Class Hierarchy

This inheritance list is sorted roughly, but not completely, alphabetically:

[detail level 1234567]

►CApplicationException
COpenCVForUnity.CoreModule.CvException	The exception that is thrown by OpenCVForUntiy
COpenCVForUnity.ArucoModule.Aruco
COpenCVForUnity.UnityUtils.ARUtils	AR utilities
COpenCVForUnity.BgsegmModule.Bgsegm
COpenCVForUnity.BioinspiredModule.Bioinspired
COpenCVForUnity.UnityUtils.MOT.ByteTrack.BYTETracker	BYTETracker C# implementation of ByteTrack that does not include an object detection algorithm. The implementation is based on "ByteTrack-cpp". (https://github.com/derpda/ByteTrack-cpp/) Only tracking algorithm are implemented. Any object detection algorithm can be easily combined. Some code has been modified to obtain the same processing results as the original code below. https://github.com/ifzhang/ByteTrack/tree/main/deploy/ncnn/cpp https://github.com/ifzhang/ByteTrack/tree/main/yolox/tracker
COpenCVForUnity.Calib3dModule.Calib3d
COpenCVForUnity.UtilsModule.Converters
COpenCVForUnity.CoreModule.Core
COpenCVForUnity.CoreModule.CvType
COpenCVForUnity.UnityUtils.DebugMatUtils
COpenCVForUnity.DnnModule.Dnn
COpenCVForUnity.Dnn_superresModule.Dnn_superres
COpenCVForUnity.FaceModule.Face
COpenCVForUnity.Features2dModule.Features2d
COpenCVForUnity.UnityUtils.Helper.FpsManager
►CIComparable
COpenCVForUnity.UnityUtils.Vec10d	10-Vector struct of double [CvType.CV_64FC10, Moments]
COpenCVForUnity.UnityUtils.Vec10d	10-Vector struct of double [CvType.CV_64FC10, Moments]
COpenCVForUnity.UnityUtils.Vec2b	2-Vector struct of byte [CvType.CV_8UC2]
COpenCVForUnity.UnityUtils.Vec2b	2-Vector struct of byte [CvType.CV_8UC2]
COpenCVForUnity.UnityUtils.Vec2c	2-Vector struct of sbyte [CvType.CV_8SC2]
COpenCVForUnity.UnityUtils.Vec2c	2-Vector struct of sbyte [CvType.CV_8SC2]
COpenCVForUnity.UnityUtils.Vec2d	2-Vector struct of double [CvType.CV_64FC2, Point]
COpenCVForUnity.UnityUtils.Vec2d	2-Vector struct of double [CvType.CV_64FC2, Point]
COpenCVForUnity.UnityUtils.Vec2f	2-Vector struct of float [CvType.CV_32FC2]
COpenCVForUnity.UnityUtils.Vec2f	2-Vector struct of float [CvType.CV_32FC2]
COpenCVForUnity.UnityUtils.Vec2i	2-Vector struct of int [CvType.CV_32SC2, Range]
COpenCVForUnity.UnityUtils.Vec2i	2-Vector struct of int [CvType.CV_32SC2, Range]
COpenCVForUnity.UnityUtils.Vec2s	2-Vector struct of short [CvType.CV_16SC2]
COpenCVForUnity.UnityUtils.Vec2s	2-Vector struct of short [CvType.CV_16SC2]
COpenCVForUnity.UnityUtils.Vec2w	2-Vector struct of ushort [CvType.CV_16UC2, Size]
COpenCVForUnity.UnityUtils.Vec2w	2-Vector struct of ushort [CvType.CV_16UC2, Size]
COpenCVForUnity.UnityUtils.Vec3b	3-Vector struct of byte [CvType.CV_8UC3]
COpenCVForUnity.UnityUtils.Vec3b	3-Vector struct of byte [CvType.CV_8UC3]
COpenCVForUnity.UnityUtils.Vec3c	3-Vector struct of sbyte [CvType.CV_8SC3]
COpenCVForUnity.UnityUtils.Vec3c	3-Vector struct of sbyte [CvType.CV_8SC3]
COpenCVForUnity.UnityUtils.Vec3d	3-Vector struct of double [CvType.CV_64FC3, Point3]
COpenCVForUnity.UnityUtils.Vec3d	3-Vector struct of double [CvType.CV_64FC3, Point3]
COpenCVForUnity.UnityUtils.Vec3f	3-Vector struct of float [CvType.CV_32FC3]
COpenCVForUnity.UnityUtils.Vec3f	3-Vector struct of float [CvType.CV_32FC3]
COpenCVForUnity.UnityUtils.Vec3i	3-Vector struct of int [CvType.CV_32SC3]
COpenCVForUnity.UnityUtils.Vec3i	3-Vector struct of int [CvType.CV_32SC3]
COpenCVForUnity.UnityUtils.Vec3s	3-Vector struct of short [CvType.CV_16SC3]
COpenCVForUnity.UnityUtils.Vec3s	3-Vector struct of short [CvType.CV_16SC3]
COpenCVForUnity.UnityUtils.Vec3w	3-Vector struct of ushort [CvType.CV_16UC3]
COpenCVForUnity.UnityUtils.Vec3w	3-Vector struct of ushort [CvType.CV_16UC3]
COpenCVForUnity.UnityUtils.Vec4b	4-Vector struct of byte [CvType.CV_8UC4]
COpenCVForUnity.UnityUtils.Vec4b	4-Vector struct of byte [CvType.CV_8UC4]
COpenCVForUnity.UnityUtils.Vec4c	4-Vector struct of sbyte [CvType.CV_8SC4]
COpenCVForUnity.UnityUtils.Vec4c	4-Vector struct of sbyte [CvType.CV_8SC4]
COpenCVForUnity.UnityUtils.Vec4d	4-Vector struct of double [CvType.CV_64FC4]
COpenCVForUnity.UnityUtils.Vec4d	4-Vector struct of double [CvType.CV_64FC4]
COpenCVForUnity.UnityUtils.Vec4f	4-Vector struct of float [CvType.CV_32FC4, DMatch]
COpenCVForUnity.UnityUtils.Vec4f	4-Vector struct of float [CvType.CV_32FC4, DMatch]
COpenCVForUnity.UnityUtils.Vec4i	4-Vector struct of int [CvType.CV_32SC4, Rect]
COpenCVForUnity.UnityUtils.Vec4i	4-Vector struct of int [CvType.CV_32SC4, Rect]
COpenCVForUnity.UnityUtils.Vec4s	4-Vector struct of short [CvType.CV_16SC4]
COpenCVForUnity.UnityUtils.Vec4s	4-Vector struct of short [CvType.CV_16SC4]
COpenCVForUnity.UnityUtils.Vec4w	4-Vector struct of ushort [CvType.CV_16UC4, Rect2d, Scalar]
COpenCVForUnity.UnityUtils.Vec4w	4-Vector struct of ushort [CvType.CV_16UC4, Rect2d, Scalar]
COpenCVForUnity.UnityUtils.Vec5d	5-Vector struct of double [CvType.CV_64FC5, RotatedRect]
COpenCVForUnity.UnityUtils.Vec5d	5-Vector struct of double [CvType.CV_64FC5, RotatedRect]
COpenCVForUnity.UnityUtils.Vec5f	5-Vector struct of float [CvType.CV_32FC5, MatOfRotatedRect]
COpenCVForUnity.UnityUtils.Vec5f	5-Vector struct of float [CvType.CV_32FC5, MatOfRotatedRect]
COpenCVForUnity.UnityUtils.Vec6f	6-Vector struct of float [CvType.CV_32FC6, KeyPoint]
COpenCVForUnity.UnityUtils.Vec6f	6-Vector struct of float [CvType.CV_32FC6, KeyPoint]
COpenCVForUnity.UnityUtils.Vec7d	7-Vector struct of double [CvType.CV_32FC7]
COpenCVForUnity.UnityUtils.Vec7d	7-Vector struct of double [CvType.CV_32FC7]
COpenCVForUnity.UnityUtils.Vec7f	7-Vector struct of float [CvType.CV_32FC7, KeyPoint]
COpenCVForUnity.UnityUtils.Vec7f	7-Vector struct of float [CvType.CV_32FC7, KeyPoint]
►COpenCVForUnity.UnityUtils.MOT.ByteTrack.IDetectionBase
COpenCVForUnity.UnityUtils.MOT.ByteTrack.Detection
►CIDisposable
►COpenCVForUnity.DisposableObject
►COpenCVForUnity.DisposableOpenCVObject
COpenCVForUnity.ArucoModule.EstimateParameters	Pose estimation parameters
COpenCVForUnity.BgsegmModule.BackgroundSubtractorLSBPDesc	This is for calculation of the LSBP descriptors
COpenCVForUnity.Calib3dModule.UsacParams
►COpenCVForUnity.CoreModule.Algorithm	This is a base class for all more or less complex algorithms in OpenCV
COpenCVForUnity.BgsegmModule.SyntheticSequenceGenerator	Synthetic frame sequence generator for testing background subtraction algorithms
COpenCVForUnity.BioinspiredModule.Retina	Class which allows the Gipsa/Listic Labs model to be used with OpenCV
COpenCVForUnity.BioinspiredModule.Retina	Class which allows the Gipsa/Listic Labs model to be used with OpenCV
COpenCVForUnity.BioinspiredModule.Retina	Class which allows the Gipsa/Listic Labs model to be used with OpenCV
COpenCVForUnity.BioinspiredModule.RetinaFastToneMapping	Wrapper class which allows the tone mapping algorithm of Meylan&al(2007) to be used with OpenCV
COpenCVForUnity.BioinspiredModule.RetinaFastToneMapping	Wrapper class which allows the tone mapping algorithm of Meylan&al(2007) to be used with OpenCV
COpenCVForUnity.BioinspiredModule.RetinaFastToneMapping	Wrapper class which allows the tone mapping algorithm of Meylan&al(2007) to be used with OpenCV
COpenCVForUnity.BioinspiredModule.TransientAreasSegmentationModule	Class which provides a transient/moving areas segmentation module
COpenCVForUnity.BioinspiredModule.TransientAreasSegmentationModule	Class which provides a transient/moving areas segmentation module
COpenCVForUnity.BioinspiredModule.TransientAreasSegmentationModule	Class which provides a transient/moving areas segmentation module
►COpenCVForUnity.Calib3dModule.StereoMatcher	The base class for stereo correspondence algorithms
COpenCVForUnity.Calib3dModule.StereoBM	Class for computing stereo correspondence using the block matching algorithm, introduced and contributed to OpenCV by K. Konolige
COpenCVForUnity.Calib3dModule.StereoBM	Class for computing stereo correspondence using the block matching algorithm, introduced and contributed to OpenCV by K. Konolige
COpenCVForUnity.Calib3dModule.StereoBM	Class for computing stereo correspondence using the block matching algorithm, introduced and contributed to OpenCV by K. Konolige
COpenCVForUnity.Calib3dModule.StereoSGBM	The class implements the modified H. Hirschmuller algorithm [HH08] that differs from the original one as follows:
COpenCVForUnity.DnnModule.Layer	This interface class allows to build new Layers - are building blocks of networks
COpenCVForUnity.FaceModule.BIF
►COpenCVForUnity.FaceModule.FaceRecognizer	Abstract base class for all face recognition models
►COpenCVForUnity.FaceModule.BasicFaceRecognizer
COpenCVForUnity.FaceModule.EigenFaceRecognizer
COpenCVForUnity.FaceModule.FisherFaceRecognizer
COpenCVForUnity.FaceModule.LBPHFaceRecognizer
►COpenCVForUnity.FaceModule.Facemark	Abstract base class for all facemark models
COpenCVForUnity.FaceModule.FacemarkKazemi
►COpenCVForUnity.FaceModule.FacemarkTrain	Abstract base class for trainable facemark models
COpenCVForUnity.FaceModule.FacemarkAAM
COpenCVForUnity.FaceModule.FacemarkLBF
COpenCVForUnity.FaceModule.MACE	Minimum Average Correlation Energy Filter useful for authentication with (cancellable) biometrical features. (does not need many positives to train (10-50), and no negatives at all, also robust to noise/salting)
►COpenCVForUnity.Features2dModule.DescriptorMatcher	Abstract base class for matching keypoint descriptors
COpenCVForUnity.Features2dModule.BFMatcher	Brute-force descriptor matcher
COpenCVForUnity.Features2dModule.FlannBasedMatcher	Flann-based descriptor matcher
►COpenCVForUnity.Features2dModule.Feature2D	Abstract base class for 2D image feature detectors and descriptor extractors
COpenCVForUnity.Features2dModule.AKAZE	Class implementing the AKAZE keypoint detector and descriptor extractor, described in [ANB13]
COpenCVForUnity.Features2dModule.AffineFeature	Class for implementing the wrapper which makes detectors and extractors to be affine invariant, described as ASIFT in [YM11]
COpenCVForUnity.Features2dModule.AgastFeatureDetector	Wrapping class for feature detection using the AGAST method. :
COpenCVForUnity.Features2dModule.BRISK	Class implementing the BRISK keypoint detector and descriptor extractor, described in [LCS11]
COpenCVForUnity.Features2dModule.FastFeatureDetector	Wrapping class for feature detection using the FAST method. :
COpenCVForUnity.Features2dModule.GFTTDetector	Wrapping class for feature detection using the goodFeaturesToTrack function. :
COpenCVForUnity.Features2dModule.KAZE	Class implementing the KAZE keypoint detector and descriptor extractor, described in [ABD12]
COpenCVForUnity.Features2dModule.MSER	Maximally stable extremal region extractor
COpenCVForUnity.Features2dModule.ORB	Class implementing the ORB (oriented BRIEF) keypoint detector and descriptor extractor
COpenCVForUnity.Features2dModule.SIFT	Class for extracting keypoints and computing descriptors using the Scale Invariant Feature Transform (SIFT) algorithm by D. Lowe [Lowe04]
COpenCVForUnity.Features2dModule.SimpleBlobDetector	Class for extracting blobs from an image. :
►COpenCVForUnity.Xfeatures2dModule.AffineFeature2D	Class implementing affine adaptation for key points
COpenCVForUnity.Xfeatures2dModule.TBMR	Class implementing the Tree Based Morse Regions (TBMR) as described in [Najman2014] extended with scaled extraction ability
COpenCVForUnity.Xfeatures2dModule.BEBLID	Class implementing BEBLID (Boosted Efficient Binary Local Image Descriptor), described in [Suarez2020BEBLID]
COpenCVForUnity.Xfeatures2dModule.BoostDesc	Class implementing BoostDesc (Learning Image Descriptors with Boosting), described in [Trzcinski13a] and [Trzcinski13b]
COpenCVForUnity.Xfeatures2dModule.BriefDescriptorExtractor	Class for computing BRIEF descriptors described in [calon2010]
COpenCVForUnity.Xfeatures2dModule.DAISY	Class implementing DAISY descriptor, described in [Tola10]
COpenCVForUnity.Xfeatures2dModule.FREAK	Class implementing the FREAK (Fast Retina Keypoint) keypoint descriptor, described in [AOV12]
COpenCVForUnity.Xfeatures2dModule.HarrisLaplaceFeatureDetector	Class implementing the Harris-Laplace feature detector as described in [Mikolajczyk2004]
COpenCVForUnity.Xfeatures2dModule.LATCH
COpenCVForUnity.Xfeatures2dModule.LUCID	Class implementing the locally uniform comparison image descriptor, described in [LUCID]
COpenCVForUnity.Xfeatures2dModule.MSDDetector	Class implementing the MSD (Maximal Self-Dissimilarity) keypoint detector, described in [Tombari14]
COpenCVForUnity.Xfeatures2dModule.StarDetector	The class implements the keypoint detector introduced by [Agrawal08], synonym of StarDetector. :
COpenCVForUnity.Xfeatures2dModule.TEBLID	Class implementing TEBLID (Triplet-based Efficient Binary Local Image Descriptor), described in [Suarez2021TEBLID]
COpenCVForUnity.Xfeatures2dModule.VGG	Class implementing VGG (Oxford Visual Geometry Group) descriptor trained end to end using "Descriptor Learning Using Convex Optimisation" (DLCO) aparatus described in [Simonyan14]
►COpenCVForUnity.Img_hashModule.ImgHashBase	The base class for image hash algorithms
COpenCVForUnity.Img_hashModule.AverageHash	Computes average hash value of the input image
COpenCVForUnity.Img_hashModule.BlockMeanHash	Image hash based on block mean
COpenCVForUnity.Img_hashModule.ColorMomentHash	Image hash based on color moments
COpenCVForUnity.Img_hashModule.MarrHildrethHash	Marr-Hildreth Operator Based Hash, slowest but more discriminative
COpenCVForUnity.Img_hashModule.PHash	PHash
COpenCVForUnity.Img_hashModule.RadialVarianceHash	Image hash based on Radon transform
COpenCVForUnity.ImgprocModule.CLAHE	Base class for Contrast Limited Adaptive Histogram Equalization
COpenCVForUnity.ImgprocModule.CLAHE	Base class for Contrast Limited Adaptive Histogram Equalization
COpenCVForUnity.ImgprocModule.CLAHE	Base class for Contrast Limited Adaptive Histogram Equalization
►COpenCVForUnity.ImgprocModule.GeneralizedHough	Finds arbitrary template in the grayscale image using Generalized Hough Transform
COpenCVForUnity.ImgprocModule.GeneralizedHoughBallard	Finds arbitrary template in the grayscale image using Generalized Hough Transform
COpenCVForUnity.ImgprocModule.GeneralizedHoughGuil	Finds arbitrary template in the grayscale image using Generalized Hough Transform
COpenCVForUnity.ImgprocModule.GeneralizedHough	Finds arbitrary template in the grayscale image using Generalized Hough Transform
COpenCVForUnity.ImgprocModule.GeneralizedHough	Finds arbitrary template in the grayscale image using Generalized Hough Transform
COpenCVForUnity.ImgprocModule.LineSegmentDetector	Line segment detector class
COpenCVForUnity.ImgprocModule.LineSegmentDetector	Line segment detector class
COpenCVForUnity.ImgprocModule.LineSegmentDetector	Line segment detector class
►COpenCVForUnity.MlModule.StatModel	Base class for statistical models in OpenCV ML
COpenCVForUnity.MlModule.ANN_MLP	Artificial Neural Networks - Multi-Layer Perceptrons
COpenCVForUnity.MlModule.ANN_MLP	Artificial Neural Networks - Multi-Layer Perceptrons
COpenCVForUnity.MlModule.ANN_MLP	Artificial Neural Networks - Multi-Layer Perceptrons
►COpenCVForUnity.MlModule.DTrees	The class represents a single decision tree or a collection of decision trees
COpenCVForUnity.MlModule.Boost	Boosted tree classifier derived from DTrees
COpenCVForUnity.MlModule.RTrees	The class implements the random forest predictor
COpenCVForUnity.MlModule.RTrees	The class implements the random forest predictor
COpenCVForUnity.MlModule.RTrees	The class implements the random forest predictor
COpenCVForUnity.MlModule.EM	The class implements the Expectation Maximization algorithm
COpenCVForUnity.MlModule.EM	The class implements the Expectation Maximization algorithm
COpenCVForUnity.MlModule.EM	The class implements the Expectation Maximization algorithm
COpenCVForUnity.MlModule.KNearest	The class implements K-Nearest Neighbors model
COpenCVForUnity.MlModule.LogisticRegression	Implements Logistic Regression classifier
COpenCVForUnity.MlModule.LogisticRegression	Implements Logistic Regression classifier
COpenCVForUnity.MlModule.LogisticRegression	Implements Logistic Regression classifier
COpenCVForUnity.MlModule.NormalBayesClassifier	Bayes classifier for normally distributed data
COpenCVForUnity.MlModule.SVM	Support Vector Machines
COpenCVForUnity.MlModule.SVM	Support Vector Machines
COpenCVForUnity.MlModule.SVM	Support Vector Machines
COpenCVForUnity.MlModule.SVMSGD
COpenCVForUnity.MlModule.SVMSGD
COpenCVForUnity.MlModule.SVMSGD
COpenCVForUnity.ObjdetectModule.ArucoDetector	The main functionality of ArucoDetector class is detection of markers in an image with detectMarkers() method
COpenCVForUnity.ObjdetectModule.BaseCascadeClassifier
COpenCVForUnity.ObjdetectModule.CharucoDetector
►COpenCVForUnity.Phase_unwrappingModule.PhaseUnwrapping	Abstract base class for phase unwrapping
COpenCVForUnity.Phase_unwrappingModule.HistogramPhaseUnwrapping	Class implementing two-dimensional phase unwrapping based on [histogramUnwrapping] This algorithm belongs to the quality-guided phase unwrapping methods. First, it computes a reliability map from second differences between a pixel and its eight neighbours. Reliability values lie between 0 and 16*pi*pi. Then, this reliability map is used to compute the reliabilities of "edges". An edge is an entity defined by two pixels that are connected horizontally or vertically. Its reliability is found by adding the the reliabilities of the two pixels connected through it. Edges are sorted in a histogram based on their reliability values. This histogram is then used to unwrap pixels, starting from the highest quality pixel
►COpenCVForUnity.PhotoModule.AlignExposures	The base class for algorithms that align images of the same scene with different exposures
COpenCVForUnity.PhotoModule.AlignMTB	This algorithm converts images to median threshold bitmaps (1 for pixels brighter than median luminance and 0 otherwise) and than aligns the resulting bitmaps using bit operations
COpenCVForUnity.PhotoModule.AlignMTB	This algorithm converts images to median threshold bitmaps (1 for pixels brighter than median luminance and 0 otherwise) and than aligns the resulting bitmaps using bit operations
COpenCVForUnity.PhotoModule.AlignMTB	This algorithm converts images to median threshold bitmaps (1 for pixels brighter than median luminance and 0 otherwise) and than aligns the resulting bitmaps using bit operations
►COpenCVForUnity.PhotoModule.CalibrateCRF	The base class for camera response calibration algorithms
COpenCVForUnity.PhotoModule.CalibrateDebevec	Inverse camera response function is extracted for each brightness value by minimizing an objective function as linear system. Objective function is constructed using pixel values on the same position in all images, extra term is added to make the result smoother
COpenCVForUnity.PhotoModule.CalibrateRobertson	Inverse camera response function is extracted for each brightness value by minimizing an objective function as linear system. This algorithm uses all image pixels
►COpenCVForUnity.PhotoModule.MergeExposures	The base class algorithms that can merge exposure sequence to a single image
COpenCVForUnity.PhotoModule.MergeDebevec	The resulting HDR image is calculated as weighted average of the exposures considering exposure values and camera response
COpenCVForUnity.PhotoModule.MergeMertens	Pixels are weighted using contrast, saturation and well-exposedness measures, than images are combined using laplacian pyramids
COpenCVForUnity.PhotoModule.MergeRobertson	The resulting HDR image is calculated as weighted average of the exposures considering exposure values and camera response
►COpenCVForUnity.PhotoModule.Tonemap	Base class for tonemapping algorithms - tools that are used to map HDR image to 8-bit range
COpenCVForUnity.PhotoModule.TonemapDrago	Adaptive logarithmic mapping is a fast global tonemapping algorithm that scales the image in logarithmic domain
COpenCVForUnity.PhotoModule.TonemapMantiuk	This algorithm transforms image to contrast using gradients on all levels of gaussian pyramid, transforms contrast values to HVS response and scales the response. After this the image is reconstructed from new contrast values
COpenCVForUnity.PhotoModule.TonemapReinhard	This is a global tonemapping operator that models human visual system
COpenCVForUnity.XphotoModule.TonemapDurand	This algorithm decomposes image into two layers: base layer and detail layer using bilateral filter and compresses contrast of the base layer thus preserving all the details
COpenCVForUnity.PlotModule.Plot2d
COpenCVForUnity.PlotModule.Plot2d
COpenCVForUnity.PlotModule.Plot2d
►COpenCVForUnity.Structured_lightModule.StructuredLightPattern	Abstract base class for generating and decoding structured light patterns
COpenCVForUnity.Structured_lightModule.GrayCodePattern	Class implementing the Gray-code pattern, based on [UNDERWORLD]
COpenCVForUnity.Structured_lightModule.GrayCodePattern	Class implementing the Gray-code pattern, based on [UNDERWORLD]
COpenCVForUnity.Structured_lightModule.GrayCodePattern	Class implementing the Gray-code pattern, based on [UNDERWORLD]
COpenCVForUnity.Structured_lightModule.SinusoidalPattern	Class implementing Fourier transform profilometry (FTP) , phase-shifting profilometry (PSP) and Fourier-assisted phase-shifting profilometry (FAPS) based on [faps]
COpenCVForUnity.Structured_lightModule.SinusoidalPattern	Class implementing Fourier transform profilometry (FTP) , phase-shifting profilometry (PSP) and Fourier-assisted phase-shifting profilometry (FAPS) based on [faps]
COpenCVForUnity.Structured_lightModule.SinusoidalPattern	Class implementing Fourier transform profilometry (FTP) , phase-shifting profilometry (PSP) and Fourier-assisted phase-shifting profilometry (FAPS) based on [faps]
COpenCVForUnity.TextModule.ERFilter	Base class for 1st and 2nd stages of Neumann and Matas scene text detection algorithm [Neumann12]. :
COpenCVForUnity.TrackingModule.legacy_MultiTracker	This class is used to track multiple objects using the specified tracker algorithm
COpenCVForUnity.TrackingModule.legacy_MultiTracker	This class is used to track multiple objects using the specified tracker algorithm
COpenCVForUnity.TrackingModule.legacy_MultiTracker	This class is used to track multiple objects using the specified tracker algorithm
►COpenCVForUnity.TrackingModule.legacy_Tracker	Base abstract class for the long-term tracker:
COpenCVForUnity.TrackingModule.legacy_TrackerBoosting	Boosting tracker
COpenCVForUnity.TrackingModule.legacy_TrackerCSRT	CSRT tracker
COpenCVForUnity.TrackingModule.legacy_TrackerKCF	KCF (Kernelized Correlation Filter) tracker
COpenCVForUnity.TrackingModule.legacy_TrackerMIL	The MIL algorithm trains a classifier in an online manner to separate the object from the background
COpenCVForUnity.TrackingModule.legacy_TrackerMOSSE	MOSSE (Minimum Output Sum of Squared Error) tracker
COpenCVForUnity.TrackingModule.legacy_TrackerMedianFlow	Median Flow tracker
COpenCVForUnity.TrackingModule.legacy_TrackerTLD	TLD (Tracking, learning and detection) tracker
COpenCVForUnity.TrackingModule.legacy_Tracker	Base abstract class for the long-term tracker:
COpenCVForUnity.TrackingModule.legacy_Tracker	Base abstract class for the long-term tracker:
►COpenCVForUnity.VideoModule.BackgroundSubtractor	Base class for background/foreground segmentation. :
COpenCVForUnity.BgsegmModule.BackgroundSubtractorCNT	Background subtraction based on counting
COpenCVForUnity.BgsegmModule.BackgroundSubtractorGMG	Background Subtractor module based on the algorithm given in [Gold2012]
COpenCVForUnity.BgsegmModule.BackgroundSubtractorGSOC	Implementation of the different yet better algorithm which is called GSOC, as it was implemented during GSOC and was not originated from any paper
COpenCVForUnity.BgsegmModule.BackgroundSubtractorLSBP	Background Subtraction using Local SVD Binary Pattern. More details about the algorithm can be found at [LGuo2016]
COpenCVForUnity.BgsegmModule.BackgroundSubtractorMOG	Gaussian Mixture-based Background/Foreground Segmentation Algorithm
COpenCVForUnity.VideoModule.BackgroundSubtractorKNN	K-nearest neighbours - based Background/Foreground Segmentation Algorithm
COpenCVForUnity.VideoModule.BackgroundSubtractorMOG2	Gaussian Mixture-based Background/Foreground Segmentation Algorithm
►COpenCVForUnity.VideoModule.DenseOpticalFlow
COpenCVForUnity.VideoModule.DISOpticalFlow	DIS optical flow algorithm
COpenCVForUnity.VideoModule.FarnebackOpticalFlow	Class computing a dense optical flow using the Gunnar Farneback's algorithm
COpenCVForUnity.VideoModule.VariationalRefinement	Variational optical flow refinement
►COpenCVForUnity.VideoModule.SparseOpticalFlow	Base interface for sparse optical flow algorithms
COpenCVForUnity.VideoModule.SparsePyrLKOpticalFlow	Class used for calculating a sparse optical flow
COpenCVForUnity.VideoModule.SparsePyrLKOpticalFlow	Class used for calculating a sparse optical flow
COpenCVForUnity.VideoModule.SparsePyrLKOpticalFlow	Class used for calculating a sparse optical flow
COpenCVForUnity.Xfeatures2dModule.PCTSignatures	Class implementing PCT (position-color-texture) signature extraction as described in [KrulisLS16]. The algorithm is divided to a feature sampler and a clusterizer. Feature sampler produces samples at given set of coordinates. Clusterizer then produces clusters of these samples using k-means algorithm. Resulting set of clusters is the signature of the input image
COpenCVForUnity.Xfeatures2dModule.PCTSignaturesSQFD	Class implementing Signature Quadratic Form Distance (SQFD)
COpenCVForUnity.XimgprocModule.AdaptiveManifoldFilter	Interface for Adaptive Manifold Filter realizations
COpenCVForUnity.XimgprocModule.ContourFitting	Class for ContourFitting algorithms. ContourFitting match two contours $\$z_a$$ and $\$z_b$$ minimizing distance
COpenCVForUnity.XimgprocModule.DTFilter	Interface for realizations of Domain Transform filter
►COpenCVForUnity.XimgprocModule.DisparityFilter	Main interface for all disparity map filters
COpenCVForUnity.XimgprocModule.DisparityWLSFilter	Disparity map filter based on Weighted Least Squares filter (in form of Fast Global Smoother that is a lot faster than traditional Weighted Least Squares filter implementations) and optional use of left-right-consistency-based confidence to refine the results in half-occlusions and uniform areas
COpenCVForUnity.XimgprocModule.DisparityWLSFilter	Disparity map filter based on Weighted Least Squares filter (in form of Fast Global Smoother that is a lot faster than traditional Weighted Least Squares filter implementations) and optional use of left-right-consistency-based confidence to refine the results in half-occlusions and uniform areas
COpenCVForUnity.XimgprocModule.DisparityWLSFilter	Disparity map filter based on Weighted Least Squares filter (in form of Fast Global Smoother that is a lot faster than traditional Weighted Least Squares filter implementations) and optional use of left-right-consistency-based confidence to refine the results in half-occlusions and uniform areas
COpenCVForUnity.XimgprocModule.DisparityFilter	Main interface for all disparity map filters
COpenCVForUnity.XimgprocModule.DisparityFilter	Main interface for all disparity map filters
COpenCVForUnity.XimgprocModule.EdgeBoxes	Class implementing EdgeBoxes algorithm from [ZitnickECCV14edgeBoxes] :
COpenCVForUnity.XimgprocModule.EdgeDrawing	Class implementing the ED (EdgeDrawing) [topal2012edge], EDLines [akinlar2011edlines], EDPF [akinlar2012edpf] and EDCircles [akinlar2013edcircles] algorithms
COpenCVForUnity.XimgprocModule.FastBilateralSolverFilter	Interface for implementations of Fast Bilateral Solver
COpenCVForUnity.XimgprocModule.FastGlobalSmootherFilter	Interface for implementations of Fast Global Smoother filter
COpenCVForUnity.XimgprocModule.FastLineDetector	Class implementing the FLD (Fast Line Detector) algorithm described in [Lee14]
COpenCVForUnity.XimgprocModule.FastLineDetector	Class implementing the FLD (Fast Line Detector) algorithm described in [Lee14]
COpenCVForUnity.XimgprocModule.FastLineDetector	Class implementing the FLD (Fast Line Detector) algorithm described in [Lee14]
COpenCVForUnity.XimgprocModule.GraphSegmentation	Graph Based Segmentation Algorithm. The class implements the algorithm described in [PFF2004]
COpenCVForUnity.XimgprocModule.GuidedFilter	Interface for realizations of (Fast) Guided Filter
COpenCVForUnity.XimgprocModule.RFFeatureGetter
COpenCVForUnity.XimgprocModule.RidgeDetectionFilter	Applies Ridge Detection Filter to an input image. Implements Ridge detection similar to the one in Mathematica using the eigen values from the Hessian Matrix of the input image using Sobel Derivatives. Additional refinement can be done using Skeletonization and Binarization. Adapted from [segleafvein] and [M_RF]
COpenCVForUnity.XimgprocModule.ScanSegment	Class implementing the F-DBSCAN (Accelerated superpixel image segmentation with a parallelized DBSCAN algorithm) superpixels algorithm by Loke SC, et al. [loke2021accelerated] for original paper
COpenCVForUnity.XimgprocModule.SelectiveSearchSegmentation	Selective search segmentation algorithm The class implements the algorithm described in [uijlings2013selective]
►COpenCVForUnity.XimgprocModule.SelectiveSearchSegmentationStrategy	Strategie for the selective search segmentation algorithm The class implements a generic stragery for the algorithm described in [uijlings2013selective]
COpenCVForUnity.XimgprocModule.SelectiveSearchSegmentationStrategyColor	Color-based strategy for the selective search segmentation algorithm The class is implemented from the algorithm described in [uijlings2013selective]
COpenCVForUnity.XimgprocModule.SelectiveSearchSegmentationStrategyFill	Fill-based strategy for the selective search segmentation algorithm The class is implemented from the algorithm described in [uijlings2013selective]
COpenCVForUnity.XimgprocModule.SelectiveSearchSegmentationStrategyMultiple	Regroup multiple strategies for the selective search segmentation algorithm
COpenCVForUnity.XimgprocModule.SelectiveSearchSegmentationStrategySize	Size-based strategy for the selective search segmentation algorithm The class is implemented from the algorithm described in [uijlings2013selective]
COpenCVForUnity.XimgprocModule.SelectiveSearchSegmentationStrategyTexture	Texture-based strategy for the selective search segmentation algorithm The class is implemented from the algorithm described in [uijlings2013selective]
►COpenCVForUnity.XimgprocModule.SparseMatchInterpolator	Main interface for all filters, that take sparse matches as an input and produce a dense per-pixel matching (optical flow) as an output
COpenCVForUnity.XimgprocModule.EdgeAwareInterpolator	Sparse match interpolation algorithm based on modified locally-weighted affine estimator from [Revaud2015] and Fast Global Smoother as post-processing filter
COpenCVForUnity.XimgprocModule.RICInterpolator	Sparse match interpolation algorithm based on modified piecewise locally-weighted affine estimator called Robust Interpolation method of Correspondences or RIC from [Hu2017] and Variational and Fast Global Smoother as post-processing filter. The RICInterpolator is a extension of the EdgeAwareInterpolator. Main concept of this extension is an piece-wise affine model based on over-segmentation via SLIC superpixel estimation. The method contains an efficient propagation mechanism to estimate among the pieces-wise models
COpenCVForUnity.XimgprocModule.StructuredEdgeDetection	Class implementing edge detection algorithm from [Dollar2013] :
COpenCVForUnity.XimgprocModule.SuperpixelLSC	Class implementing the LSC (Linear Spectral Clustering) superpixels algorithm described in [LiCVPR2015LSC]
COpenCVForUnity.XimgprocModule.SuperpixelSEEDS	Class implementing the SEEDS (Superpixels Extracted via Energy-Driven Sampling) superpixels algorithm described in [VBRV14]
COpenCVForUnity.XimgprocModule.SuperpixelSLIC	Class implementing the SLIC (Simple Linear Iterative Clustering) superpixels algorithm described in [Achanta2012]
►COpenCVForUnity.XphotoModule.WhiteBalancer	The base class for auto white balance algorithms
COpenCVForUnity.XphotoModule.GrayworldWB	Gray-world white balance algorithm
COpenCVForUnity.XphotoModule.LearningBasedWB	More sophisticated learning-based automatic white balance algorithm
COpenCVForUnity.XphotoModule.SimpleWB	A simple white balance algorithm that works by independently stretching each of the input image channels to the specified range. For increased robustness it ignores the top and bottom $\$p\mathrm{\%}$$ of pixel values
►COpenCVForUnity.CoreModule.Mat	N-dimensional dense array class
COpenCVForUnity.CoreModule.MatOfByte	A specialized Mat class for storing single-channel byte data (CV_8UC1)
COpenCVForUnity.CoreModule.MatOfDMatch	A specialized Mat class for storing DMatch objects with 32-bit floating-point attributes (CV_32FC4)
COpenCVForUnity.CoreModule.MatOfDMatch	A specialized Mat class for storing DMatch objects with 32-bit floating-point attributes (CV_32FC4)
COpenCVForUnity.CoreModule.MatOfDouble	A specialized Mat class for storing single-channel double-precision floating-point data (CV_64FC1)
COpenCVForUnity.CoreModule.MatOfFloat	A specialized Mat class for storing single-channel floating-point data (CV_32FC1)
COpenCVForUnity.CoreModule.MatOfFloat4	A specialized Mat class for storing 4-channel floating-point data (CV_32FC4)
COpenCVForUnity.CoreModule.MatOfFloat4	A specialized Mat class for storing 4-channel floating-point data (CV_32FC4)
COpenCVForUnity.CoreModule.MatOfFloat6	A specialized Mat class for storing 6-channel floating-point data (CV_32FC6)
COpenCVForUnity.CoreModule.MatOfFloat6	A specialized Mat class for storing 6-channel floating-point data (CV_32FC6)
COpenCVForUnity.CoreModule.MatOfInt	A specialized Mat class for storing single-channel integer data (CV_32SC1)
COpenCVForUnity.CoreModule.MatOfInt4	A specialized Mat class for storing 4-channel integer data (CV_32SC4)
COpenCVForUnity.CoreModule.MatOfInt4	A specialized Mat class for storing 4-channel integer data (CV_32SC4)
COpenCVForUnity.CoreModule.MatOfKeyPoint	A specialized Mat class for storing keypoints with 32-bit floating-point attributes (CV_32FC7)
COpenCVForUnity.CoreModule.MatOfKeyPoint	A specialized Mat class for storing keypoints with 32-bit floating-point attributes (CV_32FC7)
COpenCVForUnity.CoreModule.MatOfPoint	A specialized Mat class for storing 2D points with 32-bit integer coordinates (CV_32SC2)
COpenCVForUnity.CoreModule.MatOfPoint	A specialized Mat class for storing 2D points with 32-bit integer coordinates (CV_32SC2)
COpenCVForUnity.CoreModule.MatOfPoint2f	A specialized Mat class for storing 2D points with floating-point coordinates (CV_32FC2)
COpenCVForUnity.CoreModule.MatOfPoint2f	A specialized Mat class for storing 2D points with floating-point coordinates (CV_32FC2)
COpenCVForUnity.CoreModule.MatOfPoint3	A specialized Mat class for storing 3D points with 32-bit integer coordinates (CV_32SC3)
COpenCVForUnity.CoreModule.MatOfPoint3	A specialized Mat class for storing 3D points with 32-bit integer coordinates (CV_32SC3)
COpenCVForUnity.CoreModule.MatOfPoint3f	A specialized Mat class for storing 3D points with 32-bit floating-point coordinates (CV_32FC3)
COpenCVForUnity.CoreModule.MatOfPoint3f	A specialized Mat class for storing 3D points with 32-bit floating-point coordinates (CV_32FC3)
COpenCVForUnity.CoreModule.MatOfRect	A specialized Mat class for storing rectangles with 32-bit integer coordinates (CV_32SC4)
COpenCVForUnity.CoreModule.MatOfRect	A specialized Mat class for storing rectangles with 32-bit integer coordinates (CV_32SC4)
COpenCVForUnity.CoreModule.MatOfRect2d	A specialized Mat class for storing rectangles with 64-bit floating-point coordinates (CV_64FC4)
COpenCVForUnity.CoreModule.MatOfRect2d	A specialized Mat class for storing rectangles with 64-bit floating-point coordinates (CV_64FC4)
COpenCVForUnity.CoreModule.MatOfRotatedRect	A specialized Mat class for storing rotated rectangles with 32-bit floating-point coordinates (CV_32FC5)
COpenCVForUnity.CoreModule.MatOfRotatedRect	A specialized Mat class for storing rotated rectangles with 32-bit floating-point coordinates (CV_32FC5)
COpenCVForUnity.CoreModule.Mat	N-dimensional dense array class
COpenCVForUnity.CoreModule.Mat	N-dimensional dense array class
COpenCVForUnity.CoreModule.TickMeter	Class to measure passing time
COpenCVForUnity.DnnModule.DictValue	This struct stores the scalar value (or array) of one of the following type: double, cv::String or int64
COpenCVForUnity.DnnModule.Image2BlobParams	Processing params of image to blob
COpenCVForUnity.DnnModule.Image2BlobParams	Processing params of image to blob
COpenCVForUnity.DnnModule.Image2BlobParams	Processing params of image to blob
►COpenCVForUnity.DnnModule.Model	This class is presented high-level API for neural networks
COpenCVForUnity.DnnModule.ClassificationModel	This class represents high-level API for classification models
COpenCVForUnity.DnnModule.DetectionModel	This class represents high-level API for object detection networks
COpenCVForUnity.DnnModule.KeypointsModel	This class represents high-level API for keypoints models
COpenCVForUnity.DnnModule.SegmentationModel	This class represents high-level API for segmentation models
►COpenCVForUnity.DnnModule.TextDetectionModel	Base class for text detection networks
COpenCVForUnity.DnnModule.TextDetectionModel_DB	This class represents high-level API for text detection DL networks compatible with DB model
COpenCVForUnity.DnnModule.TextDetectionModel_EAST	This class represents high-level API for text detection DL networks compatible with EAST model
COpenCVForUnity.DnnModule.TextRecognitionModel	This class represents high-level API for text recognition networks
COpenCVForUnity.DnnModule.Model	This class is presented high-level API for neural networks
COpenCVForUnity.DnnModule.Model	This class is presented high-level API for neural networks
COpenCVForUnity.DnnModule.Net	This class allows to create and manipulate comprehensive artificial neural networks
COpenCVForUnity.DnnModule.Net	This class allows to create and manipulate comprehensive artificial neural networks
COpenCVForUnity.DnnModule.Net	This class allows to create and manipulate comprehensive artificial neural networks
COpenCVForUnity.Dnn_superresModule.DnnSuperResImpl	A class to upscale images via convolutional neural networks. The following four models are implemented:
►COpenCVForUnity.FaceModule.PredictCollector	Abstract base class for all strategies of prediction result handling
COpenCVForUnity.FaceModule.StandardCollector	Default predict collector
COpenCVForUnity.Features2dModule.BOWImgDescriptorExtractor	Class to compute an image descriptor using the bag of visual words
►COpenCVForUnity.Features2dModule.BOWTrainer	Abstract base class for training the bag of visual words vocabulary from a set of descriptors
COpenCVForUnity.Features2dModule.BOWKMeansTrainer	Kmeans -based class to train visual vocabulary using the bag of visual words approach. :
COpenCVForUnity.Features2dModule.BOWKMeansTrainer	Kmeans -based class to train visual vocabulary using the bag of visual words approach. :
COpenCVForUnity.Features2dModule.BOWKMeansTrainer	Kmeans -based class to train visual vocabulary using the bag of visual words approach. :
COpenCVForUnity.Features2dModule.SimpleBlobDetector_Params
COpenCVForUnity.ImgprocModule.IntelligentScissorsMB	Intelligent Scissors image segmentation
COpenCVForUnity.ImgprocModule.IntelligentScissorsMB	Intelligent Scissors image segmentation
COpenCVForUnity.ImgprocModule.IntelligentScissorsMB	Intelligent Scissors image segmentation
COpenCVForUnity.ImgprocModule.Subdiv2D
COpenCVForUnity.ImgprocModule.Subdiv2D
COpenCVForUnity.ImgprocModule.Subdiv2D
COpenCVForUnity.MlModule.ParamGrid	The structure represents the logarithmic grid range of statmodel parameters
COpenCVForUnity.MlModule.TrainData	Class encapsulating training data
►COpenCVForUnity.ObjdetectModule.Board	Board of ArUco markers
COpenCVForUnity.ObjdetectModule.CharucoBoard	ChArUco board is a planar chessboard where the markers are placed inside the white squares of a chessboard
COpenCVForUnity.ObjdetectModule.CharucoBoard	ChArUco board is a planar chessboard where the markers are placed inside the white squares of a chessboard
COpenCVForUnity.ObjdetectModule.CharucoBoard	ChArUco board is a planar chessboard where the markers are placed inside the white squares of a chessboard
COpenCVForUnity.ObjdetectModule.GridBoard	Planar board with grid arrangement of markers
COpenCVForUnity.ObjdetectModule.GridBoard	Planar board with grid arrangement of markers
COpenCVForUnity.ObjdetectModule.GridBoard	Planar board with grid arrangement of markers
COpenCVForUnity.ObjdetectModule.Board	Board of ArUco markers
COpenCVForUnity.ObjdetectModule.Board	Board of ArUco markers
COpenCVForUnity.ObjdetectModule.CascadeClassifier	Cascade classifier class for object detection
COpenCVForUnity.ObjdetectModule.CascadeClassifier	Cascade classifier class for object detection
COpenCVForUnity.ObjdetectModule.CascadeClassifier	Cascade classifier class for object detection
COpenCVForUnity.ObjdetectModule.CharucoParameters
COpenCVForUnity.ObjdetectModule.DetectorParameters	Struct DetectorParameters is used by ArucoDetector
COpenCVForUnity.ObjdetectModule.Dictionary	Dictionary is a set of unique ArUco markers of the same size
COpenCVForUnity.ObjdetectModule.FaceDetectorYN	DNN-based face detector
COpenCVForUnity.ObjdetectModule.FaceDetectorYN	DNN-based face detector
COpenCVForUnity.ObjdetectModule.FaceDetectorYN	DNN-based face detector
COpenCVForUnity.ObjdetectModule.FaceRecognizerSF	DNN-based face recognizer
►COpenCVForUnity.ObjdetectModule.GraphicalCodeDetector
COpenCVForUnity.ObjdetectModule.BarcodeDetector
COpenCVForUnity.ObjdetectModule.QRCodeDetector
COpenCVForUnity.ObjdetectModule.QRCodeDetectorAruco
COpenCVForUnity.ObjdetectModule.HOGDescriptor	Implementation of HOG (Histogram of Oriented Gradients) descriptor and object detector
COpenCVForUnity.ObjdetectModule.HOGDescriptor	Implementation of HOG (Histogram of Oriented Gradients) descriptor and object detector
COpenCVForUnity.ObjdetectModule.HOGDescriptor	Implementation of HOG (Histogram of Oriented Gradients) descriptor and object detector
COpenCVForUnity.ObjdetectModule.QRCodeDetectorAruco_Params
COpenCVForUnity.ObjdetectModule.QRCodeEncoder	Groups the object candidate rectangles. rectList Input/output vector of rectangles. Output vector includes retained and grouped rectangles. (The Python list is not modified in place.) weights Input/output vector of weights of rectangles. Output vector includes weights of retained and grouped rectangles. (The Python list is not modified in place.) groupThreshold Minimum possible number of rectangles minus 1. The threshold is used in a group of rectangles to retain it. eps Relative difference between sides of the rectangles to merge them into a group
COpenCVForUnity.ObjdetectModule.QRCodeEncoder_Params	QR code encoder parameters
COpenCVForUnity.ObjdetectModule.RefineParameters	Struct RefineParameters is used by ArucoDetector
COpenCVForUnity.Phase_unwrappingModule.HistogramPhaseUnwrapping_Params	Parameters of phaseUnwrapping constructor
COpenCVForUnity.Structured_lightModule.SinusoidalPattern_Params	Parameters of SinusoidalPattern constructor width Projector's width. height Projector's height. nbrOfPeriods Number of period along the patterns direction. shiftValue Phase shift between two consecutive patterns. methodId Allow to choose between FTP, PSP and FAPS. nbrOfPixelsBetweenMarkers Number of pixels between two consecutive markers on the same row. setMarkers Allow to set markers on the patterns. markersLocation vector used to store markers location on the patterns
►COpenCVForUnity.TextModule.BaseOCR
COpenCVForUnity.TextModule.OCRBeamSearchDecoder	OCRBeamSearchDecoder class provides an interface for OCR using Beam Search algorithm
COpenCVForUnity.TextModule.OCRHMMDecoder	OCRHMMDecoder class provides an interface for OCR using Hidden Markov Models
COpenCVForUnity.TextModule.ERFilter_Callback	Callback with the classifier is made a class
COpenCVForUnity.TextModule.OCRBeamSearchDecoder_ClassifierCallback	Callback with the character classifier is made a class
COpenCVForUnity.TextModule.OCRHMMDecoder_ClassifierCallback	Callback with the character classifier is made a class
►COpenCVForUnity.TextModule.TextDetector	An abstract class providing interface for text detection algorithms
COpenCVForUnity.TextModule.TextDetectorCNN	TextDetectorCNN class provides the functionallity of text bounding box detection. This class is representing to find bounding boxes of text words given an input image. This class uses OpenCV dnn module to load pre-trained model described in [LiaoSBWL17]. The original repository with the modified SSD Caffe version: https://github.com/MhLiao/TextBoxes. Model can be downloaded from DropBox. Modified .prototxt file with the model description can be found in opencv_contrib/modules/text/samples/textbox.prototxt
COpenCVForUnity.TrackingModule.TrackerCSRT_Params
COpenCVForUnity.TrackingModule.TrackerKCF_Params
COpenCVForUnity.VideoModule.KalmanFilter	Kalman filter class
►COpenCVForUnity.VideoModule.Tracker	Base abstract class for the long-term tracker
COpenCVForUnity.TrackingModule.TrackerCSRT	CSRT tracker
COpenCVForUnity.TrackingModule.TrackerKCF	KCF (Kernelized Correlation Filter) tracker
COpenCVForUnity.VideoModule.TrackerDaSiamRPN
COpenCVForUnity.VideoModule.TrackerGOTURN	GOTURN (Generic Object Tracking Using Regression Networks) tracker
COpenCVForUnity.VideoModule.TrackerMIL	The MIL algorithm trains a classifier in an online manner to separate the object from the background
COpenCVForUnity.VideoModule.TrackerNano	Nano tracker is a super lightweight dnn-based general object tracking
COpenCVForUnity.VideoModule.TrackerVit	VIT tracker is a super lightweight dnn-based general object tracking
COpenCVForUnity.VideoModule.Tracker	Base abstract class for the long-term tracker
COpenCVForUnity.VideoModule.Tracker	Base abstract class for the long-term tracker
COpenCVForUnity.VideoModule.TrackerDaSiamRPN_Params
COpenCVForUnity.VideoModule.TrackerGOTURN_Params
COpenCVForUnity.VideoModule.TrackerMIL_Params
COpenCVForUnity.VideoModule.TrackerNano_Params
COpenCVForUnity.VideoModule.TrackerVit_Params
COpenCVForUnity.VideoModule.TrackerVit_Params
COpenCVForUnity.VideoModule.TrackerVit_Params
COpenCVForUnity.VideoioModule.VideoCapture	Class for video capturing from video files, image sequences or cameras
COpenCVForUnity.VideoioModule.VideoWriter	Video writer class
COpenCVForUnity.VideoioModule.VideoWriter	Video writer class
COpenCVForUnity.VideoioModule.VideoWriter	Video writer class
COpenCVForUnity.Wechat_qrcodeModule.WeChatQRCode	WeChat QRCode includes two CNN-based models: A object detection model and a super resolution model. Object detection model is applied to detect QRCode with the bounding box. super resolution model is applied to zoom in QRCode when it is small
COpenCVForUnity.XimgprocModule.EdgeDrawing_Params
►CIEquatable
COpenCVForUnity.CoreModule.DMatch	Class for matching keypoint descriptors
COpenCVForUnity.CoreModule.KeyPoint	Data structure for salient point detectors
COpenCVForUnity.CoreModule.Point	Template class for 2D points specified by its coordinates x and y
COpenCVForUnity.CoreModule.Point3	Template class for 3D points specified by its coordinates x, y and z
COpenCVForUnity.CoreModule.Range	Template class specifying a continuous subsequence (slice) of a sequence
COpenCVForUnity.CoreModule.Rect	Template class for 2D rectangles
COpenCVForUnity.CoreModule.Rect2d	Template class for 2D rectangles
COpenCVForUnity.CoreModule.RotatedRect	The class represents rotated (i.e. not up-right) rectangles on a plane
COpenCVForUnity.CoreModule.Scalar	Template class for a 4-element vector derived from Vec
COpenCVForUnity.CoreModule.Size	Template class for specifying the size of an image or rectangle
COpenCVForUnity.CoreModule.TermCriteria	The class defining termination criteria for iterative algorithms
COpenCVForUnity.ImgprocModule.Moments	Template class for moments
COpenCVForUnity.UnityUtils.Vec10d	10-Vector struct of double [CvType.CV_64FC10, Moments]
COpenCVForUnity.UnityUtils.Vec2b	2-Vector struct of byte [CvType.CV_8UC2]
COpenCVForUnity.UnityUtils.Vec2c	2-Vector struct of sbyte [CvType.CV_8SC2]
COpenCVForUnity.UnityUtils.Vec2d	2-Vector struct of double [CvType.CV_64FC2, Point]
COpenCVForUnity.UnityUtils.Vec2f	2-Vector struct of float [CvType.CV_32FC2]
COpenCVForUnity.UnityUtils.Vec2i	2-Vector struct of int [CvType.CV_32SC2, Range]
COpenCVForUnity.UnityUtils.Vec2s	2-Vector struct of short [CvType.CV_16SC2]
COpenCVForUnity.UnityUtils.Vec2w	2-Vector struct of ushort [CvType.CV_16UC2, Size]
COpenCVForUnity.UnityUtils.Vec3b	3-Vector struct of byte [CvType.CV_8UC3]
COpenCVForUnity.UnityUtils.Vec3c	3-Vector struct of sbyte [CvType.CV_8SC3]
COpenCVForUnity.UnityUtils.Vec3d	3-Vector struct of double [CvType.CV_64FC3, Point3]
COpenCVForUnity.UnityUtils.Vec3f	3-Vector struct of float [CvType.CV_32FC3]
COpenCVForUnity.UnityUtils.Vec3i	3-Vector struct of int [CvType.CV_32SC3]
COpenCVForUnity.UnityUtils.Vec3s	3-Vector struct of short [CvType.CV_16SC3]
COpenCVForUnity.UnityUtils.Vec3w	3-Vector struct of ushort [CvType.CV_16UC3]
COpenCVForUnity.UnityUtils.Vec4b	4-Vector struct of byte [CvType.CV_8UC4]
COpenCVForUnity.UnityUtils.Vec4c	4-Vector struct of sbyte [CvType.CV_8SC4]
COpenCVForUnity.UnityUtils.Vec4d	4-Vector struct of double [CvType.CV_64FC4]
COpenCVForUnity.UnityUtils.Vec4f	4-Vector struct of float [CvType.CV_32FC4, DMatch]
COpenCVForUnity.UnityUtils.Vec4i	4-Vector struct of int [CvType.CV_32SC4, Rect]
COpenCVForUnity.UnityUtils.Vec4s	4-Vector struct of short [CvType.CV_16SC4]
COpenCVForUnity.UnityUtils.Vec4w	4-Vector struct of ushort [CvType.CV_16UC4, Rect2d, Scalar]
COpenCVForUnity.UnityUtils.Vec5d	5-Vector struct of double [CvType.CV_64FC5, RotatedRect]
COpenCVForUnity.UnityUtils.Vec5f	5-Vector struct of float [CvType.CV_32FC5, MatOfRotatedRect]
COpenCVForUnity.UnityUtils.Vec6f	6-Vector struct of float [CvType.CV_32FC6, KeyPoint]
COpenCVForUnity.UnityUtils.Vec7d	7-Vector struct of double [CvType.CV_32FC7]
COpenCVForUnity.UnityUtils.Vec7f	7-Vector struct of float [CvType.CV_32FC7, KeyPoint]
►COpenCVForUnity.UnityUtils.Helper.IMatUpdateFPSProvider
COpenCVForUnity.UnityUtils.Helper.AsyncGPUReadback2MatHelper	A helper component class for efficiently converting Unity Texture objects, such as RenderTexture and external texture format Texture2D, to OpenCV Mat format using AsyncGPUReadback
COpenCVForUnity.UnityUtils.Helper.Image2MatHelper	A helper component class for loading an image file using OpenCV's Imgcodecs.imread method and converting it to an OpenCV Mat format
COpenCVForUnity.UnityUtils.Helper.WebCamTexture2MatAsyncGPUHelper	A helper component class for efficiently obtaining camera frames from WebCamTexture and converting them to OpenCV Mat format in real-time using AsyncGPUReadback
COpenCVForUnity.Img_hashModule.Img_hash
COpenCVForUnity.ImgcodecsModule.Imgcodecs
COpenCVForUnity.ImgprocModule.Imgproc
►COpenCVForUnity.UnityUtils.MOT.ByteTrack.IRectBase
COpenCVForUnity.UnityUtils.MOT.ByteTrack.TlwhRect
►COpenCVForUnity.UnityUtils.Helper.ISource2MatHelper
►COpenCVForUnity.UnityUtils.Helper.ICameraSource2MatHelper
►COpenCVForUnity.UnityUtils.Helper.WebCamTexture2MatHelper	A helper component class for obtaining camera frames from WebCamTexture and converting them to OpenCV Mat format in real-time
COpenCVForUnity.UnityUtils.Helper.WebCamTexture2MatAsyncGPUHelper	A helper component class for efficiently obtaining camera frames from WebCamTexture and converting them to OpenCV Mat format in real-time using AsyncGPUReadback
►COpenCVForUnity.UnityUtils.Helper.IImageSource2MatHelper
COpenCVForUnity.UnityUtils.Helper.Image2MatHelper	A helper component class for loading an image file using OpenCV's Imgcodecs.imread method and converting it to an OpenCV Mat format
►COpenCVForUnity.UnityUtils.Helper.ITextureSource2MatHelper
COpenCVForUnity.UnityUtils.Helper.AsyncGPUReadback2MatHelper	A helper component class for efficiently converting Unity Texture objects, such as RenderTexture and external texture format Texture2D, to OpenCV Mat format using AsyncGPUReadback
►COpenCVForUnity.UnityUtils.Helper.IVideoSource2MatHelper
COpenCVForUnity.UnityUtils.Helper.UnityVideoPlayer2MatHelper	A helper component class for obtaining video frames from a file using Unity's VideoPlayer and converting them to OpenCV Mat format
COpenCVForUnity.UnityUtils.Helper.VideoCapture2MatHelper	A helper component class for obtaining video frames from a file using OpenCV's VideoCapture and converting them to OpenCV Mat format
COpenCVForUnity.UnityUtils.Helper.MultiSource2MatHelper	A versatile helper component class for obtaining frames as OpenCV Mat objects from multiple sources, allowing dynamic switching between different ISource2MatHelper classes
►CIStructuralComparable
COpenCVForUnity.UnityUtils.Vec10d	10-Vector struct of double [CvType.CV_64FC10, Moments]
COpenCVForUnity.UnityUtils.Vec2b	2-Vector struct of byte [CvType.CV_8UC2]
COpenCVForUnity.UnityUtils.Vec2c	2-Vector struct of sbyte [CvType.CV_8SC2]
COpenCVForUnity.UnityUtils.Vec2d	2-Vector struct of double [CvType.CV_64FC2, Point]
COpenCVForUnity.UnityUtils.Vec2f	2-Vector struct of float [CvType.CV_32FC2]
COpenCVForUnity.UnityUtils.Vec2i	2-Vector struct of int [CvType.CV_32SC2, Range]
COpenCVForUnity.UnityUtils.Vec2s	2-Vector struct of short [CvType.CV_16SC2]
COpenCVForUnity.UnityUtils.Vec2w	2-Vector struct of ushort [CvType.CV_16UC2, Size]
COpenCVForUnity.UnityUtils.Vec3b	3-Vector struct of byte [CvType.CV_8UC3]
COpenCVForUnity.UnityUtils.Vec3c	3-Vector struct of sbyte [CvType.CV_8SC3]
COpenCVForUnity.UnityUtils.Vec3d	3-Vector struct of double [CvType.CV_64FC3, Point3]
COpenCVForUnity.UnityUtils.Vec3f	3-Vector struct of float [CvType.CV_32FC3]
COpenCVForUnity.UnityUtils.Vec3i	3-Vector struct of int [CvType.CV_32SC3]
COpenCVForUnity.UnityUtils.Vec3s	3-Vector struct of short [CvType.CV_16SC3]
COpenCVForUnity.UnityUtils.Vec3w	3-Vector struct of ushort [CvType.CV_16UC3]
COpenCVForUnity.UnityUtils.Vec4b	4-Vector struct of byte [CvType.CV_8UC4]
COpenCVForUnity.UnityUtils.Vec4c	4-Vector struct of sbyte [CvType.CV_8SC4]
COpenCVForUnity.UnityUtils.Vec4d	4-Vector struct of double [CvType.CV_64FC4]
COpenCVForUnity.UnityUtils.Vec4f	4-Vector struct of float [CvType.CV_32FC4, DMatch]
COpenCVForUnity.UnityUtils.Vec4i	4-Vector struct of int [CvType.CV_32SC4, Rect]
COpenCVForUnity.UnityUtils.Vec4s	4-Vector struct of short [CvType.CV_16SC4]
COpenCVForUnity.UnityUtils.Vec4w	4-Vector struct of ushort [CvType.CV_16UC4, Rect2d, Scalar]
COpenCVForUnity.UnityUtils.Vec5d	5-Vector struct of double [CvType.CV_64FC5, RotatedRect]
COpenCVForUnity.UnityUtils.Vec5f	5-Vector struct of float [CvType.CV_32FC5, MatOfRotatedRect]
COpenCVForUnity.UnityUtils.Vec6f	6-Vector struct of float [CvType.CV_32FC6, KeyPoint]
COpenCVForUnity.UnityUtils.Vec7d	7-Vector struct of double [CvType.CV_32FC7]
COpenCVForUnity.UnityUtils.Vec7f	7-Vector struct of float [CvType.CV_32FC7, KeyPoint]
►CIStructuralEquatable
COpenCVForUnity.UnityUtils.Vec10d	10-Vector struct of double [CvType.CV_64FC10, Moments]
COpenCVForUnity.UnityUtils.Vec2b	2-Vector struct of byte [CvType.CV_8UC2]
COpenCVForUnity.UnityUtils.Vec2c	2-Vector struct of sbyte [CvType.CV_8SC2]
COpenCVForUnity.UnityUtils.Vec2d	2-Vector struct of double [CvType.CV_64FC2, Point]
COpenCVForUnity.UnityUtils.Vec2f	2-Vector struct of float [CvType.CV_32FC2]
COpenCVForUnity.UnityUtils.Vec2i	2-Vector struct of int [CvType.CV_32SC2, Range]
COpenCVForUnity.UnityUtils.Vec2s	2-Vector struct of short [CvType.CV_16SC2]
COpenCVForUnity.UnityUtils.Vec2w	2-Vector struct of ushort [CvType.CV_16UC2, Size]
COpenCVForUnity.UnityUtils.Vec3b	3-Vector struct of byte [CvType.CV_8UC3]
COpenCVForUnity.UnityUtils.Vec3c	3-Vector struct of sbyte [CvType.CV_8SC3]
COpenCVForUnity.UnityUtils.Vec3d	3-Vector struct of double [CvType.CV_64FC3, Point3]
COpenCVForUnity.UnityUtils.Vec3f	3-Vector struct of float [CvType.CV_32FC3]
COpenCVForUnity.UnityUtils.Vec3i	3-Vector struct of int [CvType.CV_32SC3]
COpenCVForUnity.UnityUtils.Vec3s	3-Vector struct of short [CvType.CV_16SC3]
COpenCVForUnity.UnityUtils.Vec3w	3-Vector struct of ushort [CvType.CV_16UC3]
COpenCVForUnity.UnityUtils.Vec4b	4-Vector struct of byte [CvType.CV_8UC4]
COpenCVForUnity.UnityUtils.Vec4c	4-Vector struct of sbyte [CvType.CV_8SC4]
COpenCVForUnity.UnityUtils.Vec4d	4-Vector struct of double [CvType.CV_64FC4]
COpenCVForUnity.UnityUtils.Vec4f	4-Vector struct of float [CvType.CV_32FC4, DMatch]
COpenCVForUnity.UnityUtils.Vec4i	4-Vector struct of int [CvType.CV_32SC4, Rect]
COpenCVForUnity.UnityUtils.Vec4s	4-Vector struct of short [CvType.CV_16SC4]
COpenCVForUnity.UnityUtils.Vec4w	4-Vector struct of ushort [CvType.CV_16UC4, Rect2d, Scalar]
COpenCVForUnity.UnityUtils.Vec5d	5-Vector struct of double [CvType.CV_64FC5, RotatedRect]
COpenCVForUnity.UnityUtils.Vec5f	5-Vector struct of float [CvType.CV_32FC5, MatOfRotatedRect]
COpenCVForUnity.UnityUtils.Vec6f	6-Vector struct of float [CvType.CV_32FC6, KeyPoint]
COpenCVForUnity.UnityUtils.Vec7d	7-Vector struct of double [CvType.CV_32FC7]
COpenCVForUnity.UnityUtils.Vec7f	7-Vector struct of float [CvType.CV_32FC7, KeyPoint]
COpenCVForUnity.UnityUtils.MOT.ByteTrack.KalmanFilter
COpenCVForUnity.UnityUtils.MOT.ByteTrack.Lapjv
COpenCVForUnity.UnityUtils.MatUtils
COpenCVForUnity.CoreModule.Core.MinMaxLocResult
COpenCVForUnity.MlModule.Ml
►CMonoBehaviour
COpenCVForUnity.UnityUtils.Helper.ARHelper	A helper component for managing AR (Augmented Reality) functionalities
COpenCVForUnity.UnityUtils.Helper.AsyncGPUReadback2MatHelper	A helper component class for efficiently converting Unity Texture objects, such as RenderTexture and external texture format Texture2D, to OpenCV Mat format using AsyncGPUReadback
COpenCVForUnity.UnityUtils.Helper.Image2MatHelper	A helper component class for loading an image file using OpenCV's Imgcodecs.imread method and converting it to an OpenCV Mat format
COpenCVForUnity.UnityUtils.Helper.ImageOptimizationHelper	A helper component for optimizing image processing in Unity by managing frame skipping and downscaling operations. v1.1.1
COpenCVForUnity.UnityUtils.Helper.MultiSource2MatHelper	A versatile helper component class for obtaining frames as OpenCV Mat objects from multiple sources, allowing dynamic switching between different ISource2MatHelper classes
COpenCVForUnity.UnityUtils.Helper.UnityVideoPlayer2MatHelper	A helper component class for obtaining video frames from a file using Unity's VideoPlayer and converting them to OpenCV Mat format
COpenCVForUnity.UnityUtils.Helper.VideoCapture2MatHelper	A helper component class for obtaining video frames from a file using OpenCV's VideoCapture and converting them to OpenCV Mat format
COpenCVForUnity.UnityUtils.Helper.VideoCaptureToMatHelper	VideoCapture to mat helper. v 1.0.4
COpenCVForUnity.UnityUtils.Helper.WebCamTexture2MatHelper	A helper component class for obtaining camera frames from WebCamTexture and converting them to OpenCV Mat format in real-time
►COpenCVForUnity.UnityUtils.Helper.WebCamTextureToMatHelper	WebCamTexture to mat helper. v 1.1.6
COpenCVForUnity.UnityUtils.Helper.VideoCaptureCameraInputToMatHelper	VideoCaptureCameraInput to mat helper. v 1.0.1 Depends on OpenCVForUnity version 2.4.4 (WebCamTextureToMatHelper v 1.1.3) or later. (Use the WebCamDevice.isFrontFacing and WebCamTexture.videoRotationAngle properties to flip the camera input image in VideoCaptue to the correct orientation.)
COpenCVForUnity.ObjdetectModule.Objdetect
COpenCVForUnity.Phase_unwrappingModule.Phase_unwrapping
COpenCVForUnity.PhotoModule.Photo
COpenCVForUnity.PlotModule.Plot
COpenCVForUnity.UnityUtils.PoseData
COpenCVForUnity.UnityUtils.MOT.ByteTrack.RectOperations
COpenCVForUnity.UnityUtils.Helper.Source2MatHelperUtils
COpenCVForUnity.Structured_lightModule.Structured_light
COpenCVForUnity.TextModule.Text
COpenCVForUnity.UnityUtils.MOT.ByteTrack.Track
COpenCVForUnity.TrackingModule.Tracking
COpenCVForUnity.UnityUtils.Utils
COpenCVForUnity.VideoModule.Video
COpenCVForUnity.VideoioModule.Videoio
COpenCVForUnity.Wechat_qrcodeModule.Wechat_qrcode
COpenCVForUnity.Xfeatures2dModule.Xfeatures2d
COpenCVForUnity.XimgprocModule.Ximgproc
COpenCVForUnity.XphotoModule.Xphoto
►CUnityEvent
COpenCVForUnity.UnityUtils.Helper.Source2MatHelperErrorUnityEvent
COpenCVForUnity.UnityUtils.Helper.VideoCaptureToMatHelper.ErrorUnityEvent
COpenCVForUnity.UnityUtils.Helper.WebCamTextureToMatHelper.ErrorUnityEvent