circles. If the parameter is too small, multiple neighbor circles may be falsely detected in addition to a true one. If it is too large, some circles may be missed. + The first method-specific parameter. In case of CV_HOUGH_GRADIENT it is the higher threshold of the two passed to Canny edge detector (the lower one will be twice smaller). + The second method-specific parameter. In case of CV_HOUGH_GRADIENT it is accumulator threshold at the center detection stage. The smaller it is, the more false circles may be detected. Circles, corresponding to the larger accumulator values, will be returned first. + Minimal radius of the circles to search for. + Maximal radius of the circles to search for. By default the maximal radius is set to max(image_width, image_height). + + + + + Finds circles in grayscale image using Hough transform. + + The storage for the circles detected. It can be a memory storage or single row/single column matrix (CvMat*) of type CV_32FC3, to which the circles' parameters are written. + Currently, the only implemented method is CV_HOUGH_GRADIENT, which is basically 21HT + Resolution of the accumulator used to detect centers of the circles. For example, if it is 1, the accumulator will have the same resolution as the input image, if it is 2 - accumulator will have twice smaller width and height, etc. + Minimum distance between centers of the detected circles. If the parameter is too small, multiple neighbor circles may be falsely detected in addition to a true one. If it is too large, some circles may be missed. + + + + + Finds circles in grayscale image using Hough transform. + + The storage for the circles detected. It can be a memory storage or single row/single column matrix (CvMat*) of type CV_32FC3, to which the circles' parameters are written. + Currently, the only implemented method is CV_HOUGH_GRADIENT, which is basically 21HT + Resolution of the accumulator used to detect centers of the circles. For example, if it is 1, the accumulator will have the same resolution as the input image, if it is 2 - accumulator will have twice smaller width and height, etc. + Minimum distance between centers of the detected circles. If the parameter is too small, multiple neighbor circles may be falsely detected in addition to a true one. If it is too large, some circles may be missed. + The first method-specific parameter. In case of CV_HOUGH_GRADIENT it is the higher threshold of the two passed to Canny edge detector (the lower one will be twice smaller). + + + + + Finds circles in grayscale image using Hough transform. + + The storage for the circles detected. It can be a memory storage or single row/single column matrix (CvMat*) of type CV_32FC3, to which the circles' parameters are written. + Currently, the only implemented method is CV_HOUGH_GRADIENT, which is basically 21HT + Resolution of the accumulator used to detect centers of the circles. For example, if it is 1, the accumulator will have the same resolution as the input image, if it is 2 - accumulator will have twice smaller width and height, etc. + Minimum distance between centers of the detected circles. If the parameter is too small, multiple neighbor circles may be falsely detected in addition to a true one. If it is too large, some circles may be missed. + The first method-specific parameter. In case of CV_HOUGH_GRADIENT it is the higher threshold of the two passed to Canny edge detector (the lower one will be twice smaller). + The second method-specific parameter. In case of CV_HOUGH_GRADIENT it is accumulator threshold at the center detection stage. The smaller it is, the more false circles may be detected. Circles, corresponding to the larger accumulator values, will be returned first. + + + + + Finds circles in grayscale image using Hough transform. + + The storage for the circles detected. It can be a memory storage or single row/single column matrix (CvMat*) of type CV_32FC3, to which the circles' parameters are written. + Currently, the only implemented method is CV_HOUGH_GRADIENT, which is basically 21HT + Resolution of the accumulator used to detect centers of the circles. For example, if it is 1, the accumulator will have the same resolution as the input image, if it is 2 - accumulator will have twice smaller width and height, etc. + Minimum distance between centers of the detected circles. If the parameter is too small, multiple neighbor circles may be falsely detected in addition to a true one. If it is too large, some circles may be missed. + The first method-specific parameter. In case of CV_HOUGH_GRADIENT it is the higher threshold of the two passed to Canny edge detector (the lower one will be twice smaller). + The second method-specific parameter. In case of CV_HOUGH_GRADIENT it is accumulator threshold at the center detection stage. The smaller it is, the more false circles may be detected. Circles, corresponding to the larger accumulator values, will be returned first. + Minimal radius of the circles to search for. + + + + + Finds circles in grayscale image using Hough transform. + + The storage for the circles detected. It can be a memory storage or single row/single column matrix (CvMat*) of type CV_32FC3, to which the circles' parameters are written. + Currently, the only implemented method is CV_HOUGH_GRADIENT, which is basically 21HT + Resolution of the accumulator used to detect centers of the circles. For example, if it is 1, the accumulator will have the same resolution as the input image, if it is 2 - accumulator will have twice smaller width and height, etc. + Minimum distance between centers of the detected circles. If the parameter is too small, multiple neighbor circles may be falsely detected in addition to a true one. If it is too large, some circles may be missed. + The first method-specific parameter. In case of CV_HOUGH_GRADIENT it is the higher threshold of the two passed to Canny edge detector (the lower one will be twice smaller). + The second method-specific parameter. In case of CV_HOUGH_GRADIENT it is accumulator threshold at the center detection stage. The smaller it is, the more false circles may be detected. Circles, corresponding to the larger accumulator values, will be returned first. + Minimal radius of the circles to search for. + Maximal radius of the circles to search for. By default the maximal radius is set to max(image_width, image_height). + + + + + Finds lines in binary image using Hough transform. + + The storage for the lines detected. It can be a memory storage or single row/single column matrix (CvMat*) of a particular type to which the lines' parameters are written. + The Hough transform variant. + Distance resolution in pixel-related units. + Angle resolution measured in radians. + Threshold parameter. A line is returned by the function if the corresponding accumulator value is greater than threshold. + + + + + Finds lines in binary image using Hough transform. + + The storage for the lines detected. It can be a memory storage or single row/single column matrix (CvMat*) of a particular type to which the lines' parameters are written. + The Hough transform variant. + Distance resolution in pixel-related units. + Angle resolution measured in radians. + Threshold parameter. A line is returned by the function if the corresponding accumulator value is greater than threshold. + The first method-dependent parameter. + The second method-dependent parameter. + + + + + Finds lines in binary image using Hough transform. + + The storage for the lines detected. It can be a memory storage or single row/single column matrix (CvMat*) of a particular type to which the lines' parameters are written. + The Hough transform variant. + Distance resolution in pixel-related units. + Angle resolution measured in radians. + Threshold parameter. A line is returned by the function if the corresponding accumulator value is greater than threshold. + + + + + Finds lines in binary image using Hough transform. + + The storage for the lines detected. It can be a memory storage or single row/single column matrix (CvMat*) of a particular type to which the lines' parameters are written. + The Hough transform variant. + Distance resolution in pixel-related units. + Angle resolution measured in radians. + Threshold parameter. A line is returned by the function if the corresponding accumulator value is greater than threshold. + The first method-dependent parameter. + The second method-dependent parameter. + + + + + Increments array data reference counter + + The function cvIncRefData increments CvMat or CvMatND data reference counter and returns the new counter value if the reference counter pointer is not NULL, otherwise it returns zero. + + + + Inpaints the selected region in the image. + + The inpainting mask, 8-bit 1-channel image. Non-zero pixels indicate the area that needs to be inpainted. + The output image of the same format and the same size as input. + The radius of circlular neighborhood of each point inpainted that is considered by the algorithm. + The inpainting method. + + + + Checks that array elements lie between elements of two other arrays + + The inclusive lower boundary array. + The exclusive upper boundary array. + The destination array, must have 8u or 8s type. + + + + Checks that array elements lie between two scalars + + The inclusive lower boundary. + The exclusive upper boundary. + The destination array, must have 8u or 8s type. + + + + Calculates integral images. + + The integral image, W+1xH+1, 32-bit integer or double precision floating-point (64f). + + + + Calculates integral images. + + The integral image, W+1xH+1, 32-bit integer or double precision floating-point (64f). + The integral image for squared pixel values, W+1xH+1, double precision floating-point (64f). + + + + Calculates integral images. + + The integral image, W+1xH+1, 32-bit integer or double precision floating-point (64f). + The integral image for squared pixel values, W+1xH+1, double precision floating-point (64f). + The integral for the image rotated by 45 degrees, W+1xH+1, the same data type as sum. + + + + Finds inverse or pseudo-inverse of matrix + + The destination matrix. + In case of LU method the function returns src1 determinant (src1 must be square). + If it is 0, the matrix is not inverted and src2 is filled with zeros. + In case of SVD methods the function returns the inverted condition number of src1 + + + + Finds inverse or pseudo-inverse of matrix + + The destination matrix. + Inversion method + In case of LU method the function returns src1 determinant (src1 must be square). + If it is 0, the matrix is not inverted and src2 is filled with zeros. + In case of SVD methods the function returns the inverted condition number of src1 + + + + Finds inverse or pseudo-inverse of matrix + + The destination matrix. + In case of LU method the function returns src1 determinant (src1 must be square). + If it is 0, the matrix is not inverted and src2 is filled with zeros. + In case of SVD methods the function returns the inverted condition number of src1 + + + + Finds inverse or pseudo-inverse of matrix + + The destination matrix. + Inversion method + In case of LU method the function returns src1 determinant (src1 must be square). + If it is 0, the matrix is not inverted and src2 is filled with zeros. + In case of SVD methods the function returns the inverted condition number of src1 + + + + Splits set of vectors by given number of clusters + + Number of clusters to split the set by. + Output integer vector storing cluster indices for every sample. + Specifies maximum number of iterations and/or accuracy (distance the centers move by between the subsequent iterations). + + + + Calculates Laplacian of the source image by summing second x- and y- derivatives calculated using Sobel operator. + + Destination image. + + + + Calculates Laplacian of the source image by summing second x- and y- derivatives calculated using Sobel operator. + + Destination image. + Aperture size (it has the same meaning as in cvSobel). + + + + Draws a line segment connecting two points + + First point's x-coordinate of the line segment. + First point's y-coordinate of the line segment. + Second point's x-coordinate of the line segment. + Second point's y-coordinate of the line segment. + Line color. + + + + Draws a line segment connecting two points + + First point's x-coordinate of the line segment. + First point's y-coordinate of the line segment. + Second point's x-coordinate of the line segment. + Second point's y-coordinate of the line segment. + Line color. + Line thickness. + + + + Draws a line segment connecting two points + + First point's x-coordinate of the line segment. + First point's y-coordinate of the line segment. + Second point's x-coordinate of the line segment. + Second point's y-coordinate of the line segment. + Line color. + Line thickness. + Type of the line. + + + + Draws a line segment connecting two points + + First point's x-coordinate of the line segment. + First point's y-coordinate of the line segment. + Second point's x-coordinate of the line segment. + Second point's y-coordinate of the line segment. + Line color. + Line thickness. + Type of the line. + Number of fractional bits in the point coordinates. + + + + Draws a line segment connecting two points + + First point of the line segment. + Second point of the line segment. + Line color. + + + + Draws a line segment connecting two points + + First point of the line segment. + Second point of the line segment. + Line color. + Line thickness. + + + + Draws a line segment connecting two points + + First point of the line segment. + Second point of the line segment. + Line color. + Line thickness. + Type of the line. + + + + Draws a line segment connecting two points + + First point of the line segment. + Second point of the line segment. + Line color. + Line thickness. + Type of the line. + Number of fractional bits in the point coordinates. + + + + Draws a line segment connecting two points + + First point's x-coordinate of the line segment. + First point's y-coordinate of the line segment. + Second point's x-coordinate of the line segment. + Second point's y-coordinate of the line segment. + Line color. + + + + Draws a line segment connecting two points + + First point's x-coordinate of the line segment. + First point's y-coordinate of the line segment. + Second point's x-coordinate of the line segment. + Second point's y-coordinate of the line segment. + Line color. + Line thickness. + + + + Draws a line segment connecting two points + + First point's x-coordinate of the line segment. + First point's y-coordinate of the line segment. + Second point's x-coordinate of the line segment. + Second point's y-coordinate of the line segment. + Line color. + Line thickness. + Type of the line. + + + + Draws a line segment connecting two points + + First point's x-coordinate of the line segment. + First point's y-coordinate of the line segment. + Second point's x-coordinate of the line segment. + Second point's y-coordinate of the line segment. + Line color. + Line thickness. + Type of the line. + Number of fractional bits in the point coordinates. + + + + Draws a line segment connecting two points + + First point of the line segment. + Second point of the line segment. + Line color. + + + + Draws a line segment connecting two points + + First point of the line segment. + Second point of the line segment. + Line color. + Line thickness. + + + + Draws a line segment connecting two points + + First point of the line segment. + Second point of the line segment. + Line color. + Line thickness. + Type of the line. + + + + Draws a line segment connecting two points + + First point of the line segment. + Second point of the line segment. + Line color. + Line thickness. + Type of the line. + Number of fractional bits in the point coordinates. + + + + Performs forward or inverse linear-polar image transform + + + + + + + + Performs forward or inverse linear-polar image transform + + + + + + + + + Calculates natural logarithm of every array element absolute value + + The destination array, it should have double type or the same type as the source. + + + + Remaps image to log-polar space. + The function emulates the human "foveal" vision and can be used for fast scale and rotation-invariant template matching, for object tracking etc. + + Destination image. + The transformation center, where the output precision is maximal. + Magnitude scale parameter. See below. + + + + Remaps image to log-polar space. + The function emulates the human "foveal" vision and can be used for fast scale and rotation-invariant template matching, for object tracking etc. + + Destination image. + The transformation center, where the output precision is maximal. + Magnitude scale parameter. See below. + A combination of interpolation method and the optional flags. + + + + Performs look-up table transform of array + + Destination array of arbitrary depth and of the same number of channels as the source array. + Look-up table of 256 elements; should have the same depth as the destination array. In case of multi-channel source and destination arrays, the table should either have a single-channel (in this case the same table is used for all channels), or the same number of channels as the source/destination array. + + + + Performs look-up table transform of array + + Destination array of arbitrary depth and of the same number of channels as the source array. + Look-up table of 256 elements; should have the same depth as the destination array. + + + + Performs look-up table transform of array + + Destination array of arbitrary depth and of the same number of channels as the source array. + Look-up table of 256 elements; should have the same depth as the destination array. + + + + Performs look-up table transform of array + + Destination array of arbitrary depth and of the same number of channels as the source array. + Look-up table of 256 elements; should have the same depth as the destination array. + + + + Performs look-up table transform of array + + Destination array of arbitrary depth and of the same number of channels as the source array. + Look-up table of 256 elements; should have the same depth as the destination array. + + + + Performs look-up table transform of array + + Destination array of arbitrary depth and of the same number of channels as the source array. + Look-up table of 256 elements; should have the same depth as the destination array. + + + + Compares template against overlapped image regions. + + Searched template; must be not greater than the source image and the same data type as the image. + A map of comparison results; single-channel 32-bit floating-point. If image is W×H and templ is w×h then result must be W-w+1×H-h+1. + Specifies the way the template must be compared with image regions. + + + + Finds per-element maximum of two arrays + + The second source array. + The destination array. + + + + Finds per-element maximum of array and scalar + + The scalar value. + The destination array. + + + + Finds per-element minimum of two arrays + + The second source array. + The destination array. + + + + Finds circumscribed rectangle of minimal area for given 2D point set + + The function cvMinAreaRect2 finds a circumscribed rectangle of the minimal area for 2D point set by building convex hull for the set and applying rotating calipers technique to the hull. + + + + Finds circumscribed rectangle of minimal area for given 2D point set + + The point tested against the contour. + The function cvMinAreaRect2 finds a circumscribed rectangle of the minimal area for 2D point set by building convex hull for the set and applying rotating calipers technique to the hull. + + + + Finds circumscribed rectangle of minimal area for given 2D point set + + Output parameter. The center of the enclosing circle. + Output parameter. The radius of the enclosing circle. + The function cvMinEnclosingCircle finds the minimal circumscribed circle for 2D point set using iterative algorithm. + It returns true if the resultant circle contains all the input points and false otherwise (i.e. algorithm failed). + + + + Finds global minimum and maximum in array or subarray + + Pointer to returned minimum value. + Pointer to returned maximum value. + + + + Finds global minimum and maximum in array or subarray + + Pointer to returned minimum value. + Pointer to returned maximum value. + The optional mask that is used to select a subarray. + + + + Finds global minimum and maximum in array or subarray + + Pointer to returned minimum location. + Pointer to returned maximum location. + + + + Finds global minimum and maximum in array or subarray + + Pointer to returned minimum location. + Pointer to returned maximum location. + The optional mask that is used to select a subarray. + + + + Finds global minimum and maximum in array or subarray + + Pointer to returned minimum value. + Pointer to returned maximum value. + Pointer to returned minimum location. + Pointer to returned maximum location. + + + + Finds global minimum and maximum in array or subarray + + Pointer to returned minimum value. + Pointer to returned maximum value. + Pointer to returned minimum location. + Pointer to returned maximum location. + The optional mask that is used to select a subarray. + + + + Finds per-element minimum of array and scalar + + The scalar value. + The destination array. + + + + Moments + + (For images only) If the flag is non-zero, all the zero pixel values are treated as zeroes, all the others are treated as 1’s + + + + + Calculates per-element product of two arrays + + The second source array. + The destination array. + + + + Calculates per-element product of two arrays + + The second source array. + The destination array. + Optional scale factor + + + + Calculates absolute array norm, absolute difference norm or relative difference norm + + + + + + Calculates absolute array norm, absolute difference norm or relative difference norm + + The second source image. If it is null, the absolute norm of arr1 is calculated, otherwise absolute or relative norm of arr1-arr2 is calculated. + + + + + Calculates absolute array norm, absolute difference norm or relative difference norm + + The second source image. If it is null, the absolute norm of arr1 is calculated, otherwise absolute or relative norm of arr1-arr2 is calculated. + Type of norm + + + + + Calculates absolute array norm, absolute difference norm or relative difference norm + + The second source image. If it is null, the absolute norm of arr1 is calculated, otherwise absolute or relative norm of arr1-arr2 is calculated. + Type of norm + The optional operation mask. + + + + + Normalizes array to a certain norm or value range + + The output array; in-place operation is supported. + + + + Normalizes array to a certain norm or value range + + The output array; in-place operation is supported. + The minimum/maximum value of the output array or the norm of output array. + The maximum/minimum value of the output array. + + + + Normalizes array to a certain norm or value range + + The output array; in-place operation is supported. + The minimum/maximum value of the output array or the norm of output array. + The maximum/minimum value of the output array. + The normalization type. + + + + Normalizes array to a certain norm or value range + + The output array; in-place operation is supported. + The minimum/maximum value of the output array or the norm of output array. + The maximum/minimum value of the output array. + The normalization type. + The operation mask. Makes the function consider and normalize only certain array elements. + + + + Performs per-element bit-wise inversion of array elements + + The destination array. + + + + Calculates per-element bit-wise disjunction of two arrays + + The second source array. + The destination array. + + + + Calculates per-element bit-wise disjunction of two arrays + + The second source array. + The destination array. + Operation mask, 8-bit single channel array; specifies elements of destination array to be changed. + + + + Calculates per-element bit-wise disjunction of array and scalar + + Scalar to use in the operation. + The destination array. + + + + Calculates per-element bit-wise disjunction of array and scalar + + Scalar to use in the operation. + The destination array. + Operation mask, 8-bit single channel array; specifies elements of destination array to be changed. + + + + Performs perspective matrix transform of vector array + + The destination three-channel floating-point array. + 3×3 or 4×4 transformation matrix. + + + + Point in contour test + + The point tested against the contour. + If it is true, the function estimates distance from the point to the nearest contour edge. + The function cvPointPolygonTest determines whether the point is inside contour, outside, or lies on an edge (or coinsides with a vertex). It returns positive, negative or zero value, correspondingly. When measure_dist=0, the return value is +1, -1 and 0, respectively. When measure_dist≠0, it is a signed distance between the point and the nearest contour edge. + + + + Draws simple or thick polygons + + Array of pointers to polylines. + Indicates whether the polylines must be drawn closed. If closed, the function draws the line from the last vertex of every contour to the first vertex. + Polyline color. + + + + Draws simple or thick polygons + + Array of pointers to polylines. + Indicates whether the polylines must be drawn closed. If closed, the function draws the line from the last vertex of every contour to the first vertex. + Polyline color. + Thickness of the polyline edges. + + + + Draws simple or thick polygons + + Array of pointers to polylines. + Indicates whether the polylines must be drawn closed. If closed, the function draws the line from the last vertex of every contour to the first vertex. + Polyline color. + Thickness of the polyline edges. + Type of the line segments. + + + + Draws simple or thick polygons + + Array of pointers to polylines. + Indicates whether the polylines must be drawn closed. If closed, the function draws the line from the last vertex of every contour to the first vertex. + Polyline color. + Thickness of the polyline edges. + Type of the line segments. + Number of fractional bits in the vertex coordinates. + + + + Draws simple or thick polygons + + Array of pointers to polylines. + Indicates whether the polylines must be drawn closed. If closed, the function draws the line from the last vertex of every contour to the first vertex. + Polyline color. + + + + Draws simple or thick polygons + + Array of pointers to polylines. + Indicates whether the polylines must be drawn closed. If closed, the function draws the line from the last vertex of every contour to the first vertex. + Polyline color. + Thickness of the polyline edges. + + + + Draws simple or thick polygons + + Array of pointers to polylines. + Indicates whether the polylines must be drawn closed. If closed, the function draws the line from the last vertex of every contour to the first vertex. + Polyline color. + Thickness of the polyline edges. + Type of the line segments. + + + + Draws simple or thick polygons + + Array of pointers to polylines. + Indicates whether the polylines must be drawn closed. If closed, the function draws the line from the last vertex of every contour to the first vertex. + Polyline color. + Thickness of the polyline edges. + Type of the line segments. + Number of fractional bits in the vertex coordinates. + + + + Raises every array element to power + + The destination array, should be the same type as the source. + The exponent of power. + + + + Calculates feature map for corner detection + + Image to store the corner candidates. + + + + Calculates feature map for corner detection + + Image to store the corner candidates. + Aperture parameter for Sobel operator. + + + + Return pointer to the particular array element + + The first zero-based component of the element index + pointer to the particular array element + + + + Return pointer to the particular array element + + The first zero-based component of the element index + Type of matrix elements + pointer to the particular array element + + + + Return pointer to the particular array element + + The first zero-based component of the element index + The second zero-based component of the element index + pointer to the particular array element + + + + Return pointer to the particular array element + + The first zero-based component of the element index + The second zero-based component of the element index + Type of matrix elements + pointer to the particular array element + + + + Return pointer to the particular array element + + The first zero-based component of the element index + The second zero-based component of the element index + The third zero-based component of the element index + pointer to the particular array element + + + + Return pointer to the particular array element + + The first zero-based component of the element index + The second zero-based component of the element index + The third zero-based component of the element index + Type of matrix elements + pointer to the particular array element + + + + Return pointer to the particular array element + + Array of the element indices + pointer to the particular array element + + + + Return pointer to the particular array element + + Array of the element indices + Type of matrix elements + pointer to the particular array element + + + + Return pointer to the particular array element + + Array of the element indices + Type of matrix elements + Optional input parameter for sparse matrices. Non-zero value of the parameter means that the requested element is created if it does not exist already. + pointer to the particular array element + + + + Return pointer to the particular array element + + Array of the element indices + Type of matrix elements + Optional input parameter for sparse matrices. Non-zero value of the parameter means that the requested element is created if it does not exist already. + Optional input parameter for sparse matrices. If the pointer is not NULL, the function does not recalculate the node hash value, but takes it from the specified location. It is useful for speeding up pair-wise operations + pointer to the particular array element + + + + Draws text string + + String to print. + Coordinates of the bottom-left corner of the first letter. + Pointer to the font structure. + Text color. + + + + Downsamples image. + + The destination image, should have 2x smaller width and height than the source. + + + + Downsamples image. + + The destination image, should have 2x smaller width and height than the source. + Type of the filter used for convolution; only CV_GAUSSIAN_5x5 is currently supported. + + + + Does meanshift image segmentation. + + The destination image of the same format and the same size as the source. + The spatial window radius. + The color window radius. + + + + Does meanshift image segmentation. + + The destination image of the same format and the same size as the source. + The spatial window radius. + The color window radius. + Maximum level of the pyramid for the segmentation. + + + + Does meanshift image segmentation. + + The destination image of the same format and the same size as the source. + The spatial window radius. + The color window radius. + Maximum level of the pyramid for the segmentation. + Termination criteria: when to stop meanshift iterations. + + + + Upsamples image. + + The destination image, should have 2x smaller width and height than the source. + + + + Upsamples image. + + The destination image, should have 2x smaller width and height than the source. + Type of the filter used for convolution; only CV_GAUSSIAN_5x5 is currently supported. + + + + Randomly shuffles the array elements + + + + + Randomly shuffles the array elements + + The Random Number Generator used to shuffle the elements. When the pointer is null, a temporary RNG will be created and used. + + + + Randomly shuffles the array elements + + The Random Number Generator used to shuffle the elements. When the pointer is null, a temporary RNG will be created and used. + The relative parameter that characterizes intensity of the shuffling performed. + + + + Fills matrix with given range of numbers as following: + arr(i,j) = (end-start) * (i*cols(arr)+j) / (cols(arr)*rows(arr)) + + The lower inclusive boundary of the range. + The upper exclusive boundary of the range. + + + + Draws simple, thick or filled rectangle + + X-coordinate of the one of the rectangle vertices. + Y-coordinate of the one of the rectangle vertices. + X-coordinate of the opposite rectangle vertex. + Y-coordinate of the opposite rectangle vertex. + Line color (RGB) or brightness (grayscale image). + + + + Draws simple, thick or filled rectangle + + X-coordinate of the one of the rectangle vertices. + Y-coordinate of the one of the rectangle vertices. + X-coordinate of the opposite rectangle vertex. + Y-coordinate of the opposite rectangle vertex. + Line color (RGB) or brightness (grayscale image). + Thickness of lines that make up the rectangle. Negative values, e.g. CV_FILLED, make the function to draw a filled rectangle. + + + + Draws simple, thick or filled rectangle + + X-coordinate of the one of the rectangle vertices. + Y-coordinate of the one of the rectangle vertices. + X-coordinate of the opposite rectangle vertex. + Y-coordinate of the opposite rectangle vertex. + Line color (RGB) or brightness (grayscale image). + Thickness of lines that make up the rectangle. Negative values, e.g. CV_FILLED, make the function to draw a filled rectangle. + Type of the line, see cvLine description. + + + + Draws simple, thick or filled rectangle + + X-coordinate of the one of the rectangle vertices. + Y-coordinate of the one of the rectangle vertices. + X-coordinate of the opposite rectangle vertex. + Y-coordinate of the opposite rectangle vertex. + Line color (RGB) or brightness (grayscale image). + Thickness of lines that make up the rectangle. Negative values, e.g. CV_FILLED, make the function to draw a filled rectangle. + Type of the line, see cvLine description. + Number of fractional bits in the point coordinates. + + + + Draws simple, thick or filled rectangle + + One of the rectangle vertices. + Opposite rectangle vertex. + Line color (RGB) or brightness (grayscale image). + + + + Draws simple, thick or filled rectangle + + One of the rectangle vertices. + Opposite rectangle vertex. + Line color (RGB) or brightness (grayscale image). + Thickness of lines that make up the rectangle. Negative values, e.g. CV_FILLED, make the function to draw a filled rectangle. + + + + Draws simple, thick or filled rectangle + + One of the rectangle vertices. + Opposite rectangle vertex. + Line color (RGB) or brightness (grayscale image). + Thickness of lines that make up the rectangle. Negative values, e.g. CV_FILLED, make the function to draw a filled rectangle. + Type of the line, see cvLine description. + + + + Draws simple, thick or filled rectangle + + One of the rectangle vertices. + Opposite rectangle vertex. + Line color (RGB) or brightness (grayscale image). + Thickness of lines that make up the rectangle. Negative values, e.g. CV_FILLED, make the function to draw a filled rectangle. + Type of the line, see cvLine description. + Number of fractional bits in the point coordinates. + + + + Draws simple, thick or filled rectangle + + Rectangle. + Line color (RGB) or brightness (grayscale image). + + + + Draws simple, thick or filled rectangle + + Rectangle. + Line color (RGB) or brightness (grayscale image). + Thickness of lines that make up the rectangle. Negative values, e.g. CV_FILLED, make the function to draw a filled rectangle. + + + + Draws simple, thick or filled rectangle + + Rectangle. + Line color (RGB) or brightness (grayscale image). + Thickness of lines that make up the rectangle. Negative values, e.g. CV_FILLED, make the function to draw a filled rectangle. + Type of the line, see cvLine description. + + + + Draws simple, thick or filled rectangle + + Rectangle. + Line color (RGB) or brightness (grayscale image). + Thickness of lines that make up the rectangle. Negative values, e.g. CV_FILLED, make the function to draw a filled rectangle. + Type of the line, see cvLine description. + Number of fractional bits in the point coordinates. + + + + Draws simple, thick or filled rectangle + + X-coordinate of the one of the rectangle vertices. + Y-coordinate of the one of the rectangle vertices. + X-coordinate of the opposite rectangle vertex. + Y-coordinate of the opposite rectangle vertex. + Line color (RGB) or brightness (grayscale image). + + + + Draws simple, thick or filled rectangle + + X-coordinate of the one of the rectangle vertices. + Y-coordinate of the one of the rectangle vertices. + X-coordinate of the opposite rectangle vertex. + Y-coordinate of the opposite rectangle vertex. + Line color (RGB) or brightness (grayscale image). + Thickness of lines that make up the rectangle. Negative values, e.g. CV_FILLED, make the function to draw a filled rectangle. + + + + Draws simple, thick or filled rectangle + + X-coordinate of the one of the rectangle vertices. + Y-coordinate of the one of the rectangle vertices. + X-coordinate of the opposite rectangle vertex. + Y-coordinate of the opposite rectangle vertex. + Line color (RGB) or brightness (grayscale image). + Thickness of lines that make up the rectangle. Negative values, e.g. CV_FILLED, make the function to draw a filled rectangle. + Type of the line, see cvLine description. + + + + Draws simple, thick or filled rectangle + + X-coordinate of the one of the rectangle vertices. + Y-coordinate of the one of the rectangle vertices. + X-coordinate of the opposite rectangle vertex. + Y-coordinate of the opposite rectangle vertex. + Line color (RGB) or brightness (grayscale image). + Thickness of lines that make up the rectangle. Negative values, e.g. CV_FILLED, make the function to draw a filled rectangle. + Type of the line, see cvLine description. + Number of fractional bits in the point coordinates. + + + + Draws simple, thick or filled rectangle + + One of the rectangle vertices. + Opposite rectangle vertex. + Line color (RGB) or brightness (grayscale image). + + + + Draws simple, thick or filled rectangle + + One of the rectangle vertices. + Opposite rectangle vertex. + Line color (RGB) or brightness (grayscale image). + Thickness of lines that make up the rectangle. Negative values, e.g. CV_FILLED, make the function to draw a filled rectangle. + + + + Draws simple, thick or filled rectangle + + One of the rectangle vertices. + Opposite rectangle vertex. + Line color (RGB) or brightness (grayscale image). + Thickness of lines that make up the rectangle. Negative values, e.g. CV_FILLED, make the function to draw a filled rectangle. + Type of the line, see cvLine description. + + + + Draws simple, thick or filled rectangle + + One of the rectangle vertices. + Opposite rectangle vertex. + Line color (RGB) or brightness (grayscale image). + Thickness of lines that make up the rectangle. Negative values, e.g. CV_FILLED, make the function to draw a filled rectangle. + Type of the line, see cvLine description. + Number of fractional bits in the point coordinates. + + + + Draws simple, thick or filled rectangle + + Rectangle. + Line color (RGB) or brightness (grayscale image). + + + + Draws simple, thick or filled rectangle + + Rectangle. + Line color (RGB) or brightness (grayscale image). + Thickness of lines that make up the rectangle. Negative values, e.g. CV_FILLED, make the function to draw a filled rectangle. + + + + Draws simple, thick or filled rectangle + + Rectangle. + Line color (RGB) or brightness (grayscale image). + Thickness of lines that make up the rectangle. Negative values, e.g. CV_FILLED, make the function to draw a filled rectangle. + Type of the line, see cvLine description. + + + + Draws simple, thick or filled rectangle + + Rectangle. + Line color (RGB) or brightness (grayscale image). + Thickness of lines that make up the rectangle. Negative values, e.g. CV_FILLED, make the function to draw a filled rectangle. + Type of the line, see cvLine description. + Number of fractional bits in the point coordinates. + + + + Reduces matrix to a vector + + The output single-row/single-column vector that accumulates somehow all the matrix rows/columns. + + + + Reduces matrix to a vector + + The output single-row/single-column vector that accumulates somehow all the matrix rows/columns. + The dimension index along which the matrix is reduce. 0 means that the matrix is reduced to a single row, 1 means that the matrix is reduced to a single column. -1 means that the dimension is chosen automatically by analysing the dst size. + + + + Reduces matrix to a vector + + The output single-row/single-column vector that accumulates somehow all the matrix rows/columns. + The dimension index along which the matrix is reduce. 0 means that the matrix is reduced to a single row, 1 means that the matrix is reduced to a single column. -1 means that the dimension is chosen automatically by analysing the dst size. + The reduction operation. + + + + Releases array data. + + + + + Applies generic geometrical transformation to the image. + + Destination image. + The map of x-coordinates (32fC1 image). + The map of y-coordinates (32fC1 image). + + + + Applies generic geometrical transformation to the image. + + Destination image. + The map of x-coordinates (32fC1 image). + The map of y-coordinates (32fC1 image). + A combination of interpolation method and the optional flag(s). + + + + Applies generic geometrical transformation to the image. + + Destination image. + The map of x-coordinates (32fC1 image). + The map of y-coordinates (32fC1 image). + A combination of interpolation method and the optional flag(s). + A value used to fill outliers. + + + + Fill destination array with tiled source array + + Destination array, image or matrix. + + + + Changes shape of matrix/image without copying data + + Output header to be filled. + New number of channels. new_cn = 0 means that number of channels remains unchanged. + + + + + Changes shape of matrix/image without copying data + + Output header to be filled. + New number of channels. new_cn = 0 means that number of channels remains unchanged. + New number of rows. new_rows = 0 means that number of rows remains unchanged unless it needs to be changed according to new_cn value. destination array to be changed. + + + + + Changes shape of matrix/image without copying data + + Output header to be filled. + New number of channels. new_cn = 0 means that number of channels remains unchanged. + + + + + Changes shape of matrix/image without copying data + + Output header to be filled. + New number of channels. new_cn = 0 means that number of channels remains unchanged. + New number of rows. new_rows = 0 means that number of rows remains unchanged unless it needs to be changed according to new_cn value. destination array to be changed. + + + + + Changes shape of multi-dimensional array w/o copying data + + + Size of output header to distinguish between IplImage, CvMat and CvMatND output headers. + Output header to be filled. + New number of channels. new_cn = 0 means that number of channels remains unchanged. + New number of dimensions. new_dims = 0 means that number of dimensions remains the same. + Array of new dimension sizes. Only new_dims-1 values are used, because the total number of elements must remain the same. Thus, if new_dims = 1, new_sizes array is not used + + + + + Changes shape of multi-dimensional array w/o copying data + + + Output header to be filled. + New number of channels. new_cn = 0 means that number of channels remains unchanged. + New number of dimensions. new_dims = 0 means that number of dimensions remains the same. + Array of new dimension sizes. Only new_dims-1 values are used, because the total number of elements must remain the same. Thus, if new_dims = 1, new_sizes array is not used + + + + + Resizes image src so that it fits exactly to dst. + If ROI is set, the function consideres the ROI as supported as usual. + + Destination image. + + + + Resizes image src so that it fits exactly to dst. + If ROI is set, the function consideres the ROI as supported as usual. + + Destination image. + Interpolation method. + + + + Implements a particular case of application of line iterators. + The function reads all the image points lying on the line between pt1 and pt2, including the ending points, and stores them into the buffer. + + Starting the line point. + Ending the line point. + Buffer to store the line points. + The line connectivity, 4 or 8. + + + + + Calculates sum of scaled array and another array + + Scale factor for the first array. + The second source array. + The destination array + + + + Calculates sum of scaled array and another array + + Scale factor for the first array. + The second source array. + The destination array + + + + Sets every element of array to given value + + Fill value. + + + + Sets every element of array to given value + + Fill value. + Operation mask, 8-bit single channel array; specifies elements of destination array to be changed. + + + + Change the particular array element + + The first zero-based component of the element index + The assigned value + + + + Change the particular array element + + The first zero-based component of the element index + The second zero-based component of the element index + The assigned value + + + + Change the particular array element + + The first zero-based component of the element index + The second zero-based component of the element index + The third zero-based component of the element index + The assigned value + + + + Change the particular array element + + The assigned value + Array of the element indices + + + + Assigns user data to the array header. + Header should be initialized before using cvCreate*Header, cvInit*Header or cvMat (in case of matrix) function. + + + User data. + Full row length in bytes. + + + + Assigns user data to the array header. + Header should be initialized before using cvCreate*Header, cvInit*Header or cvMat (in case of matrix) function. + + User data. + Full row length in bytes. + + + + Initializes scaled identity matrix + + + + + Initializes scaled identity matrix + + The value to assign to the diagonal elements. + + + + Change the particular array element + + The first zero-based component of the element index + The assigned value + + + + Change the particular array element + + The first zero-based component of the element index + The second zero-based component of the element index + The assigned value + + + + Change the particular array element + + The first zero-based component of the element index + The second zero-based component of the element index + The third zero-based component of the element index + The assigned value + + + + Change the particular array element + + The assigned value + Array of the element indices + + + + Clears the array + + + + + Clears the array + + + + + Smooths the image in one of several ways. + + The destination image. + + + + Smooths the image in one of several ways. + + The destination image. + Type of the smoothing. + + + + Smooths the image in one of several ways. + + The destination image. + Type of the smoothing. + The first parameter of smoothing operation. + + + + Smooths the image in one of several ways. + + The destination image. + Type of the smoothing. + The first parameter of smoothing operation. + The second parameter of smoothing operation. In case of simple scaled/non-scaled and Gaussian blur if param2 is zero, it is set to param1. + + + + Smooths the image in one of several ways. + + The destination image. + Type of the smoothing. + The first parameter of smoothing operation. + The second parameter of smoothing operation. In case of simple scaled/non-scaled and Gaussian blur if param2 is zero, it is set to param1. + In case of Gaussian kernel this parameter may specify Gaussian sigma (standard deviation). If it is zero, it is calculated from the kernel size. + + + + Smooths the image in one of several ways. + + The destination image. + Type of the smoothing. + The first parameter of smoothing operation. + The second parameter of smoothing operation. In case of simple scaled/non-scaled and Gaussian blur if param2 is zero, it is set to param1. + In case of Gaussian kernel this parameter may specify Gaussian sigma (standard deviation). If it is zero, it is calculated from the kernel size. + In case of non-square Gaussian kernel the parameter may be used to specify a different (from param3) sigma in the vertical direction. + + + + Calculates first, second, third or mixed image derivatives using extended Sobel operator + + Destination image. + Order of the derivative x. + Order of the derivative y. + + + + Calculates first, second, third or mixed image derivatives using extended Sobel operator + + Destination image. + Order of the derivative x. + Order of the derivative y. + Size of the extended Sobel kernel. + + + + Sorts the rows/cols of an array ascending/descending + + + + + Sorts the rows/cols of an array ascending/descending + + Optional destination array + + + + Sorts the rows/cols of an array ascending/descending + + Optional destination array + Index matrix + + + + Sorts the rows/cols of an array ascending/descending + + Optional destination array + Index matrix + Sorting parameter + + + + Divides multi-channel array into several single-channel arrays or extracts a single channel from the array + + Destination channel 0 + Destination channel 1 + Destination channel 2 + Destination channel 3 + + + + Divides multi-channel array into several single-channel arrays or extracts a single channel from the array + + Destination channel 0 + Destination channel 1 + Destination channel 2 + Destination channel 3 + + + + Adds the square of source image to accumulator + + Accumulator of the same number of channels as input image, 32-bit or 64-bit floating-point. + + + + Adds the square of source image to accumulator + + Accumulator of the same number of channels as input image, 32-bit or 64-bit floating-point. + Optional operation mask. + + + + Initializes contour scanning process + + Container of the retrieved contours. + CvContourScanner + + + + Initializes contour scanning process + + Container of the retrieved contours. + Size of the sequence header, >=sizeof(CvChain) if method=CV_CHAIN_CODE, and >=sizeof(CvContour) otherwise. + CvContourScanner + + + + Initializes contour scanning process + + Container of the retrieved contours. + Size of the sequence header, >=sizeof(CvChain) if method=CV_CHAIN_CODE, and >=sizeof(CvContour) otherwise. + Retrieval mode; see cvFindContours. + CvContourScanner + + + + Initializes contour scanning process + + Container of the retrieved contours. + Size of the sequence header, >=sizeof(CvChain) if method=CV_CHAIN_CODE, and >=sizeof(CvContour) otherwise. + Retrieval mode; see cvFindContours. + Approximation method. It has the same meaning as in cvFindContours, but CV_LINK_RUNS can not be used here. + CvContourScanner + + + + Initializes contour scanning process + + Container of the retrieved contours. + Size of the sequence header, >=sizeof(CvChain) if method=CV_CHAIN_CODE, and >=sizeof(CvContour) otherwise. + Retrieval mode; see cvFindContours. + Approximation method. It has the same meaning as in cvFindContours, but CV_LINK_RUNS can not be used here. + ROI offset; see cvFindContours. + CvContourScanner + + + + Computes per-element difference between two arrays + + The second source array. + The destination array. + + + + Computes per-element difference between two arrays + + The second source array. + The destination array. + Operation mask, 8-bit single channel array; specifies elements of destination array to be changed. + + + + Computes difference between array and scalar + + Subtracted scalar. + The destination array. + + + + Computes difference between array and scalar + + Subtracted scalar. + The destination array. + Operation mask, 8-bit single channel array; specifies elements of destination array to be changed. + + + + Computes difference between scalar and array + + Scalar to subtract from. + The destination array. + + + + Computes difference between scalar and array + + Scalar to subtract from. + The destination array. + Operation mask, 8-bit single channel array; specifies elements of destination array to be changed. + + + + Summarizes array elements + + sum S of array elements, independently for each channel + + + + Performs singular value decomposition of real floating-point matrix + + Resulting singular value matrix (M×N or N×N) or vector (N×1). + + + + Performs singular value decomposition of real floating-point matrix + + Resulting singular value matrix (M×N or N×N) or vector (N×1). + Optional left orthogonal matrix (M×M or M×N). If CV_SVD_U_T is specified, the number of rows and columns in the sentence above should be swapped. + + + + Performs singular value decomposition of real floating-point matrix + + Resulting singular value matrix (M×N or N×N) or vector (N×1). + Optional left orthogonal matrix (M×M or M×N). If CV_SVD_U_T is specified, the number of rows and columns in the sentence above should be swapped. + Optional right orthogonal matrix (N×N) + + + + Performs singular value decomposition of real floating-point matrix + + Resulting singular value matrix (M×N or N×N) or vector (N×1). + Optional left orthogonal matrix (M×M or M×N). If CV_SVD_U_T is specified, the number of rows and columns in the sentence above should be swapped. + Optional right orthogonal matrix (N×N) + Operation flags + + + + Applies fixed-level threshold to array elements. + + Destination array; must be either the same type as src or 8-bit. + Threshold value. + Maximum value to use with CV_THRESH_BINARY and CV_THRESH_BINARY_INV thresholding types. + Thresholding type. + + + + Returns trace of matrix + + sum of diagonal elements of the matrix src1 + + + + Transposes matrix + + The destination matrix. + + + + Transposes matrix + + The destination matrix. + + + + Transforms image to compensate lens distortion. + + The output (corrected) image. + The camera matrix (A) [fx 0 cx; 0 fy cy; 0 0 1]. + The vector of distortion coefficients, 4x1 or 1x4 [k1, k2, p1, p2]. + + + + Transforms image to compensate lens distortion. + + The output (corrected) image. + The camera matrix (A) [fx 0 cx; 0 fy cy; 0 0 1]. + The vector of distortion coefficients, 4x1 or 1x4 [k1, k2, p1, p2]. + + + + + + + + + + + + + + + + + + + + + + Applies perspective transformation to the image. + + Destination image. + 3x3 transformation matrix. + + + + Applies perspective transformation to the image. + + Destination image. + 3x3 transformation matrix. + A combination of interpolation method and the optional flags. + + + + Applies perspective transformation to the image. + + Destination image. + 3x3 transformation matrix. + A combination of interpolation method and the optional flags. + A value used to fill outliers. + + + + Does watershed segmentation. + + The input/output 32-bit single-channel image (map) of markers. + + + + Performs per-element bit-wise "exclusive or" operation on two arrays + + The second source array. + The destination array. am> + + + + Performs per-element bit-wise "exclusive or" operation on two arrays + + The second source array. + The destination array. + Operation mask, 8-bit single channel array; specifies elements of destination array to be changed. + + + + Performs per-element bit-wise "exclusive or" operation on array and scalar + + Scalar to use in the operation. + The destination array. + + + + Performs per-element bit-wise "exclusive or" operation on array and scalar + + Scalar to use in the operation. + The destination array. + Operation mask, 8-bit single channel array; specifies elements of destination array to be changed. + + + + Default constructor + + + + + Constructor + + If true, this matrix will be disposed by GC automatically. + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + Get number of dimensions + + + + + Get type of the array + + + + + Get number of channels + + + + + Get bit Depth + + + + + Return the particular array element (cvGet1D/Set1D) + + The first zero-based component of the element index + + + + + Return the particular array element (cvGet2D/Set2D) + + The first zero-based component of the element index + The second zero-based component of the element index + + + + + Return the particular array element (cvGet3D/Set3D) + + The first zero-based component of the element index + The second zero-based component of the element index + The third zero-based component of the element index + + + + + Finds lines in binary image using Hough transform. + + Distance resolution in pixel-related units. + Angle resolution measured in radians. + Threshold parameter. A line is returned by the function if the corresponding accumulator value is greater than threshold. + + + + + Finds lines in binary image using Hough transform. + + Distance resolution in pixel-related units. + Angle resolution measured in radians. + Threshold parameter. A line is returned by the function if the corresponding accumulator value is greater than threshold. + The first method-dependent parameter. + The second method-dependent parameter. + + + + + Finds lines in binary image using Hough transform. + + Distance resolution in pixel-related units. + Angle resolution measured in radians. + Threshold parameter. A line is returned by the function if the corresponding accumulator value is greater than threshold. + + + + + Finds lines in binary image using Hough transform. + + Distance resolution in pixel-related units. + Angle resolution measured in radians. + Threshold parameter. A line is returned by the function if the corresponding accumulator value is greater than threshold. + The first method-dependent parameter. + The second method-dependent parameter. + + + + + Composes multi-channel array from several single-channel arrays or inserts a single channel into the array. (cvMerge) + + Input channel 0 + Input channel 1 + Input channel 2 + Input channel 3 + + + + Composes multi-channel array from several single-channel arrays or inserts a single channel into the array. (cvCvtPlaneToPix) + + Input channel 0 + Input channel 1 + Input channel 2 + Input channel 3 + + + + Fills array with random numbers and updates the RNG state + + RNG state initialized by cvRNG. + Distribution type. + The first parameter of distribution. In case of uniform distribution it is the inclusive lower boundary of random numbers range. In case of normal distribution it is the mean value of random numbers. + The second parameter of distribution. In case of uniform distribution it is the exclusive upper boundary of random numbers range. In case of normal distribution it is the standard deviation of random numbers. + + + + Saves the image to the specified file. The image format is chosen depending on the filename extension, see cvLoadImage. + Only 8-bit single-channel or 3-channel (with 'BGR' channel order) images can be saved using this function. + + Name of the file. + + + + + Saves the image to the specified file. The image format is chosen depending on the filename extension, see cvLoadImage. + Only 8-bit single-channel or 3-channel (with 'BGR' channel order) images can be saved using this function. + + Name of the file. + + + + + + Saves the image to the specified file. The image format is chosen depending on the filename extension, see cvLoadImage. + Only 8-bit single-channel or 3-channel (with 'BGR' channel order) images can be saved using this function. + + Name of the file. + + + + + + Extract this image to the memory using cvEncodeImage + + Image extension to decide encoding format. + Encoding options. + + + + + Extract this image to the memory using cvEncodeImage + + Destination stream. + Image extension to decide encoding format. + Encoding options. + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Position in relative units + + + + + Start of the file + + + + + End of the file + + + + + Error status + + + + + everithing is ok [CV_StsOk] + + + + + pseudo error for back trace [CV_StsBackTrace] + + + + + unknown /unspecified error [CV_StsError] + + + + + internal error (bad state) [CV_StsInternal] + + + + + insufficient memory [CV_StsNoMem] + + + + + function arg/param is bad [CV_StsBadArg] + + + + + unsupported function [CV_StsBadFunc] + + + + + iter. didn't converge [CV_StsNoConv] + + + + + tracing [CV_StsAutoTrace] + + + + + image header is NULL [CV_HeaderIsNull] + + + + + image size is invalid [CV_BadImageSize] + + + + + offset is invalid [CV_BadOffset] + + + + + [CV_BadOffset] + + + + + [CV_BadStep] + + + + + [CV_BadModelOrChSeq] + + + + + [CV_BadNumChannels] + + + + + [CV_BadNumChannel1U] + + + + + [CV_BadDepth] + + + + + [CV_BadAlphaChannel] + + + + + [CV_BadOrder] + + + + + [CV_BadOrigin] + + + + + [CV_BadAlign] + + + + + [CV_BadCallBack] + + + + + [CV_BadTileSize] + + + + + [CV_BadCOI] + + + + + [CV_BadROISize] + + + + + [CV_MaskIsTiled] + + + + + null pointer [CV_StsNullPtr] + + + + + incorrect vector length [CV_StsVecLengthErr] + + + + + incorr. filter structure content [CV_StsFilterStructContentErr] + + + + + incorr. transform kernel content [CV_StsKernelStructContentErr] + + + + + incorrect filter ofset value [CV_StsFilterOffsetErr] + + + + + the input/output structure size is incorrect [CV_StsBadSize] + + + + + division by zero [CV_StsDivByZero] + + + + + in-place operation is not supported [CV_StsInplaceNotSupported] + + + + + request can't be completed [CV_StsObjectNotFound] + + + + + formats of input/output arrays differ [CV_StsUnmatchedFormats] + + + + + flag is wrong or not supported [CV_StsBadFlag] + + + + + bad CvPoint [CV_StsBadPoint] + + + + + bad format of mask (neither 8uC1 nor 8sC1) [CV_StsBadMask] + + + + + sizes of input/output structures do not match [CV_StsUnmatchedSizes] + + + + + the data format/type is not supported by the function [CV_StsUnsupportedFormat] + + + + + some of parameters are out of range [CV_StsOutOfRange] + + + + + invalid syntax/structure of the parsed file [CV_StsParseError] + + + + + the requested function/feature is not implemented [CV_StsNotImplemented] + + + + + an allocated block has been corrupted [CV_StsBadMemBlock] + + + + + Error mode + + + + + The program is terminated after error handler is called. This is the default value. + It is useful for debugging, as the error is signalled immediately after it occurs. + However, for production systems other two methods may be preferable as they provide more control. + [CV_ErrModeLeaf] + + + + + The program is not terminated, but the error handler is called. + The stack is unwinded (it is done w/o using C++ exception mechanism). + User may check error code after calling Cxcore function with cvGetErrStatus and react. + [CV_ErrModeParent] + + + + + Similar to Parent mode, but no error handler is called. + [CV_ErrModeSilent] + + + + + 4-character code of codec used to compress the frames. + + + + + pt[i] + + + + + + + next[i] + + + + + + + Handles loading embedded dlls into memory, based on http://stackoverflow.com/questions/666799/embedding-unmanaged-dll-into-a-managed-c-sharp-dll. + + This code is based on https://github.com/charlesw/tesseract + + + + + + + + + The default base directory name to copy the assemblies too. + + + + + Map processor + + + + + Used as a sanity check for the returned processor architecture to double check the returned value. + + + + + Additional user-defined DLL paths + + + + + constructor + + + + + + + + + + + + + + + + + + + + + + + + + Get's the current process architecture while keeping track of any assumptions or possible errors. + + + + + + Determines if the dynamic link library file name requires a suffix + and adds it if necessary. + + + + + Given the processor architecture, returns the name of the platform. + + + + + + + + + + List of attributes + + + + + const char** attr; + + + + + struct CvAttrList* next; + + + + + NULL-terminated array of (attribute_name,attribute_value) pairs + + + + + pointer to next chunk of the attributes list + + + + + sizeof(CvAttrList) + + + + + initializes CvAttrList structure + + array of (attribute_name,attribute_value) pairs + + + + initializes CvAttrList structure + + array of (attribute_name,attribute_value) pairs + pointer to next chunk of the attributes list + + + + + + + + + Rotated 2D box + + + + + Center of the box. + + + + + Box width and length. + + + + + Angle between the horizontal axis and the first side (i.e. length) in degrees + + + + + sizeof(CvBox2D) + + + + + Constructor + + + + + + + + Finds box vertices + + Array of vertices + + + + + + + + + + + Specifies whether this object contains the same members as the specified Object. + + The Object to test. + This method returns true if obj is the same type as this object and has the same members as this object. + + + + + + + The Object to test. + This method returns true if obj is the same type as this object and has the same members as this object. + + + + + + + The Object to test. + This method returns true if obj is the same type as this object and has the same members as this object. + + + + Returns a hash code for this object. + + An integer value that specifies a hash value for this object. + + + + Converts this object to a human readable string. + + A string that represents this object. + + + + Chain Reader + + + + + Target chain + + + + + Default constructor + + + + + Initialize by cvStartReadChainPoints + + Pointer to chain + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + sizeof(CvChainPtReader) + + + + + Data pointer (CvChainPtReader*) + + + + + + + + + + + + + + + schar deltas[8][2] + + + + + Initializes chain reader + + Pointer to chain + + + + Gets next chain point + + Current chain point. + + + + + + + + + + CvConDensation + + + + + Track whether Dispose has been called + + + + + Initialize from pointer + + struct CvConDensation* + + + + Allocates ConDensation filter structure + + Dimension of the state vector. + Dimension of the measurement vector. + Number of samples. + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + sizeof(CvConDensation) + + + + + Dimension of measurement vector + + + + + Dimension of state vector + + + + + Matrix of the linear Dynamics system + + + + + Vector of State + + + + + Number of the Samples + + + + + Array of the Sample Vectors + + + + + + + + + + + + + + + + + Temporary array of the Sample Vectors + + + + + Confidence for each Sample + + + + + Cumulative confidence + + + + + Temporary vector + + + + + RandomVector to update sample set + + + + + RandomVector to update sample set + + + + + A balanced kd-tree index of feature vectors + + + + + Track whether Dispose has been called + + + + + Constructs a tree of feature vectors + + n x d matrix of n d-dimensional feature vectors (CV_32FC1 or CV_64FC1). + + + + Constructs from native pointer + + struct CvFeatureTree* + + + + Constructs a tree of feature vectors + + n x d matrix of n d-dimensional feature vectors (CV_32FC1 or CV_64FC1). + + + + + Constructs kd-tree from set of feature descriptors + + + + + + + Constructs spill-tree from set of feature descriptors + + + + + + + Constructs spill-tree from set of feature descriptors + + + + + + + + Constructs spill-tree from set of feature descriptors + + + + + + + + + Constructs spill-tree from set of feature descriptors + + + + + + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + Finds approximate k nearest neighbors of given vectors using best-bin-first search. + + m x d matrix of (row-)vectors to find the nearest neighbors of. + m x k set of row indices of matching vectors (referring to matrix passed to cvCreateFeatureTree). Contains -1 in some columns if fewer than k neighbors found. + m x k matrix of distances to k nearest neighbors. + + + + Finds approximate k nearest neighbors of given vectors using best-bin-first search. + + m x d matrix of (row-)vectors to find the nearest neighbors of. + m x k set of row indices of matching vectors (referring to matrix passed to cvCreateFeatureTree). Contains -1 in some columns if fewer than k neighbors found. + m x k matrix of distances to k nearest neighbors. + The number of neighbors to find. + + + + Finds approximate k nearest neighbors of given vectors using best-bin-first search. + + m x d matrix of (row-)vectors to find the nearest neighbors of. + m x k set of row indices of matching vectors (referring to matrix passed to cvCreateFeatureTree). Contains -1 in some columns if fewer than k neighbors found. + m x k matrix of distances to k nearest neighbors. + The number of neighbors to find. + The maximum number of leaves to visit. + + + + Performs orthogonal range seaching on the given kd-tree. + + 1 x d or d x 1 vector (CV_32FC1 or CV_64FC1) giving minimum value for each dimension. + 1 x d or d x 1 vector (CV_32FC1 or CV_64FC1) giving maximum value for each dimension. + 1 x m or m x 1 vector (CV_32SC1) to contain output row indices (referring to matrix passed to cvCreateFeatureTree). + the number of such vectors found. + + + + Edge of graph + + + + + Initializes from native pointer + + + + + + Initializes from native pointer + + + + + + sizeof(CvGraphEdge) + + + + + Edge flags + + + + + Edge weight + + + + + The next edges in the incidence lists for staring (0) and ending (1) vertices + + + + + The starting (0) and ending (1) vertices + + + + + + + + + + + CvGraphScanner + + + + + Track whether Dispose has been called + + + + + Initialize from pointer + + + + + + Creates structure for depth-first graph traversal + + Graph. + + + + Creates structure for depth-first graph traversal + + Graph. + Initial vertex to start from. If NULL, the traversal starts from the first vertex (a vertex with the minimal index in the sequence of vertices). + + + + Creates structure for depth-first graph traversal + + Graph. + Initial vertex to start from. If NULL, the traversal starts from the first vertex (a vertex with the minimal index in the sequence of vertices). + Event mask indicating which events are interesting to the user (where cvNextGraphItem function returns control to the user) It can be CV_GRAPH_ALL_ITEMS (all events are interesting) or combination of the following flags: +
* CV_GRAPH_VERTEX - stop at the graph vertices visited for the first time +
* CV_GRAPH_TREE_EDGE - stop at tree edges (tree edge is the edge connecting the last visited vertex and the vertex to be visited next) +
* CV_GRAPH_BACK_EDGE - stop at back edges (back edge is an edge connecting the last visited vertex with some of its ancestors in the search tree) +
* CV_GRAPH_FORWARD_EDGE - stop at forward edges (forward edge is an edge conecting the last visited vertex with some of its descendants in the search tree). The forward edges are only possible during oriented graph traversal) +
* CV_GRAPH_CROSS_EDGE - stop at cross edges (cross edge is an edge connecting different search trees or branches of the same tree. The cross edges are only possible during oriented graphs traversal) +
* CV_GRAPH_ANY_EDGE - stop and any edge (tree, back, forward and cross edges) +
* CV_GRAPH_NEW_TREE - stop in the beginning of every new search tree. When the traversal procedure visits all vertices and edges reachible from the initial vertex (the visited vertices together with tree edges make up a tree), it searches for some unvisited vertex in the graph and resumes the traversal process from that vertex. Before starting a new tree (including the very first tree when cvNextGraphItem is called for the first time) it generates CV_GRAPH_NEW_TREE event. +
For unoriented graphs each search tree corresponds to a connected component of the graph. +
* CV_GRAPH_BACKTRACKING - stop at every already visited vertex during backtracking - returning to already visited vertexes of the traversal tree. + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + sizeof(CvGraphScanner) + + + + + Current graph vertex (or current edge origin) + + + + + Current graph edge destination vertex + + + + + Current edge + + + + + the graph + + + + + the graph vertex stack + + + + + the lower bound of certainly visited vertices + + + + + event mask + + + + + Returns index of graph vertex + + The function cvNextGraphItem traverses through the graph until an event interesting to the user (that is, an event, specified in the mask in cvCreateGraphScanner call) is met or the traversal is over. In the first case it returns one of the events, listed in the description of mask parameter above and with the next call it resumes the traversal. In the latter case it returns CV_GRAPH_OVER (-1). When the event is CV_GRAPH_VERTEX, or CV_GRAPH_BACKTRACKING or CV_GRAPH_NEW_TREE, the currently observed vertex is stored in scanner->vtx. And if the event is edge-related, the edge itself is stored at scanner->edge, the previously visited vertex - at scanner->vtx and the other ending vertex of the edge - at scanner->dst. + + + + Vertex of graph + + + + + Allocates memory + + + + + Initializes from native pointer + + + + + + Initializes from native pointer + + + + + + sizeof(CvGraphVtx) + + + + + Edge flags + + + + + The first incident edge + + + + + + + + + + + a single tree classifier (stump in the simplest case) that returns the response for the feature + at the particular image location (i.e. pixel sum over subrectangles of the window) and gives out + a value depending on the responce + + + + + Initializes from native pointer + + struct CvHaarClassifier* + + + + sizeof(CvHaarClassifier) + + + + + Number of nodes in the decision tree + + + + + Array of haar features + + + + + branch threshold. if feature responce is <= threshold, left branch is chosen, otherwise right branch is chosed. + + + + + index of the left child (or negated index if the left child is a leaf) + + + + + index of the right child (or negated index if the right child is a leaf) + + + + + output value correponding to the leaf. + + + + + A haar feature which consists of 2-3 rectangles with appropriate weights. + + + + + Initializes from native pointer + + struct CvHaarFeature* + + + + sizeof(CvHaarClassifier) + + + + + 0 means up-right feature, 1 means 45--rotated feature + + + + + Elements of the haar feature + + + + + An element of a haar feature + + + + + a boosted battery of classifiers(=stage classifier): + the stage classifier returns 1 + if the sum of the classifiers' responces + is greater than threshold and 0 otherwise + + + + + Initializes from native pointer + + struct CvHaarStageClassifier* + + + + sizeof(CvHaarStageClassifier) + + + + + Number of classifiers in the battery + + + + + Threshold for the boosted classifier + + + + + Array of classifiers + + + + + + + + + + + + + + + + + + + + Hu moments + + + + + Default constructor + + + + + Initialize by cvGetHuMoments + + Pointer to the moment state structure. + + + + CvLineIterator + + + + + Constructor + + + + + Initializes line iterator + + Image to sample the line from. + First ending point of the line segment. + Second ending point of the line segment. + The function cvInitLineIterator initializes the line iterator and returns the number of pixels between two end points. Both points must be inside the image. After the iterator has been initialized, all the points on the raster line that connects the two ending points may be retrieved by successive calls of NextLinePoint point. The points on the line are calculated one by one using 4-connected or 8-connected Bresenham algorithm. + + + + Initializes line iterator + + Image to sample the line from. + First ending point of the line segment. + Second ending point of the line segment. + The scanned line connectivity, 4 or 8. + The function cvInitLineIterator initializes the line iterator and returns the number of pixels between two end points. Both points must be inside the image. After the iterator has been initialized, all the points on the raster line that connects the two ending points may be retrieved by successive calls of NextLinePoint point. The points on the line are calculated one by one using 4-connected or 8-connected Bresenham algorithm. + + + + Initializes line iterator + + Image to sample the line from. + First ending point of the line segment. + Second ending point of the line segment. + The scanned line connectivity, 4 or 8. + The flag, indicating whether the line should be always scanned from the left-most point to the right-most out of pt1 and pt2 (leftToRight=true), or it is scanned in the specified order, from pt1 to pt2 (leftToRight=false). + The function cvInitLineIterator initializes the line iterator and returns the number of pixels between two end points. Both points must be inside the image. After the iterator has been initialized, all the points on the raster line that connects the two ending points may be retrieved by successive calls of NextLinePoint point. The points on the line are calculated one by one using 4-connected or 8-connected Bresenham algorithm. + + + + Initializes line iterator + + Image to sample the line from. + First ending point of the line segment. + Second ending point of the line segment. + The scanned line connectivity, 4 or 8. + The flag, indicating whether the line should be always scanned from the left-most point to the right-most out of pt1 and pt2 (leftToRight=true), or it is scanned in the specified order, from pt1 to pt2 (leftToRight=false). + The function cvInitLineIterator initializes the line iterator and returns the number of pixels between two end points. Both points must be inside the image. After the iterator has been initialized, all the points on the raster line that connects the two ending points may be retrieved by successive calls of NextLinePoint point. The points on the line are calculated one by one using 4-connected or 8-connected Bresenham algorithm. + + + + Initializes line iterator + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + sizeof(CvLineIterator) + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + CV_NEXT_LINE_POINT + + + + + Gets the value of the current point + + + + + Supports a simple iteration over a generic collection. + + + + + + + + + + + + Memory storage block + + + + + Constructs from native pointer + + struct CvMemBlock* + + + + sizeof(CvMemBlock) + + + + + + + + + + + + + + + Memory storage position + + + + + Default constructor + + + + + Initializes from native pointer + + struct CvMemStoragePos* + + + + sizeof(CvMemStoragePos) + + + + + + + + + + + + + + + Moment state structure + + + + + Default constructor + + + + + Initialize by cvMoments + + Image (1-channel or 3-channel with COI set) or polygon (CvSeq of points or a vector of points). + (For images only) If the flag is non-zero, all the zero pixel values are treated as zeroes, all the others are treated as 1’s. + + + + Retrieves central moment from moment state structure + + x order of the retrieved moment, x_order >= 0 + y order of the retrieved moment, y_order >= 0 and x_order + y_order <= 3 + Central moment + + + + Calculates seven Hu invariants + + Pointer to Hu moments structure + + + + Retrieves normalized central moment from moment state structure + + x order of the retrieved moment, x_order >= 0 + y order of the retrieved moment, y_order >= 0 and x_order + y_order <= 3 + Central moment + + + + Retrieves spatial moment from moment state structure + + x order of the retrieved moment, x_order >= 0 + y order of the retrieved moment, y_order >= 0 and x_order + y_order <= 3 + Spatial moments + + + + Structure containing object information + + + + + Track whether Dispose has been called + + + + + Constructor (cvCreatePOSITObject) + + Points of the 3D object model. + + + + Constructs from pointer + + struct CvPOSITObject* + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + Implements POSIT algorithm + + Object points projections on the 2D image plane. + Focal length of the camera used. + Termination criteria of the iterative POSIT algorithm. + Matrix of rotations. + Translation vector. + + + + CvRandState + + + typedef struct CvRandState + { + CvRNG _state; /* RNG state (the current seed and carry)*/ + int _disttype; /* distribution type */ + CvScalar _param[2]; /* parameters of RNG */ + } + CvRandState; + + + + + RNG _state (the current seed and carry) + + + + + distribution type + + + + + parameters of RNG + + + + + + + + + + + + + + + + + + + + + + + + + + + Initializes from pointer + + + + + + + + + + + + Fills array with random numbers + + The array to randomize + + + + Initialize CvRandState structure + + The first parameter of distribution. In case of uniform distribution it is the inclusive lower boundary of random numbers range. In case of normal distribution it is the mean value of random numbers. + The second parameter of distribution. In case of uniform distribution it is the exclusive upper boundary of random numbers range. In case of normal distribution it is the standard deviation of random numbers. + Seed value + + + + Initialize CvRandState structure + + The first parameter of distribution. In case of uniform distribution it is the inclusive lower boundary of random numbers range. In case of normal distribution it is the mean value of random numbers. + The second parameter of distribution. In case of uniform distribution it is the exclusive upper boundary of random numbers range. In case of normal distribution it is the standard deviation of random numbers. + Seed value + Type of distribution + + + + Changes RNG range while preserving RNG _state + + The first parameter of distribution. In case of uniform distribution it is the inclusive lower boundary of random numbers range. In case of normal distribution it is the mean value of random numbers. + The second parameter of distribution. In case of uniform distribution it is the exclusive upper boundary of random numbers range. In case of normal distribution it is the standard deviation of random numbers. + + + + Changes RNG range while preserving RNG _state + + The first parameter of distribution. In case of uniform distribution it is the inclusive lower boundary of random numbers range. In case of normal distribution it is the mean value of random numbers. + The second parameter of distribution. In case of uniform distribution it is the exclusive upper boundary of random numbers range. In case of normal distribution it is the standard deviation of random numbers. + Index dimension to initialize, -1 = all + + + + sparse array iterator + + + + + Target sparse mat + + + + + Default constructor + + + + + Initializes with CvSparseMat + + Input array + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + sizeof(CvSparseMatIterator) + + + + + + + + + + + + + + + + + + + + Moves iterator to the next sparse matrix element and returns pointer to it. + + + + + + Initializes sparse array elements iterator + + Input array + the first sparse matrix element + + + + + + + + + + + + + + + + An element of CvSparseMat + + + + + Default constructor + + CvSparseNode* + + + + sizeof(CvSparseNode) + + + + + + + + + + + + + + + Class that is used to traverse trees + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Default Constructor + + + + + Construct by cvInitTreeNodeIterator + + + + + + + Construct by cvInitTreeNodeIterator + + + + + + + Returns the currently observed node and moves iterator toward the next node + + + + + + Returns the currently observed node and moves iterator toward the next node + + + + + + + Returns the currently observed node and moves iterator toward the previous node + + + + + + Returns the currently observed node and moves iterator toward the previous node + + + + + + Class that is used to traverse trees + + + + + + Default Constructor + + + + + Construct by cvInitTreeNodeIterator + + + + + + + Construct by cvInitTreeNodeIterator + + + + + + + Convert to generic class + + + + + + Returns the currently observed node and moves iterator toward the next node + + + + + + Returns the currently observed node and moves iterator toward the previous node + + + + + + + + + + + + + + + + + + Sequence writer + + + + + Track whether Dispose has been called + + + + + Default constructor + + + + + Initializes process of writing data to sequence (cvStartAppendToSeq). + + Pointer to the sequence. + Writer state; initialized by the function. + + + + Creates new sequence and initializes writer for it (cvStartWriteSeq). + + Flags of the created sequence. If the sequence is not passed to any function working with a specific type of sequences, the sequence value may be equal to 0, otherwise the appropriate type must be selected from the list of predefined sequence types. + Size of the sequence header. The parameter value may not be less than sizeof(CvSeq). If a certain type or extension is specified, it must fit the base type header. + Size of the sequence elements in bytes; must be consistent with the sequence type. For example, if the sequence of points is created (element type CV_SEQ_ELTYPE_POINT ), then the parameter elem_size must be equal to sizeof(CvPoint). + Sequence location. + + + + Initializes from pointer + + CvSeqWriter* + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + sizeof(CvSeqWriter) + + + + + size of sequence header + + + + + Sequence, beign read + + + + + current block + + + + + pointer to element be read next + + + + + pointer to the beginning of block + + + + + pointer to the End of block + + + + + Finishes process of writing sequence + + the pointer to the written sequence. + + + + Updates sequence headers from the writer state (cvFlushSeqWriter). + + + + + (CV_WRITE_SEQ_ELEM_VAR) + + + + + + (CV_WRITE_SEQ_ELEM) + + + + + + + Sequence writer + + + + + Default constructor + + + + + Initializes process of writing data to sequence (cvStartAppendToSeq). + + Pointer to the sequence. + Writer state; initialized by the function. + + + + Creates new sequence and initializes writer for it (cvStartWriteSeq). + + Flags of the created sequence. If the sequence is not passed to any function working with a specific type of sequences, the sequence value may be equal to 0, otherwise the appropriate type must be selected from the list of predefined sequence types. + Size of the sequence header. The parameter value may not be less than sizeof(CvSeq). If a certain type or extension is specified, it must fit the base type header. + Size of the sequence elements in bytes; must be consistent with the sequence type. For example, if the sequence of points is created (element type CV_SEQ_ELTYPE_POINT ), then the parameter elem_size must be equal to sizeof(CvPoint). + Sequence location. + + + + Initializes from non generic writer + + + + + + Initializes from pointer + + CvSeqWriter* + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + (CV_WRITE_SEQ_ELEM) + + + + + + Contour tree + + + + + Initializes from native pointer + + + + + + Creates hierarchical representation of contour + + Input contour. + Container for output tree. + Approximation accuracy. + + + + + sizeof(CvContourTree) + + + + + The first point of the binary tree root segment + + + + + The last point of the binary tree root segment + + + + + Restores contour from tree. + + Container for the reconstructed contour. + Criteria, where to stop reconstruction. + + + + + Oriented or unoriented weigted graph + + + + + Default constructor + + + + + Creates empty graph + + Type of the created graph. Usually, it is either CV_SEQ_KIND_GRAPH for generic unoriented graphs and CV_SEQ_KIND_GRAPH | CV_GRAPH_FLAG_ORIENTED for generic oriented graphs. + Graph vertex size; the custom vertex structure must start with CvGraphVtx (use CV_GRAPH_VERTEX_FIELDS()) + Graph edge size; the custom edge structure must start with CvGraphEdge (use CV_GRAPH_EDGE_FIELDS()) + The graph container. + The function cvCreateGraph creates an empty graph and returns it. + + + + Creates empty graph + + Type of the created graph. Usually, it is either CV_SEQ_KIND_GRAPH for generic unoriented graphs and CV_SEQ_KIND_GRAPH | CV_GRAPH_FLAG_ORIENTED for generic oriented graphs. + Graph header size; may not be less than sizeof(CvGraph). + Graph vertex size; the custom vertex structure must start with CvGraphVtx (use CV_GRAPH_VERTEX_FIELDS()) + Graph edge size; the custom edge structure must start with CvGraphEdge (use CV_GRAPH_EDGE_FIELDS()) + The graph container. + The function cvCreateGraph creates an empty graph and returns it. + + + + Initializes from native pointer + + struct CvGraph* + + + + sizeof(CvGraph) + + + + + Set of edges + + + + + Returns index of graph vertex + + The function cvClearGraph removes all vertices and edges from the graph. The function has O(1) time complexity. + + + + Clone graph + + Container for the copy. + The function cvCloneGraph creates full copy of the graph. If the graph vertices or edges have pointers to some external data, it still be shared between the copies. The vertex and edge indices in the new graph may be different from the original, because the function defragments the vertex and edge sets. + + + + Finds edge in graph + + Index of the starting vertex of the edge. + Index of the ending vertex of the edge. For unoriented graph the order of the vertex parameters does not matter. + The function cvFindGraphEdge finds the graph edge connecting two specified vertices and returns pointer to it or NULL if the edge does not exists. + + + + Finds edge in graph + + Index of the starting vertex of the edge. + Index of the ending vertex of the edge. For unoriented graph the order of the vertex parameters does not matter. + The function cvFindGraphEdge finds the graph edge connecting two specified vertices and returns pointer to it or NULL if the edge does not exists. + + + + Finds edge in graph + + Starting vertex of the edge. + Ending vertex of the edge. For unoriented graph the order of the vertex parameters does not matter. + The function cvFindGraphEdge finds the graph edge connecting two specified vertices and returns pointer to it or NULL if the edge does not exists. + + + + Finds edge in graph + + Starting vertex of the edge. + Ending vertex of the edge. For unoriented graph the order of the vertex parameters does not matter. + The function cvFindGraphEdge finds the graph edge connecting two specified vertices and returns pointer to it or NULL if the edge does not exists. + + + + Adds edge to graph + + Index of the starting vertex of the edge. + Index of the ending vertex of the edge. For unoriented graph the order of the vertex parameters does not matter. + The function cvGraphAddEdge connects two specified vertices. The function returns 1 if the edge has been added successfully, 0 if the edge connecting the two vertices exists already and -1 if either of the vertices was not found, the starting and the ending vertex are the same or there is some other critical situation. In the latter case (i.e. when the result is negative) the function also reports an error by default. + + + + Adds edge to graph + + Index of the starting vertex of the edge. + Index of the ending vertex of the edge. For unoriented graph the order of the vertex parameters does not matter. + Optional input parameter, initialization data for the edge. + The function cvGraphAddEdge connects two specified vertices. The function returns 1 if the edge has been added successfully, 0 if the edge connecting the two vertices exists already and -1 if either of the vertices was not found, the starting and the ending vertex are the same or there is some other critical situation. In the latter case (i.e. when the result is negative) the function also reports an error by default. + + + + Adds edge to graph + + Index of the starting vertex of the edge. + Index of the ending vertex of the edge. For unoriented graph the order of the vertex parameters does not matter. + Optional input parameter, initialization data for the edge. + Optional output parameter to contain the address of the inserted edge. + The function cvGraphAddEdge connects two specified vertices. The function returns 1 if the edge has been added successfully, 0 if the edge connecting the two vertices exists already and -1 if either of the vertices was not found, the starting and the ending vertex are the same or there is some other critical situation. In the latter case (i.e. when the result is negative) the function also reports an error by default. + + + + Adds edge to graph + + Starting vertex of the edge. + Ending vertex of the edge. For unoriented graph the order of the vertex parameters does not matter. + The function cvGraphAddEdge connects two specified vertices. The function returns 1 if the edge has been added successfully, 0 if the edge connecting the two vertices exists already and -1 if either of the vertices was not found, the starting and the ending vertex are the same or there is some other critical situation. In the latter case (i.e. when the result is negative) the function also reports an error by default. + + + + Adds edge to graph + + Starting vertex of the edge. + Ending vertex of the edge. For unoriented graph the order of the vertex parameters does not matter. + Optional input parameter, initialization data for the edge. + The function cvGraphAddEdge connects two specified vertices. The function returns 1 if the edge has been added successfully, 0 if the edge connecting the two vertices exists already and -1 if either of the vertices was not found, the starting and the ending vertex are the same or there is some other critical situation. In the latter case (i.e. when the result is negative) the function also reports an error by default. + + + + Adds edge to graph + + Starting vertex of the edge. + Ending vertex of the edge. For unoriented graph the order of the vertex parameters does not matter. + Optional input parameter, initialization data for the edge. + Optional output parameter to contain the address of the inserted edge. + The function cvGraphAddEdge connects two specified vertices. The function returns 1 if the edge has been added successfully, 0 if the edge connecting the two vertices exists already and -1 if either of the vertices was not found, the starting and the ending vertex are the same or there is some other critical situation. In the latter case (i.e. when the result is negative) the function also reports an error by default. + + + + Adds vertex to graph + + The function cvGraphAddVtx adds a vertex to the graph and returns the vertex index. + + + + Adds vertex to graph + + Optional input argument used to initialize the added vertex (only user-defined fields beyond sizeof(CvGraphVtx) are copied). + The function cvGraphAddVtx adds a vertex to the graph and returns the vertex index. + + + + Adds vertex to graph + + Optional input argument used to initialize the added vertex (only user-defined fields beyond sizeof(CvGraphVtx) are copied). + The address of the new vertex is written there. + The function cvGraphAddVtx adds a vertex to the graph and returns the vertex index. + + + + Returns index of graph edge + + Graph edge. + The function cvGraphEdgeIdx returns index of the graph edge. + + + + Returns count of edges + + + + + + Returns count of vertex + + + + + + Removes edge from graph + + Index of the starting vertex of the edge. + Index of the ending vertex of the edge. For unoriented graph the order of the vertex parameters does not matter. + The function cvGraphRemoveEdge removes the edge connecting two specified vertices. If the vertices are not connected [in that order], the function does nothing. + + + + Removes edge from graph + + Starting vertex of the edge. + Ending vertex of the edge. For unoriented graph the order of the vertex parameters does not matter. + The function cvGraphRemoveEdgeByPtr removes the edge connecting two specified vertices. If the vertices are not connected [in that order], the function does nothing. + + + + Removes vertex from graph + + Index of the removed vertex. + The function cvGraphRemoveAddVtx removes a vertex from the graph together with all the edges incident to it. The function reports an error, if the input vertex does not belong to the graph. The return value is number of edges deleted, or -1 if the vertex does not belong to the graph. + + + + Removes vertex from graph + + Vertex to remove + The function cvGraphRemoveVtxByPtr removes a vertex from the graph together with all the edges incident to it. The function reports an error, if the vertex does not belong to the graph. The return value is number of edges deleted, or -1 if the vertex does not belong to the graph. + + + + Counts edges indicent to the vertex + + Index of the graph vertex. + The function cvGraphVtxDegree returns the number of edges incident to the specified vertex, both incoming and outcoming. + + + + Counts edges indicent to the vertex + + Index of the graph vertex. + The function cvGraphVtxDegree returns the number of edges incident to the specified vertex, both incoming and outcoming. + + + + Returns index of graph vertex + + Graph vertex. + The function cvGraphVtxIdx returns index of the graph vertex. + + + + The user-defined distance function for cvCalcEMD2. It takes coordinates of two points and returns the distance between the points. + + + + + + + + WndProc + + + Windows message ID + + + + + + + Angle Unit for cvCartToPolar + + + + + Angle in radians + + + + + Angle in degrees + + + + + Similarity measure (cvMatchContourTrees) + + + + + [CV_CONTOUR_TREES_MATCH_I1] + + + + + Orientation for Convex Hull function + + + + + Clockwise + [CV_CLOCKWISE] + + + + + Counter clockwise + [CV_COUNTER_CLOCKWISE] + + + + + + + + + + + + + + + + + + + + + + + + + Event mask indicating which events are interesting to the user + + + + + Stop at the graph vertices visited for the first time + [CV_GRAPH_VERTEX] + + + + + Stop at tree edges (tree edge is the edge connecting the last visited vertex and the vertex to be visited next) + [CV_GRAPH_TREE_EDGE] + + + + + Stop at back edges (back edge is an edge connecting the last visited vertex with some of its ancestors in the search tree) + [CV_GRAPH_BACK_EDGE] + + + + + Stop at forward edges (forward edge is an edge conecting the last visited vertex with some of its descendants in the search tree). The forward edges are only possible during oriented graph traversal) + [CV_GRAPH_FORWARD_EDGE] + + + + + Stop at cross edges (cross edge is an edge connecting different search trees or branches of the same tree. The cross edges are only possible during oriented graphs traversal) + [CV_GRAPH_CROSS_EDGE] + + + + + Stop and any edge (tree, back, forward and cross edges) + [CV_GRAPH_ANY_EDGE] + + + + + Stop in the beginning of every new search tree. When the traversal procedure visits all vertices and edges reachible from the initial vertex (the visited vertices together with tree edges make up a tree), it searches for some unvisited vertex in the graph and resumes the traversal process from that vertex. Before starting a new tree (including the very first tree when cvNextGraphItem is called for the first time) it generates CV_GRAPH_NEW_TREE event. + For unoriented graphs each search tree corresponds to a connected component of the graph. + [CV_GRAPH_NEW_TREE] + + + + + Stop at every already visited vertex during backtracking - returning to already visited vertexes of the traversal tree. + [CV_GRAPH_BACKTRACKING] + + + + + All events are interesting + [CV_GRAPH_OVER] + + + + + All events are interesting + [CV_GRAPH_ALL_ITEMS] + + + + + Flags for PCA operations + + + + + The vectors are stored as rows (i.e. all the components of a certain vector are stored continously) + [CV_PCA_DATA_AS_ROW] + + + + + The vectors are stored as columns (i.e. values of a certain vector component are stored continuously) + [CV_PCA_DATA_AS_COL] + + + + + Use pre-computed average vector + [CV_PCA_USE_AVG] + + + + + cvConvertImage operation flags + + + + + + + + + + flip the image vertically [CV_CVTIMG_FLIP] + + + + + swap red and blue channels [CV_CVTIMG_SWAP_RB] + + + + + PixelConnectivity for LineIterator + + + + + Connectivity 4 (N,S,E,W) + + + + + Connectivity 8 (N,S,E,W,NE,SE,SW,NW) + + + + + The operation flags for cvStereoRectify + + + + + Default value (=0). + the function can shift one of the image in horizontal or vertical direction (depending on the orientation of epipolar lines) in order to maximise the useful image area. + + + + + the function makes the principal points of each camera have the same pixel coordinates in the rectified views. + [CV_CALIB_ZERO_DISPARITY] + + + + + Origin of IplImage + + + + + top-left origin [IPL_ORIGIN_TL (0)] + + + + + bottom-left origin (Windows bitmaps style) [IPL_ORIGIN_BL (1)] + + + + + circle structure retrieved from cvHoughCircle + + + + + Center coordinate of the circle + + + + + Radius + + + + + Constructor + + center + radius + + + + Specifies whether this object contains the same members as the specified Object. + + The Object to test. + This method returns true if obj is the same type as this object and has the same members as this object. + + + + Compares two CvPoint objects. The result specifies whether the members of each object are equal. + + A Point to compare. + A Point to compare. + This operator returns true if the members of left and right are equal; otherwise, false. + + + + Compares two CvPoint objects. The result specifies whether the members of each object are unequal. + + A Point to compare. + A Point to compare. + This operator returns true if the members of left and right are unequal; otherwise, false. + + + + Specifies whether this object contains the same members as the specified Object. + + The Object to test. + This method returns true if obj is the same type as this object and has the same members as this object. + + + + Returns a hash code for this object. + + An integer value that specifies a hash value for this object. + + + + Converts this object to a human readable string. + + A string that represents this object. + + + + Structure describing a single contour convexity detect + + + + + sizeof(CvConvexityDefect) + + + + + Point of the contour where the defect begins + + + + + Point of the contour where the defect ends + + + + + The farthest from the convex hull point within the defect + + + + + Distance between the farthest point and the convex hull + + + + + Constructor + + + + + + + + + Rectangle structure retrieved from cvHaarDetectObjects + + + + + Bounding rectangle for the object (average rectangle of a group) + + + + + Number of neighbor rectangles in the group + + + + + Constructor + + Bounding rectangle for the object (average rectangle of a group) + number of neighbor rectangles in the group + + + + Specifies whether this object contains the same members as the specified Object. + + The Object to test. + This method returns true if obj is the same type as this object and has the same members as this object. + + + + Compares two CvPoint objects. The result specifies whether the members of each object are equal. + + A Point to compare. + A Point to compare. + This operator returns true if the members of left and right are equal; otherwise, false. + + + + Compares two CvPoint objects. The result specifies whether the members of each object are unequal. + + A Point to compare. + A Point to compare. + This operator returns true if the members of left and right are unequal; otherwise, false. + + + + implicit cast to CvRect (for backward compatibility) + + + + + + + Specifies whether this object contains the same members as the specified Object. + + The Object to test. + This method returns true if obj is the same type as this object and has the same members as this object. + + + + Returns a hash code for this object. + + An integer value that specifies a hash value for this object. + + + + Converts this object to a human readable string. + + A string that represents this object. + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Various MSER algorithm parameters + + + + + Native structure field + + + + + delta, in the code, it compares (size_{i}-size_{i-delta})/size_{i-delta} + + + + + prune the area which bigger than max_area + + + + + prune the area which smaller than min_area + + + + + prune the area have simliar size to its children + + + + + trace back to cut off mser with diversity < min_diversity + + + + + for color image, the evolution steps + + + + + the area threshold to cause re-initialize + + + + + ignore too small margin + + + + + the aperture size for edge blur + + + + + Creates MSER parameters + + + + + Creates MSER parameters + + delta, in the code, it compares (size_{i}-size_{i-delta})/size_{i-delta} + prune the area which smaller than min_area + prune the area which bigger than max_area + prune the area have simliar size to its children + trace back to cut off mser with diversity < min_diversity + for color image, the evolution steps + the area threshold to cause re-initialize + ignore too small margin + the aperture size for edge blur + + + + Creates a new object that is a copy of the current instance. + + A new object that is a copy of this instance. + + + + + + + + + + + + + + + + + + + + + + + + Constructor + + + + + + + + Specifies whether this object contains the same members as the specified Object. + + The Object to test. + This method returns true if obj is the same type as this object and has the same members as this object. + + + + Compares two CvPoint objects. The result specifies whether the members of each object are equal. + + A Point to compare. + A Point to compare. + This operator returns true if the members of left and right are equal; otherwise, false. + + + + Compares two CvPoint objects. The result specifies whether the members of each object are unequal. + + A Point to compare. + A Point to compare. + This operator returns true if the members of left and right are unequal; otherwise, false. + + + + Specifies whether this object contains the same members as the specified Object. + + The Object to test. + This method returns true if obj is the same type as this object and has the same members as this object. + + + + Returns a hash code for this object. + + An integer value that specifies a hash value for this object. + + + + Converts this object to a human readable string. + + A string that represents this object. + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Specifies whether this object contains the same members as the specified Object. + + The Object to test. + This method returns true if obj is the same type as this object and has the same members as this object. + + + + Compares two CvPoint objects. The result specifies whether the members of each object are equal. + + A Point to compare. + A Point to compare. + This operator returns true if the members of left and right are equal; otherwise, false. + + + + Compares two CvPoint objects. The result specifies whether the members of each object are unequal. + + A Point to compare. + A Point to compare. + This operator returns true if the members of left and right are unequal; otherwise, false. + + + + implicit cast to CvRect (for backward compatibility) + + + + + + + Specifies whether this object contains the same members as the specified Object. + + The Object to test. + This method returns true if obj is the same type as this object and has the same members as this object. + + + + Returns a hash code for this object. + + An integer value that specifies a hash value for this object. + + + + Converts this object to a human readable string. + + A string that represents this object. + + + + Structure describes the position of the filter in the feature pyramid + + + + + x-coordinate, usually zero-based + + + + + y-coordinate, usually zero-based + + + + + + + + + + sizeof(CvLSVMFilterPosition) + + + + + Constructor + + x-coordinate, usually zero-based + y-coordinate, usually zero-based + + + + + Specifies whether this object contains the same members as the specified Object. + + The Object to test. + This method returns true if obj is the same type as this object and has the same members as this object. + + + + Compares two CvLSVMFilterPosition objects. + + A Point to compare. + A Point to compare. + This operator returns true if the X, Y and L values of left and right are equal; otherwise, false. + + + + Compares two CvPoint objects. + + A Point to compare. + A Point to compare. + + + + + Specifies whether this object contains the same members as the specified Object. + + The Object to test. + This method returns true if obj is the same type as this object and has the same members as this object. + + + + Returns a hash code for this object. + + An integer value that specifies a hash value for this object. + + + + Converts this object to a human readable string. + + A string that represents this object. + + + + structure contains the bounding box and confidence level for detected object + + + + + + + + + + + + + + + + + + + + + + Specifies whether this object contains the same members as the specified Object. + + The Object to test. + This method returns true if obj is the same type as this object and has the same members as this object. + + + + Compares two CvPoint objects. The result specifies whether the members of each object are equal. + + A Point to compare. + A Point to compare. + This operator returns true if the members of left and right are equal; otherwise, false. + + + + Compares two CvPoint objects. The result specifies whether the members of each object are unequal. + + A Point to compare. + A Point to compare. + This operator returns true if the members of left and right are unequal; otherwise, false. + + + + Specifies whether this object contains the same members as the specified Object. + + The Object to test. + This method returns true if obj is the same type as this object and has the same members as this object. + + + + Returns a hash code for this object. + + An integer value that specifies a hash value for this object. + + + + Converts this object to a human readable string. + + A string that represents this object. + + + + Connected component + + + + + Empty constructor + + + + + Constructor + + struct CvConnectedComp* + + + + Creates a CvConnectedComp from a pointer + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + sizeof(CvConnectedComp) + + + + + area of the connected component + + + + + average color of the connected component + + + + + ROI of the component + + + + + optional component boundary (the contour might have child contours corresponding to the holes) + + + + + CvcontourScanner + + + + + Track whether Dispose has been called + + + + + Initializes contour scanning process + + The source 8-bit single channel binary image. + Container of the retrieved contours. + + + + Initializes contour scanning process + + The source 8-bit single channel binary image. + Container of the retrieved contours. + Size of the sequence header, >=sizeof(CvChain) if method=CV_CHAIN_CODE, and >=sizeof(CvContour) otherwise. + + + + Initializes contour scanning process + + The source 8-bit single channel binary image. + Container of the retrieved contours. + Size of the sequence header, >=sizeof(CvChain) if method=CV_CHAIN_CODE, and >=sizeof(CvContour) otherwise. + Retrieval mode; see cvFindContours. + + + + Initializes contour scanning process + + The source 8-bit single channel binary image. + Container of the retrieved contours. + Size of the sequence header, >=sizeof(CvChain) if method=CV_CHAIN_CODE, and >=sizeof(CvContour) otherwise. + Retrieval mode; see cvFindContours. + Approximation method. It has the same meaning as in cvFindContours, but CV_LINK_RUNS can not be used here. + + + + Initializes contour scanning process + + The source 8-bit single channel binary image. + Container of the retrieved contours. + Size of the sequence header, >=sizeof(CvChain) if method=CV_CHAIN_CODE, and >=sizeof(CvContour) otherwise. + Retrieval mode; see cvFindContours. + Approximation method. It has the same meaning as in cvFindContours, but CV_LINK_RUNS can not be used here. + ROI offset; see cvFindContours. + CvContourScanner + + + + Initializes contour scanning process + + The source 8-bit single channel binary image. + Container of the retrieved contours. + Size of the sequence header, >=sizeof(CvChain) if method=CV_CHAIN_CODE, and >=sizeof(CvContour) otherwise. + Retrieval mode; see cvFindContours. + Approximation method. It has the same meaning as in cvFindContours, but CV_LINK_RUNS can not be used here. + ROI offset; see cvFindContours. + CvContourScanner + + + + Initializes contour scanning process + + + + + Initializes contour scanning process + + The source 8-bit single channel binary image. + Container of the retrieved contours. + CvContourScanner + + + + Initializes contour scanning process + + The source 8-bit single channel binary image. + Container of the retrieved contours. + Size of the sequence header, >=sizeof(CvChain) if method=CV_CHAIN_CODE, and >=sizeof(CvContour) otherwise. + CvContourScanner + + + + Initializes contour scanning process + + The source 8-bit single channel binary image. + Container of the retrieved contours. + Size of the sequence header, >=sizeof(CvChain) if method=CV_CHAIN_CODE, and >=sizeof(CvContour) otherwise. + Retrieval mode; see cvFindContours. + CvContourScanner + + + + Initializes contour scanning process + + The source 8-bit single channel binary image. + Container of the retrieved contours. + Size of the sequence header, >=sizeof(CvChain) if method=CV_CHAIN_CODE, and >=sizeof(CvContour) otherwise. + Retrieval mode; see cvFindContours. + Approximation method. It has the same meaning as in cvFindContours, but CV_LINK_RUNS can not be used here. + CvContourScanner + + + + Initializes contour scanning process + + The source 8-bit single channel binary image. + Container of the retrieved contours. + Size of the sequence header, >=sizeof(CvChain) if method=CV_CHAIN_CODE, and >=sizeof(CvContour) otherwise. + Retrieval mode; see cvFindContours. + Approximation method. It has the same meaning as in cvFindContours, but CV_LINK_RUNS can not be used here. + ROI offset; see cvFindContours. + CvContourScanner + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + Finishes scanning process + + + + + + Finds next contour in the image + + + + + Replaces retrieved contour + + Substituting contour. + + + + Returns an enumerator that iterates through the collection. + + A System.Collections.Generic.IEnumerator<T> that can be used to iterate through the collection. + + + + + + + + + + Basic element of the file storage - scalar or collection + + + + + Initializes from pointer + + struct CvFileNode* + + + + Initializes from pointer + + struct CvFileNode* + + + + sizeof(CvFileNode) + + + + + Type of file node + + + + + Dataの先頭8バイトを返す + + + + + scalar floating-point number + + + + + scalar integer number + + + + + text string + + + + + sequence (ordered collection of file nodes) + + + + + map (collection of named file nodes) + + + + + File node name + + + + + Returns name of file node + + name of the file node or null + + + + Retrieves integer value from file node + + integer that is represented by the file node. If the file node is null, default_value is returned. + + + + Retrieves integer value from file node + + The value that is returned if node is null. + integer that is represented by the file node. If the file node is null, defaultValue is returned. + + + + Retrieves floating-point value from file node + + returns floating-point value that is represented by the file node. If the file node is null, default_value is returned. + + + + Retrieves floating-point value from file node + + The value that is returned if node is null. + returns floating-point value that is represented by the file node. If the file node is null, defaultValue is returned. + + + + Retrieves text string from file node + + returns text string that is represented by the file node. + + + + Retrieves text string from file node + + The value that is returned if node is null. + returns text string that is represented by the file node. If the file node is null, defaultValue is returned. + + + + File Storage + + + + + Track whether Dispose has been called + + + + + Opens file storage for reading or writing data + + Name of the file associated with the storage. + Memory storage used for temporary data and for storing dynamic structures, such as CvSeq or CvGraph. If it is null, a temporary memory storage is created and used. + + + + + Opens file storage for reading or writing data + + Name of the file associated with the storage. + Memory storage used for temporary data and for storing dynamic structures, such as CvSeq or CvGraph. If it is null, a temporary memory storage is created and used. + + + + + + Initializes from pointer + + struct CvFileStorage* + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + Ends writing a structure + + + + + Finds node in the map or file storage + + The parent map. If it is null, the function searches a top-level node. If both map and key are nulls, the function returns the root file node - a map that contains top-level nodes. + Unique pointer to the node name, retrieved with cvGetHashedKey. + + + + + Finds node in the map or file storage + + The parent map. If it is null, the function searches a top-level node. If both map and key are nulls, the function returns the root file node - a map that contains top-level nodes. + Unique pointer to the node name, retrieved with cvGetHashedKey. + Flag that specifies, whether an absent node should be added to the map, or not. + + + + + Finds node in the map or file storage + + The parent map. If it is null, the function searches in all the top-level nodes (streams), starting from the first one. + The file node name. + + + + + Retrieves one of top-level nodes of the file storage + + One of top-level file nodes + + + + Retrieves one of top-level nodes of the file storage + + Zero-based index of the stream. In most cases, there is only one stream in the file, however there can be several. + One of top-level file nodes + + + + Returns a unique pointer for given name + + Literal node name. + The unique pointer for each particular file node name. + + + + Returns a unique pointer for given name + + Literal node name. + Length of the name (if it is known a priori), or -1 if it needs to be calculated. + The unique pointer for each particular file node name. + + + + Decodes object and returns pointer to it + + + The root object node. + + + + + Finds object and decodes it + + + The parent map. If it is null, the function searches a top-level node. + The node name. + + + + + Finds file node and returns its value + + The parent map. If it is null, the function searches a top-level node. + The node name. + + + + + Finds file node and returns its value + + The parent map. If it is null, the function searches a top-level node. + The node name. + The value that is returned if the file node is not found. + + + + + Reads multiple numbers + + + The file node (a sequence) to read numbers from. + Reference to the destination array. + Specification of each array element. It has the same format as in cvWriteRawData. + + + + Initializes file node sequence reader + + + The sequence reader. Initialize it with cvStartReadRawData. + The number of elements to read. + Destination array. + Specification of each array element. It has the same format as in cvWriteRawData. + + + + Finds file node and returns its value + + The parent map. If it is null, the function searches a top-level node. + The node name. + + + + + Finds file node and returns its value + + The parent map. If it is null, the function searches a top-level node. + The node name. + The value that is returned if the file node is not found. + + + + + Finds file node and returns its value + + The parent map. If it is null, the function searches a top-level node. + The node name. + + + + + Finds file node and returns its value + + The parent map. If it is null, the function searches a top-level node. + The node name. + The value that is returned if the file node is not found. + + + + + Starts the next stream + + + + + Initializes file node sequence reader + + The file node (a sequence) to read numbers from. + Output reference to the sequence reader. + + + + Starts writing a new structure + + Name of the written structure. The structure can be accessed by this name when the storage is read. + A combination one of the NodeType flags + + + + Starts writing a new structure + + Name of the written structure. The structure can be accessed by this name when the storage is read. + A combination one of the NodeType flags + Optional parameter - the object type name. + In case of XML it is written as type_id attribute of the structure opening tag. + In case of YAML it is written after a colon following the structure name. Mainly it comes with user objects. + When the storage is read, the encoded type name is used to determine the object type. + + + + Writes user object + + Name, of the written object. Should be null if and only if the parent structure is a sequence. + Pointer to the object. + + + + Writes user object + + Name, of the written object. Should be null if and only if the parent structure is a sequence. + Pointer to the object. + The attributes of the object. They are specific for each particular type. + + + + Writes comment + + The written comment, single-line or multi-line. + + + + Writes comment + + The written comment, single-line or multi-line. + If true, the function tries to put the comment in the end of current line. + If the flag is false, if the comment is multi-line, or if it does not fit in the end of the current line, the comment starts from a new line. + + + + Writes file node to another file storage + + New name of the file node in the destination file storage. To keep the existing name, use cvGetFileNodeName(node). + The written node + If the written node is a collection and this parameter is true, no extra level of hierarchy is created. + Instead, all the elements of node are written into the currently written structure. + Of course, map elements may be written only to map, and sequence elements may be written only to sequence. + + + + Writes an integer value + + Name of the written value. Should be NULL if and only if the parent structure is a sequence. + The written value. + + + + Writes multiple numbers + + Type of the elements in src + Written array + Format + + + + Writes a floating-point value + + Name of the written value. Should be null if and only if the parent structure is a sequence. + The written value. + + + + Writes a text string + + Name of the written string. Should be null if and only if the parent structure is a sequence. + The written text string. + + + + Writes a text string + + Name of the written string. Should be null if and only if the parent structure is a sequence. + The written text string. + If true, the written string is put in quotes, regardless of whether they are required or not. + Otherwise, if the flag is false, quotes are used only when they are required (e.g. when the string starts with a digit or contains spaces). + + + + Cascade or tree of stage classifiers + + + + + Track whether Dispose has been called + + + + + Initializes from native pointer + + + + + + Initializes by native pointer + + + If true, this object will be disposed by GC automatically. + + + + Loads object from file (cvLoad) + + File name (xml/yaml) + + + + + Loads a trained cascade classifier from file or the classifier database embedded in OpenCV (cvLoadHaarClassifierCascade) + + Name of directory containing the description of a trained cascade classifier. + Original size of objects the cascade has been trained on. Note that it is not stored in the cascade and therefore must be specified separately. + The function is obsolete. Nowadays object detection classifiers are stored in XML or YAML files, rather than in directories. To load cascade from a file, use cvLoad function. + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + sizeof(CvHaarClassifierCascade) + + + + + Signature + + + + + Number of stages + + + + + Original object size (the cascade is trained for) + + + + + Current object size + + + + + Current scale + + + + + Array of stage classifiers + + + + + Hidden optimized representation of the cascade, created by cvSetImagesForHaarClassifierCascade + + + + + Finds rectangular regions in the given image that are likely to contain objects the cascade has been trained for and returns those regions as a sequence of rectangles. + + Image to detect objects in. + Memory storage to store the resultant sequence of the object candidate rectangles. + + + + + Finds rectangular regions in the given image that are likely to contain objects the cascade has been trained for and returns those regions as a sequence of rectangles. + + Image to detect objects in. + Memory storage to store the resultant sequence of the object candidate rectangles. + The factor by which the search window is scaled between the subsequent scans, for example, 1.1 means increasing window by 10%. + + + + + Finds rectangular regions in the given image that are likely to contain objects the cascade has been trained for and returns those regions as a sequence of rectangles. + + Image to detect objects in. + Memory storage to store the resultant sequence of the object candidate rectangles. + The factor by which the search window is scaled between the subsequent scans, for example, 1.1 means increasing window by 10%. + Minimum number (minus 1) of neighbor rectangles that makes up an object. All the groups of a smaller number of rectangles than min_neighbors-1 are rejected. If min_neighbors is 0, the function does not any grouping at all and returns all the detected candidate rectangles, which may be useful if the user wants to apply a customized grouping procedure. + + + + + Finds rectangular regions in the given image that are likely to contain objects the cascade has been trained for and returns those regions as a sequence of rectangles. + + Image to detect objects in. + Memory storage to store the resultant sequence of the object candidate rectangles. + The factor by which the search window is scaled between the subsequent scans, for example, 1.1 means increasing window by 10%. + Minimum number (minus 1) of neighbor rectangles that makes up an object. All the groups of a smaller number of rectangles than min_neighbors-1 are rejected. If min_neighbors is 0, the function does not any grouping at all and returns all the detected candidate rectangles, which may be useful if the user wants to apply a customized grouping procedure. + Mode of operation. Currently the only flag that may be specified is CV_HAAR_DO_CANNY_PRUNING. If it is set, the function uses Canny edge detector to reject some image regions that contain too few or too much edges and thus can not contain the searched object. The particular threshold values are tuned for face detection and in this case the pruning speeds up the processing. + + + + + Finds rectangular regions in the given image that are likely to contain objects the cascade has been trained for and returns those regions as a sequence of rectangles. + + Image to detect objects in. + Memory storage to store the resultant sequence of the object candidate rectangles. + The factor by which the search window is scaled between the subsequent scans, for example, 1.1 means increasing window by 10%. + Minimum number (minus 1) of neighbor rectangles that makes up an object. All the groups of a smaller number of rectangles than min_neighbors-1 are rejected. If min_neighbors is 0, the function does not any grouping at all and returns all the detected candidate rectangles, which may be useful if the user wants to apply a customized grouping procedure. + Mode of operation. Currently the only flag that may be specified is CV_HAAR_DO_CANNY_PRUNING. If it is set, the function uses Canny edge detector to reject some image regions that contain too few or too much edges and thus can not contain the searched object. The particular threshold values are tuned for face detection and in this case the pruning speeds up the processing. + Minimum window size. By default, it is set to the size of samples the classifier has been trained on (~20×20 for face detection). + + + + + + Runs cascade of boosted classifier at given image location + + Top-left corner of the analyzed region. Size of the region is a original window size scaled by the currenly set scale. The current window size may be retrieved using cvGetHaarClassifierCascadeWindowSize function. + positive value if the analyzed rectangle passed all the classifier stages (it is a candidate) and zero or negative value otherwise. + + + + Runs cascade of boosted classifier at given image location + + Top-left corner of the analyzed region. Size of the region is a original window size scaled by the currenly set scale. The current window size may be retrieved using cvGetHaarClassifierCascadeWindowSize function. + Initial zero-based index of the cascade stage to start from. The function assumes that all the previous stages are passed. This feature is used internally by cvHaarDetectObjects for better processor cache utilization. + positive value if the analyzed rectangle passed all the classifier stages (it is a candidate) and zero or negative value otherwise. + + + + Assigns images to the hidden cascade + + Integral (sum) single-channel image of 32-bit integer format. This image as well as the two subsequent images are used for fast feature evaluation and brightness/contrast normalization. They all can be retrieved from input 8-bit or floating point single-channel image using The function cvIntegral. + Square sum single-channel image of 64-bit floating-point format. + Tilted sum single-channel image of 32-bit integer format. + Window scale for the cascade. If scale=1, original window size is used (objects of that size are searched) - the same size as specified in cvLoadHaarClassifierCascade (24x24 in case of "<default_face_cascade>"), if scale=2, a two times larger window is used (48x48 in case of default face cascade). While this will speed-up search about four times, faces smaller than 48x48 cannot be detected. + + + + Muti-dimensional histogram + + + + + Track whether Dispose has been called + + + + + Creates an empty histogram + + + + + Creates a histogram from pointer + + + + + Creates a histogram of the specified size and returns the pointer to the created histogram. + + Number of histogram dimensions. + Histogram representation format. + + + + + Creates a histogram of the specified size and returns the pointer to the created histogram. + + Number of histogram dimensions. + Histogram representation format. + Array of ranges for histogram bins. Its meaning depends on the uniform parameter value. The ranges are used for when histogram is calculated or backprojected to determine, which histogram bin corresponds to which value/tuple of values from the input image[s]. + + + + + Creates a histogram of the specified size and returns the pointer to the created histogram. + + Number of histogram dimensions. + Histogram representation format. + Array of ranges for histogram bins. Its meaning depends on the uniform parameter value. The ranges are used for when histogram is calculated or backprojected to determine, which histogram bin corresponds to which value/tuple of values from the input image[s]. + Uniformity flag. + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + sizeof(CvHistogram) + + + + + Histogram representation format + + + + + Histogram bins. + if Type == Array then returns CvMatND, else if Type == Sparse then CvSparseMat + + + + + Histogram bins. + if Type == Array then returns CvMatND, else if Type == Sparse then CvSparseMat + + + + + Number of histogram dimensions. + + + + + For uniform histograms (thresh). + + + + + For non-uniform histograms. + + + + + Calculates the histogram of one single-channel image. + The elements of a tuple that is used to increment a histogram bin are taken at the same location from the corresponding input images. + + Source image. + + + + Calculates the histogram of one single-channel image. + The elements of a tuple that is used to increment a histogram bin are taken at the same location from the corresponding input images. + + Source image. + Accumulation flag. If it is set, the histogram is not cleared in the beginning. This feature allows user to compute a single histogram from several images, or to update the histogram online. + + + + Calculates the histogram of one single-channel image. + The elements of a tuple that is used to increment a histogram bin are taken at the same location from the corresponding input images. + + Source image. + Accumulation flag. If it is set, the histogram is not cleared in the beginning. This feature allows user to compute a single histogram from several images, or to update the histogram online. + The operation mask, determines what pixels of the source images are counted. + + + + Calculates the histogram of single-channel images. + The elements of a tuple that is used to increment a histogram bin are taken at the same location from the corresponding input images. + + Source images, all are of the same size and type. + + + + Calculates the histogram of single-channel images. + The elements of a tuple that is used to increment a histogram bin are taken at the same location from the corresponding input images. + + Source images, all are of the same size and type. + Accumulation flag. If it is set, the histogram is not cleared in the beginning. This feature allows user to compute a single histogram from several images, or to update the histogram online. + + + + Calculates the histogram of single-channel images. + The elements of a tuple that is used to increment a histogram bin are taken at the same location from the corresponding input images. + + Source images, all are of the same size and type. + Accumulation flag. If it is set, the histogram is not cleared in the beginning. This feature allows user to compute a single histogram from several images, or to update the histogram online. + The operation mask, determines what pixels of the source images are counted. + + + + Calculates the histogram of one single-channel image. + The elements of a tuple that is used to increment a histogram bin are taken at the same location from the corresponding input images. + + A Source image (though, you may pass CvMat** as well). + + + + Calculates the histogram of one single-channel image. + The elements of a tuple that is used to increment a histogram bin are taken at the same location from the corresponding input images. + + A Source image (though, you may pass CvMat** as well). + Accumulation flag. If it is set, the histogram is not cleared in the beginning. This feature allows user to compute a single histogram from several images, or to update the histogram online. + + + + Calculates the histogram of one single-channel image. + The elements of a tuple that is used to increment a histogram bin are taken at the same location from the corresponding input images. + + A Source image (though, you may pass CvMat** as well). + Accumulation flag. If it is set, the histogram is not cleared in the beginning. This feature allows user to compute a single histogram from several images, or to update the histogram online. + The operation mask, determines what pixels of the source images are counted. + + + + Calculates the histogram of single-channel images. + The elements of a tuple that is used to increment a histogram bin are taken at the same location from the corresponding input images. + + Source images (though, you may pass CvMat** as well), all are of the same size and type. + + + + Calculates the histogram of single-channel images. + The elements of a tuple that is used to increment a histogram bin are taken at the same location from the corresponding input images. + + Source images (though, you may pass CvMat** as well), all are of the same size and type. + Accumulation flag. If it is set, the histogram is not cleared in the beginning. This feature allows user to compute a single histogram from several images, or to update the histogram online. + + + + Calculates the histogram of single-channel images. + The elements of a tuple that is used to increment a histogram bin are taken at the same location from the corresponding input images. + + Source images (though, you may pass CvMat** as well), all are of the same size and type. + Accumulation flag. If it is set, the histogram is not cleared in the beginning. This feature allows user to compute a single histogram from several images, or to update the histogram online. + The operation mask, determines what pixels of the source images are counted. + + + + Calculates back projection + + Source images (though you may pass CvMat** as well), all are of the same size and type + Destination back projection image of the same type as the source images. + + + + + Calculates back projection + + Source images (though you may pass CvMat** as well), all are of the same size and type + Destination back projection image of the same type as the source images. + + + + + Locates a template within image by histogram comparison + + Source images (though you may pass CvMat** as well), all are of the same size and type + Destination image. + Size of patch slid though the source images. + Compasion method, passed to cvCompareHist (see description of that function). + + + + + Locates a template within image by histogram comparison + + Source images (though you may pass CvMat** as well), all are of the same size and type + Destination image. + Size of patch slid though the source images. + Compasion method, passed to cvCompareHist (see description of that function). + Normalization factor for histograms, will affect normalization scale of destination image, pass 1. if unsure. + + + + + Locates a template within image by histogram comparison + + Source images (though you may pass CvMat** as well), all are of the same size and type + Destination image. + Size of patch slid though the source images. + Compasion method, passed to cvCompareHist (see description of that function). + + + + + Locates a template within image by histogram comparison + + Source images (though you may pass CvMat** as well), all are of the same size and type + Destination image. + Size of patch slid though the source images. + Compasion method, passed to cvCompareHist (see description of that function). + Normalization factor for histograms, will affect normalization scale of destination image, pass 1. if unsure. + + + + + Calculates bayesian probabilistic histograms + + + + + + + Divides one histogram by another. + + first histogram (the divisor). + second histogram. + destination histogram. + + + + Divides one histogram by another. + + first histogram (the divisor). + second histogram. + destination histogram. + scale factor for the destination histogram. + + + + Sets all histogram bins to 0 in case of dense histogram and removes all histogram bins in case of sparse array. + + + + + Compares two dense histograms. + + target histogram + Comparison method. + + + + + Makes a copy of the histogram. + If the second histogram dst is null, a new histogram of the same size as src is created. + Otherwise, both histograms must have equal types and sizes. + Then the function copies the source histogram bins values to destination histogram and sets the same bin values ranges as in src. + + Reference to destination histogram. + + + + Returns pointer to histogram bin. + + 1st index of the bin. + + + + + Returns pointer to histogram bin. + + 1st index of the bin. + 2rd index of the bin. + + + + + Returns pointer to histogram bin. + + 1st index of the bin. + 2nd index of the bin. + 3rd index of the bin. + + + + + Returns pointer to histogram bin. + + Indices of the bin. + + + + + Finds minimum and maximum histogram bins. + + The minimum value of the histogram. + The maximum value of the histogram. + + + + Finds minimum and maximum histogram bins. + + The minimum value of the histogram. + The maximum value of the histogram. + The array of coordinates for minimum. + The array of coordinates for maximum. + + + + Normalizes the histogram bins by scaling them, such that the sum of the bins becomes equal to factor. + + Threshold level. + + + + Queries value of histogram bin. + + 1st index of the bin. + + + + + Queries value of histogram bin. + + 1st index of the bin. + 2nd index of the bin. + + + + + Queries value of histogram bin. + + 1st index of the bin. + 2nd index of the bin. + 3rd index of the bin. + + + + + Queries value of histogram bin. + + Array of indices. + + + + + Sets bounds of histogram bins + + Array of bin ranges arrays. + + + + Sets bounds of histogram bins + + Array of bin ranges arrays. + Uniformity flag. + + + + Clears histogram bins that are below the specified threshold. + + Threshold level. + + + + Kalman filter state + + + + + Track whether Dispose has been called + + + + + Allocates Kalman filter structure + + dimensionality of the state vector + dimensionality of the measurement vector + + + + + Allocates Kalman filter structure + + dimensionality of the state vector + dimensionality of the measurement vector + dimensionality of the control vector + + + + + Initializes by native pointer + + + + + + ポインタと自動解放の可否を指定して初期化 + + struct CvMemStorage* + 自動的にGCで解放してよいかどうか + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + sizeof(CvKalman) + + + + + Number of measurement vector dimensions + + + + + Number of state vector dimensions + + + + + Number of control vector dimensions + + + + + Predicted state (x'(k)): x(k)=A*x(k-1)+B*u(k) + + + + + Corrected state (x(k)): x(k)=x'(k)+K(k)*(z(k)-H*x'(k)) + + + + + State transition matrix (A) + + + + + Control matrix (B) (it is not used if there is no control + + + + + Measurement matrix (H) + + + + + Process noise covariance matrix (Q) + + + + + Measurement noise covariance matrix (R) + + + + + Priori error estimate covariance matrix (P'(k)): P'(k)=A*P(k-1)*At + Q) + + + + + Kalman gain matrix (K(k)): K(k)=P'(k)*Ht*inv(H*P'(k)*Ht+R) + + + + + Posteriori error estimate covariance matrix (P(k)): P(k)=(I-K(k)*H)*P'(k) + + + + + Temporary matrix 1 + + + + + Temporary matrix 2 + + + + + Temporary matrix 3 + + + + + Temporary matrix 4 + + + + + Temporary matrix 5 + + + + + state_pre->data.fl + + + + + state_post->data.fl + + + + + transition_matrix->data.fl + + + + + measurement_matrix->data.fl + + + + + measurement_noise_cov->data.fl + + + + + process_noise_cov->data.fl + + + + + gain->data.fl + + + + + error_cov_pre->data.fl + + + + + error_cov_post->data.fl + + + + + temp1->data.fl + + + + + temp2->data.fl + + + + + Adjusts model state (cvKalmanCorrect). + + CvMat containing the measurement vector. + The function stores adjusted state at kalman->state_post and returns it on output. + + + + Adjusts model state + + CvMat containing the measurement vector. + The function stores adjusted state at kalman->state_post and returns it on output. + + + + Estimates subsequent model state (cvKalmanPredict). + + The function returns the estimated state. + + + + Estimates subsequent model state (cvKalmanPredict). + + Control vector (uk), should be null iff there is no external control (control_params=0). + The function returns the estimated state. + + + + Estimates subsequent model state + + The function returns the estimated state. + + + + Estimates subsequent model state + + Control vector (uk), should be null iff there is no external control (control_params=0). + The function returns the estimated state. + + + + Sequence reader + + + + + Default constructor + + + + + sizeof(CvSeqReader) + + + + + size of sequence header + + + + + Sequence, beign read + + + + + current block + + + + + pointer to element be read next + + + + + pointer to the beginning of block + + + + + pointer to the End of block + + + + + seq->first->start_index + + + + + pointer to the End of block + + + + + Gets/Sets the current reader position + + + + + Returns the current reader position (cvGetSeqReaderPos). + + the current reader position + + + + 次のシーケンスへ (CV_NEXT_SEQ_ELEM相当) + + + + + + 前のシーケンスへ (CV_PREV_SEQ_ELEM相当) + + + + + + シーケンスの要素を一つ読みだして、読み出しポインタを次へ1つ移動させる (CV_READ_SEQ_ELEM相当) + + + + + シーケンスの前の要素を一つ読みだして、読み出しポインタを前へ1つ移動させる (CV_REV_READ_SEQ_ELEM相当) + + + + + Moves the reader to specified position (cvSetSeqReaderPos). + + The destination position. If the positioning mode is used (see the next parameter) the actual position will be index mod reader->seq->total. + + + + Moves the reader to specified position (cvSetSeqReaderPos). + + The destination position. If the positioning mode is used (see the next parameter) the actual position will be index mod reader->seq->total. + If it is true, then index is a relative to the current position. + + + + The structure for block matching stereo correspondence algorithm + + + + + Track whether Dispose has been called + + + + + Creates block matching stereo correspondence structure (CreateStereoBMState) + + + + + Creates block matching stereo correspondence structure (CreateStereoBMState) + + ID of one of the pre-defined parameter sets. Any of the parameters can be overridden after creating the structure. + + + + Creates block matching stereo correspondence structure (CreateStereoBMState) + + ID of one of the pre-defined parameter sets. Any of the parameters can be overridden after creating the structure. + The number of disparities. If the parameter is 0, it is taken from the preset, otherwise the supplied value overrides the one from preset. + + + + Initializes from native pointer + + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + sizeof(CvStereoBMState) + + + + + pre filters' type (0 for now) + + + + + pre filters' size (~5x5..21x21) + + + + + pre filters' cap (up to ~31) + + + + + window size of correspondence using Sum of Absolute Difference(SAD) (Could be 5x5..21x21) + + + + + minimum disparity of correspondence using Sum of Absolute Difference(SAD) (=0) + + + + + maximum disparity - minimum disparity of correspondence using Sum of Absolute Difference(SAD) + + + + + post filters' areas with no texture are ignored + + + + + filter out pixels if there are other close matches with different disparity + + + + + Disparity variation window (not used) + + + + + Acceptable range of variation in window (not used) + + + + + Computes the disparity map using block matching algorithm (cvFindStereoCorrespondenceBM) + + The left single-channel, 8-bit image. + The right image of the same size and the same type. + The output single-channel 16-bit signed disparity map of the same size as input images. Its elements will be the computed disparities, multiplied by 16 and rounded to integer's. + + + + All the keys (names) of elements in the read file storage are stored in the hash to speed up the lookup operations + + + + + Initializes from pointer + + struct CvStringHashNode* + + + + sizeof(CvStringHashNode) + + + + + + + + + + + + + + + + + + + + The structure which can be used as a structuring element in the morphological operations. + + + + + Track whether Dispose has been called + + + + + Allocates and fills the structure IplConvKernel, which can be used as a structuring element in the morphological operations. + + Number of columns in the structuring element. + Number of rows in the structuring element. + Relative horizontal offset of the anchor point. + Relative vertical offset of the anchor point. + Shape of the structuring element. + + + + + Allocates and fills the structure IplConvKernel, which can be used as a structuring element in the morphological operations. + + Number of columns in the structuring element. + Number of rows in the structuring element. + Relative horizontal offset of the anchor point. + Relative vertical offset of the anchor point. + Shape of the structuring element. + Pointer to the structuring element data, a plane array, representing row-by-row scanning of the element matrix. + Non-zero values indicate points that belong to the element. If the pointer is null, then all values are considered non-zero, + that is, the element is of a rectangular shape. This parameter is considered only if the shape is CV_SHAPE_CUSTOM . + + + + + Initialize by a native pointer (IplConvKernel*) + + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + sizeof(IplConvKernel) + + + + + + + + + + + + + + + + + + + + + + + + + int* + + + + + + + + + + The structure for graph cuts-based stereo correspondence algorithm + + + + + Track whether Dispose has been called + + + + + Creates the state of graph cut-based stereo correspondence algorithm (cvCreateStereoGCState) + + The number of disparities. The disparity search range will be state->minDisparity ≤ disparity < state->minDisparity + state->numberOfDisparities + Maximum number of iterations. On each iteration all possible (or reasonable) alpha-expansions are tried. The algorithm may terminate earlier if it could not find an alpha-expansion that decreases the overall cost function value. + + + + Initializes from native pointer + + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + sizeof(CvStereoGCState) + + + + + threshold for piece-wise linear data cost function (5 by default) + + + + + radius for smoothness cost function (1 by default; means Potts model) + + + + + parameters for the cost function (usually computed adaptively from the input data) + + + + + parameters for the cost function (usually computed adaptively from the input data) + + + + + parameters for the cost function (usually computed adaptively from the input data) + + + + + + + + + + cost of occlusion (10000 by default) + + + + + minimum disparity of SAD(Sum of Absolute Difference) (0 by default) + + + + + maximum disparity - minimum disparity of SAD(Sum of Absolute Difference) ; defined by user + + + + + number of iterations; defined by user. + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Computes the disparity map using graph cut-based algorithm (cvFindStereoCorrespondenceGC) + + The left single-channel, 8-bit image. + The right image of the same size and the same type. + The optional output single-channel 16-bit signed left disparity map of the same size as input images. + The optional output single-channel 16-bit signed right disparity map of the same size as input images. + + + + Computes the disparity map using graph cut-based algorithm (cvFindStereoCorrespondenceGC) + + The left single-channel, 8-bit image. + The right image of the same size and the same type. + The optional output single-channel 16-bit signed left disparity map of the same size as input images. + The optional output single-channel 16-bit signed right disparity map of the same size as input images. + If the parameter is not zero, the algorithm will start with pre-defined disparity maps. Both dispLeft and dispRight should be valid disparity maps. Otherwise, the function starts with blank disparity maps (all pixels are marked as occlusions). + + + + Font structure + + + + + + + + + + Initializes font structure + + Font name identifier. Only a subset of Hershey fonts are supported now. + Horizontal scale. If equal to 1.0f, the characters have the original width depending on the font type. If equal to 0.5f, the characters are of half the original width. + Vertical scale. If equal to 1.0f, the characters have the original height depending on the font type. If equal to 0.5f, the characters are of half the original height. + + + + Initializes font structure + + Font name identifier. Only a subset of Hershey fonts are supported now. + Horizontal scale. If equal to 1.0f, the characters have the original width depending on the font type. If equal to 0.5f, the characters are of half the original width. + Vertical scale. If equal to 1.0f, the characters have the original height depending on the font type. If equal to 0.5f, the characters are of half the original height. + Approximate tangent of the character slope relative to the vertical line. Zero value means a non-italic font, 1.0f means ≈45° slope, etc. thickness Thickness of lines composing letters outlines. The function cvLine is used for drawing letters. + + + + Initializes font structure + + Font name identifier. Only a subset of Hershey fonts are supported now. + Horizontal scale. If equal to 1.0f, the characters have the original width depending on the font type. If equal to 0.5f, the characters are of half the original width. + Vertical scale. If equal to 1.0f, the characters have the original height depending on the font type. If equal to 0.5f, the characters are of half the original height. + Approximate tangent of the character slope relative to the vertical line. Zero value means a non-italic font, 1.0f means ≈45° slope, etc. thickness Thickness of lines composing letters outlines. The function cvLine is used for drawing letters. + Thickness of the text strokes. + + + + Initializes font structure + + Font name identifier. Only a subset of Hershey fonts are supported now. + Horizontal scale. If equal to 1.0f, the characters have the original width depending on the font type. If equal to 0.5f, the characters are of half the original width. + Vertical scale. If equal to 1.0f, the characters have the original height depending on the font type. If equal to 0.5f, the characters are of half the original height. + Approximate tangent of the character slope relative to the vertical line. Zero value means a non-italic font, 1.0f means ≈45° slope, etc. thickness Thickness of lines composing letters outlines. The function cvLine is used for drawing letters. + Thickness of the text strokes. + Type of the strokes, see cvLine description. + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + sizeof(CvFont) + + + + + ColorFont -> cvScalar(blue_component, green_component, red\_component[, alpha_component]) + + + + + ColorFont -> cvScalar(blue_component, green_component, red\_component[, alpha_component]) + + + + + Font name identifier + + + + + font data and metrics + + + + + + + + + + + + + + + Horizontal scale. If equal to 1.0f, the characters have the original width depending on the font type. If equal to 0.5f, the characters are of half the original width. + + + + + Vertical scale. If equal to 1.0f, the characters have the original height depending on the font type. If equal to 0.5f, the characters are of half the original height. + + + + + slope coefficient: 0 - normal, >0 - italic + + + + + letters thickness + + + + + horizontal interval between letters + + + + + Type of the strokes + + + + + Retrieves width and height of text string + + Input string. + + + + Retrieves width and height of text string + + Input string. + y-coordinate of the baseline relatively to the bottom-most text point. + + + + Quad-edge of planar subdivision + + + + + Initializes from native pointer + + + + + + Creates an instance from native pointer + + + + + + + explicit cast from IntPtr to CvQuadEdge2D + + + + + + + Reads a CvQuadEdge2D instance from CvSeqReader + + + + + + + explicit cast to CvSubdiv2DEdge + + + + + + + Converts to a CvSubdiv2DEdge instance + + + + + + sizeof(CvQuadEdge2D) + + + + + CvSubdiv2DEdge pt[4]; + + + + + CvSubdiv2DEdge next[4]; + + + + + Random number generator + + + + + 64-bit seed value + + + + + Initializes with seed=-1 + + + + + Initializes with specified seed value + + + + + + Initializes with specified seed value + + + + + + Initializes with specified time data + + + + + + explicit cast to ulong + + + + + + + explicit cast to CvRNG + + + + + + + Fills array with random numbers and updates the RNG state + + The destination array. + Distribution type. + The first parameter of distribution. In case of uniform distribution it is the inclusive lower boundary of random numbers range. In case of normal distribution it is the mean value of random numbers. + The second parameter of distribution. In case of uniform distribution it is the exclusive upper boundary of random numbers range. In case of normal distribution it is the standard deviation of random numbers. + + + + Returns 32-bit unsigned integer and updates RNG + + uniformly-distributed random 32-bit unsigned integer + + + + Returns 32-bit unsigned integer and updates RNG + + the exclusive upper boundary of random numbers range. + uniformly-distributed random 32-bit unsigned integer + + + + Returns 32-bit unsigned integer and updates RNG + + the inclusive lower boundary of random numbers range. + the exclusive upper boundary of random numbers range. + + + + + Returns floating-point random number and updates RNG + + uniformly-distributed random floating-point number from 0..1 range (1 is not included). + + + + Continuous sequence block + + + + + Default constructor + + + + + Initializes from native pointer + + CvSeqBlock* + + + + sizeof(CvSeqBlock) + + + + + previous sequence block + + + + + next sequence block + + + + + index of the first element in the block + sequence->first->start_index + + + + + number of elements in the block + + + + + pointer to the first element of the block + + + + + List of free nodes + + + + + Default constructor + + + + + Initializes from native pointer + + struct CvSetElem* + + + + sizeof(CvSetElem) + + + + + if the node is free, the field is a pointer to next free node + + + + + it is true if the node is free and false otherwise + + + + + Planar subdivision + + + + + Default constructor + + + + + Initializes using cvCreateSubdivDelaunay2D + + + + + + + Initializes from native pointer + + struct CvSubdiv2D* + + + + sizeof(CvSubdiv2D) + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Calculates coordinates of Voronoi diagram cells (CalcSubdivVoronoi2D). + + + + + Removes all virtual points (cvClearSubdivVoronoi2D). + + + + + Finds the closest subdivision vertex to given point + + Input point. + + + + + Inserts a single point to Delaunay triangulation (cvSubdivDelaunay2D). + + Inserted point. + + + + + CvSubdiv2Dの初期化 + + + + + + Inserts a single point to Delaunay triangulation (cvSubdiv2DLocate). + + The point to locate. + The output edge the point falls onto or right to. + + + + + Inserts a single point to Delaunay triangulation (cvSubdiv2DLocate). + + The point to locate. + The output edge the point falls onto or right to. + Optional output vertex double pointer the input point coinsides with. + + + + + + + + + + Initializes from native pointer + + + + + + sizeof(CvChain) + + + + + + + + + + Approximates Freeman chain(s) with polygonal curve + + Storage location for the resulting polylines. + + + + + Approximates Freeman chain(s) with polygonal curve + + Storage location for the resulting polylines. + Approximation method. + /// + + + + Approximates Freeman chain(s) with polygonal curve + + Storage location for the resulting polylines. + Approximation method. + Method parameter (not used now). + + + + + Approximates Freeman chain(s) with polygonal curve + + Storage location for the resulting polylines. + Approximation method. + Method parameter (not used now). + Approximates only those contours whose perimeters are not less than minimal_perimeter. Other chains are removed from the resulting structure. + + + + + Approximates Freeman chain(s) with polygonal curve + + Storage location for the resulting polylines. + Approximation method. + Method parameter (not used now). + Approximates only those contours whose perimeters are not less than minimal_perimeter. Other chains are removed from the resulting structure. + If true, the function approximates all chains that access can be obtained to from src_seq by h_next or v_next links. If false, the single chain is approximated. + + + + + Contour data + + + + + Initializes from native pointer + + + + + + sizeof(CvContour) + + + + + + + + + + + + + + + Multi-channel matrix + + + + + Track whether Dispose has been called + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Allocates header for the new matrix and underlying data, and returns a pointer to the created matrix. + + Number of rows in the matrix. + Number of columns in the matrix. + Type of the matrix elements. + + + + + Allocates header for the new matrix and underlying data, and returns a pointer to the created matrix. (cvCreateMatHeader + cvSetData) + + Number of rows in the matrix. + Number of columns in the matrix. + Type of the matrix elements. + Data of elements. The type of the array must be blittable. + + + + + Allocates header for the new matrix and underlying data, and returns a pointer to the created matrix. (cvCreateMatHeader + cvSetData) + + Number of rows in the matrix. + Number of columns in the matrix. + Type of the matrix elements. + Data of elements. The type of the array must be blittable. + + + + + + Allocates header for the new matrix and underlying data, and returns a pointer to the created matrix. (cvCreateMatHeader + cvSetData) + + Number of rows in the matrix. + Number of columns in the matrix. + Type of the matrix elements. + Data pointer of elements. + + + + + Allocates header for the new matrix and underlying data, and returns a pointer to the created matrix. + + Number of rows in the matrix. + Number of columns in the matrix. + Type of the matrix elements. + Initial value of elements + + + + + Loads an image from the specified file and returns the reference to the loaded image as CvMat. + + Name of file to be loaded. + the reference to the loaded image. + + + + Loads an image from the specified file and returns the reference to the loaded image as CvMat. + + Name of file to be loaded. + Specifies colorness and Depth of the loaded image. + the reference to the loaded image. + + + + Initializes by native pointer + + + + + + Initializes by native pointer + + + If true, this matrix will be disposed by GC automatically. + + + + Allocates memory + + If true, this matrix will be disposed by GC automatically. + + + + Creates CvMat from double liner array + + + CvMat (F64C1) + + + + Creates CvMat from float liner array + + + CvMat (F32C1) + + + + Creates CvMat from int liner array + + + CvMat (S32C1) + + + + Creates CvMat from short liner array + + + CvMat (S16C1) + + + + Creates CvMat from byte liner array + + + CvMat (U8C1) + + + + Creates CvMat from generic liner array + + + + + + + + + Creates CvMat from double rectangular array + + + CvMat (F64C1) + + + + Creates CvMat from float rectangular array + + + CvMat (F32C1) + + + + Creates CvMat from int rectangular array + + + CvMat (S32C1) + + + + Creates CvMat from short rectangular array + + + CvMat (S16C1) + + + + Creates CvMat from byte rectangular array + + + CvMat (U8C1) + + + + Creates CvMat from generic rectangular array. + + + + + + + + + 2次元のRectangular Arrayを1次元配列に変換する + + + + + + + + Loads an image from the specified file and returns the reference to the loaded image as CvMat. + + Name of file to be loaded. + the reference to the loaded image. + + + + Loads an image from the specified file and returns the reference to the loaded image as CvMat. + + Name of file to be loaded. + Specifies colorness and Depth of the loaded image. + the reference to the loaded image. + + + + Creates the IplImage instance from image data (using cvDecodeImageM) + + + + + + + + Creates the IplImage instance from System.IO.Stream (using cvDecodeImageM) + + + + + + + + Calculates affine transform from 3 corresponding points (cvGetAffineTransform). + + Coordinates of 3 triangle vertices in the source image. + Coordinates of the 3 corresponding triangle vertices in the destination image. + + + + + Calculates perspective transform from 4 corresponding points. + + Coordinates of 4 quadrangle vertices in the source image. + Coordinates of the 4 corresponding quadrangle vertices in the destination image. + + + + + Initializes identity matrix + + Number of rows in the matrix. + Number of columns in the matrix. + Type of the matrix elements. + + + + Initializes scaled identity matrix + + Number of rows in the matrix. + Number of columns in the matrix. + Type of the matrix elements. + The value to assign to the diagonal elements. + + + + Calculates affine matrix of 2d rotation. + + Center of the rotation in the source image. + The rotation angle in degrees. Positive values mean couter-clockwise rotation (the coordiate origin is assumed at top-left corner). + Isotropic scale factor. + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + sizeof(CvMat) + + + + + CvMat signature (CV_MAT_MAGIC_VAL), element type and flags + + + + + Full row length in bytes + + + + + Data pointer + + + + + Data pointer as byte* + + + + + Data pointer as short* + + + + + Data pointer as int* + + + + + Data pointer as float* + + + + + Data pointer as double* + + + + + Data pointer(byte*) which can be accessed without unsafe code. + + + + + Data pointer(short*) which can be accessed without unsafe code. + + + + + Data pointer(int*) which can be accessed without unsafe code. + + + + + Data pointer(float*) which can be accessed without unsafe code. + + + + + Data pointer(double*) which can be accessed without unsafe code. + + + + + number of columns + + + + + number of columns + + + + + number of rows + + + + + number of rows + + + + + + + + + + Number of dimensions (=2) + + + + + Gets/Sets the particular element of single-channel floating-point matrix (cvmGet/cvmSet) + + The zero-based index of row. + The zero-based index of column. + the particular element's value + + + + Unary plus operator + + matrix + + + + + Unary negation operator + + matrix + + + + + Logical nagation operator + + matrix + + + + + Binary plus operator (cvAdd) + + matrix + matrix + + + + + Binary plus operator (cvAddS) + + matrix + scalar + + + + + Binary negation operator (cvSub) + + matrix + matrix + + + + + Binary negation operator (cvSub) + + matrix + scalar + + + + + Multiplicative operator (cvMatMul) + + matrix + matrix + + + + + Multiplicative operator (cvAddWeighted) + + matrix + scalar + + + + + Multiplicative operator (cvAddWeighted) + + scalar + matrix + + + + + Division operator (cvAddWeighted) + + matrix + scalar + + + + + Bitwise AND operator (cvAnd) + + matrix + matrix + + + + + Bitwise AND operator (cvAndS) + + matrix + scalar + + + + + Bitwise OR operator (cvOr) + + matrix + matrix + + + + + Bitwise OR operator (cvOrS) + + matrix + scalar + + + + + Bitwise XOR operator (cvXor) + + matrix + matrix + + + + + Bitwise XOR operator (cvXorS) + + matrix + scalar + + + + + Finds intrinsic and extrinsic camera parameters using calibration pattern + + Image size in pixels + + + + Finds intrinsic and extrinsic camera parameters using calibration pattern + + Image size in pixels + Aperture width in realworld units + Aperture width in realworld units + + + + Finds intrinsic and extrinsic camera parameters using calibration pattern + + Image size in pixels + Aperture width in realworld units + Aperture width in realworld units + Field of view angle in x direction in degrees + Field of view angle in y direction in degrees + + + + Finds intrinsic and extrinsic camera parameters using calibration pattern + + Image size in pixels + Aperture width in realworld units + Aperture width in realworld units + Field of view angle in x direction in degrees + Field of view angle in y direction in degrees + Focal length in realworld units + + + + Finds intrinsic and extrinsic camera parameters using calibration pattern + + Image size in pixels + Aperture width in realworld units + Aperture width in realworld units + Field of view angle in x direction in degrees + Field of view angle in y direction in degrees + Focal length in realworld units + The principal point in realworld units + + + + Finds intrinsic and extrinsic camera parameters using calibration pattern + + Image size in pixels + Aperture width in realworld units + Aperture width in realworld units + Field of view angle in x direction in degrees + Field of view angle in y direction in degrees + Focal length in realworld units + The principal point in realworld units + The pixel aspect ratio ~ fy/fx + + + + Creates matrix copy (cvCloneMat) + + a copy of input array + + + + Makes an matrix that have the same size, depth and channels as this image + + + + + + Completes the symmetric matrix from the lower part + + + + + Completes the symmetric matrix from the lower (LtoR=0) or from the upper (LtoR!=0) part + + + + + + For points in one image of stereo pair computes the corresponding epilines in the other image + + Index of the image (1 or 2) that contains the points + Fundamental matrix + Computed epilines, 3xN or Nx3 array + + + + Convert points to/from homogeneous coordinates + + The output point array, must contain the same number of points as the input; The dimensionality must be the same, 1 less or 1 more than the input, and also within 2..4. + + + + Convert points to/from homogeneous coordinates + + The output point array, must contain the same number of points as the input; The dimensionality must be the same, 1 less or 1 more than the input, and also within 2..4. + + + + Decode image stored in the buffer + + Specifies color type of the loaded image + + + + + Decode image stored in the buffer + + Specifies color type of the loaded image + + + + + Computes projection matrix decomposition + + The output 3x3 internal calibration matrix K + The output 3x3 external rotation matrix R + The output 4x1 external homogenious position vector C + + + + Computes projection matrix decomposition + + The output 3x3 internal calibration matrix K + The output 3x3 external rotation matrix R + The output 4x1 external homogenious position vector C + Optional 3x3 rotation matrix around x-axis + Optional 3x3 rotation matrix around y-axis + Optional 3x3 rotation matrix around z-axis + + + + Computes projection matrix decomposition + + The output 3x3 internal calibration matrix K + The output 3x3 external rotation matrix R + The output 4x1 external homogenious position vector C + Optional 3x3 rotation matrix around x-axis + Optional 3x3 rotation matrix around y-axis + Optional 3x3 rotation matrix around z-axis + Optional 3 points containing the three Euler angles of rotation + + + + Encode image and store the result as a byte vector (single-row 8uC1 matrix) + + The file extension that defines the output format + The format-specific parameters + + + + + Encode image and store the result as a byte vector (single-row 8uC1 matrix) + + The file extension that defines the output format + The format-specific parameters + + + + + Returns stream that indicates data pointer. + (The return value must be closed manually) + + + + + + Initializes matrix header. + + Number of rows in the matrix. + Number of columns in the matrix. + Type of the matrix elements. + + + + + Initializes matrix header. + + + Number of rows in the matrix. + Number of columns in the matrix. + Type of the matrix elements. + Optional data pointer assigned to the matrix header. + + + + + Initializes matrix header. + + + Number of rows in the matrix. + Number of columns in the matrix. + Type of the matrix elements. + Optional data pointer assigned to the matrix header. + Full row width in bytes of the data assigned. By default, the minimal possible step is used, r.e., no gaps is assumed between subsequent rows of the matrix. + + + + + Return the particular element of single-channel floating-point matrix + + The zero-based index of row. + The zero-based index of column. + + + + + Return the particular element of single-channel floating-point matrix + + The zero-based index of row. + The zero-based index of column. + The new value of the matrix element + + + + Converts rotation matrix to rotation vector or vice versa + + The output rotation matrix (3x3) or rotation vector (3x1 or 1x3), respectively. + + + + + Converts rotation matrix to rotation vector or vice versa + + The output rotation matrix (3x3) or rotation vector (3x1 or 1x3), respectively. + Optional output Jacobian matrix, 3x9 or 9x3 - partial derivatives of the output array components w.r.t the input array components. + + + + + Computes RQ decomposition for 3x3 matrices + + The output 3x3 upper-triangular matrix R + The output 3x3 orthogonal matrix Q + + + + Computes RQ decomposition for 3x3 matrices + + The output 3x3 upper-triangular matrix R + The output 3x3 orthogonal matrix Q + Optional 3x3 rotation matrix around x-axis + Optional 3x3 rotation matrix around y-axis + Optional 3x3 rotation matrix around z-axis + + + + Computes RQ decomposition for 3x3 matrices + + The output 3x3 upper-triangular matrix R + The output 3x3 orthogonal matrix Q + Optional 3x3 rotation matrix around x-axis + Optional 3x3 rotation matrix around y-axis + Optional 3x3 rotation matrix around z-axis + Optional 3 points containing the three Euler angles of rotation + + + + Transposes matrix + + + + + Transposes matrix + + + + + Computes the ideal point coordinates from the observed point coordinates + + The ideal point coordinates, after undistortion and reverse perspective transformation. + The camera matrix A=[fx 0 cx; 0 fy cy; 0 0 1]. + The vector of distortion coefficients, 4x1, 1x4, 5x1 or 1x5. + The rectification transformation in object space (3x3 matrix). R1 or R2, computed by cvStereoRectify can be passed here. If the parameter is null, the identity matrix is used. + The new camera matrix (3x3) or the new projection matrix (3x4). P1 or P2, computed by cvStereoRectify can be passed here. If the parameter is null, the identity matrix is used. + + + + Converts this CvMat object to a managed linear array. + + + + + + Converts this CvMat object to a managed rectangular array. + + + + + + Converts this object to a human readable string. + + A string that represents this object. + + + + + + + + + + + + + + + + Growing memory storage + + + + + Track whether Dispose has been called + + + + + Creates memory storage + + + + + Creates memory storage + + Size of the storage blocks in bytes. If it is 0, the block size is set to default value - currently it is ≈64K. + + + + Initializes from native poitner + + struct CvMemStorage* + + + + Initializes by native pointer + + + If true, this object will be disposed by GC automatically. + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + sizeof(CvMemStorage) + + + + + + + + + + first allocated block + + + + + the current memory block - top of the stack + + + + + borrows new blocks from + + + + + block size + + + + + free space in the top block (in bytes) + + + + + Allocates memory buffer in the storage (cvMemStorageAlloc). + + Buffer size. + + + + + Allocates text string in the storage (cvMemStorageAllocString). + + The string + + + + + Clears memory storage (cvClearMemStorage)． + + + + + Creates child memory storage (cvCreateChildMemStorage). + + + + + + Restores memory storage position (cvRestoreMemStoragePos). + + New storage top position + + + + Saves memory storage position (cvSaveMemStoragePos). + + position of the storage top. + + + + Multi-dimensional dense multi-channel array + + + + + Track whether Dispose has been called + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Allocates header for multi-dimensional dense array and the underlying data, and returns pointer to the created array. + + Number of array dimensions. It must not exceed CV_MAX_DIM (=32 by default, though it may be changed at build time) + Array of dimension sizes. + Type of array elements. + + + + + Allocates header for multi-dimensional dense array and the underlying data, and returns pointer to the created array. + + Number of array dimensions. It must not exceed CV_MAX_DIM (=32 by default, though it may be changed at build time) + Array of dimension sizes. + Type of array elements. + Optional data pointer assigned to the matrix header. + + + + + Initializes from native pointer + + + + + + Initializes by native pointer + + + If true, this matrix will be disposed by GC automatically. + + + + Allocates memory + + + + + Allocates memory + + If true, this matrix will be disposed by GC automatically. + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + Unary plus operator + + matrix + + + + + Unary negation operator + + matrix + + + + + Logical nagation operator + + matrix + + + + + Binary plus operator (cvAdd) + + matrix + matrix + + + + + Binary plus operator (cvAddS) + + matrix + scalar + + + + + Binary negation operator (cvSub) + + matrix + matrix + + + + + Binary negation operator (cvSub) + + matrix + scalar + + + + + Multiplicative operator (cvMatMul) + + matrix + matrix + + + + + Multiplicative operator (cvAddWeighted) + + matrix + scalar + + + + + Division operator (cvAddWeighted) + + matrix + scalar + + + + + Bitwise AND operator (cvAnd) + + matrix + matrix + + + + + Bitwise AND operator (cvAndS) + + matrix + scalar + + + + + Bitwise OR operator (cvOr) + + matrix + matrix + + + + + Bitwise OR operator (cvOrS) + + matrix + scalar + + + + + Bitwise XOR operator (cvXor) + + matrix + matrix + + + + + Bitwise XOR operator (cvXorS) + + matrix + scalar + + + + + sizeof(CvMatND) + + + + + Get number of dimensions of the array + + + + + CvMatND signature (CV_MATND_MAGIC_VAL), element type and flags + + + + + + + + + + Pairs (number of elements, distance between elements in bytes) for every dimension + + + + + Pairs (number of elements, distance between elements in bytes) for every dimension + + + + + + + + + + + Data pointer + + + + + Data pointer as byte* + + + + + Data pointer as short* + + + + + Data pointer as int* + + + + + Data pointer as float* + + + + + Data pointer as double* + + + + + Data pointer(byte*) which can be accessed without unsafe code. + + + + + Data pointer(short*) which can be accessed without unsafe code. + + + + + Data pointer(int*) which can be accessed without unsafe code. + + + + + Data pointer(float*) which can be accessed without unsafe code. + + + + + Data pointer(double*) which can be accessed without unsafe code. + + + + + Creates full copy of multi-dimensional array + + a copy of input array + + + + Initializes multi-dimensional array header. + + Number of array dimensions. + Array of dimension sizes. + Type of array elements. The same as for CvMat. + + + + + Initializes multi-dimensional array header. + + + Number of array dimensions. + Array of dimension sizes. + Type of array elements. The same as for CvMat. + Optional data pointer assigned to the matrix header. + + + + + Generic growable sequence of elements + + + + + + Creates sequence. header_size=sizeof(CvSeq) + + Flags of the created sequence. If the sequence is not passed to any function working with a specific type of sequences, the sequence value may be set to 0, otherwise the appropriate type must be selected from the list of predefined sequence types. + Sequence location. + + + + + Creates sequence + + Flags of the created sequence. If the sequence is not passed to any function working with a specific type of sequences, the sequence value may be set to 0, otherwise the appropriate type must be selected from the list of predefined sequence types. + Size of the sequence header; must be greater or equal to sizeof(CvSeq). If a specific type or its extension is indicated, this type must fit the base type header. + Sequence location. + + + + CvSeq -> CvSeq<t> + + + + + + Initializes from native pointer + + struct CvSeq* + + + + Creates CvSeq<t> from an IEnumerable<t> instance (ex. Array, List<t>) + + IEnumerable<t> instance + Flags of the created sequence + Sequence location + CvSeq<t> + + + + previous sequence + + + + + next sequence + + + + + 2nd previous sequence + + + + + 2nd next sequence + + + + + Indexer (cvGetSeqElem) + + + + + + + Creates a copy of sequence (cvCloneSeq). + + + + + + Creates a copy of sequence (cvCloneSeq). + + The destination storage to keep the new sequence header and the copied data if any. If it is null, the function uses the storage containing the input sequence. + + + + + Returns index of concrete sequence element (cvSeqElemIdx). + + the element within the sequence. + the index of a sequence element or a negative number if the element is not found. + + + + Returns index of concrete sequence element (cvSeqElemIdx). + + the element within the sequence. + the address of the sequence block that contains the element is stored in this location. + the index of a sequence element or a negative number if the element is not found. + + + + Returns pointer to sequence element by its index + + Index of element. + + + + + Inserts element in sequence middle (cvSeqInsert). + + Index before which the element is inserted. Inserting before 0 (the minimal allowed value of the parameter) is equal to cvSeqPushFront and inserting before seq->total (the maximal allowed value of the parameter) is equal to cvSeqPush. + Inserted element. + Inserted element. + + + + Splits sequence into equivalence classes + + The storage to store the sequence of equivalence classes. If it is null, the function uses seq->storage for output labels. + Output parameter. Double pointer to the sequence of 0-based labels of input sequence elements. + The relation function that should return non-zero if the two particular sequence elements are from the same class, and zero otherwise. The partitioning algorithm uses transitive closure of the relation function as equivalence criteria. + + + + + Removes element from sequence end (cvSeqPop). + + removed element + + + + Removes element from sequence beginning (cvSeqPopFront). + + removed element + + + + Removes several elements from the either end of sequence (cvSeqPopMulti). + + Number of elements to pop. + The flags specifying the modified sequence end + + + + Adds element to sequence end (cvSeqPush)． + + Added element. + pointer to the allocated element. + + + + Adds element to sequence beginning (cvSeqPushFront). + + Added element. + pointer to the added element + + + + Pushes several elements to the either end of sequence (cvSeqPushMulti). + + Added elements. + The flags specifying the modified sequence end + + + + Searches element in sequence (cvSeqSearch). + + The element to look for + The comparison function that returns negative, zero or positive value depending on the elements relation + Whether the sequence is sorted or not. + Output parameter; index of the found element. + + + + + Makes separate header for the sequence slice (cvSeqSlice). + + The part of the sequence to extract. + + + + + Makes separate header for the sequence slice (cvSeqSlice). + + The part of the sequence to extract. + The destination storage to keep the new sequence header and the copied data if any. If it is null, the function uses the storage containing the input sequence. + + + + + Makes separate header for the sequence slice (cvSeqSlice). + + The part of the sequence to extract. + The destination storage to keep the new sequence header and the copied data if any. If it is null, the function uses the storage containing the input sequence. + The flag that indicates whether to copy the elements of the extracted slice (copy_data=true) or not (copy_data=false) + + + + + Sorts sequence element using the specified comparison function (cvSeqSort). + + The comparison function that returns negative, zero or positive value depending on the elements relation (see the above declaration and the example below) - similar function is used by qsort from C runtime except that in the latter userdata is not used + + + + Initializes process of sequential reading from sequence (cvStartReadSeq). + + Reader state; initialized by the function. + + + + Initializes process of sequential reading from sequence (cvStartReadSeq). + + Reader state; initialized by the function. + Determines the direction of the sequence traversal. If reverse is false, the reader is positioned at the first sequence element, otherwise it is positioned at the last element. + + + + Copies sequence to one continuous block of memory (cvCvtSeqToArray). + + + + + + Copies sequence to one continuous block of memory (cvCvtSeqToArray). + + The sequence part to copy to the array. + + + + + Approximates polygonal curve(s) with desired precision. + + Header size of approximated curve[s]. + Container for approximated contours. If it is null, the input sequences' storage is used. + Approximation method; only ApproxPolyMethod.DP is supported, that corresponds to Douglas-Peucker algorithm. + Method-specific parameter; in case of CV_POLY_APPROX_DP it is a desired approximation accuracy. + + + + + Approximates polygonal curve(s) with desired precision. + + Header size of approximated curve[s]. + Container for approximated contours. If it is null, the input sequences' storage is used. + Approximation method; only ApproxPolyMethod.DP is supported, that corresponds to Douglas-Peucker algorithm. + Method-specific parameter; in case of CV_POLY_APPROX_DP it is a desired approximation accuracy. + If case if src_seq is sequence it means whether the single sequence should be approximated + or all sequences on the same level or below src_seq (see cvFindContours for description of hierarchical contour structures). + And if src_seq is array (CvMat*) of points, the parameter specifies whether the curve is closed (parameter2==true) or not (parameter2==false). + + + + + Returns an enumerator that iterates through the collection. + + A IEnumerator<CvSeq> that can be used to iterate through the collection. + + + + Returns an enumerator that iterates through a collection. + + An System.Collections.IEnumerator object that can be used to iterate through the collection. + + + + Collection of nodes + + + + + Default constructor + + + + + Creates empty set + + Type of the created set. + Set header size; may not be less than sizeof(CvSet). + Set element size; may not be less than CvSetElem. + Container for the set. + + + + Initializes from native pointer + + struct CvSet* + + + + sizeof(CvSet) + + + + + list of free nodes + + + + + + + + + + Clears set + + The function cvClearSet removes all elements from set. It has O(1) time complexity. + + + + Finds set element by its index + + Index of the set element within a sequence. + the pointer to it or null if the index is invalid or the corresponding node is free. + + + + Occupies a node in the set + + the index to the node + + + + Occupies a node in the set + + Optional input argument, inserted element. If not null, the function copies the data to the allocated node (The MSB of the first integer field is cleared after copying). + the index to the node + + + + Occupies a node in the set + + Optional input argument, inserted element. If not null, the function copies the data to the allocated node (The MSB of the first integer field is cleared after copying). + Optional output argument; the pointer to the allocated cell. + the index to the node + + + + Adds element to set (fast variant) + + pointer to a new node + + + + Removes element from set + + Index of the removed element. + + + + Removes set element given its pointer + + Removed element. + + + + Sequence reader + + + + + + Default constructor + + + + + Sequence, beign read + + + + + シーケンスの要素を一つ読みだして、読み出しポインタを次へ1つ移動させる (CV_READ_SEQ_ELEM相当) + + + + + シーケンスの前の要素を一つ読みだして、読み出しポインタを前へ1つ移動させる (CV_REV_READ_SEQ_ELEM相当) + + + + + Multi-dimensional sparse multi-channel array + + + + + Track whether Dispose has been called + + + + + Initializes from native pointer + + CvSparseMat* + + + + ポインタと自動解放の可否を指定して初期化 + + + + + + + Creates sparse array (cvCreateSparseMat). + + Number of array dimensions. As opposite to the dense matrix, the number of dimensions is practically unlimited (up to 2^16). + Array of dimension sizes. + Type of array elements. + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + Unary plus operator + + matrix + + + + + Unary negation operator + + matrix + + + + + Logical nagation operator + + matrix + + + + + Binary plus operator (cvAdd) + + matrix + matrix + + + + + Binary plus operator (cvAddS) + + matrix + scalar + + + + + Binary negation operator (cvSub) + + matrix + matrix + + + + + Binary negation operator (cvSub) + + matrix + scalar + + + + + Multiplicative operator (cvMatMul) + + matrix + matrix + + + + + Multiplicative operator (cvAddWeighted) + + matrix + scalar + + + + + Division operator (cvAddWeighted) + + matrix + scalar + + + + + Bitwise AND operator (cvAnd) + + matrix + matrix + + + + + Bitwise AND operator (cvAndS) + + matrix + scalar + + + + + Bitwise OR operator (cvOr) + + matrix + matrix + + + + + Bitwise OR operator (cvOrS) + + matrix + scalar + + + + + Bitwise XOR operator (cvXor) + + matrix + matrix + + + + + Bitwise XOR operator (cvXorS) + + matrix + scalar + + + + + sizeof(CvSparseMat) + + + + + Get number of dimensions of the array + + + + + CvSparseMat signature (CV_SPARSE_MAT_MAGIC_VAL), element type and flags + + + + + Size of hashtable + + + + + hashtable: each entry has a list of nodes having the same "hashvalue modulo hashsize" + + + + + A pool of hashtable nodes + + + + + Index offset in bytes for the array nodes + + + + + Value offset in bytes for the array nodes + + + + + Arr of dimension sizes + + + + + Creates full copy of sparse array + + a copy of input array + + + + CV_NODE_IDX + + + + + + + CV_NODE_VAL + + + + + + + + Growable sequence of elements + + + + + to keep alive storage + + + + + Default constructor + + + + + Creates sequence. header_size=sizeof(CvSeq) + + Flags of the created sequence. If the sequence is not passed to any function working with a specific type of sequences, the sequence value may be set to 0, otherwise the appropriate type must be selected from the list of predefined sequence types. + Size of the sequence elements in bytes. The size must be consistent with the sequence type. For example, for a sequence of points to be created, the element type CV_SEQ_ELTYPE_POINT should be specified and the parameter elem_size must be equal to sizeof(CvPoint). + Sequence location. + + + + + Creates sequence + + Flags of the created sequence. If the sequence is not passed to any function working with a specific type of sequences, the sequence value may be set to 0, otherwise the appropriate type must be selected from the list of predefined sequence types. + Size of the sequence header; must be greater or equal to sizeof(CvSeq). If a specific type or its extension is indicated, this type must fit the base type header. + Size of the sequence elements in bytes. The size must be consistent with the sequence type. For example, for a sequence of points to be created, the element type CV_SEQ_ELTYPE_POINT should be specified and the parameter elem_size must be equal to sizeof(CvPoint). + Sequence location. + + + + Initializes from native pointer + + struct CvSeq* + + + + sizeof(CvSeq) + + + + + previous sequence + + + + + next sequence + + + + + 2nd previous sequence + + + + + 2nd next sequence + + + + + total number of elements + + + + + size of sequence element in bytes + + + + + maximal bound of the last block + + + + + current write pointer + + + + + how many elements allocated when the sequence grows (sequence granularity) + + + + + where the seq is stored + + + + + free blocks list + + + + + pointer to the first sequence block + + + + + Calculates pair-wise geometrical histogram for contour + + Calculated histogram; must be two-dimensional. + + + + Clears sequence + + + + + Creates a copy of sequence (cvCloneSeq). + + + + + + Creates a copy of sequence (cvCloneSeq). + + The destination storage to keep the new sequence header and the copied data if any. If it is null, the function uses the storage containing the input sequence. + + + + + ICloneable.Clone + + + + + + Alias for Moments with CvSeq contours + + + + + + Creates hierarchical representation of contour + + Container for output tree. + Approximation accuracy. + + + + + Returns index of concrete sequence element (cvSeqElemIdx). + + Element type + the element within the sequence. + the index of a sequence element or a negative number if the element is not found. + + + + Returns index of concrete sequence element (cvSeqElemIdx). + + Element type + the element within the sequence. + the address of the sequence block that contains the element is stored in this location. + the index of a sequence element or a negative number if the element is not found. + + + + Returns pointer to sequence element by its index + + Element type + Index of element. + + + + + Inserts element in sequence middle (cvSeqInsert). + + Element type + Index before which the element is inserted. Inserting before 0 (the minimal allowed value of the parameter) is equal to cvSeqPushFront and inserting before seq->total (the maximal allowed value of the parameter) is equal to cvSeqPush. + Inserted element. + Inserted element. + + + + Inserts array in the middle of sequence (cvSeqInsertSlice). + + The part of the sequence to remove. + The array to take elements from. + + + + Reverses the order of sequence elements (cvSeqInvert). + + + + + Removes element from sequence middle (cvSeqRemove). + + Index of removed element. + + + + Removes sequence slice (cvSeqRemoveSlice). + + The part of the sequence to remove. + + + + Splits sequence into equivalence classes + + The storage to store the sequence of equivalence classes. If it is null, the function uses seq->storage for output labels. + Output parameter. Double pointer to the sequence of 0-based labels of input sequence elements. + The relation function that should return non-zero if the two particular sequence elements are from the same class, and zero otherwise. The partitioning algorithm uses transitive closure of the relation function as equivalence criteria. + + + + + Removes element from sequence end (cvSeqPop). + + Element type + removed element + + + + Removes element from sequence beginning (cvSeqPopFront). + + Element type + removed element + + + + Removes several elements from the either end of sequence (cvSeqPopMulti). + + Element type + Number of elements to pop. + The flags specifying the modified sequence end + + + + allocates a space for one more element (cvSeqPush)． + + pointer to the allocated element. + + + + Adds element to sequence end (cvSeqPush)． + + Element type + Added element. + pointer to the allocated element. + + + + Adds element to sequence beginning (cvSeqPushFront). + + Element type + Added element. + pointer to the added element + + + + Pushes several elements to the either end of sequence (cvSeqPushMulti). + + Element type + Added elements. + The flags specifying the modified sequence end + + + + Searches element in sequence (cvSeqSearch). + + The element to look for + The comparison function that returns negative, zero or positive value depending on the elements relation + Whether the sequence is sorted or not. + Output parameter; index of the found element. + + + + + Sets up sequence block size + + Desirable sequence block size in elements. + + + + Makes separate header for the sequence slice (cvSeqSlice). + + The part of the sequence to extract. + + + + + Makes separate header for the sequence slice (cvSeqSlice). + + The part of the sequence to extract. + The destination storage to keep the new sequence header and the copied data if any. If it is null, the function uses the storage containing the input sequence. + + + + + Makes separate header for the sequence slice (cvSeqSlice). + + The part of the sequence to extract. + The destination storage to keep the new sequence header and the copied data if any. If it is null, the function uses the storage containing the input sequence. + The flag that indicates whether to copy the elements of the extracted slice (copy_data=true) or not (copy_data=false) + + + + + Sorts sequence element using the specified comparison function (cvSeqSort). + + The comparison function that returns negative, zero or positive value depending on the elements relation (see the above declaration and the example below) - similar function is used by qsort from C runtime except that in the latter userdata is not used + + + + Initializes process of writing data to sequence (cvStartAppendToSeq). + + Writer state; initialized by the function. + + + + Initializes process of sequential reading from sequence (cvStartReadSeq). + + Reader state; initialized by the function. + + + + Initializes process of sequential reading from sequence (cvStartReadSeq). + + Reader state; initialized by the function. + Determines the direction of the sequence traversal. If reverse is false, the reader is positioned at the first sequence element, otherwise it is positioned at the last element. + + + + Copies sequence to one continuous block of memory (cvCvtSeqToArray). + + + + + + + Copies sequence to one continuous block of memory (cvCvtSeqToArray). + + + The sequence part to copy to the array. + + + + + The comparison function that returns negative, zero or positive value depending on the elements relation + + + + + + + + The comparison function that returns negative, zero or positive value depending on the elements relation + + + + + + + + + Delegate to be called every time mouse event occurs in the specified window. + + one of CV_EVENT_ + x-coordinates of mouse pointer in image coordinates + y-coordinates of mouse pointer in image coordinates + a combination of CV_EVENT_FLAG + + + + Delegate to be called every time the slider changes the position. + + + + + + Delegate to be called every time the slider changes the position. + + + + + + + + + + + + + + DisposableObject + ICvPtrHolder + + + + + Data pointer + + + + + Track whether Dispose has been called + + + + + Default constructor + + + + + + + + + + + + + + + + + + + + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + Native pointer of OpenCV structure + + + + + Adaptive thresholding algorithms + + + + + It is a mean of block_size × block_size pixel neighborhood, subtracted by param1. + [CV_ADAPTIVE_THRESH_MEAN_C] + + + + + it is a weighted sum (Gaussian) of block_size × block_size pixel neighborhood, subtracted by param1. + [CV_ADAPTIVE_THRESH_GAUSSIAN_C] + + + + + Size of the extended Sobel kernel + + + + + Size 1 + + + + + Size 3 + + + + + Size 5 + + + + + Size 7 + + + + + Corresponds to 3x3 Scharr filter that may give more accurate results than 3x3 Sobel. + [CV_SCHARR] + + + + + Approximation method + + + + + Corresponds to Douglas-Peucker algorithm. + [CV_POLY_APPROX_DP] + + + + + The flag specifying the relation between the elements to be checked + + + + + src1(I) "equal to" src2(I) + [CV_CMP_EQ] + + + + + src1(I) "greater than" src2(I) + [CV_CMP_GT] + + + + + src1(I) "greater or equal" src2(I) + [CV_CMP_GE] + + + + + src1(I) "less than" src2(I) + [CV_CMP_LT] + + + + + src1(I) "less or equal" src2(I) + [CV_CMP_LE] + + + + + src1(I) "not equal to" src2(I) + [CV_CMP_NE] + + + + + Bit Depth of image elements + + + + + unsigned 1-bit integers [IPL_DEPTH_1U] + + + + + unsigned 8-bit integers [IPL_DEPTH_8U] + + + + + signed 8-bit integers [IPL_DEPTH_8S] + + + + + unsigned 16-bit integers [IPL_DEPTH_16U] + + + + + signed 16-bit integers [IPL_DEPTH_16S] + + + + + signed 32-bit integers [IPL_DEPTH_32S] + + + + + single precision floating-point numbers [IPL_DEPTH_32F] + + + + + double precision floating-point numbers [IPL_DEPTH_64F] + + + + + Type of the border to create around the copied source image rectangle + + + + + Border is filled with the fixed value, passed as last parameter of the function. + [IPL_BORDER_CONSTANT] + + + + + The pixels from the top and bottom rows, the left-most and right-most columns are replicated to fill the border. + [IPL_BORDER_REPLICATE] + + + + + [IPL_BORDER_REFLECT] + + + + + [IPL_BORDER_REFLECT_101] + + + + + [IPL_BORDER_WRAP] + + + + + [BORDER_DEFAULT] + + + + + [cv::BORDER_ISOLATED] + + + + + -1 + + + + + Different flags for cvCalibrateCamera2 and cvStereoCalibrate + + + + + = 0 + + + + + = 0 + + + + + If it is set, camera_matrix1,2, as well as dist_coeffs1,2 are fixed, so that only extrinsic parameters are optimized. + [CV_CALIB_FIX_INTRINSIC] + + + + + The flag allows the function to optimize some or all of the intrinsic parameters, depending on the other flags, but the initial values are provided by the user + [CV_CALIB_USE_INTRINSIC_GUESS] + + + + + The principal points are fixed during the optimization. + [CV_CALIB_FIX_PRINCIPAL_POINT] + + + + + fxk and fyk are fixed. + [CV_CALIB_FIX_FOCAL_LENGTH] + + + + + fyk is optimized, but the ratio fxk/fyk is fixed. + [CV_CALIB_FIX_ASPECT_RATIO] + + + + + Enforces fx0=fx1 and fy0=fy1. CV_CALIB_ZERO_TANGENT_DIST - Tangential distortion coefficients for each camera are set to zeros and fixed there. + [CV_CALIB_SAME_FOCAL_LENGTH] + + + + + Tangential distortion coefficients are set to zeros and do not change during the optimization. + [CV_CALIB_ZERO_TANGENT_DIST] + + + + + The 0-th distortion coefficients (k1) are fixed + [CV_CALIB_FIX_K1] + + + + + The 1-th distortion coefficients (k2) are fixed + [CV_CALIB_FIX_K2] + + + + + The 4-th distortion coefficients (k3) are fixed + [CV_CALIB_FIX_K3] + + + + + Do not change the corresponding radial distortion coefficient during the optimization. + If CV_CALIB_USE_INTRINSIC_GUESS is set, the coefficient from the supplied distCoeffs matrix is used, otherwise it is set to 0. + [CV_CALIB_FIX_K4] + + + + + Do not change the corresponding radial distortion coefficient during the optimization. + If CV_CALIB_USE_INTRINSIC_GUESS is set, the coefficient from the supplied distCoeffs matrix is used, otherwise it is set to 0. + [CV_CALIB_FIX_K5] + + + + + Do not change the corresponding radial distortion coefficient during the optimization. + If CV_CALIB_USE_INTRINSIC_GUESS is set, the coefficient from the supplied distCoeffs matrix is used, otherwise it is set to 0. + [CV_CALIB_FIX_K6] + + + + + Enable coefficients k4, k5 and k6. + To provide the backward compatibility, this extra flag should be explicitly specified to make the calibration function + use the rational model and return 8 coefficients. If the flag is not set, the function will compute only 5 distortion coefficients. + [CV_CALIB_RATIONAL_MODEL] + + + + + Various operation flags for cvFindChessboardCorners + + + + + No options + + + + + Use adaptive thresholding to convert the image to black-n-white, rather than a fixed threshold level (computed from the average image brightness). + [CV_CALIB_CB_ADAPTIVE_THRESH] + + + + + Normalize the image using cvNormalizeHist before applying fixed or adaptive thresholding. + [CV_CALIB_CB_NORMALIZE_IMAGE] + + + + + Use additional criteria (like contour area, perimeter, square-like shape) to filter out false quads that are extracted at the contour retrieval stage. + [CV_CALIB_CB_FILTER_QUADS] + + + + + Camera device types + + + + + autodetect + [CV_CAP_ANY] + + + + + MIL proprietary drivers + [CV_CAP_MIL] + + + + + platform native + [CV_CAP_VFW] + + + + + platform native + [CV_CAP_V4L] + + + + + platform native + [CV_CAP_V4L2] + + + + + IEEE 1394 drivers + [CV_CAP_FIREWIRE] + + + + + IEEE 1394 drivers + [CV_CAP_IEEE1394] + + + + + IEEE 1394 drivers + [CV_CAP_FIREWARE] + + + + + IEEE 1394 drivers + [CV_CAP_DC1394] + + + + + IEEE 1394 drivers + [CV_CAP_CMU1394] + + + + + TYZX proprietary drivers + [CV_CAP_STEREO] + + + + + TYZX proprietary drivers + [CV_CAP_TYZX] + + + + + TYZX proprietary drivers + [CV_TYZX_LEFT] + + + + + TYZX proprietary drivers + [CV_TYZX_RIGHT] + + + + + TYZX proprietary drivers + [CV_TYZX_COLOR] + + + + + TYZX proprietary drivers + [CV_TYZX_Z] + + + + + QuickTime + [CV_CAP_QT] + + + + + Unicap drivers + [CV_CAP_UNICAP] + + + + + DirectShow (via videoInput) + [CV_CAP_DSHOW] + + + + + PvAPI, Prosilica GigE SDK + [CV_CAP_PVAPI] + + + + + OpenNI (for Kinect) + [CV_CAP_OPENNI] + + + + + Android + [CV_CAP_ANDROID] + + + + + XIMEA Camera API + [CV_CAP_XIAPI] + + + + + Property identifiers for CvCapture + + + + + Position in milliseconds from the file beginning + [CV_CAP_PROP_POS_MSEC] + + + + + Position in frames (only for video files) + [CV_CAP_PROP_POS_FRAMES] + + + + + Position in relative units (0 - start of the file, 1 - end of the file) + [CV_CAP_PROP_POS_AVI_RATIO] + + + + + Width of frames in the video stream (only for cameras) + [CV_CAP_PROP_FRAME_WIDTH] + + + + + Height of frames in the video stream (only for cameras) + [CV_CAP_PROP_FRAME_HEIGHT] + + + + + Frame rate (only for cameras) + [CV_CAP_PROP_FPS] + + + + + 4-character code of codec (only for cameras). + [CV_CAP_PROP_FOURCC] + + + + + Number of frames in the video stream + [CV_CAP_PROP_FRAME_COUNT] + + + + + The format of the Mat objects returned by retrieve() + [CV_CAP_PROP_FORMAT] + + + + + A backend-specific value indicating the current capture mode + [CV_CAP_PROP_MODE] + + + + + Brightness of image (only for cameras) + [CV_CAP_PROP_BRIGHTNESS] + + + + + contrast of image (only for cameras) + [CV_CAP_PROP_CONTRAST] + + + + + Saturation of image (only for cameras) + [CV_CAP_PROP_SATURATION] + + + + + hue of image (only for cameras) + [CV_CAP_PROP_HUE] + + + + + Gain of the image (only for cameras) + [CV_CAP_PROP_GAIN] + + + + + Exposure (only for cameras) + [CV_CAP_PROP_EXPOSURE] + + + + + Boolean flags indicating whether images should be converted to RGB + [CV_CAP_PROP_CONVERT_RGB] + + + + + + [CV_CAP_PROP_WHITE_BALANCE] + + + + + TOWRITE (note: only supported by DC1394 v 2.x backend currently) + [CV_CAP_PROP_RECTIFICATION] + + + + + + [CV_CAP_PROP_MONOCROME] + + + + + + [CV_CAP_PROP_SHARPNESS] + + + + + exposure control done by camera, + user can adjust refernce level using this feature + [CV_CAP_PROP_AUTO_EXPOSURE] + + + + + + [CV_CAP_PROP_GAMMA] + + + + + + [CV_CAP_PROP_TEMPERATURE] + + + + + + [CV_CAP_PROP_TRIGGER] + + + + + + [CV_CAP_PROP_TRIGGER_DELAY] + + + + + + [CV_CAP_PROP_WHITE_BALANCE_RED_V] + + + + + + [CV_CAP_PROP_MAX_DC1394] + + + + + property for highgui class CvCapture_Android only + [CV_CAP_PROP_AUTOGRAB] + + + + + readonly, tricky property, returns cpnst char* indeed + [CV_CAP_PROP_SUPPORTED_PREVIEW_SIZES_STRING] + + + + + readonly, tricky property, returns cpnst char* indeed + [CV_CAP_PROP_PREVIEW_FORMAT] + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + flag that synchronizes the remapping depth map to image map + by changing depth generator's view point (if the flag is "on") or + sets this view point to its normal one (if the flag is "off"). + + + + + + + + + + + + + + + + + + + + + + + + + default is 1 + + + + + ip for anable multicast master mode. 0 for disable multicast + + + + + Change image resolution by binning or skipping. + + + + + Output data format. + + + + + Horizontal offset from the origin to the area of interest (in pixels). + + + + + Vertical offset from the origin to the area of interest (in pixels). + + + + + Defines source of trigger. + + + + + Generates an internal trigger. PRM_TRG_SOURCE must be set to TRG_SOFTWARE. + + + + + Selects general purpose input + + + + + Set general purpose input mode + + + + + Get general purpose level + + + + + Selects general purpose output + + + + + Set general purpose output mode + + + + + Selects camera signalling LED + + + + + Define camera signalling LED functionality + + + + + Calculates White Balance(must be called during acquisition) + + + + + Automatic white balance + + + + + Automatic exposure/gain + + + + + Exposure priority (0.5 - exposure 50%, gain 50%). + + + + + Maximum limit of exposure in AEAG procedure + + + + + Maximum limit of gain in AEAG procedure + + + + + Average intensity of output signal AEAG should achieve(in %) + + + + + Image capture timeout in milliseconds + + + + + Capture type of CvCapture (Camera or AVI file) + + + + + Captures from an AVI file + + + + + Captures from digital camera + + + + + + + + + + The operation flags for cvCheckArr + + + + + The function just checks that every element is neither NaN nor ±Infinity. + + + + + The function checks that every value of array is within [minVal,maxVal) range. + [CV_CHECK_RANGE] + + + + + The function does not raises an error if an element is invalid or out of range. + [CV_CHECK_QUIET] + + + + + Color conversion operation for cvCvtColor + + + + + Approximation method (for all the modes, except CV_RETR_RUNS, which uses built-in approximation). + + + + + CV_CHAIN_CODE - output contours in the Freeman chain code. All other methods output polygons (sequences of vertices). + + + + + CV_CHAIN_APPROX_NONE - translate all the points from the chain code into points; + + + + + CV_CHAIN_APPROX_SIMPLE - compress horizontal, vertical, and diagonal segments, that is, the function leaves only their ending points; + + + + + CV_CHAIN_APPROX_TC89_L1 - apply one of the flavors of Teh-Chin chain approximation algorithm. + + + + + V_CHAIN_APPROX_TC89_KCOS - apply one of the flavors of Teh-Chin chain approximation algorithm. + + + + + CV_LINK_RUNS - use completely different contour retrieval algorithm via linking of horizontal segments of 1’s. Only CV_RETR_LIST retrieval mode can be used with this method. + + + + + Approximation methods for cvFindContours + + + + + Retrieve only the extreme outer contours + [CV_RETR_EXTERNAL] + + + + + Retrieve all the contours and puts them in the list + [CV_RETR_LIST] + + + + + Retrieve all the contours and organizes them into two-level hierarchy: top level are external boundaries of the components, second level are boundaries of the holes + [CV_RETR_CCOMP] + + + + + Retrieve all the contours and reconstructs the full hierarchy of nested contours + [CV_RETR_TREE] + + + + + + [CV_RETR_FLOODFILL] + + + + + Operation flags for cvCovarMatrix + + + + + scale * [vects[0]-avg,vects[1]-avg,...]^T * [vects[0]-avg,vects[1]-avg,...] + that is, the covariation matrix is count×count. Such an unusual covariation matrix is used for fast PCA of a set of very large vectors + (see, for example, Eigen Faces technique for face recognition). Eigenvalues of this "scrambled" matrix will match to the eigenvalues of + the true covariation matrix and the "true" eigenvectors can be easily calculated from the eigenvectors of the "scrambled" covariation matrix. + [CV_COVAR_SCRAMBLED] + + + + + scale * [vects[0]-avg,vects[1]-avg,...]*[vects[0]-avg,vects[1]-avg,...]^T + that is, cov_mat will be a usual covariation matrix with the same linear size as the total number of elements in every input vector. + One and only one of CV_COVAR_SCRAMBLED and CV_COVAR_NORMAL must be specified + [CV_COVAR_NORMAL] + + + + + If the flag is specified, the function does not calculate avg from the input vectors, + but, instead, uses the passed avg vector. This is useful if avg has been already calculated somehow, + or if the covariation matrix is calculated by parts - in this case, avg is not a mean vector of the input sub-set of vectors, + but rather the mean vector of the whole set. + [CV_COVAR_USE_AVG] + + + + + If the flag is specified, the covariation matrix is scaled by the number of input vectors. + [CV_COVAR_SCALE] + + + + + Means that all the input vectors are stored as rows of a single matrix, vects[0].count is ignored in this case, + and avg should be a single-row vector of an appropriate size. + [CV_COVAR_ROWS] + + + + + Means that all the input vectors are stored as columns of a single matrix, vects[0].count is ignored in this case, + and avg should be a single-column vector of an appropriate size. + [CV_COVAR_COLS] + + + + + Type of termination criteria + + + + + [CV_TERMCRIT_ITER] + + + + + [CV_TERMCRIT_NUMBER] + + + + + [CV_TERMCRIT_EPS] + + + + + Filters used in pyramid decomposition + + + + + [CV_GAUSSIAN_5x5] + + + + + Transformation flags for cvDCT + + + + + Do forward 1D or 2D transform. + (Forward and Inverse are mutually exclusive, of course.) + [CV_DXT_FORWARD] + + + + + Do inverse 1D or 2D transform. + (Forward and Inverse are mutually exclusive, of course.) + [CV_DXT_INVERSE] + + + + + Do forward or inverse transform of every individual row of the input matrix. + This flag allows user to transform multiple vectors simultaneously and can be used to decrease the overhead + (which is sometimes several times larger than the processing itself), to do 3D and higher-dimensional transforms etc. + [CV_DXT_ROWS] + + + + + Transformation flags for cvDFT + + + + + Zero + [0] + + + + + Do forward 1D or 2D transform. The result is not scaled. + (Forward and Inverse are mutually exclusive, of course.) + [CV_DXT_FORWARD] + + + + + Do inverse 1D or 2D transform. The result is not scaled. + (Forward and Inverse are mutually exclusive, of course.) + [CV_DXT_INVERSE] + + + + + Scale the result: divide it by the number of array elements. Usually, it is combined with Inverse. + [CV_DXT_SCALE] + + + + + Shortcut of Inverse | Scale + [CV_DXT_INVERSE_SCALE] + + + + + Do forward or inverse transform of every individual row of the input matrix. + This flag allows user to transform multiple vectors simultaneously and can be used to decrease the overhead + (which is sometimes several times larger than the processing itself), to do 3D and higher-dimensional transforms etc. + [CV_DXT_ROWS] + + + + + Array diagonal + + + + + corresponds to the main diagonal + + + + + corresponds to the diagonal above the main etc. + + + + + corresponds to the diagonal below the main etc. + + + + + Mode of correspondence retrieval + + + + + [CV_DISPARITY_BIRCHFIELD] + + + + + Type of distance for cvDistTransform + + + + + User defined distance [CV_DIST_USER] + + + + + distance = |x1-x2| + |y1-y2| [CV_DIST_L1] + + + + + the simple euclidean distance [CV_DIST_L2] + + + + + distance = max(|x1-x2|,|y1-y2|) [CV_DIST_C] + + + + + L1-L2 metric: distance = 2(sqrt(1+x*x/2) - 1)) [CV_DIST_L12] + + + + + distance = c^2(|x|/c-log(1+|x|/c)), c = 1.3998 [CV_DIST_FAIR] + + + + + distance = c^2/2(1-exp(-(x/c)^2)), c = 2.9846 [CV_DIST_WELSCH] + + + + + distance = |x|<c ? x^2/2 : c(|x|-c/2), c=1.345 [CV_DIST_HUBER] + + + + + Distribution type for cvRandArr, etc. + + + + + Uniform distribution + [CV_RAND_UNI] + + + + + Normal or Gaussian distribution + [CV_RAND_NORMAL] + + + + + Shape of the structuring element + + + + + A rectangular element + [CV_SHAPE_RECT] + + + + + A cross-shaped element + [CV_SHAPE_CROSS] + + + + + An elliptic element + [CV_SHAPE_ELLIPSE] + + + + + A user-defined element. In this case the parameter values specifies the mask, that is, which neighbors of the pixel must be considered. + [CV_SHAPE_CUSTOM] + + + + + File storage mode + + + + + The storage is open for reading + [CV_STORAGE_READ] + + + + + The storage is open for writing + [CV_STORAGE_WRITE] + + + + + The storage is open for writing text data + [CV_STORAGE_WRITE_TEXT] + + + + + The storage is open for writing binary data + [CV_STORAGE_WRITE_BINARY] + + + + + The storage is open for appending + [CV_STORAGE_APPEND] + + + + + + [CV_STORAGE_MEMORY] + + + + + + [CV_STORAGE_FORMAT_MASK] + + + + + + [CV_STORAGE_FORMAT_AUTO] + + + + + + [CV_STORAGE_FORMAT_XML] + + + + + + [CV_STORAGE_FORMAT_YAML] + + + + + Specifies how to flip the array + + + + + means flipping around x-axis + + + + + means flipping around y-axis + + + + + means flipping around both axises + + + + + Font name identifier. + Only a subset of Hershey fonts (http://sources.isc.org/utils/misc/hershey-font.txt) are supported now. + + + + + Normal size sans-serif font + [CV_FONT_HERSHEY_SIMPLEX] + + + + + Small size sans-serif font + [CV_FONT_HERSHEY_PLAIN] + + + + + Normal size sans-serif font (more complex than HersheySimplex) + [CV_FONT_HERSHEY_DUPLEX] + + + + + Normal size serif font + [CV_FONT_HERSHEY_COMPLEX] + + + + + Normal size serif font (more complex than HersheyComplex) + [CV_FONT_HERSHEY_TRIPLEX] + + + + + Smaller version of HersheyComplex + [CV_FONT_HERSHEY_COMPLEX_SMALL] + + + + + Hand-writing style font + [CV_FONT_HERSHEY_SCRIPT_SIMPLEX] + + + + + More complex variant of HersheyScriptSimplex + [CV_FONT_HERSHEY_SCRIPT_COMPLEX] + + + + + Means italic or oblique font. + [CV_FONT_ITALIC] + + + + + + [CV_FONT_VECTOR0] + + + + + Method for computing the fundamental matrix + + + + + for 7-point algorithm. N == 7 + [CV_FM_7POINT] + + + + + for 8-point algorithm. N >= 8 + [CV_FM_8POINT] + + + + + for LMedS algorithm. N > 8 + [CV_FM_LMEDS_ONLY] + + + + + for RANSAC algorithm. N > 8 + [CV_FM_RANSAC_ONLY] + + + + + for LMedS algorithm. N > 8 + [CV_FM_LMEDS] + + + + + for RANSAC algorithm. N > 8 + [CV_FM_RANSAC] + + + + + The operation flags for cvGEMM + + + + + = 0 + + + + + = 0 + + + + + Transpose src1 + [CV_GEMM_A_T] + + + + + Transpose src2 + [CV_GEMM_B_T] + + + + + Transpose src3 + [CV_GEMM_C_T] + + + + + Modes of operation for cvHaarDetectObjects + + + + + = 0 + + + + + If it is set, the function uses Canny edge detector to reject some image regions that contain too few or too much edges and thus can not contain the searched object. + The particular threshold values are tuned for face detection and in this case the pruning speeds up the processing. + [CV_HAAR_DO_CANNY_PRUNING] + + + + + For each scale factor used the function will downscale the image rather than "zoom" the feature coordinates in the classifier cascade. + Currently, the option can only be used alone, i.e. the flag can not be set together with the others. + [CV_HAAR_SCALE_IMAGE] + + + + + If it is set, the function finds the largest object (if any) in the image. That is, the output sequence will contain one (or zero) element(s). + [CV_HAAR_FIND_BIGGEST_OBJECT] + + + + + It should be used only when FindBiggestObject is set and min_neighbors > 0. + If the flag is set, the function does not look for candidates of a smaller size + as soon as it has found the object (with enough neighbor candidates) at the current scale. + Typically, when min_neighbors is fixed, the mode yields less accurate (a bit larger) object rectangle + than the regular single-object mode (flags=FindBiggestObject), + but it is much faster, up to an order of magnitude. A greater value of min_neighbors may be specified to improve the accuracy. + [CV_HAAR_DO_ROUGH_SEARCH] + + + + + Comparison methods for cvCompareHist + + + + + Correlation [CV_COMP_CORREL] + + + + + Chi-Square [CV_COMP_CHISQR] + + + + + Intersection [CV_COMP_INTERSECT] + + + + + Bhattacharyya distance [CV_COMP_BHATTACHARYYA] + + + + + Histogram representation format + + + + + Histogram data is represented as an multi-dimensional dense array CvMatND. + [CV_HIST_ARRAY] + + + + + Histogram data is represented as a multi-dimensional sparse array CvSparseMat. + [CV_HIST_SPARSE] + + + + + The method used to computed homography matrix + + + + + Regular method using all the point pairs + [= 0] + + + + + Least-Median robust method + [CV_LMEDS] + + + + + RANSAC-based robust method + [CV_RANSAC] + + + + + Methods for cvHoughCircles + + + + + [CV_HOUGH_GRADIENT] + + + + + The Hough transform variant + + + + + Classical or standard Hough transform. + Every line is represented by two floating-point numbers (ρ, θ), where ρ is a distance between (0,0) point and the line, + and θ is the angle between x-axis and the normal to the line. + Thus, the matrix must be (the created sequence will be) of CV_32FC2 type. + [CV_HOUGH_STANDARD] + + + + + Probabilistic Hough transform (more efficient in case if picture contains a few long linear segments). + It returns line segments rather than the whole lines. Every segment is represented by starting and ending points, + and the matrix must be (the created sequence will be) of CV_32SC4 type. + [CV_HOUGH_PROBABILISTIC] + + + + + Multi-scale variant of classical Hough transform. The lines are encoded the same way as in HoughLinesMethod.Standard. + [CV_HOUGH_MULTI_SCALE] + + + + + The inpainting method + + + + + Navier-Stokes based method. + [CV_INPAINT_NS] + + + + + The method by Alexandru Telea + [CV_INPAINT_TELEA] + + + + + The flags specifying the modified sequence end + + + + + the elements are added/removed to the end of sequence + + + + + the elements are added/removed to the beginning of sequenc + + + + + Inversion methods + + + + + Gaussian elimination with optimal pivot element chose + [CV_LU] + + + + + Singular value decomposition (SVD) method + [CV_SVD] + + + + + + [DECOMP_EIG] + + + + + SVD method for a symmetric positively-defined matrix + [CV_SVD_SYM] + + + + + + [CV_CHOLESKY] + + + + + + [CV_QR] + + + + + + [CV_NORMAL] + + + + + Type of the line + + + + + 8-connected line. + [= 8] + + + + + 4-connected line. + [= 4] + + + + + Antialiased line. + [CV_AA] + + + + + Miscellaneous flags for cvCalcOpticalFlowPyrLK + + + + + Pyramid for the first frame is pre-calculated before the call. + [CV_LKFLOW_PYR_A_READY] + + + + + Pyramid for the second frame is pre-calculated before the call. + [CV_LKFLOW_PYR_B_READY] + + + + + Array B contains initial coordinates of features before the function call. + [CV_LKFLOW_INITIAL_GUESSES] + + + + + Array B contains initial coordinates of features before the function call. + [cv::OPTFLOW_USE_INITIAL_FLOW] + + + + + + [CV_LKFLOW_GET_MIN_EIGENVALS] + + + + + Comparison methods for cvMatchShapes + + + + + [CV_CONTOURS_MATCH_I1] + + + + + [CV_CONTOURS_MATCH_I2] + + + + + [CV_CONTOURS_MATCH_I3] + + + + + Specifies the way the template must be compared with image regions + + + + + [CV_TM_SQDIFF] + + + + + [CV_TM_SQDIFF_NORMED] + + + + + [CV_TM_CCORR] + + + + + [CV_TM_CCORR_NORMED] + + + + + [CV_TM_CCOEFF] + + + + + [CV_TM_CCOEFF_NORMED] + + + + + Type of the matrix elements. + Usually it is specified in form (S|U|F)<bit_depth>C<number_of_channels>, + + + + + 1-channel 8-bit unsigned integers [CV_8UC1] + + + + + 2-channel 8-bit unsigned integers [CV_8UC2] + + + + + 3-channel 8-bit unsigned integers [CV_8UC3] + + + + + 4-channel 8-bit unsigned integers [CV_8UC4] + + + + + 1-channel 8-bit signed integers [CV_8SC1] + + + + + 2-channel 8-bit signed integers [CV_8SC2] + + + + + 3-channel 8-bit signed integers [CV_8SC3] + + + + + 4-channel 8-bit signed integers [CV_8SC4] + + + + + 1-channel 16-bit unsigned integers [CV_16UC1] + + + + + 2-channel 16-bit unsigned integers [CV_16UC2] + + + + + 3-channel 16-bit unsigned integers [CV_16UC3] + + + + + 4-channel 16-bit unsigned integers [CV_16UC4] + + + + + 1-channel 16-bit signed integers [CV_16SC1] + + + + + 2-channel 16-bit signed integers [CV_16SC2] + + + + + 3-channel 16-bit signed integers [CV_16SC3] + + + + + 4-channel 16-bit signed integers [CV_16SC4] + + + + + 1-channel 32-bit signed integers [CV_32SC1] + + + + + 2-channel 32-bit signed integers [CV_32SC2] + + + + + 3-channel 32-bit signed integers [CV_32SC3] + + + + + 4-channel 32-bit signed integers [CV_32SC4] + + + + + 1-channel 32-bit floating-point numbers [CV_32FC1] + + + + + 2-channel 32-bit floating-point numbers [CV_32FC2] + + + + + 3-channel 32-bit floating-point numbers [CV_32FC3] + + + + + 4-channel 32-bit floating-point numbers [CV_32FC4] + + + + + 1-channel 64-bit floating-point numbers [CV_64FC1] + + + + + 2-channel 64-bit floating-point numbers [CV_64FC2] + + + + + 3-channel 64-bit floating-point numbers [CV_64FC3] + + + + + 4-channel 64-bit floating-point numbers [CV_64FC4] + + + + + Type of morphological operation + + + + + Opening + [CV_MOP_OPEN] + + + + + Closing + [CV_MOP_CLOSE] + + + + + Morphological gradient + [CV_MOP_GRADIENT] + + + + + "Top hat" + [CV_MOP_TOPHAT] + + + + + "Black hat" + [CV_MOP_BLACKHAT] + + + + + Operation flags for cvMulSpectrums + + + + + Treat each row of the arrays as a separate spectrum. + [CV_DXT_ROWS] + + + + + Conjugate the second argument of cvMulSpectrums. + [CV_DXT_MUL_CONJ] + + + + + File node type + + + + + + + + + + + + + + + + + + + + + + + + + not used + + + + + + + + + + + + + + + used only for writing structures to YAML format + + + + + + + + + + + + + + + + + + + + Type of norm + + + + + The C-norm (maximum of absolute values) of the array is normalized. + [CV_C] + + + + + The L1-norm (sum of absolute values) of the array is normalized. + [CV_L1] + + + + + The (Euclidean) L2-norm of the array is normalized. + [CV_L2] + + + + + [NORM_L2SQR] + + + + + [NORM_HAMMING] + + + + + [NORM_HAMMING2] + + + + + [CV_NORM_MASK] + + + + + [CV_RELATIVE] + + + + + [CV_DIFF] + + + + + The array values are scaled and shifted to the specified range. + [CV_MINMAX] + + + + + [CV_DIFF_C] + + + + + [CV_DIFF_L1] + + + + + [CV_DIFF_L2] + + + + + [CV_RELATIVE_C] + + + + + [CV_RELATIVE_L1] + + + + + [CV_RELATIVE_L2] + + + + + The dimension index along which the matrix is reduce. + + + + + The matrix is reduced to a single row. + [= 0] + + + + + The matrix is reduced to a single column. + [= 1] + + + + + The dimension is chosen automatically by analysing the dst size. + [= -1] + + + + + The reduction operations for cvReduce + + + + + The output is the sum of all the matrix rows/columns. + [CV_REDUCE_SUM] + + + + + The output is the mean vector of all the matrix rows/columns. + [CV_REDUCE_AVG] + + + + + The output is the maximum (column/row-wise) of all the matrix rows/columns. + [CV_REDUCE_MAX] + + + + + The output is the minimum (column/row-wise) of all the matrix rows/columns. + [CV_REDUCE_MIN] + + + + + Specifies, which of edges of the same quad-edge as the input one to return + + + + + the input edge (e on the picture above if e is the input edge) + [= 0] + + + + + the rotated edge (eRot) + [= 1] + + + + + the reversed edge (reversed e (in green)) + [= 2] + + + + + the reversed rotated edge (reversed eRot (in green)) + [= 3] + + + + + The field flagscontain the particular dynamic type signature + (CV_SEQ_MAGIC_VAL for dense sequences and CV_SET_MAGIC_VAL for sparse sequences) in the highest 16 bits and miscellaneous information about the sequence. + The lowest CV_SEQ_ELTYPE_BITS bits contain the ID of the element type. + + + + + If the sequence is not passed to any function working with a specific type of sequences, you may use this value + + + + + (x,y) [CV_SEQ_ELTYPE_POINT] + + + + + freeman code: 0..7 [CV_SEQ_ELTYPE_CODE] + + + + + unspecified type of sequence elements [CV_SEQ_ELTYPE_GENERIC] + + + + + =6 [CV_SEQ_ELTYPE_PTR] + + + + + &elem: pointer to element of other sequence [CV_SEQ_ELTYPE_PPOINT] + + + + + #elem: index of element of some other sequence [CV_SEQ_ELTYPE_INDEX] + + + + + &next_o, &next_d, &vtx_o, &vtx_d [CV_SEQ_ELTYPE_GRAPH_EDGE] + + + + + first_edge, &(x,y) [CV_SEQ_ELTYPE_GRAPH_VERTEX] + + + + + vertex of the binary tree [CV_SEQ_ELTYPE_TRIAN_ATR] + + + + + connected component [CV_SEQ_ELTYPE_CONNECTED_COMP] + + + + + (x,y,z) [CV_SEQ_ELTYPE_POINT3D] + + + + + 1-channel 8-bit unsigned integers [CV_8UC1] + + + + + 2-channel 8-bit unsigned integers [CV_8UC2] + + + + + 3-channel 8-bit unsigned integers [CV_8UC3] + + + + + 4-channel 8-bit unsigned integers [CV_8UC4] + + + + + 1-channel 8-bit signed integers [CV_8SC1] + + + + + 2-channel 8-bit signed integers [CV_8SC2] + + + + + 3-channel 8-bit signed integers [CV_8SC3] + + + + + 4-channel 8-bit signed integers [CV_8SC4] + + + + + 1-channel 16-bit unsigned integers [CV_16UC1] + + + + + 2-channel 16-bit unsigned integers [CV_16UC2] + + + + + 3-channel 16-bit unsigned integers [CV_16UC3] + + + + + 4-channel 16-bit unsigned integers [CV_16UC4] + + + + + 1-channel 16-bit signed integers [CV_16SC1] + + + + + 2-channel 16-bit signed integers [CV_16SC2] + + + + + 3-channel 16-bit signed integers [CV_16SC3] + + + + + 4-channel 16-bit signed integers [CV_16SC4] + + + + + 1-channel 32-bit signed integers [CV_32SC1] + + + + + 2-channel 32-bit signed integers [CV_32SC2] + + + + + 3-channel 32-bit signed integers [CV_32SC3] + + + + + 4-channel 32-bit signed integers [CV_32SC4] + + + + + 1-channel 32-bit floating-point numbers [CV_32FC1] + + + + + 2-channel 32-bit floating-point numbers [CV_32FC2] + + + + + 3-channel 32-bit floating-point numbers [CV_32FC3] + + + + + 4-channel 32-bit floating-point numbers [CV_32FC4] + + + + + 1-channel 64-bit floating-point numbers [CV_64FC1] + + + + + 2-channel 64-bit floating-point numbers [CV_64FC2] + + + + + 3-channel 64-bit floating-point numbers [CV_64FC3] + + + + + 4-channel 64-bit floating-point numbers [CV_64FC4] + + + + + [CV_SEQ_KIND_GENERIC] + + + + + [CV_SEQ_KIND_GENERIC] + + + + + [CV_SEQ_KIND_BIN_TREE] + + + + + [CV_SEQ_KIND_GRAPH] + + + + + [CV_SEQ_KIND_SUBDIV2D] + + + + + flags for curves [CV_SEQ_FLAG_CLOSED] + + + + + flags for curves [CV_SEQ_FLAG_SIMPLE] + + + + + flags for curves [CV_SEQ_FLAG_CONVEX] + + + + + flags for curves [CV_SEQ_FLAG_HOLE] + + + + + flags for graphs [CV_GRAPH_FLAG_ORIENTED] + + + + + flags for graphs [CV_GRAPH_FLAG_ORIENTED] + + + + + flags for graphs [CV_GRAPH_FLAG_ORIENTED] + + + + + point sets [CV_SEQ_POINT_SET] + + + + + point sets [CV_SEQ_POINT3D_SET] + + + + + point sets [CV_SEQ_POLYLINE] + + + + + point sets [CV_SEQ_POLYGON] + + + + + point sets [CV_SEQ_CONTOUR] + + + + + point sets [CV_SEQ_SIMPLE_POLYGON] + + + + + chain-coded curves [CV_SEQ_CHAIN] + + + + + chain-coded curves [CV_SEQ_CHAIN_CONTOUR] + + + + + binary tree for the contour [CV_SEQ_POLYGON_TREE] + + + + + sequence of the connected components [CV_SEQ_CONNECTED_COMP] + + + + + sequence of the integer numbers [CV_SEQ_INDEX] + + + + + Type of the smoothing operations + + + + + (simple blur with no scaling) - for each pixel the result is a sum of pixels values in size1×size2 neighborhood of the pixel. + If the neighborhood size varies from pixel to pixel, compute the sums using integral image (cvIntegral). + [CV_BLUR_NO_SCALE] + + + + + (simple blur) - for each pixel the result is the average value (brightness/color) of size1×size2 neighborhood of the pixel. + [CV_BLUR] + + + + + (Gaussian blur) - the image is smoothed using the Gaussian kernel of aperture size size1×size2. sigma1 and sigma2 may optionally be used to specify shape of the kernel. + [CV_GAUSSIAN] + + + + + (median blur) - the image is smoothed using medial filter of size size1×size1 (i.e. only square aperture can be used). + That is, for each pixel the result is the median computed over size1×size1 neighborhood. + [CV_MEDIAN] + + + + + (bilateral filter) - the image is smoothed using a bilateral 3x3 filter with color sigma=sigma1 and spatial sigma=sigma2. + If size1!=0, then a circular kernel with diameter size1 is used; otherwise the diameter of the kernel is computed from sigma2. + [CV_BILATERAL] + + + + + Order flags for cvSort + + + + + ID of one of the pre-defined parameter sets for CreateStereoBMState + + + + + [CV_STEREO_BM_BASIC] + + + + + [CV_STEREO_BM_FISH_EYE] + + + + + [CV_STEREO_BM_NARROW] + + + + + Kinds of locating point for cvSubdiv2DLocate + + + + + One of input arguments is invalid. Runtime error is raised or, if silent or "parent" error processing mode is selected + [CV_PTLOC_ERROR] + + + + + Point is outside the subdivision reference rectangle. + [CV_PTLOC_OUTSIDE_RECT] + + + + + Point falls into some facet. + [CV_PTLOC_INSIDE] + + + + + Point coincides with one of subdivision vertices. + [CV_PTLOC_VERTEX] + + + + + Point falls onto the edge. + [CV_PTLOC_ON_EDGE] + + + + + Operation flags for cvSVD + + + + + No flags + [0] + + + + + No flags + [0] + + + + + enables modification of matrix src1 during the operation. It speeds up the processing. + [CV_SVD_MODIFY_A] + + + + + means that the transposed matrix U is returned. Specifying the flag speeds up the processing. + [CV_SVD_U_T] + + + + + means that the transposed matrix V is returned. Specifying the flag speeds up the processing. + [CV_SVD_V_T] + + + + + Thresholding type + + + + + [CV_THRESH_BINARY] + + + + + [CV_THRESH_BINARY_INV] + + + + + [CV_THRESH_TRUNC] + + + + + [CV_THRESH_TOZERO] + + + + + [CV_THRESH_TOZERO_INV] + + + + + [CV_THRESH_MASK] + + + + + Otsu algorithm + [CV_THRESH_OTSU] + + + + + Video capturing class + + + + + Capture type (File or Camera) + + + + + Track whether Dispose has been called + + + + + Allocates and initialized the CvCapture structure for reading a video stream from the camera. + Currently two camera interfaces can be used on Windows: Video for Windows (VFW) and Matrox Imaging Library (MIL); and two on Linux: V4L and FireWire (IEEE1394). + + Index of the camera to be used. If there is only one camera or it does not matter what camera to use -1 may be passed. + + + + + Allocates and initialized the CvCapture structure for reading a video stream from the camera. + Currently two camera interfaces can be used on Windows: Video for Windows (VFW) and Matrox Imaging Library (MIL); and two on Linux: V4L and FireWire (IEEE1394). + + Device type + + + + + Allocates and initialized the CvCapture structure for reading a video stream from the camera. + Currently two camera interfaces can be used on Windows: Video for Windows (VFW) and Matrox Imaging Library (MIL); and two on Linux: V4L and FireWire (IEEE1394). + + Device type + Index of the camera to be used. If there is only one camera or it does not matter what camera to use -1 may be passed. + + + + + Allocates and initialized the CvCapture structure for reading a video stream from the camera. + Currently two camera interfaces can be used on Windows: Video for Windows (VFW) and Matrox Imaging Library (MIL); and two on Linux: V4L and FireWire (IEEE1394). + + Index of the camera to be used. If there is only one camera or it does not matter what camera to use -1 may be passed. + + + + + Allocates and initialized the CvCapture structure for reading a video stream from the camera. + Currently two camera interfaces can be used on Windows: Video for Windows (VFW) and Matrox Imaging Library (MIL); and two on Linux: V4L and FireWire (IEEE1394). + + Device type + + + + + Allocates and initialized the CvCapture structure for reading a video stream from the camera. + Currently two camera interfaces can be used on Windows: Video for Windows (VFW) and Matrox Imaging Library (MIL); and two on Linux: V4L and FireWire (IEEE1394). + + Device type + Index of the camera to be used. If there is only one camera or it does not matter what camera to use -1 may be passed. + + + + + Allocates and initialized the CvCapture structure for reading the video stream from the specified file. + After the allocated structure is not used any more it should be released by cvReleaseCapture function. + + Name of the video file. + + + + + Allocates and initialized the CvCapture structure for reading the video stream from the specified file. + After the allocated structure is not used any more it should be released by cvReleaseCapture function. + + Name of the video file. + + + + + ポインタから初期化 + + CvCapture* + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + Gets the capture type (File or Camera) + + + + + Gets or sets film current position in milliseconds or video capture timestamp + + + + + Gets or sets 0-based index of the frame to be decoded/captured next + + + + + Gets or sets relative position of video file + + + + + Gets or sets width of frames in the video stream + + + + + Gets or sets height of frames in the video stream + + + + + Gets or sets frame rate + + + + + Gets or sets 4-character code of codec + + + + + Gets number of frames in video file + + + + + Gets or sets brightness of image (only for cameras) + + + + + Gets or sets contrast of image (only for cameras) + + + + + Gets or sets saturation of image (only for cameras) + + + + + Gets or sets hue of image (only for cameras) + + + + + The format of the Mat objects returned by retrieve() + + + + + A backend-specific value indicating the current capture mode + + + + + Gain of the image (only for cameras) + + + + + Exposure (only for cameras) + + + + + Boolean flags indicating whether images should be converted to RGB + + + + + + + + + + TOWRITE (note: only supported by DC1394 v 2.x backend currently) + + + + + + + + + + + [CV_CAP_PROP_SHARPNESS] + + + + + exposure control done by camera, + user can adjust refernce level using this feature + [CV_CAP_PROP_AUTO_EXPOSURE] + + + + + + [CV_CAP_PROP_GAMMA] + + + + + + [CV_CAP_PROP_TEMPERATURE] + + + + + + [CV_CAP_PROP_TRIGGER] + + + + + + [CV_CAP_PROP_TRIGGER_DELAY] + + + + + + [CV_CAP_PROP_WHITE_BALANCE_RED_V] + + + + + + [CV_CAP_PROP_MAX_DC1394] + + + + + property for highgui class CvCapture_Android only + [CV_CAP_PROP_AUTOGRAB] + + + + + readonly, tricky property, returns cpnst char* indeed + [CV_CAP_PROP_SUPPORTED_PREVIEW_SIZES_STRING] + + + + + readonly, tricky property, returns cpnst char* indeed + [CV_CAP_PROP_PREVIEW_FORMAT] + + + + + + [CV_CAP_PROP_OPENNI_OUTPUT_MODE] + + + + + in mm + [CV_CAP_PROP_OPENNI_FRAME_MAX_DEPTH] + + + + + in mm + [CV_CAP_PROP_OPENNI_BASELINE] + + + + + in pixels + [CV_CAP_PROP_OPENNI_FOCAL_LENGTH] + + + + + flag + [CV_CAP_PROP_OPENNI_REGISTRATION_ON] + + + + + flag that synchronizes the remapping depth map to image map + by changing depth generator's view point (if the flag is "on") or + sets this view point to its normal one (if the flag is "off"). + [CV_CAP_PROP_OPENNI_REGISTRATION] + + + + + + [CV_CAP_OPENNI_IMAGE_GENERATOR_OUTPUT_MODE] + + + + + + [CV_CAP_OPENNI_DEPTH_GENERATOR_BASELINE] + + + + + + [CV_CAP_OPENNI_DEPTH_GENERATOR_FOCAL_LENGTH] + + + + + + [CV_CAP_OPENNI_DEPTH_GENERATOR_REGISTRATION_ON] + + + + + default is 1 + [CV_CAP_GSTREAMER_QUEUE_LENGTH] + + + + + ip for anable multicast master mode. 0 for disable multicast + [CV_CAP_PROP_PVAPI_MULTICASTIP] + + + + + Change image resolution by binning or skipping. + [CV_CAP_PROP_XI_DOWNSAMPLING] + + + + + Output data format. + [CV_CAP_PROP_XI_DATA_FORMAT] + + + + + Horizontal offset from the origin to the area of interest (in pixels). + [CV_CAP_PROP_XI_OFFSET_X] + + + + + Vertical offset from the origin to the area of interest (in pixels). + [CV_CAP_PROP_XI_OFFSET_Y] + + + + + Defines source of trigger. + [CV_CAP_PROP_XI_TRG_SOURCE] + + + + + Generates an internal trigger. PRM_TRG_SOURCE must be set to TRG_SOFTWARE. + [CV_CAP_PROP_XI_TRG_SOFTWARE] + + + + + Selects general purpose input + [CV_CAP_PROP_XI_GPI_SELECTOR] + + + + + Set general purpose input mode + [CV_CAP_PROP_XI_GPI_MODE] + + + + + Get general purpose level + [CV_CAP_PROP_XI_GPI_LEVEL] + + + + + Selects general purpose output + [CV_CAP_PROP_XI_GPO_SELECTOR] + + + + + Set general purpose output mode + [CV_CAP_PROP_XI_GPO_MODE] + + + + + Selects camera signalling LED + [CV_CAP_PROP_XI_LED_SELECTOR] + + + + + Define camera signalling LED functionality + [CV_CAP_PROP_XI_LED_MODE] + + + + + Calculates White Balance(must be called during acquisition) + [CV_CAP_PROP_XI_MANUAL_WB] + + + + + Automatic white balance + [CV_CAP_PROP_XI_AUTO_WB] + + + + + Automatic exposure/gain + [CV_CAP_PROP_XI_AEAG] + + + + + Exposure priority (0.5 - exposure 50%, gain 50%). + [CV_CAP_PROP_XI_EXP_PRIORITY] + + + + + Maximum limit of exposure in AEAG procedure + [CV_CAP_PROP_XI_AE_MAX_LIMIT] + + + + + Maximum limit of gain in AEAG procedure + [CV_CAP_PROP_XI_AG_MAX_LIMIT] + + + + + default is 1 + [CV_CAP_PROP_XI_AEAG_LEVEL] + + + + + default is 1 + [CV_CAP_PROP_XI_TIMEOUT] + + + + + Retrieves the specified property of camera or video file. + + property identifier. + property value + + + + Retrieves the specified property of camera or video file. + + property identifier. + property value + + + + Grabs the frame from camera or file. The grabbed frame is stored internally. + The purpose of this function is to grab frame fast that is important for syncronization in case of reading from several cameras simultaneously. + The grabbed frames are not exposed because they may be stored in compressed format (as defined by camera/driver). + To retrieve the grabbed frame, cvRetrieveFrame should be used. + + + + + + Grabs a frame from camera or video file, decompresses and returns it. + This function is just a combination of cvGrabFrame and cvRetrieveFrame in one call. + The returned image should not be released or modified by user. + + + + + + Returns the pointer to the image grabbed with cvGrabFrame function. + The returned image should not be released or modified by user. + + + + + + Returns the pointer to the image grabbed with cvGrabFrame function. + The returned image should not be released or modified by user. + + non-zero streamIdx is only valid for multi-head camera live streams + + + + + Returns the pointer to the image grabbed with cvGrabFrame function. + The returned image should not be released or modified by user. + + non-zero streamIdx is only valid for multi-head camera live streams + + + + + Sets the specified property of video capturing. + + property identifier. + value of the property. + + + + + Sets the specified property of video capturing. + + property identifier. + value of the property. + + + + + Int32の各バイトにアクセスしやすくするための共用体 + + + + + AVI Video File Writer + + + + + Track whether Dispose has been called + + + + + Creates video writer structure. + + Name of the output video file. + 4-character code of codec used to compress the frames. For example, "PIM1" is MPEG-1 codec, "MJPG" is motion-jpeg codec etc. + Under Win32 it is possible to pass null in order to choose compression method and additional compression parameters from dialog. + Framerate of the created video stream. + Size of video frames. + + + + Creates video writer structure. + + Name of the output video file. + 4-character code of codec used to compress the frames. For example, "PIM1" is MPEG-1 codec, "MJPG" is motion-jpeg codec etc. + Under Win32 it is possible to pass null in order to choose compression method and additional compression parameters from dialog. + Framerate of the created video stream. + Size of video frames. + If it is true, the encoder will expect and encode color frames, otherwise it will work with grayscale frames (the flag is currently supported on Windows only). + + + + Creates video writer structure. + + Name of the output video file. + 4-character code of codec used to compress the frames. For example, "PIM1" is MPEG-1 codec, "MJPG" is motion-jpeg codec etc. + Under Win32 it is possible to pass null in order to choose compression method and additional compression parameters from dialog. + Framerate of the created video stream. + Size of video frames. + + + + + Creates video writer structure. + + Name of the output video file. + 4-character code of codec used to compress the frames. For example, "PIM1" is MPEG-1 codec, "MJPG" is motion-jpeg codec etc. + Under Win32 it is possible to pass null in order to choose compression method and additional compression parameters from dialog. + Framerate of the created video stream. + Size of video frames. + If it is true, the encoder will expect and encode color frames, otherwise it will work with grayscale frames (the flag is currently supported on Windows only). + + + + + Creates video writer structure. + + Name of the output video file. + 4-character code of codec used to compress the frames. For example, "PIM1" is MPEG-1 codec, "MJPG" is motion-jpeg codec etc. + Under Win32 it is possible to pass null in order to choose compression method and additional compression parameters from dialog. + Framerate of the created video stream. + Size of video frames. + + + + + Creates video writer structure. + + Name of the output video file. + 4-character code of codec used to compress the frames. For example, "PIM1" is MPEG-1 codec, "MJPG" is motion-jpeg codec etc. + Under Win32 it is possible to pass null in order to choose compression method and additional compression parameters from dialog. + Framerate of the created video stream. + Size of video frames. + If it is true, the encoder will expect and encode color frames, otherwise it will work with grayscale frames (the flag is currently supported on Windows only). + + + + + ポインタから初期化 + + CvVideoWriter* + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + Get output video file name + + + + + Frames per second of the output vide + + + + + Get size of frame image + + + + + Get whether output frames is color or not + + + + + Writes/appends one frame to video file. + + the written frame. + + + + + Represents a OpenCV-based class which has a native pointer. + + + + + Unmanaged OpenCV data pointer + + + + + Polar line segment retrieved from cvHoughLines2 + + + + + Length of the line + + + + + Angle of the line (radian) + + + + + Constructor + + Length of the line + Angle of the line (radian) + + + + Specifies whether this object contains the same members as the specified Object. + + The Object to test. + This method returns true if obj is the same type as this object and has the same members as this object. + + + + Compares two CvPoint objects. The result specifies whether the members of each object are equal. + + A Point to compare. + A Point to compare. + This operator returns true if the members of left and right are equal; otherwise, false. + + + + Compares two CvPoint objects. The result specifies whether the members of each object are unequal. + + A Point to compare. + A Point to compare. + This operator returns true if the members of left and right are unequal; otherwise, false. + + + + Specifies whether this object contains the same members as the specified Object. + + The Object to test. + This method returns true if obj is the same type as this object and has the same members as this object. + + + + Returns a hash code for this object. + + An integer value that specifies a hash value for this object. + + + + Converts this object to a human readable string. + + A string that represents this object. + + + + Calculates a intersection of the specified two lines + + + + + + + + Calculates a intersection of the specified two lines + + + + + + + CvLineSegmentPointに変換する + + + + + + + 指定したx座標を両端とするような線分に変換する + + + + + + + + 指定したy座標を両端とするような線分に変換する + + + + + + + + 指定したy座標を通るときのx座標を求める + + + + + + + 指定したx座標を通るときのy座標を求める + + + + + + + A sequence slice + + + + + start index (inclusive) + + + + + end index (exclusive) + + + + + sizeof(CvSlice) + + + + + シーケンス全体をあらわすスライスのスライス長を取得する + + + + + シーケンス全体をあらわすスライスを取得する + + + + + Constructor + + + + + + + Calculates the sequence slice length + + Sequence + + + + + Compares two CvPoint objects. The result specifies whether the members of each object are equal. + + A Point to compare. + A Point to compare. + This operator returns true if the members of left and right are equal; otherwise, false. + + + + Compares two CvPoint objects. The result specifies whether the members of each object are unequal. + + A Point to compare. + A Point to compare. + This operator returns true if the members of left and right are unequal; otherwise, false. + + + + Specifies whether this object contains the same members as the specified Object. + + The Object to test. + This method returns true if obj is the same type as this object and has the same members as this object. + + + + Specifies whether this object contains the same members as the specified Object. + + The Object to test. + This method returns true if obj is the same type as this object and has the same members as this object. + + + + Returns a hash code for this object. + + An integer value that specifies a hash value for this object. + + + + Converts this object to a human readable string. + + A string that represents this object. + + + + one of edges within quad-edge, lower 2 bits is index (0..3) + and upper bits are quad-edge pointer + + + typedef size_t CvSubdiv2DEdge; + typedef unsigned int size_t; + + + + + Data (size_t) + + + + + Constructor + + + + + + Constructor + + + + + + Constructor + + + + + + Implicit cast to uint + + + + + + + Implicit cast to ulong + + + + + + + Implicit cast to IntPtr + + + + + + + Implicit cast from uint to CvSubdiv2DEdge + + + + + + + Implicit cast from IntPtr to CvSubdiv2DEdge + + + + + + + Implicit cast from IntPtr to CvSubdiv2DEdge + + + + + + + Returns one of edges related to given (cvSubdiv2DGetEdge). + + Specifies, which of related edges to return + one the edges related to the input edge + + + + Returns edge destination (cvSubdiv2DEdgeDst)． + + The edge destination. If the edge is from dual subdivision and the virtual point coordinates are not calculated yet, the returned pointer may be null. + + + + Returns edge origin (cvSubdiv2DEdgeOrg)． + + The edge origin. If the edge is from dual subdivision and the virtual point coordinates are not calculated yet, the returned pointer may be null. + + + + Returns another edge of the same quad-edge (cvSubdiv2DRotateEdge). + + one the edges of the same quad-edge as the input edge. + + + + Converts this object to a human readable string. + + A string that represents this object. + + + + Point of original or dual subdivision + + + + + Initializes from native pointer + + + + + + Initializes from native pointer + + + + + + Creates a CvSubdiv2DPoint instance from native pointer + + + + + + + Explicit cast from IntPtr to CvSubdiv2DPoint + + + + + + + sizeof(CvSubdiv2DPoint) + + + + + Miscellaneous flags + + + + + + + + + + + + + + + + + + + + Specifies, which of related edges to return + + + + + Next around the edge origin (eOnext on the picture above if e is the input edge) + [CV_NEXT_AROUND_ORG] + + + + + Next around the edge vertex (eDnext) + [CV_NEXT_AROUND_DST] + + + + + Previous around the edge origin (reversed eRnext) + [CV_PREV_AROUND_ORG] + + + + + Previous around the edge destination (reversed eLnext) + [CV_PREV_AROUND_DST] + + + + + Next around the left facet (eLnext) + [CV_NEXT_AROUND_LEFT] + + + + + Next around the right facet (eRnext) + [CV_NEXT_AROUND_RIGHT] + + + + + Previous around the left facet (reversed eOnext) + [CV_PREV_AROUND_LEFT] + + + + + Previous around the right facet (reversed eDnext) + [CV_PREV_AROUND_RIGHT] + + + + + SURF keypoints + + + + + Position of the feature within the image + + + + + -1, 0 or +1. sign of the laplacian at the point. + can be used to speedup feature comparison + (normally features with laplacians of different signs can not match) + + + + + size of the feature + + + + + orientation of the feature: 0..360 degrees + + + + + value of the hessian (can be used to approximately estimate the feature strengths; + see also params._hessianThreshold) + + + + + Constructor + + Position of the feature within the image + -1, 0 or +1. sign of the laplacian at the point. + can be used to speedup feature comparison + (normally features with laplacians of different signs can not match) + size of the feature + orientation of the feature: 0..360 degrees + value of the hessian (can be used to approximately estimate the feature strengths; see also params._hessianThreshold) + + + + Initializes from native pointer + + CvSURFPoint* + + + + Creates CvSURFPoint instance from native ponter + + + + + + + Termination criteria for iterative algorithms + + + + + A combination of CriteriaType flags + + + + + Maximum number of iterations + + + + + Accuracy to achieve + + + + + sizeof(CvTermCriteria) + + + + + Constructor + + maximum number of iterations + + + + Constructor + + accuracy to achieve + + + + Constructor + + maximum number of iterations + accuracy to achieve + + + + Constructor + + a combination of CriteriaType flags + maximum number of iterations + accuracy to achieve + + + + Check termination criteria and transform it so that type=CriteriaType.Iteration | CriteriaType.Epsilon, + and both max_iter and epsilon are valid + + Default epsilon + Default maximum number of iteration + + + + + Sub-pixel accurate size of a rectangle + + + + + Width of the box + + + + + Height of the box + + + + + sizeof(CvSize2D32f) + + + + + Represents a CvSize2D32f structure with its properties left uninitialized. + + + + + Constructor + + Width of the box + Height of the box + + + + Creates a CvSize with the coordinates of the specified CvSize2D32f. + + A CvSize2D32f that specifies the coordinates for the new CvSize. + + + + + Creates a CvSize2D32f with the coordinates of the specified CvSize. + + A CvSize that specifies the coordinates for the new CvSize2D32f. + + + + + Specifies whether this object contains the same members as the specified Object. + + The Object to test. + This method returns true if obj is the same type as this object and has the same members as this object. + + + + Compares two CvPoint objects. The result specifies whether the members of each object are equal. + + A Point to compare. + A Point to compare. + This operator returns true if the members of left and right are equal; otherwise, false. + + + + Compares two CvPoint objects. The result specifies whether the members of each object are unequal. + + A Point to compare. + A Point to compare. + This operator returns true if the members of left and right are unequal; otherwise, false. + + + + Specifies whether this object contains the same members as the specified Object. + + The Object to test. + This method returns true if obj is the same type as this object and has the same members as this object. + + + + Returns a hash code for this object. + + An integer value that specifies a hash value for this object. + + + + Converts this object to a human readable string. + + A string that represents this object. + + + + 2D point with double precision floating-point coordinates + + + + + x-coordinate, usually zero-based + + + + + y-coordinate, usually zero-based + + + + + sizeof(CvPoint2D64f) + + + + + Represents a CvPoint2D64f structure with its properties left uninitialized. + + + + + Constructor + + x-coordinate, usually zero-based + y-coordinate, usually zero-based + + + + Creates a CvPoint with the coordinates of the specified CvPoint2D64f. + + A CvPoint2D64f that specifies the coordinates for the new CvPoint. + + + + + Creates a CvPoint2D64f with the coordinates of the specified CvPoint. + + A CvPoint that specifies the coordinates for the new CvPoint2D64f. + + + + + Creates a CvPoint2D32f with the coordinates of the specified CvPoint2D64f. + + A CvPoint2D64f that specifies the coordinates for the new CvPoint2D32f. + + + + + Creates a CvPoint2D64f with the coordinates of the specified CvPoint2D32f. + + A CvPoint2D32f that specifies the coordinates for the new CvPoint2D64f. + + + + + Specifies whether this object contains the same members as the specified Object. + + The Object to test. + This method returns true if obj is the same type as this object and has the same members as this object. + + + + Compares two CvPoint objects. The result specifies whether the values of the X and Y properties of the two CvPoint objects are equal. + + A Point to compare. + A Point to compare. + This operator returns true if the X and Y values of left and right are equal; otherwise, false. + + + + Compares two CvPoint2D64f objects. The result specifies whether the values of the X or Y properties of the two CvPoint2D64f objects are unequal. + + A Point to compare. + A Point to compare. + This operator returns true if the values of either the X properties or the Y properties of left and right differ; otherwise, false. + + + + Unary plus operator + + + + + + + Unary minus operator + + + + + + + Shifts point by a certain offset + + + + + + + + Shifts point by a certain offset + + + + + + + + Shifts point by a certain offset + + + + + + + + Specifies whether this object contains the same members as the specified Object. + + The Object to test. + This method returns true if obj is the same type as this object and has the same members as this object. + + + + Returns a hash code for this object. + + An integer value that specifies a hash value for this object. + + + + Converts this object to a human readable string. + + A string that represents this object. + + + + 3D point with floating-point coordinates + + + + + x-coordinate, usually zero-based + + + + + y-coordinate, usually zero-based + + + + + z-coordinate, usually zero-based + + + + + sizeof(CvPoint3D32f) + + + + + Represents a CvPoint3D32f structure with its properties left uninitialized. + + + + + Constructor + + x-coordinate, usually zero-based + y-coordinate, usually zero-based + z-coordinate, usually zero-based + + + + Constructor + + x-coordinate, usually zero-based + y-coordinate, usually zero-based + z-coordinate, usually zero-based + + + + Specifies whether this object contains the same members as the specified Object. + + The Object to test. + This method returns true if obj is the same type as this object and has the same members as this object. + + + + Compares two CvPoint3D32f objects. The result specifies whether the values of the X, Y and Z properties of the two CvPoint3D32f objects are equal. + + A Point to compare. + A Point to compare. + This operator returns true if the X, Y and Z values of left and right are equal; otherwise, false. + + + + Compares two CvPoint3D32f objects. The result specifies whether the values of the X, Y or Z properties of the two CvPoint3D32f objects are unequal. + + A Point to compare. + A Point to compare. + This operator returns true if the values of either the X properties, Y properties or the Z properties of left and right differ; otherwise, false. + + + + Unary plus operator + + + + + + + Unary minus operator + + + + + + + Shifts point by a certain offset + + + + + + + + Shifts point by a certain offset + + + + + + + + Shifts point by a certain offset + + + + + + + + Specifies whether this object contains the same members as the specified Object. + + The Object to test. + This method returns true if obj is the same type as this object and has the same members as this object. + + + + Returns a hash code for this object. + + An integer value that specifies a hash value for this object. + + + + Converts this object to a human readable string. + + A string that represents this object. + + + + Returns the distance between the specified two points + + + + + + + + Returns the distance between the specified two points + + + + + + + 3D point with double precision floating-point coordinates + + + + + x-coordinate, usually zero-based + + + + + y-coordinate, usually zero-based + + + + + z-coordinate, usually zero-based + + + + + sizeof(CvPoint3D64f) + + + + + Represents a CvPoint3D64f structure with its properties left uninitialized. + + + + + Constructor + + x-coordinate, usually zero-based + y-coordinate, usually zero-based + z-coordinate, usually zero-based + + + + Creates a CvPoint3D32f with the coordinates of the specified CvPoint3D64f. + + A CvPoint3D64f that specifies the coordinates for the new CvPoint3D32f. + + + + + Creates a CvPoint3D64f with the coordinates of the specified CvPoint3D32f. + + A CvPoint3D32f that specifies the coordinates for the new CvPoint3D64f. + + + + + Specifies whether this object contains the same members as the specified Object. + + The Object to test. + This method returns true if obj is the same type as this object and has the same members as this object. + + + + Compares two CvPoint3D64f objects. The result specifies whether the values of the X, Y and Z properties of the two CvPoint3D64f objects are equal. + + A Point to compare. + A Point to compare. + This operator returns true if the X, Y and Z values of left and right are equal; otherwise, false. + + + + Compares two CvPoint3D64f objects. The result specifies whether the values of the X, Y or Z properties of the two CvPoint3D64f objects are unequal. + + A Point to compare. + A Point to compare. + This operator returns true if the values of either the X properties, Y properties or the Z properties of left and right differ; otherwise, false. + + + + Unary plus operator + + + + + + + Unary minus operator + + + + + + + Shifts point by a certain offset + + + + + + + + Shifts point by a certain offset + + + + + + + + Shifts point by a certain offset + + + + + + + + Specifies whether this object contains the same members as the specified Object. + + The Object to test. + This method returns true if obj is the same type as this object and has the same members as this object. + + + + Returns a hash code for this object. + + An integer value that specifies a hash value for this object. + + + + Converts this object to a human readable string. + + A string that represents this object. + + + + Returns the distance between the specified two points + + + + + + + + Returns the distance between the specified two points + + + + + + + Line segment structure retrieved from cvHoughLines2 + + + + + 1st Point + + + + + 2nd Point + + + + + Constructor + + 1st Point + 2nd Point + + + + Specifies whether this object contains the same members as the specified Object. + + The Object to test. + This method returns true if obj is the same type as this object and has the same members as this object. + + + + Compares two CvPoint objects. The result specifies whether the members of each object are equal. + + A Point to compare. + A Point to compare. + This operator returns true if the members of left and right are equal; otherwise, false. + + + + Compares two CvPoint objects. The result specifies whether the members of each object are unequal. + + A Point to compare. + A Point to compare. + This operator returns true if the members of left and right are unequal; otherwise, false. + + + + Specifies whether this object contains the same members as the specified Object. + + The Object to test. + This method returns true if obj is the same type as this object and has the same members as this object. + + + + Returns a hash code for this object. + + An integer value that specifies a hash value for this object. + + + + Converts this object to a human readable string. + + A string that represents this object. + + + + Calculates a intersection of the specified two lines + + + + + + + + Calculates a intersection of the specified two lines + + + + + + + Calculates a intersection of the specified two segments + + + + + + + + Calculates a intersection of the specified two segments + + + + + + + Returns a boolean value indicating whether the specified two segments intersect. + + + + + + + + Returns a boolean value indicating whether the specified two segments intersect. + + + + + + + Returns a boolean value indicating whether a line and a segment intersect. + + Line + Segment + + + + + Calculates a intersection of a line and a segment + + + + + + + + + + + + + + + Translates the Point by the specified amount. + + The amount to offset the x-coordinate. + The amount to offset the y-coordinate. + + + + + Translates the Point by the specified amount. + + The Point used offset this CvPoint. + + + + + 線分が交差しているかどうか + + + + + + + + Structure which represents t* + + + + + + IntPtr + + + + + Null pointer + + + + + Constructor + + + + + + Address + + + + + entity of the pointer (*t) + + + + + implicit cast to IntPtr + + + + + + + explicit cast to t + + + + + + + A class to access a native pointer like array + + + + + pointer + + + + + sizeof(T) + + + + + Initializes from IntPtr + + + + + + Initializes from void* + + + + + + Unmanaged pointer (T*) + + + + + + Indexer + + zero-based component of the element index + the particular array element + + + + Return the particular element of array + + zero-based component of the element index + the particular array element + + + + Change the particular array element + + zero-based component of the element index + The assigned value + + + + + + + + + + Data pointer + + + + + Indexer + + + + + + + + ptr[index] + + + + + + + + ptr[index] = value; + + + + + + + + Managed wrapper of array pointer (Single**) + + + + + pointer + + + + + Initializes from IntPtr + + + + + + Initializes from Single** + + + + + + Unmanaged pointer (Single**) + + + + + + Indexer + + The first zero-based component of the element index + The second zero-based component of the element index + the particular array element + + + + Return the particular element of array + + The first zero-based component of the element index + The second zero-based component of the element index + the particular array element + + + + Change the particular array element + + The first zero-based component of the element index + The second zero-based component of the element index + The assigned value + + + + Structure that represents RGB color (alias of CvScalar). + + + + + Red + + + + + Green + + + + + Blue + + + + + Constructor + + Red + Green + Blue + + + + Constructor + + Red + Green + Blue + + + + Construct from + + A value specifying the 32-bit ARGB value. + + + + Creates a random color + + + + + + Creates a CvScalar with the members of the specified CvColor. + + A CvColor that specifies the coordinates for the new CvScalar. + CvScalar + + + + Creates a CvColor with the members of the specified CvScalar. + + A CvScalar that specifies the coordinates for the new CvPoint. + CvColor + + + + Compares two CvPoint objects. The result specifies whether the members of each CvPoint object are equal. + + A Point to compare. + A Point to compare. + This operator returns true if the members of left and right are equal; otherwise, false. + + + + Compares two CvPoint objects. The result specifies whether the members of each CvPoint object are unequal. + + A Point to compare. + A Point to compare. + This operator returns true if the members of left and right are unequal; otherwise, false. + + + + Specifies whether this object contains the same members as the specified Object. + + The Object to test. + This method returns true if obj is the same type as this object and has the same members as this object. + + + + Specifies whether this object contains the same members as the specified Object. + + The Object to test. + This method returns true if obj is the same type as this object and has the same members as this object. + + + + Returns a hash code for this object. + + An integer value that specifies a hash value for this object. + + + + Converts this object to a human readable string. + + A string that represents this object. + + + + #F0F8FF + + + + + #FAEBD7 + + + + + #00FFFF + + + + + #7FFFD4 + + + + + #F0FFFF + + + + + #F5F5DC + + + + + #FFE4C4 + + + + + #000000 + + + + + #FFEBCD + + + + + #0000FF + + + + + #8A2BE2 + + + + + #A52A2A + + + + + #DEB887 + + + + + #5F9EA0 + + + + + #7FFF00 + + + + + #D2691E + + + + + #FF7F50 + + + + + #6495ED + + + + + #FFF8DC + + + + + #DC143C + + + + + #00FFFF + + + + + #00008B + + + + + #008B8B + + + + + #B8860B + + + + + #A9A9A9 + + + + + #006400 + + + + + #BDB76B + + + + + #8B008B + + + + + #556B2F + + + + + #FF8C00 + + + + + #9932CC + + + + + #8B0000 + + + + + #E9967A + + + + + #8FBC8F + + + + + #483D8B + + + + + #2F4F4F + + + + + #00CED1 + + + + + #9400D3 + + + + + #FF1493 + + + + + #00BFFF + + + + + #696969 + + + + + #1E90FF + + + + + #B22222 + + + + + #FFFAF0 + + + + + #228B22 + + + + + #FF00FF + + + + + #DCDCDC + + + + + #F8F8FF + + + + + #FFD700 + + + + + #DAA520 + + + + + #808080 + + + + + #008000 + + + + + #ADFF2F + + + + + #F0FFF0 + + + + + #FF69B4 + + + + + #CD5C5C + + + + + #4B0082 + + + + + #FFFFF0 + + + + + #F0E68C + + + + + #E6E6FA + + + + + #FFF0F5 + + + + + #7CFC00 + + + + + #FFFACD + + + + + #ADD8E6 + + + + + #F08080 + + + + + #E0FFFF + + + + + #FAFAD2 + + + + + #D3D3D3 + + + + + #90EE90 + + + + + #FFB6C1 + + + + + #FFA07A + + + + + #20B2AA + + + + + #87CEFA + + + + + #778899 + + + + + #B0C4DE + + + + + #FFFFE0 + + + + + #00FF00 + + + + + #32CD32 + + + + + #FAF0E6 + + + + + #FF00FF + + + + + #800000 + + + + + #66CDAA + + + + + #0000CD + + + + + #BA55D3 + + + + + #9370DB + + + + + #3CB371 + + + + + #7B68EE + + + + + #00FA9A + + + + + #48D1CC + + + + + #C71585 + + + + + #191970 + + + + + #F5FFFA + + + + + #FFE4E1 + + + + + #FFE4B5 + + + + + #FFDEAD + + + + + #000080 + + + + + #FDF5E6 + + + + + #808000 + + + + + #6B8E23 + + + + + #FFA500 + + + + + #FF4500 + + + + + #DA70D6 + + + + + #EEE8AA + + + + + #98FB98 + + + + + #AFEEEE + + + + + #DB7093 + + + + + #FFEFD5 + + + + + #FFDAB9 + + + + + #CD853F + + + + + #FFC0CB + + + + + #DDA0DD + + + + + #B0E0E6 + + + + + #800080 + + + + + #FF0000 + + + + + #BC8F8F + + + + + #4169E1 + + + + + #8B4513 + + + + + #FA8072 + + + + + #F4A460 + + + + + #2E8B57 + + + + + #FFF5EE + + + + + #A0522D + + + + + #C0C0C0 + + + + + #87CEEB + + + + + #6A5ACD + + + + + #708090 + + + + + #FFFAFA + + + + + #00FF7F + + + + + #4682B4 + + + + + #D2B48C + + + + + #008080 + + + + + #D8BFD8 + + + + + #FF6347 + + + + + #40E0D0 + + + + + #EE82EE + + + + + #F5DEB3 + + + + + #FFFFFF + + + + + #F5F5F5 + + + + + #FFFF00 + + + + + #9ACD32 + + + + + 2D point with integer coordinates + + + + + x-coordinate, usually zero-based + + + + + y-coordinate, usually zero-based + + + + + sizeof(CvPoint) + + + + + Represents a CvPoint structure with its properties left uninitialized. + + + + + Constructor + + x-coordinate, usually zero-based + y-coordinate, usually zero-based + + + + Specifies whether this object contains the same members as the specified Object. + + The Object to test. + This method returns true if obj is the same type as this object and has the same members as this object. + + + + Compares two CvPoint objects. The result specifies whether the values of the X and Y properties of the two CvPoint objects are equal. + + A Point to compare. + A Point to compare. + This operator returns true if the X and Y values of left and right are equal; otherwise, false. + + + + Compares two CvPoint objects. The result specifies whether the values of the X or Y properties of the two CvPoint objects are unequal. + + A Point to compare. + A Point to compare. + This operator returns true if the values of either the X properties or the Y properties of left and right differ; otherwise, false. + + + + Unary plus operator + + + + + + + Unary minus operator + + + + + + + Shifts point by a certain offset + + + + + + + + Shifts point by a certain offset + + + + + + + + Shifts point by a certain offset + + + + + + + + Specifies whether this object contains the same members as the specified Object. + + The Object to test. + This method returns true if obj is the same type as this object and has the same members as this object. + + + + Returns a hash code for this object. + + An integer value that specifies a hash value for this object. + + + + Converts this object to a human readable string. + + A string that represents this object. + + + + Returns the distance between the specified two points + + + + + + + + Returns the distance between the specified two points + + + + + + + Calculates the dot product of two 2D vectors. + + + + + + + + Calculates the dot product of two 2D vectors. + + + + + + + Calculates the cross product of two 2D vectors. + + + + + + + + Calculates the cross product of two 2D vectors. + + + + + + + 2D point with floating-point coordinates + + + + + x-coordinate, usually zero-based + + + + + y-coordinate, usually zero-based + + + + + sizeof(CvPoint2D32f) + + + + + Represents a CvPoint2D64f structure with its properties left uninitialized. + + + + + Constructor + + x-coordinate, usually zero-based + y-coordinate, usually zero-based + + + + Constructor + + x-coordinate, usually zero-based + y-coordinate, usually zero-based + + + + Creates a CvPoint with the coordinates of the specified CvPoint2D32f. + + A CvPoint2D32f that specifies the coordinates for the new CvPoint. + + + + + Creates a CvPoint2D32f with the coordinates of the specified CvPoint. + + A CvPoint that specifies the coordinates for the new CvPoint2D32f. + + + + + Specifies whether this object contains the same members as the specified Object. + + The Object to test. + This method returns true if obj is the same type as this object and has the same members as this object. + + + + Compares two CvPoint objects. The result specifies whether the values of the X and Y properties of the two CvPoint objects are equal. + + A Point to compare. + A Point to compare. + This operator returns true if the X and Y values of left and right are equal; otherwise, false. + + + + Compares two CvPoint2D32f objects. The result specifies whether the values of the X or Y properties of the two CvPoint2D32f objects are unequal. + + A Point to compare. + A Point to compare. + This operator returns true if the values of either the X properties or the Y properties of left and right differ; otherwise, false. + + + + Unary plus operator + + + + + + + Unary minus operator + + + + + + + Shifts point by a certain offset + + + + + + + + Shifts point by a certain offset + + + + + + + + Shifts point by a certain offset + + + + + + + + Specifies whether this object contains the same members as the specified Object. + + The Object to test. + This method returns true if obj is the same type as this object and has the same members as this object. + + + + Returns a hash code for this object. + + An integer value that specifies a hash value for this object. + + + + Converts this object to a human readable string. + + A string that represents this object. + + + + Interpolation method + + + + + Nearest-neighbor interpolation, + [CV_INTER_NN] + + + + + Bilinear interpolation (used by default) + [CV_INTER_LINEAR] + + + + + Bicubic interpolation. + [CV_INTER_CUBIC] + + + + + Resampling using pixel area relation. It is the preferred method for image decimation that gives moire-free results. In case of zooming it is similar to CV_INTER_NN method. + [CV_INTER_AREA] + + + + + Fill all the destination image pixels. If some of them correspond to outliers in the source image, they are set to fillval. + [CV_WARP_FILL_OUTLIERS] + + + + + Indicates that matrix is inverse transform from destination image to source and, + thus, can be used directly for pixel interpolation. Otherwise, the function finds the inverse transform from map_matrix. + [CV_WARP_INVERSE_MAP] + + + + + [INTER_LANCZOS4] + + + + + [INTER_MAX] + + + + + Trackbar that is shown on CvWindow + + + + + Track whether Dispose has been called + + + + + Constructor (value=0, max=100) + + Trackbar name + Window name + Callback handler + + + + Constructor + + Trackbar name + Window name + Initial slider position + The upper limit of the range this trackbar is working with. + Callback handler + + + + Constructor + + Trackbar name + Window name + Initial slider position + The upper limit of the range this trackbar is working with. + Callback handler + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + Name of this trackbar + + + + + Name of parent window + + + + + Gets or sets a numeric value that represents the current position of the scroll box on the track bar. + + + + + Gets the upper limit of the range this trackbar is working with. + + + + + Gets the callback delegate which occurs when the Value property of a track bar changes, either by movement of the scroll box or by manipulation in code. + + + + + + + + + + + + + + + Wrapper of HighGUI window + + + + + Track whether Dispose has been called + + + + + Creates a window with a random name + + + + + Creates a window with a random name and a specified image + + + + + + Creates a window with a specified image and flag + + Flags of the window. Currently the only supported flag is WindowMode.AutoSize. + If it is set, window size is automatically adjusted to fit the displayed image (see cvShowImage), while user can not change the window size manually. + + + + + Creates a window + + Name of the window which is used as window identifier and appears in the window caption. + + + + Creates a window + + Name of the window which is used as window identifier and appears in the window caption. + Flags of the window. Currently the only supported flag is WindowMode.AutoSize. + If it is set, window size is automatically adjusted to fit the displayed image (see cvShowImage), while user can not change the window size manually. + + + + Creates a window + + Name of the window which is used as window identifier and appears in the window caption. + Image to be shown. + + + + Creates a window + + Name of the window which is used as window identifier and appears in the window caption. + Flags of the window. Currently the only supported flag is WindowMode.AutoSize. + If it is set, window size is automatically adjusted to fit the displayed image (see cvShowImage), while user can not change the window size manually. + Image to be shown. + + + + ウィンドウ名が指定されなかったときに、適当な名前を作成して返す. + + + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + Destroys this window. + + + + + Destroys all the opened HighGUI windows. + + + + + Gets or sets an image to be shown + + + + + Gets window name + + + + + Gets window handle + + + + + + + + + + Event handler to be called every time mouse event occurs in the specified window. + + + + + Returns true if the library is compiled with Qt + + + + + Creates the trackbar and attaches it to this window + + Name of created trackbar. + the function to be called every time the slider changes the position. This function should be prototyped as void Foo(int); + + + + + Creates the trackbar and attaches it to this window + + Name of created trackbar. + The position of the slider + Maximal position of the slider. Minimal position is always 0. + the function to be called every time the slider changes the position. This function should be prototyped as void Foo(int); + + + + + Creates the trackbar and attaches it to this window + + Name of created trackbar. + The position of the slider + Maximal position of the slider. Minimal position is always 0. + the function to be called every time the slider changes the position. This function should be prototyped as void Foo(int); + + + + + + Display text on the window's image as an overlay for delay milliseconds. This is not editing the image's data. The text is display on the top of the image. + + Overlay text to write on the window’s image + Delay to display the overlay text. If this function is called before the previous overlay text time out, the timer is restarted and the text updated. . If this value is zero, the text never disapers. + + + + + + Text to write on the window’s statusbar + Delay to display the text. If this function is called before the previous text time out, the timer is restarted and the text updated. If this value is zero, the text never disapers. + + + + Get Property of the window + + Property identifier + Value of the specified property + + + + Load parameters of the window. + + + + + Sets window position + + New x coordinate of top-left corner + New y coordinate of top-left corner + + + + Sets window size + + New width + New height + + + + Save parameters of the window. + + + + + Set Property of the window + + Property identifier + New value of the specified property + + + + Shows the image in this window + + Image to be shown. + + + + Waits for a pressed key + + Key code + + + + Waits for a pressed key + + Delay in milliseconds. + Key code + + + + + + + + + + + + + + + + + Retrieves a created window by name + + + + + + + Represents a class which manages its own memory. + + + + + Default constructor + + + + + Constructor + + true if you permit disposing this class by GC + + + + Releases the resources + + + + + Releases the resources + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + Destructor + + + + + Gets a value indicating whether this instance has been disposed. + + + + + Gets or sets a value indicating whether you permit disposing this instance. + + + + + Gets or sets a handle which allocates using cvSetData. + + + + + Gets or sets a memory address allocated by AllocMemory. + + + + + Gets or sets the byte length of the allocated memory + + + + + Pins the object to be allocated by cvSetData. + + + + + + + Allocates the specified size of memory. + + + + + + + Notifies the allocated size of memory. + + + + + + If this object is disposed, then ObjectDisposedException is thrown. + + + + + Specifies colorness and Depth of the loaded image + + + + + 8 bit, color or gray [CV_LOAD_IMAGE_UNCHANGED] + + + + + 8 bit, gray [CV_LOAD_IMAGE_GRAYSCALE] + + + + + 8 bit unless combined with AnyDepth, color [CV_LOAD_IMAGE_COLOR] + + + + + any Depth, if specified on its own gray [CV_LOAD_IMAGE_ANYDEPTH] + + + + + by itself equivalent to Unchanged but can be modified with AnyDepth [CV_LOAD_IMAGE_ANYCOLOR] + + + + + IPL image header + + + + + Track whether Dispose has been called + + + + + Default constructor + + + + + Allocates memory + + If true, this matrix will be disposed by GC automatically. + + + + Loads an image from the specified file. + + Name of file to be loaded. + + + + Loads an image from the specified file. + + Name of file to be loaded. + Specifies colorness and Depth of the loaded image. + the reference to the loaded image. + + + + Creates header and allocates data (cvCreateImage). + + Image width and height. + Bit depth of image elements. + Number of channels per element(pixel). + + + + Creates header and allocates data (cvCreateImage). + + Image width. + Image height. + Bit depth of image elements. + Number of channels per element(pixel). + + + + Initializes by native pointer (IplImage*) + + IntPtr + + + + Initializes by native pointer (IplImage*) + + + If true, this matrix will be disposed by GC automatically. + + + + Clean up any resources being used. + + + If disposing equals true, the method has been called directly or indirectly by a user's code. Managed and unmanaged resources can be disposed. + If false, the method has been called by the runtime from inside the finalizer and you should not reference other objects. Only unmanaged resources can be disposed. + + + + + Creates the IplImage instance from image file + + + + + + + Creates the IplImage instance from image file. + First this function tries to use cvLoadImage. If failed, this function tries to use GDI+. + + + + + + + + Creates the IplImage instance from image data (using cvDecodeImage) + + + + + + + + Creates the IplImage instance from System.IO.Stream + + + + + + + + Creates an IplImage instance from pixel data + + Image width and height. + Number of channels per element(pixel). + Pointer to the pixel data array + + + + + Creates an IplImage instance from pixel data + + Image width. + Image height. + Number of channels per element(pixel). + Pointer to the pixel data array + + + + + Creates an IplImage instance from pixel data + + Image width and height. + Bit depth of image elements. + Number of channels per element(pixel). + Pixel data array + + + + + Creates an IplImage instance from pixel data + + Image width. + Image height. + Bit depth of image elements. + Number of channels per element(pixel). + Pixel data array + + + + + Creates an IplImage instance from pixel data + + Image width and height. + Number of channels per element(pixel). + Pixel data array + + + + + Creates an IplImage instance from pixel data + + Image width. + Image height. + Number of channels per element(pixel). + Pixel data array + + + + + Creates an IplImage instance from pixel data + + Image width and height. + Number of channels per element(pixel). + Pixel data array + + + + + Creates an IplImage instance from pixel data + + Image width. + Image height. + Number of channels per element(pixel). + Pixel data array + + + + + sizeof(IplImage) + + + + + Alignment of image rows (4 or 8). + OpenCV ignores it and uses widthStep instead + + + + + Ignored by OpenCV + + + + + Border completion mode, ignored by OpenCV + + + + + Ignored by OpenCV + + + + + Ignored by OpenCV + + + + + Ignored by OpenCV + + + + + 0 - interleaved color channels, 1 - separate color channels. + cvCreateImage can only create interleaved images + + + + + Pixel Depth in bits + + + + + Image height in pixels + + + + + version (=0) + + + + + Pointer to aligned image data. + You can access each pixel by this pointer casted as byte*. + + + + + Pointer to aligned image data. + + + + + Pointer to a very origin of image data (not necessarily aligned) - + it is needed for correct image deallocation. + + + + + image data size in bytes (=image->height*image->widthStep in case of interleaved data) + + + + + Must be NULL in OpenCV + + + + + Most of OpenCV functions support 1,2,3 or 4 channels + + + + + sizeof(IplImage) + + + + + 0 - top-left origin, + 1 - bottom-left origin (Windows bitmaps style) + + + + + image ROI. when it is not NULL, this specifies image region to process + + + + + image ROI. when it is not NULL, this specifies image region to process + + + + + Image width in pixels + + + + + Size of aligned image row in bytes + + + + + Must be NULL in OpenCV + + + + + Gets size of the original image + + + + + Gets/Sets COI (cvGetImageCOI/cvSetImageCOI) + + + + + Gets/Sets ROI (cvGetImageROI/cvSetImageROI) + + + + + Gets number of dimensions (=2) + + + + + Bits per pixel + + + + + Unary plus operator + + matrix + + + + + Unary negation operator + + matrix + + + + + Logical nagation operator + + matrix + + + + + Binary plus operator (cvAdd) + + matrix + matrix + + + + + Binary plus operator (cvAddS) + + matrix + scalar + + + + + Binary negation operator (cvSub) + + matrix + matrix + + + + + Binary negation operator (cvSub) + + matrix + scalar + + + + + Multiplicative operator (cvMatMul) + + matrix + matrix + + + + + Multiplicative operator (cvAddWeighted) + + matrix + scalar + + + + + Division operator (cvAddWeighted) + + matrix + scalar + + + + + Bitwise AND operator (cvAnd) + + matrix + matrix + + + + + Bitwise AND operator (cvAndS) + + matrix + scalar + + + + + Bitwise OR operator (cvOr) + + matrix + matrix + + + + + Bitwise OR operator (cvOrS) + + matrix + scalar + + + + + Bitwise XOR operator (cvXor) + + matrix + matrix + + + + + Bitwise XOR operator (cvXorS) + + matrix + scalar + + + + + Performs a fast check if a chessboard is in the input image. + This is a workaround to a problem of cvFindChessboardCorners being slow on images with no chessboard + + chessboard size + Returns 1 if a chessboard can be in this image and findChessboardCorners should be called, + 0 if there is no chessboard, -1 in case of error + + + + Makes a full copy of image + + + + + + Makes a full copy of image + + + + + + Makes an image that have the same size, depth and channels as this image + + + + + + Allocates, initializes, and returns structure IplImage (cvCreateImageHeader). + + Image width and height. + Image depth. + Number of channels. + Reference to image header + + + + Deletes moire in given image + + + + + + + + + + + + Returns index of channel of interest + + channel of interest of the image (it returns 0 if all the channels are selected) + + + + Returns image ROI coordinates (cvGetImageROI). + The rectangle cvRect(0,0,image.Width,image.Height) is returned if there is no ROI. + + + + + + Returns stream that indicates data pointer. + (The return value must be closed manually) + + + + + + Initializes allocated by user image header (cvInitImageHeader). + + Image width and height. + Image depth. + Number of channels. + Initialzed IplImage header + + + + Initializes allocated by user image header (cvInitImageHeader). + + Image width and height. + Image depth. + Number of channels. + Origin of image + Initialzed IplImage header + + + + Initializes allocated by user image header (cvInitImageHeader). + + Image width and height. + Image depth. + Number of channels. + Origin of image + Alignment for image rows, typically 4 or 8 bytes. + Initialzed IplImage header + + + + + + + + + + + Does image segmentation by pyramids. + + The destination image. + + + + + + + Does image segmentation by pyramids. + + The destination image. + Storage; stores the resulting sequence of connected components. + Pointer to the output sequence of the segmented components. + Maximum level of the pyramid for the segmentation. + Error threshold for establishing the links. + Error threshold for the segments clustering. + + + + Releases image ROI. After that the whole image is considered selected (cvResetImageROI). + + + + + Sets channel of interest to given value (cvSetImageCOI). + Value 0 means that all channels are selected, 1 means that the first channel is selected etc. + + Channel of interest. + + + + Sets image ROI to given rectangle (cvSetImageROI). + + ROI rectangle. + + + + Sets image ROI to given rectangle (cvSetImageROI). + + + + + + + + + Changes contour position to minimize its energy + + Contour points (snake). + Weight of continuity energy, single float or array of length floats, one per each contour point. + Weight of curvature energy, similar to alpha. + Weight of image energy, similar to alpha. + Size of neighborhood of every point used to search the minimum, both win.width and win.height must be odd. + Termination criteria. + + + + Changes contour position to minimize its energy + + Contour points (snake). + Weight of continuity energy, single float or array of length floats, one per each contour point. + Weight of curvature energy, similar to alpha. + Weight of image energy, similar to alpha. + Size of neighborhood of every point used to search the minimum, both win.width and win.height must be odd. + Termination criteria. + Gradient flag. If true, the function calculates gradient magnitude for every image pixel and consideres it as the energy field, otherwise the input image itself is considered. + + + + Changes contour position to minimize its energy + + Contour points (snake). + Weights of continuity energy, single float or array of length floats, one per each contour point. + Weights of curvature energy, similar to alpha. + Weights of image energy, similar to alpha. + Size of neighborhood of every point used to search the minimum, both win.width and win.height must be odd. + Termination criteria. + + + + Changes contour position to minimize its energy + + Contour points (snake). + Weights of continuity energy, single float or array of length floats, one per each contour point. + Weights of curvature energy, similar to alpha. + Weights of image energy, similar to alpha. + Size of neighborhood of every point used to search the minimum, both win.width and win.height must be odd. + Termination criteria. + Gradient flag. If true, the function calculates gradient magnitude for every image pixel and consideres it as the energy field, otherwise the input image itself is considered. + + + + Divides multi-channel array into several single-channel arrays + + + + + + Transposes matrix + + + + + Transposes matrix + + + + + Copies pixel data to this image + + Pixel data array + + + + + Copies pixel data to this image + + Pointer to the pixel data array + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + The SerializationInfo to populate with data. + The destination for this serialization. + + + + + + + + + + + Mouse events + + + + + [CV_EVENT_MOUSEMOVE] + + + + + [CV_EVENT_LBUTTONDOWN] + + + + + [CV_EVENT_RBUTTONDOWN] + + + + + [CV_EVENT_MBUTTONDOWN] + + + + + [CV_EVENT_LBUTTONUP] + + + + + [CV_EVENT_RBUTTONUP] + + + + + [CV_EVENT_MBUTTONUP] + + + + + [CV_EVENT_LBUTTONDBLCLK] + + + + + [CV_EVENT_RBUTTONDBLCLK] + + + + + [CV_EVENT_MBUTTONDBLCLK] + + + + + [CV_EVENT_FLAG_LBUTTON] + + + + + [CV_EVENT_FLAG_RBUTTON] + + + + + [CV_EVENT_FLAG_MBUTTON] + + + + + [CV_EVENT_FLAG_CTRLKEY] + + + + + [CV_EVENT_FLAG_SHIFTKEY] + + + + + [CV_EVENT_FLAG_ALTKEY] + + + + + Flags for the window + + + + + No flags + [0] + + + + + Window size is automatically adjusted to fit the displayed image, while user can not change the window size manually. + [CV_WINDOW_AUTOSIZE] + + + + + window with opengl support + + + + + Show new enhance GUI (Qt Backend Only) + [CV_GUI_EXPANDED] + + + + + Show old style window without statusbar and toolbar (Qt Backend Only) + [CV_GUI_NORMAL] + + + + + Image size is automatically adjusted to fit the window size + + + + + Fullscreen + [CV_WINDOW_FULLSCREEN] + + + + + Fix aspect ratio + [CV_WINDOW_FREERATIO] + + + + + Respect the image ratio + [CV_WINDOW_KEEPRATIO] + + + + + OpenCV functions that declared by DllImport + + + + + + + + + + repsresents whether OpenCV is built with Qt + + + + + Static constructor + + + + + Load DLL files dynamically using Win32 LoadLibrary + + + + + + Returns whether the OS is Windows or not + + + + + + Returns whether the OS is *nix or not + + + + + + Returns whether the runtime is Mono or not + + + + + + Returns true if the library is compiled with Qt + + + + + Throws exception when HasQt is false + + + + + Custom error handler to be thrown by OpenCV + + + + + Custom error handler to ignore all OpenCV errors + + + + + Default error handler + + + + + The exception that is thrown by OpenCvSharp. + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Offset and size of a rectangle + + + + + x-coordinate of the left-most rectangle corner[s] + + + + + y-coordinate of the top-most or bottom-most rectangle corner[s] + + + + + Width of the rectangle + + + + + Height of the rectangle + + + + + sizeof(CvRect) + + + + + Represents a CvRect structure with its properties left uninitialized. + + + + + Constructor + + x-coordinate of the left-most rectangle corner[s] + y-coordinate of the top-most or bottom-most rectangle corner[s] + width of the rectangle + height of the rectangle + + + + Constructor + + coordinate of the left-most rectangle corner + size of the rectangle + + + + Creates a CvRect with the specified upper-left and lower-right corners. + + The x-coordinate of the upper-left corner of this CvRect structure. + The y-coordinate of the upper-left corner of this CvRect structure. + The x-coordinate of the lower-right corner of this CvRect structure. + The y-coordinate of the lower-right corner of this CvRect structure. + + + + Specifies whether this object contains the same members as the specified Object. + + The Object to test. + This method returns true if obj is the same type as this object and has the same members as this object. + + + + Compares two CvRect objects. The result specifies whether the members of each object are equal. + + A Point to compare. + A Point to compare. + This operator returns true if the members of left and right are equal; otherwise, false. + + + + Compares two CvRect objects. The result specifies whether the members of each object are unequal. + + A Point to compare. + A Point to compare. + This operator returns true if the members of left and right are unequal; otherwise, false. + + + + Shifts rectangle by a certain offset + + + + + + + + Shifts rectangle by a certain offset + + + + + + + + Expands or shrinks rectangle by a certain amount + + + + + + + + Expands or shrinks rectangle by a certain amount + + + + + + + + Determines the CvRect structure that represents the intersection of two rectangles. + + A rectangle to intersect. + A rectangle to intersect. + + + + + Gets a CvRect structure that contains the union of two CvRect structures. + + A rectangle to union. + A rectangle to union. + + + + + Gets the y-coordinate of the top edge of this CvRect structure. + + + + + Gets the y-coordinate that is the sum of the Y and Height property values of this CvRect structure. + + + + + Gets the x-coordinate of the left edge of this CvRect structure. + + + + + Gets the x-coordinate that is the sum of X and Width property values of this CvRect structure. + + + + + Coordinate of the left-most rectangle corner [CvPoint(X, Y)] + + + + + Size of the rectangle [CvSize(Width, Height)] + + + + + Coordinate of the left-most rectangle corner [CvPoint(X, Y)] + + + + + Coordinate of the right-most rectangle corner [CvPoint(X+Width, Y+Height)] + + + + + Determines if the specified point is contained within the rectangular region defined by this Rectangle. + + x-coordinate of the point + y-coordinate of the point + + + + + Determines if the specified point is contained within the rectangular region defined by this Rectangle. + + point + + + + + Determines if the specified rectangle is contained within the rectangular region defined by this Rectangle. + + rectangle + + + + + Inflates this CvRect by the specified amount. + + The amount to inflate this Rectangle horizontally. + The amount to inflate this Rectangle vertically. + + + + Inflates this CvRect by the specified amount. + + The amount to inflate this rectangle. + + + + Creates and returns an inflated copy of the specified CvRect structure. + + The Rectangle with which to start. This rectangle is not modified. + The amount to inflate this Rectangle horizontally. + The amount to inflate this Rectangle vertically. + + + + + Determines the CvRect structure that represents the intersection of two rectangles. + + A rectangle to intersect. + A rectangle to intersect. + + + + + Determines the CvRect structure that represents the intersection of two rectangles. + + A rectangle to intersect. + + + + + Determines if this rectangle intersects with rect. + + Rectangle + + + + + Gets a CvRect structure that contains the union of two CvRect structures. + + A rectangle to union. + + + + + Gets a CvRect structure that contains the union of two CvRect structures. + + A rectangle to union. + A rectangle to union. + + + + + Specifies whether this object contains the same members as the specified Object. + + The Object to test. + This method returns true if obj is the same type as this object and has the same members as this object. + + + + Returns a hash code for this object. + + An integer value that specifies a hash value for this object. + + + + Converts this object to a human readable string. + + A string that represents this object. + + + + A container for 1-,2-,3- or 4-tuples of numbers + + + + + 1st element + + + + + 2nd element + + + + + 3rd element + + + + + 4th element + + + + + sizeof(CvScalar) + + + + + Constructor + + + + + + Constructor + + + + + + + Constructor + + + + + + + + Constructor + + + + + + + + + Initializes val[0]...val[3] with val0123 + + + + + + + Initializes val[0] with val0, val[1]...val[3] with zeros + + + + + + + Indexer + + + + + + + Creates a CvScalar with the members of the specified array. + + An array that specifies the members for the new CvScalar. + + + + + Creates a CvScalar with the specified double value like cvRealScalar. + + A double value that specifies the members for the new CvScalar. + + + + + Creates a CvScalar with the specified double array. + + A CvScalar that specifies the members for the new array. + double[4] + + + + Returns a double value with the specified CvScalar's Val0. + + A CvScalar that specifies the new double value. + + + + + Specifies whether this object contains the same members as the specified Object. + + The Object to test. + This method returns true if obj is the same type as this object and has the same members as this object. + + + + Compares two CvPoint objects. The result specifies whether the members of each object are equal. + + A Point to compare. + A Point to compare. + This operator returns true if the members of left and right are equal; otherwise, false. + + + + Compares two CvPoint objects. The result specifies whether the members of each object are unequal. + + A Point to compare. + A Point to compare. + This operator returns true if the members of left and right are unequal; otherwise, false. + + + + Specifies whether this object contains the same members as the specified Object. + + The Object to test. + This method returns true if obj is the same type as this object and has the same members as this object. + + + + Returns a hash code for this object. + + An integer value that specifies a hash value for this object. + + + + Converts this object to a human readable string. + + A string that represents this object. + + + + Pixel-accurate size of a rectangle + + + + + Width of the rectangle + + + + + Height of the rectangle + + + + + sizeof(CvSize) + + + + + Represents a CvSize structure with its properties left uninitialized. + + + + + Constructor + + Width of the rectangle + Height of the rectangle + + + + Specifies whether this object contains the same members as the specified Object. + + The Object to test. + This method returns true if obj is the same type as this object and has the same members as this object. + + + + Compares two CvPoint objects. The result specifies whether the members of each object are equal. + + A Point to compare. + A Point to compare. + This operator returns true if the members of left and right are equal; otherwise, false. + + + + Compares two CvPoint objects. The result specifies whether the members of each object are unequal. + + A Point to compare. + A Point to compare. + This operator returns true if the members of left and right are unequal; otherwise, false. + + + + Specifies whether this object contains the same members as the specified Object. + + The Object to test. + This method returns true if obj is the same type as this object and has the same members as this object. + + + + Returns a hash code for this object. + + An integer value that specifies a hash value for this object. + + + + Converts this object to a human readable string. + + A string that represents this object. + + + + + + + + + + Data pointer + + + + + Indexer + + + + + + + ptr[index] + + + + + + + ptr[index] = value; + + + + + + + Win32API Wrapper + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Managed wrapper of array pointer (Byte*) + + + + + Pointer + + + + + Initializes from IntPtr + + + + + + Initializes from Byte* + + + + + + Unmanaged pointer (Single*) + + + + + + Indexer + + zero-based component of the element index + the particular array element + + + + Return the particular element of array + + zero-based component of the element index + the particular array element + + + + Change the particular array element + + zero-based component of the element index + The assigned value + + + + Managed wrapper of array pointer (Int16*) + + + + + Pointer + + + + + Initializes from IntPtr + + + + + + Initializes from Int16* + + + + + + Unmanaged pointer (Int16*) + + + + + + Indexer + + zero-based component of the element index + the particular array element + + + + Return the particular element of array + + zero-based component of the element index + the particular array element + + + + Change the particular array element + + zero-based component of the element index + The assigned value + + + + Managed wrapper of array pointer (Int32*) + + + + + Pointer + + + + + Initializes from IntPtr + + + + + + Initializes from Int32* + + + + + + Unmanaged pointer (Int32*) + + + + + + Indexer + + zero-based component of the element index + the particular array element + + + + Return the particular element of array + + zero-based component of the element index + the particular array element + + + + Change the particular array element + + zero-based component of the element index + The assigned value + + + + Converts this pointer into a managed array + + length of the result array + + + + + Managed wrapper of array pointer (Single*) + + + + + Pointer + + + + + Initializes from IntPtr + + + + + + Initializes from Single* + + + + + + Unmanaged pointer (Single*) + + + + + + Indexer + + zero-based component of the element index + the particular array element + + + + Return the particular element of array + + zero-based component of the element index + the particular array element + + + + Change the particular array element + + zero-based component of the element index + The assigned value + + + + Converts this pointer into a managed array + + length of the result array + + + + + Managed wrapper of array pointer (Double*) + + + + + Pointer + + + + + Initializes from IntPtr + + + + + + Initializes from Double* + + + + + + Unmanaged pointer (Double*) + + + + + + Indexer + + zero-based component of the element index + the particular array element + + + + Return the particular element of array + + zero-based component of the element index + the particular array element + + + + Change the particular array element + + zero-based component of the element index + The assigned value + + + + A class which has a pointer of OpenCV structure + + + + + Data pointer + + + + + Default constructor + + + + + + + + + + + Native pointer of OpenCV structure + + + + + The default exception to be thrown by OpenCV + + + + + The numeric code for error status + + + + + The source file name where error is encountered + + + + + A description of the error + + + + + The source file name where error is encountered + + + + + The line number in the souce where error is encountered + + + + + Constructor + + The numeric code for error status + The source file name where error is encountered + A description of the error + The source file name where error is encountered + The line number in the souce where error is encountered + + + diff --git a/OpenCV/OpenCV.csproj b/OpenCV/OpenCV.csproj index ddf0637..687d35f 100644 --- a/OpenCV/OpenCV.csproj +++ b/OpenCV/OpenCV.csproj @@ -35,23 +35,23 @@ False - bin\Debug\OpenCvSharp.dll + Libs\OpenCvSharp.dll False - bin\Debug\OpenCvSharp.Blob.dll + Libs\OpenCvSharp.Blob.dll False - bin\Debug\OpenCvSharp.CPlusPlus.dll + Libs\OpenCvSharp.CPlusPlus.dll False - bin\Debug\OpenCvSharp.Extensions.dll + Libs\OpenCvSharp.Extensions.dll False - bin\Debug\OpenCvSharp.UserInterface.dll + Libs\OpenCvSharp.UserInterface.dll @@ -72,12 +72,31 @@ Form1.cs - + + Form + + + CVDialog.cs + + + Form + + + MainForm.cs + + + Form1.cs + + CVDialog.cs + + + MainForm.cs + ResXFileCodeGenerator Resources.Designer.cs @@ -100,5 +119,13 @@ + + + + + + + + \ No newline at end of file diff --git a/OpenCV/OpenCV/Canny.cs b/OpenCV/OpenCV/Canny.cs new file mode 100644 index 0000000..6efb918 --- /dev/null +++ b/OpenCV/OpenCV/Canny.cs @@ -0,0 +1,22 @@ +using OpenCvSharp; +using System; +using System.Collections.Generic; +using System.Linq; +using System.Text; +using System.Threading.Tasks; + +namespace OpenCV.OpenCV +{ + internal partial class OpenCVClass : IDisposable + { + IplImage _canny; + + public IplImage CannyEdge(IplImage src) + { + _canny = new IplImage(src.Size, BitDepth.U8, 1); + Cv.Canny(src, _canny, 100, 255, ApertureSize.Size3); + + return _canny; + } + } +} diff --git a/OpenCV/OpenCV/OpenCVClass.cs b/OpenCV/OpenCV/OpenCVClass.cs new file mode 100644 index 0000000..b0ea72f --- /dev/null +++ b/OpenCV/OpenCV/OpenCVClass.cs @@ -0,0 +1,291 @@ +using OpenCvSharp; +using System; + +namespace OpenCV.OpenCV +{ + partial class OpenCVClass : IDisposable + { + IplImage _gray; + IplImage _inversion; + IplImage _bin; + IplImage _blur; + IplImage _zoomin; + IplImage _zoomout; + IplImage _resize; + IplImage _slice; + IplImage _symm; + IplImage _rotate; + IplImage _affine; + IplImage _perspective; + IplImage _draw; + IplImage _hsv; + IplImage _hsvRed; + IplImage _morp; + + IplConvKernel _convKernel; + + public IplImage GrayScale(IplImage src) + { + _gray = new IplImage(src.Size, BitDepth.U8, 1); + Cv.CvtColor(src, _gray, ColorConversion.BgrToGray); + return _gray; + } + + public IplImage InversionImage(IplImage src) + { + _inversion = new IplImage(src.Size, BitDepth.U8, 3); + Cv.Not(src, _inversion); + return _inversion; + } + + public IplImage Binary(IplImage src, int threshold) + { + _bin = GrayScale(src); + Cv.Threshold(_bin, _bin, threshold, 255, ThresholdType.Binary); + return _bin; + } + + public IplImage Blur(IplImage src) + { + _blur = new IplImage(src.Size, BitDepth.U8, 3); + Cv.Smooth(src, _blur, SmoothType.Blur, 9); // param1은 홀수, 중간 픽셀 선택을 위함 + return _blur; + } + + public IplImage ZoomIn(IplImage src) + { + _zoomin = new IplImage(new CvSize(src.Width * 2, src.Height * 2) , BitDepth.U8, 3); + Cv.PyrUp(src, _zoomin, CvFilter.Gaussian5x5); + return _zoomin; + } + + public IplImage ZoomOut(IplImage src) + { + _zoomout = new IplImage(new CvSize(src.Width / 2, src.Height / 2), BitDepth.U8, 3); + Cv.PyrDown(src, _zoomout, CvFilter.Gaussian5x5); + return _zoomout; + } + + public IplImage Resize(IplImage src, double widthRate, double heightRate) + { + _resize = new IplImage(new CvSize((int)(src.Width * widthRate), (int)(src.Height * heightRate)), BitDepth.U8, 3); + Cv.Resize(src, _resize, Interpolation.Linear); + return _resize; + } + + public IplImage Slice(IplImage src, int x, int y, int roiWidht, int roiHeight) + { + //slice = new IplImage(new CvSize(roiWidht, roiHeight), BitDepth.U8, 3); + + //src.ROI = new CvRect(x, y, roiWidht, roiHeight); + //src.SetROI(new CvRect(x, y, roiWidht, roiHeight)); + //Cv.SetImageROI(src, new CvRect(x, y, roiWidht, roiHeight)); + + //Cv.Copy(src, slice); + //Cv.Resize(src, slice); + //slice = src.Clone(); // 속성까지 복사되어 채널 등 값이 변경됨 + + //src.ResetROI(); + //Cv.ResetImageROI(src); + + CvRect roi = new CvRect(x, y, roiWidht, roiHeight); + _slice = src.Clone(roi); + + return _slice; + } + + public IplImage Symmetry(IplImage src, FlipMode mode) + { + _symm = new IplImage(src.Size, BitDepth.U8, 3); + Cv.Flip(src, _symm, mode); + return _symm; + } + + public IplImage Rotate(IplImage src, double angle) + { + _rotate = new IplImage(src.Size, BitDepth.U8, 3); + CvMat matrix = Cv.GetRotationMatrix2D(new CvPoint2D32f(src.Width / 2, src.Height / 2), angle, 1); + Cv.WarpAffine(src, _rotate, matrix, Interpolation.Linear, CvScalar.ScalarAll(0)); + return _rotate; + } + + public IplImage AffineImage(IplImage src, CvPoint2D32f[] srcPoints, CvPoint2D32f[] dstPoints) + { + if (srcPoints.Length != 3 || dstPoints.Length != 3) + return null; + + _affine = new IplImage(src.Size, BitDepth.U8, 3); + CvMat matrix = Cv.GetAffineTransform(srcPoints, dstPoints); + Cv.WarpAffine(src, _affine, matrix, Interpolation.Linear, CvScalar.RealScalar(0)); + return _affine; + } + + public IplImage PerspectiveImage(IplImage src, CvPoint2D32f[] srcPoints, CvPoint2D32f[] dstPoints) + { + if (srcPoints.Length != 4 || dstPoints.Length != 4) + return null; + + _perspective = new IplImage(src.Size, BitDepth.U8, 3); + CvMat matrix = Cv.GetPerspectiveTransform(srcPoints, dstPoints); + Cv.WarpPerspective(src, _perspective, matrix, Interpolation.Linear, CvScalar.RealScalar(0)); + return _perspective; + } + + public IplImage DrawImage() + { + _draw = new IplImage(new CvSize(640, 480), BitDepth.U8, 3); + Cv.DrawLine(_draw, new CvPoint(100, 100), new CvPoint(500, 200), CvColor.Blue, 20); + Cv.DrawCircle(_draw, new CvPoint(200, 200), 50, CvColor.Red, -1); + Cv.DrawRect(_draw, new CvPoint(300, 150), new CvPoint(500, 300), CvColor.Green, 5); + Cv.DrawEllipse(_draw, new CvPoint(150, 400), new CvSize(100, 50), 0, 90, 360, CvColor.Green, -1); + Cv.PutText(_draw, "Open CV", new CvPoint(400, 400), new CvFont(FontFace.HersheyComplex, 1, 1), CvColor.White); + + return _draw; + } + + public IplImage HSV(IplImage src) + { + _hsv = new IplImage(src.Size, BitDepth.U8, 3); + + IplImage h = new IplImage(src.Size, BitDepth.U8, 1); + IplImage s = new IplImage(src.Size, BitDepth.U8, 1); + IplImage v = new IplImage(src.Size, BitDepth.U8, 1); + + Cv.CvtColor(src, _hsv, ColorConversion.BgrToHsv); + Cv.Split(_hsv, h, s, v, null); + + _hsv.SetZero(); + + // Hue + //Cv.InRangeS(h, 20, 30, h); // Yellow + //Cv.Copy(src, hsv, h); + + // Hue - Red + IplImage lowerRed = new IplImage(src.Size, BitDepth.U8, 1); + IplImage upperRed = new IplImage(src.Size, BitDepth.U8, 1); + IplImage red = new IplImage(src.Size, BitDepth.U8, 1); + Cv.InRangeS(h, 0, 10, lowerRed); + Cv.InRangeS(h, 170, 179, upperRed); + Cv.AddWeighted(lowerRed, 1.0, upperRed, 1.0, 0.0, red); + Cv.Copy(src, _hsv, red); + + // Saturation + //Cv.InRangeS(s, 20, 30, s); + //Cv.Copy(src, hsv, s); + + // Value + //Cv.InRangeS(v, 20, 30, v); + //Cv.Copy(src, hsv, v); + + return _hsv; + } + + public IplImage HSVRed(IplImage src) + { + _hsvRed = new IplImage(src.Size, BitDepth.U8, 3); + + IplImage lowerRed = new IplImage(src.Size, BitDepth.U8, 1); + IplImage upperRed = new IplImage(src.Size, BitDepth.U8, 1); + IplImage red = new IplImage(src.Size, BitDepth.U8, 1); + + Cv.CvtColor(src, _hsvRed, ColorConversion.BgrToHsv); + + Cv.InRangeS(_hsvRed, new CvScalar(0, 100, 100), new CvScalar(10, 255, 255), lowerRed); + Cv.InRangeS(_hsvRed, new CvScalar(170, 100, 100), new CvScalar(179, 255, 255), upperRed); + Cv.AddWeighted(lowerRed, 1.0, upperRed, 1.0, 0.0, red); + + _hsvRed.SetZero(); + Cv.Copy(src, _hsvRed, red); + + return _hsvRed; + } + + private void Release(params IplImage[] images) + { + for (int i = 0; i < images.Length; i++) + { + if (images[i] != null) + Cv.ReleaseImage(images[i]); + } + } + + public IplImage DilateImage(IplImage src, int threshold, int iteration) + { + _morp = new IplImage(src.Size, BitDepth.U8, 1); + _bin = Binary(src, threshold); + Cv.Dilate(_bin, _morp, _convKernel, iteration); + + return _morp; + } + + public IplImage ErodeImage(IplImage src, int threshold, int iteration) + { + _morp = new IplImage(src.Size, BitDepth.U8, 1); + _bin = Binary(src, threshold); + Cv.Erode(_bin, _morp, _convKernel, iteration); + + return _morp; + } + + public IplImage DEImage(IplImage src, int threshold, int iteration) + { + _morp = new IplImage(src.Size, BitDepth.U8, 1); + _bin = Binary(src, threshold); + Cv.Dilate(_bin, _morp, _convKernel, iteration); + Cv.Erode(_morp, _morp, _convKernel, iteration); + + return _morp; + } + + public IplImage EDImage(IplImage src, int threshold, int iteration) + { + _morp = new IplImage(src.Size, BitDepth.U8, 1); + _bin = Binary(src, threshold); + Cv.Erode(_bin, _morp, _convKernel, iteration); + Cv.Dilate(_morp, _morp, _convKernel, iteration); + + return _morp; + } + + public IplImage MorphologyImage(IplImage src, MorphologyOperation option, int iteration) + { + if (_convKernel == null) + return null; + + _morp = new IplImage(src.Size, BitDepth.U8, 1); + _bin = Binary(src, 50); + + Cv.MorphologyEx(_bin, _morp, _bin, _convKernel, option, iteration); + return _morp; + } + + public virtual void Dispose() + { + Release( + _gray, + _inversion, + _bin, + _blur, + _zoomin, + _zoomout, + _resize, + _slice, + _symm, + _rotate, + _affine, + _perspective, + _draw, + _hsv, + _hsvRed, + _morp, + _canny + ); + } + + public IplConvKernel ConvKernel + { + get { return this._convKernel; } + set { this._convKernel = value; } + } + } +} diff --git a/OpenCV/OpenCVClass.cs b/OpenCV/OpenCVClass.cs deleted file mode 100644 index 1298a7f..0000000 --- a/OpenCV/OpenCVClass.cs +++ /dev/null @@ -1,290 +0,0 @@ -using OpenCvSharp; -using System; - -namespace OpenCV -{ - class OpenCVClass : IDisposable - { - IplImage gray; - IplImage inversion; - IplImage bin; - IplImage blur; - IplImage zoomin; - IplImage zoomout; - IplImage resize; - IplImage slice; - IplImage symm; - IplImage rotate; - IplImage affine; - IplImage perspective; - IplImage draw; - IplImage hsv; - IplImage hsvRed; - IplImage morp; - - IplConvKernel convKernel; - - public IplImage GrayScale(IplImage src) - { - gray = new IplImage(src.Size, BitDepth.U8, 1); - Cv.CvtColor(src, gray, ColorConversion.BgrToGray); - return gray; - } - - public IplImage InversionImage(IplImage src) - { - inversion = new IplImage(src.Size, BitDepth.U8, 3); - Cv.Not(src, inversion); - return inversion; - } - - public IplImage Binary(IplImage src, int threshold) - { - bin = GrayScale(src); - Cv.Threshold(bin, bin, threshold, 255, ThresholdType.Binary); - return bin; - } - - public IplImage Blur(IplImage src) - { - blur = new IplImage(src.Size, BitDepth.U8, 3); - Cv.Smooth(src, blur, SmoothType.Blur, 9); // param1은 홀수, 중간 픽셀 선택을 위함 - return blur; - } - - public IplImage ZoomIn(IplImage src) - { - zoomin = new IplImage(new CvSize(src.Width * 2, src.Height * 2) , BitDepth.U8, 3); - Cv.PyrUp(src, zoomin, CvFilter.Gaussian5x5); - return zoomin; - } - - public IplImage ZoomOut(IplImage src) - { - zoomout = new IplImage(new CvSize(src.Width / 2, src.Height / 2), BitDepth.U8, 3); - Cv.PyrDown(src, zoomout, CvFilter.Gaussian5x5); - return zoomout; - } - - public IplImage Resize(IplImage src, double widthRate, double heightRate) - { - resize = new IplImage(new CvSize((int)(src.Width * widthRate), (int)(src.Height * heightRate)), BitDepth.U8, 3); - Cv.Resize(src, resize, Interpolation.Linear); - return resize; - } - - public IplImage Slice(IplImage src, int x, int y, int roiWidht, int roiHeight) - { - //slice = new IplImage(new CvSize(roiWidht, roiHeight), BitDepth.U8, 3); - - //src.ROI = new CvRect(x, y, roiWidht, roiHeight); - //src.SetROI(new CvRect(x, y, roiWidht, roiHeight)); - //Cv.SetImageROI(src, new CvRect(x, y, roiWidht, roiHeight)); - - //Cv.Copy(src, slice); - //Cv.Resize(src, slice); - //slice = src.Clone(); // 속성까지 복사되어 채널 등 값이 변경됨 - - //src.ResetROI(); - //Cv.ResetImageROI(src); - - CvRect roi = new CvRect(x, y, roiWidht, roiHeight); - slice = src.Clone(roi); - - return slice; - } - - public IplImage Symmetry(IplImage src, FlipMode mode) - { - symm = new IplImage(src.Size, BitDepth.U8, 3); - Cv.Flip(src, symm, mode); - return symm; - } - - public IplImage Rotate(IplImage src, double angle) - { - rotate = new IplImage(src.Size, BitDepth.U8, 3); - CvMat matrix = Cv.GetRotationMatrix2D(new CvPoint2D32f(src.Width / 2, src.Height / 2), angle, 1); - Cv.WarpAffine(src, rotate, matrix, Interpolation.Linear, CvScalar.ScalarAll(0)); - return rotate; - } - - public IplImage AffineImage(IplImage src, CvPoint2D32f[] srcPoints, CvPoint2D32f[] dstPoints) - { - if (srcPoints.Length != 3 || dstPoints.Length != 3) - return null; - - affine = new IplImage(src.Size, BitDepth.U8, 3); - CvMat matrix = Cv.GetAffineTransform(srcPoints, dstPoints); - Cv.WarpAffine(src, affine, matrix, Interpolation.Linear, CvScalar.RealScalar(0)); - return affine; - } - - public IplImage PerspectiveImage(IplImage src, CvPoint2D32f[] srcPoints, CvPoint2D32f[] dstPoints) - { - if (srcPoints.Length != 4 || dstPoints.Length != 4) - return null; - - perspective = new IplImage(src.Size, BitDepth.U8, 3); - CvMat matrix = Cv.GetPerspectiveTransform(srcPoints, dstPoints); - Cv.WarpPerspective(src, perspective, matrix, Interpolation.Linear, CvScalar.RealScalar(0)); - return perspective; - } - - public IplImage DrawImage() - { - draw = new IplImage(new CvSize(640, 480), BitDepth.U8, 3); - Cv.DrawLine(draw, new CvPoint(100, 100), new CvPoint(500, 200), CvColor.Blue, 20); - Cv.DrawCircle(draw, new CvPoint(200, 200), 50, CvColor.Red, -1); - Cv.DrawRect(draw, new CvPoint(300, 150), new CvPoint(500, 300), CvColor.Green, 5); - Cv.DrawEllipse(draw, new CvPoint(150, 400), new CvSize(100, 50), 0, 90, 360, CvColor.Green, -1); - Cv.PutText(draw, "Open CV", new CvPoint(400, 400), new CvFont(FontFace.HersheyComplex, 1, 1), CvColor.White); - - return draw; - } - - public IplImage HSV(IplImage src) - { - hsv = new IplImage(src.Size, BitDepth.U8, 3); - - IplImage h = new IplImage(src.Size, BitDepth.U8, 1); - IplImage s = new IplImage(src.Size, BitDepth.U8, 1); - IplImage v = new IplImage(src.Size, BitDepth.U8, 1); - - Cv.CvtColor(src, hsv, ColorConversion.BgrToHsv); - Cv.Split(hsv, h, s, v, null); - - hsv.SetZero(); - - // Hue - //Cv.InRangeS(h, 20, 30, h); // Yellow - //Cv.Copy(src, hsv, h); - - // Hue - Red - IplImage lowerRed = new IplImage(src.Size, BitDepth.U8, 1); - IplImage upperRed = new IplImage(src.Size, BitDepth.U8, 1); - IplImage red = new IplImage(src.Size, BitDepth.U8, 1); - Cv.InRangeS(h, 0, 10, lowerRed); - Cv.InRangeS(h, 170, 179, upperRed); - Cv.AddWeighted(lowerRed, 1.0, upperRed, 1.0, 0.0, red); - Cv.Copy(src, hsv, red); - - // Saturation - //Cv.InRangeS(s, 20, 30, s); - //Cv.Copy(src, hsv, s); - - // Value - //Cv.InRangeS(v, 20, 30, v); - //Cv.Copy(src, hsv, v); - - return hsv; - } - - public IplImage HSVRed(IplImage src) - { - hsvRed = new IplImage(src.Size, BitDepth.U8, 3); - - IplImage lowerRed = new IplImage(src.Size, BitDepth.U8, 1); - IplImage upperRed = new IplImage(src.Size, BitDepth.U8, 1); - IplImage red = new IplImage(src.Size, BitDepth.U8, 1); - - Cv.CvtColor(src, hsvRed, ColorConversion.BgrToHsv); - - Cv.InRangeS(hsvRed, new CvScalar(0, 100, 100), new CvScalar(10, 255, 255), lowerRed); - Cv.InRangeS(hsvRed, new CvScalar(170, 100, 100), new CvScalar(179, 255, 255), upperRed); - Cv.AddWeighted(lowerRed, 1.0, upperRed, 1.0, 0.0, red); - - hsvRed.SetZero(); - Cv.Copy(src, hsvRed, red); - - return hsvRed; - } - - private void Release(params IplImage[] images) - { - for (int i = 0; i < images.Length; i++) - { - if (images[i] != null) - Cv.ReleaseImage(images[i]); - } - } - - public IplImage DilateImage(IplImage src, int threshold, int iteration) - { - morp = new IplImage(src.Size, BitDepth.U8, 1); - bin = Binary(src, threshold); - Cv.Dilate(bin, morp, convKernel, iteration); - - return morp; - } - - public IplImage ErodeImage(IplImage src, int threshold, int iteration) - { - morp = new IplImage(src.Size, BitDepth.U8, 1); - bin = Binary(src, threshold); - Cv.Erode(bin, morp, convKernel, iteration); - - return morp; - } - - public IplImage DEImage(IplImage src, int threshold, int iteration) - { - morp = new IplImage(src.Size, BitDepth.U8, 1); - bin = Binary(src, threshold); - Cv.Dilate(bin, morp, convKernel, iteration); - Cv.Erode(morp, morp, convKernel, iteration); - - return morp; - } - - public IplImage EDImage(IplImage src, int threshold, int iteration) - { - morp = new IplImage(src.Size, BitDepth.U8, 1); - bin = Binary(src, threshold); - Cv.Erode(bin, morp, convKernel, iteration); - Cv.Dilate(morp, morp, convKernel, iteration); - - return morp; - } - - public IplImage MorphologyImage(IplImage src, MorphologyOperation option, int iteration) - { - if (convKernel == null) - return null; - - morp = new IplImage(src.Size, BitDepth.U8, 1); - bin = Binary(src, 50); - - Cv.MorphologyEx(bin, morp, bin, convKernel, option, iteration); - return morp; - } - - public void Dispose() - { - Release( - gray, - inversion, - bin, - blur, - zoomin, - zoomout, - resize, - slice, - symm, - rotate, - affine, - perspective, - draw, - hsv, - hsvRed, - morp - ); - } - - public IplConvKernel ConvKernel - { - get { return this.convKernel; } - set { this.convKernel = value; } - } - } -} diff --git a/OpenCV/Program.cs b/OpenCV/Program.cs index 2474f3e..375246e 100644 --- a/OpenCV/Program.cs +++ b/OpenCV/Program.cs @@ -1,4 +1,5 @@ -using System; +using OpenCV.Forms; +using System; using System.Collections.Generic; using System.Linq; using System.Threading.Tasks; @@ -16,7 +17,7 @@ namespace OpenCV { Application.EnableVisualStyles(); Application.SetCompatibleTextRenderingDefault(false); - Application.Run(new Form1()); + Application.Run(new MainForm()); } } }