| Package | Description |
|---|---|
| org.bytedeco.javacpp | |
| org.bytedeco.javacpp.helper |
| Class and Description |
|---|
| cvkernels.KernelData |
| opencv_aruco.Board
\brief Board of markers
A board is a set of markers in the 3D space with a common cordinate system.
|
| opencv_aruco.CharucoBoard
\addtogroup aruco
\{
|
| opencv_aruco.DetectorParameters
\brief Parameters for the detectMarker process:
- adaptiveThreshWinSizeMin: minimum window size for adaptive thresholding before finding
contours (default 3).
|
| opencv_aruco.Dictionary
\addtogroup aruco
\{
|
| opencv_aruco.GridBoard
\brief Planar board with grid arrangement of markers
More common type of board.
|
| opencv_bgsegm.BackgroundSubtractorCNT
\brief Background subtraction based on counting.
|
| opencv_bgsegm.BackgroundSubtractorGMG
\brief Background Subtractor module based on the algorithm given in \cite Gold2012 .
|
| opencv_bgsegm.BackgroundSubtractorGSOC
\brief Implementation of the different yet better algorithm which is called GSOC, as it was implemented during GSOC and was not originated from any paper.
|
| opencv_bgsegm.BackgroundSubtractorLSBP
\brief Background Subtraction using Local SVD Binary Pattern.
|
| opencv_bgsegm.BackgroundSubtractorLSBPDesc
\brief This is for calculation of the LSBP descriptors.
|
| opencv_bgsegm.BackgroundSubtractorMOG
\addtogroup bgsegm
\{
|
| opencv_bgsegm.SyntheticSequenceGenerator
\brief Synthetic frame sequence generator for testing background subtraction algorithms.
|
| opencv_bioinspired.Retina
\brief class which allows the Gipsa/Listic Labs model to be used with OpenCV.
|
| opencv_bioinspired.RetinaFastToneMapping
\addtogroup bioinspired
\{
|
| opencv_bioinspired.RetinaParameters
\brief retina model parameters structure
|
| opencv_bioinspired.RetinaParameters.IplMagnoParameters
Inner Plexiform Layer Magnocellular channel (IplMagno)
|
| opencv_bioinspired.RetinaParameters.OPLandIplParvoParameters
Outer Plexiform Layer (OPL) and Inner Plexiform Layer Parvocellular (IplParvo) parameters
|
| opencv_bioinspired.SegmentationParameters
\addtogroup bioinspired
\{
|
| opencv_bioinspired.TransientAreasSegmentationModule
\brief class which provides a transient/moving areas segmentation module
|
| opencv_calib3d.CirclesGridFinderParameters |
| opencv_calib3d.CirclesGridFinderParameters2 |
| opencv_calib3d.CvLevMarq
\} calib3d_c
|
| opencv_calib3d.CvPOSITObject
\
Camera Calibration, Pose Estimation and Stereo *
\
|
| opencv_calib3d.CvStereoBMState |
| opencv_calib3d.StereoBM
\brief Class for computing stereo correspondence using the block matching algorithm, introduced and
contributed to OpenCV by K.
|
| opencv_calib3d.StereoMatcher
\brief The base class for stereo correspondence algorithms.
|
| opencv_calib3d.StereoSGBM
\brief The class implements the modified H.
|
| opencv_core.Algorithm
\brief This is a base class for all more or less complex algorithms in OpenCV
|
| opencv_core.BufferPoolController
\addtogroup core
\{
|
| opencv_core.ByteVectorVector |
| opencv_core.Complexd |
| opencv_core.Complexf
\addtogroup core_basic
\{
|
| opencv_core.ConjGradSolver
\brief This class is used to perform the non-linear non-constrained minimization of a function
with known gradient,
|
| opencv_core.Context |
| opencv_core.Context.Impl |
| opencv_core.Cv_iplAllocateImageData |
| opencv_core.Cv_iplCloneImage |
| opencv_core.Cv_iplCreateImageHeader |
| opencv_core.Cv_iplCreateROI |
| opencv_core.Cv_iplDeallocate |
| opencv_core.Cv16suf |
| opencv_core.Cv32suf |
| opencv_core.Cv64suf |
| opencv_core.CvAttrList
\brief List of attributes.
|
| opencv_core.CvBox2D
\sa RotatedRect
|
| opencv_core.CvChain
Chain/Contour
|
| opencv_core.CvCloneFunc |
| opencv_core.CvCmpFunc
a < b ? -1 : a > b ? 1 : 0
|
| opencv_core.CvContour |
| opencv_core.CvErrorCallback |
| opencv_core.CvFileNode
Basic element of the file storage - scalar or collection:
|
| opencv_core.CvFileNodeHash |
| opencv_core.CvFileStorage
"black box" file storage
|
| opencv_core.CvGraph
Graph is "derived" from the set (this is set a of vertices)
and includes another set (edges)
|
| opencv_core.CvGraphEdge
\name Graph
|
| opencv_core.CvGraphScanner |
| opencv_core.CvGraphVtx |
| opencv_core.CvGraphVtx2D |
| opencv_core.CvHistogram |
| opencv_core.CvIsInstanceFunc |
| opencv_core.CvLineIterator
Line iterator state:
|
| opencv_core.CvMat
Deprecated.
CvMat is now obsolete; consider using Mat instead.
|
| opencv_core.CvMatND
Deprecated.
consider using cv::Mat instead
|
| opencv_core.CvMemBlock
Memory storage
|
| opencv_core.CvMemStorage |
| opencv_core.CvMemStoragePos |
| opencv_core.CvModuleInfo |
| opencv_core.CvNArrayIterator
matrix iterator: used for n-ary operations on dense arrays
|
| opencv_core.CvPluginFuncInfo
System data types
|
| opencv_core.CvPoint
CvPoint and variants
|
| opencv_core.CvPoint2D32f |
| opencv_core.CvPoint2D64f |
| opencv_core.CvPoint3D32f |
| opencv_core.CvPoint3D64f |
| opencv_core.CvReadFunc |
| opencv_core.CvRect
\sa Rect_
|
| opencv_core.CvReleaseFunc |
| opencv_core.CvScalar
\sa Scalar_
|
| opencv_core.CvSeq
Pointer to the first sequence block.
|
| opencv_core.CvSeqBlock
Sequence
|
| opencv_core.CvSeqReader
pointer to previous element
|
| opencv_core.CvSeqWriter
pointer to the end of block
|
| opencv_core.CvSet |
| opencv_core.CvSetElem
\brief Set
Order is not preserved.
|
| opencv_core.CvSize
CvSize's & CvBox
|
| opencv_core.CvSize2D32f |
| opencv_core.CvSlice |
| opencv_core.CvSparseMat |
| opencv_core.CvSparseMatIterator |
| opencv_core.CvSparseNode
iteration through a sparse array
|
| opencv_core.CvString |
| opencv_core.CvStringHashNode
All the keys (names) of elements in the read file storage
are stored in the hash to speed up the lookup operations:
|
| opencv_core.CvTermCriteria
\sa TermCriteria
|
| opencv_core.CvTreeNodeIterator
Iteration through the sequence tree
|
| opencv_core.CvType
\addtogroup core_c_glue
\{
|
| opencv_core.CvTypeInfo
\brief Type information
|
| opencv_core.CvWriteFunc |
| opencv_core.DCT2D |
| opencv_core.Device |
| opencv_core.DeviceInfo
\brief Class providing functionality for querying the specified GPU properties.
|
| opencv_core.DFT1D |
| opencv_core.DFT2D |
| opencv_core.DMatch
\brief Class for matching keypoint descriptors
|
| opencv_core.DMatchVector |
| opencv_core.DMatchVector.Iterator |
| opencv_core.DMatchVectorVector |
| opencv_core.DMatchVectorVector.Iterator |
| opencv_core.DownhillSolver
\brief This class is used to perform the non-linear non-constrained minimization of a function,
|
| opencv_core.ErrorCallback |
| opencv_core.Event |
| opencv_core.FileNode
\brief File Storage Node class.
|
| opencv_core.FileNodeIterator
\brief used to iterate through sequences and mappings.
|
| opencv_core.FileNodeIterator.SeqReader |
| opencv_core.FileStorage
\brief XML/YAML/JSON file storage class that encapsulates all the information necessary for writing or
reading data to/from a file.
|
| opencv_core.Formatted
\} core_cluster
|
| opencv_core.Formatter
\todo document
|
| opencv_core.GpuMat
\brief Base storage class for GPU memory with reference counting.
|
| opencv_core.GpuMat.Allocator |
| opencv_core.GpuMatVector |
| opencv_core.GpuMatVector.Iterator |
| opencv_core.Hamming
replaced with CV_Assert(expr) in Debug configuration
|
| opencv_core.HostMem
\brief Class with reference counting wrapping special memory type allocation functions from CUDA.
|
| opencv_core.Image2D |
| opencv_core.InstrNode
\endcond
|
| opencv_core.IntDoubleMap |
| opencv_core.IntDoubleMap.Iterator |
| opencv_core.IntDoublePairVector |
| opencv_core.IntIntPair |
| opencv_core.IntIntPairVector |
| opencv_core.IntVectorVector |
| opencv_core.IplConvKernel |
| opencv_core.IplConvKernelFP |
| opencv_core.IplImage
The IplImage is taken from the Intel Image Processing Library, in which the format is native.
|
| opencv_core.IplROI |
| opencv_core.IplTileInfo |
| opencv_core.Kernel |
| opencv_core.KernelArg |
| opencv_core.KeyPoint
\brief Data structure for salient point detectors.
|
| opencv_core.KeyPointVector |
| opencv_core.KeyPointVector.Iterator |
| opencv_core.KeyPointVectorVector |
| opencv_core.KeyPointVectorVector.Iterator |
| opencv_core.LDA
\brief Linear Discriminant Analysis
\todo document this class
|
| opencv_core.Mat
\brief n-dimensional dense array class \anchor CVMat_Details
|
| opencv_core.MatAllocator
\brief Custom array allocator
|
| opencv_core.MatBytePairVector |
| opencv_core.MatConstIterator
\brief Template sparse n-dimensional array class derived from SparseMat
|
| opencv_core.MatExpr
\brief Matrix expression representation
\anchor MatrixExpressions
This is a list of implemented matrix operations that can be combined in arbitrary complex
expressions (here A, B stand for matrices ( Mat ), s for a scalar ( Scalar ), alpha for a
real-valued scalar ( double )):
- Addition, subtraction, negation:
A+B, A-B, A+s, A-s, s+A, s-A, -A
- Scaling: A*alpha
- Per-element multiplication and division: A.mul(B), A/B, alpha/A
- Matrix multiplication: A*B
- Transposition: A.t() (means AT)
- Matrix inversion and pseudo-inversion, solving linear systems and least-squares problems:
A.inv([method]) (~ A<sup>-1</sup>), A.inv([method])*B (~ X: AX=B)
- Comparison: A cmpop B, A cmpop alpha, alpha cmpop A, where *cmpop* is one of
>, >=, ==, !=, <=, <. |
| opencv_core.MatOp |
| opencv_core.MatSize |
| opencv_core.MatStep |
| opencv_core.MatVector |
| opencv_core.MatVector.Iterator |
| opencv_core.MatVectorVector |
| opencv_core.MatVectorVector.Iterator |
| opencv_core.MinProblemSolver
\brief Basic interface for all solvers
|
| opencv_core.MinProblemSolver.Function
\brief Represents function being optimized
|
| opencv_core.Moments
\} core_basic
|
| opencv_core.Mutex |
| opencv_core.NAryMatIterator
\brief n-ary multi-dimensional array iterator.
|
| opencv_core.NodeData |
| opencv_core.NodeDataTls |
| opencv_core.NodeDataTlsData |
| opencv_core.NodeDataTlsVector |
| opencv_core.NodeDataTlsVector.Iterator |
| opencv_core.OclPlatform |
| opencv_core.ParallelLoopBody
\brief Base class for parallel data processors
|
| opencv_core.Param |
| opencv_core.PCA
\brief Principal Component Analysis
|
| opencv_core.PlatformInfo |
| opencv_core.Point
\brief Template class for 2D points specified by its coordinates
x and y. |
| opencv_core.Point2d |
| opencv_core.Point2dVector |
| opencv_core.Point2dVector.Iterator |
| opencv_core.Point2dVectorVector |
| opencv_core.Point2dVectorVector.Iterator |
| opencv_core.Point2f |
| opencv_core.Point2fVector |
| opencv_core.Point2fVector.Iterator |
| opencv_core.Point2fVectorVector |
| opencv_core.Point2fVectorVector.Iterator |
| opencv_core.Point3d |
| opencv_core.Point3f |
| opencv_core.Point3fVector |
| opencv_core.Point3fVector.Iterator |
| opencv_core.Point3fVectorVector |
| opencv_core.Point3fVectorVector.Iterator |
| opencv_core.Point3i
\brief Template class for 3D points specified by its coordinates
x, y and z. |
| opencv_core.Point3iVector |
| opencv_core.Point3iVector.Iterator |
| opencv_core.PointVector |
| opencv_core.PointVector.Iterator |
| opencv_core.PointVectorVector |
| opencv_core.PointVectorVector.Iterator |
| opencv_core.Program |
| opencv_core.ProgramSource |
| opencv_core.Queue |
| opencv_core.Range
\brief Template class specifying a continuous subsequence (slice) of a sequence.
|
| opencv_core.Rect
\brief Template class for 2D rectangles
|
| opencv_core.Rect2d |
| opencv_core.Rect2dVector |
| opencv_core.Rect2dVector.Iterator |
| opencv_core.Rect2f |
| opencv_core.RectVector |
| opencv_core.RectVector.Iterator |
| opencv_core.RectVectorVector |
| opencv_core.RectVectorVector.Iterator |
| opencv_core.RefOrVoid
\} core_utils
|
| opencv_core.RNG
\brief Random Number Generator
|
| opencv_core.RNG_MT19937
\brief Mersenne Twister random number generator
|
| opencv_core.RotatedRect
\brief The class represents rotated (i.e.
|
| opencv_core.Scalar
\brief Template class for a 4-element vector derived from Vec.
|
| opencv_core.Scalar4i |
| opencv_core.ScalarVector |
| opencv_core.ScalarVector.Iterator |
| opencv_core.Size
\brief Template class for specifying the size of an image or rectangle.
|
| opencv_core.Size2d |
| opencv_core.Size2f |
| opencv_core.SizeVector |
| opencv_core.SizeVector.Iterator |
| opencv_core.SparseMat
\brief The class SparseMat represents multi-dimensional sparse numerical arrays.
|
| opencv_core.SparseMat.Hdr
the sparse matrix header
|
| opencv_core.SparseMat.Node
sparse matrix node - element of a hash table
|
| opencv_core.SparseMatConstIterator
\brief Read-Only Sparse Matrix Iterator.
|
| opencv_core.SparseMatIterator
\brief Read-write Sparse Matrix Iterator
|
| opencv_core.Stream
\brief This class encapsulates a queue of asynchronous calls.
|
| opencv_core.Stream.StreamCallback |
| opencv_core.StringVector |
| opencv_core.StringVector.Iterator |
| opencv_core.SVD
\brief Singular Value Decomposition
|
| opencv_core.TargetArchs
\brief Class providing a set of static methods to check what NVIDIA\* card architecture the CUDA module was
built for.
|
| opencv_core.TermCriteria
\brief The class defining termination criteria for iterative algorithms.
|
| opencv_core.Texture2D |
| opencv_core.TickMeter
\brief a Class to measure passing time.
|
| opencv_core.TLSDataContainer |
| opencv_core.UMat
\todo document
|
| opencv_core.UMatBytePairVector |
| opencv_core.UMatData
\brief Comma-separated Matrix Initializer
|
| opencv_core.UMatVector |
| opencv_core.UMatVector.Iterator |
| opencv_cudaarithm.Convolution
\brief Base class for convolution (or cross-correlation) operator.
|
| opencv_cudaarithm.DFT
\brief Base class for DFT operator as a cv::Algorithm.
|
| opencv_cudaarithm.LookUpTable
\brief Base class for transform using lookup table.
|
| opencv_cudafilters.Filter
\addtogroup cudafilters
\{
|
| opencv_cudaimgproc.CannyEdgeDetector
\} cudaimgproc_hist
|
| opencv_cudaimgproc.CornernessCriteria
\} cudaimgproc_hough
|
| opencv_cudaimgproc.CornersDetector
\brief Base class for Corners Detector.
|
| opencv_cudaimgproc.CudaCLAHE
\brief Base class for Contrast Limited Adaptive Histogram Equalization.
|
| opencv_cudaimgproc.HoughCirclesDetector
\brief Base class for circles detector algorithm.
|
| opencv_cudaimgproc.HoughLinesDetector
\addtogroup cudaimgproc_hough
\{
|
| opencv_cudaimgproc.HoughSegmentDetector
\brief Base class for line segments detector algorithm.
|
| opencv_cudaimgproc.TemplateMatching
\brief Base class for Template Matching.
|
| opencv_cudaobjdetect.CudaCascadeClassifier
\brief Cascade classifier class used for object detection.
|
| opencv_cudaobjdetect.HOG
\brief The class implements Histogram of Oriented Gradients (\cite Dalal2005) object detector.
|
| opencv_cudaoptflow.BroxOpticalFlow
\brief Class computing the optical flow for two images using Brox et al Optical Flow algorithm (\cite Brox2004).
|
| opencv_cudaoptflow.DenseOpticalFlow
\brief Base interface for dense optical flow algorithms.
|
| opencv_cudaoptflow.DensePyrLKOpticalFlow
\brief Class used for calculating a dense optical flow.
|
| opencv_cudaoptflow.FarnebackOpticalFlow
\brief Class computing a dense optical flow using the Gunnar Farneback's algorithm.
|
| opencv_cudaoptflow.OpticalFlowDual_TVL1
\brief Implementation of the Zach, Pock and Bischof Dual TV-L1 Optical Flow method.
|
| opencv_cudaoptflow.SparseOpticalFlow
\brief Base interface for sparse optical flow algorithms.
|
| opencv_cudaoptflow.SparsePyrLKOpticalFlow
\brief Class used for calculating a sparse optical flow.
|
| opencv_dnn._Range
\}
\}
|
| opencv_dnn.AbsLayer |
| opencv_dnn.ActivationLayer |
| opencv_dnn.BackendNode
\brief Derivatives of this class encapsulates functions of certain backends.
|
| opencv_dnn.BackendWrapper
\brief Derivatives of this class wraps cv::Mat for different backends and targets.
|
| opencv_dnn.BaseConvolutionLayer |
| opencv_dnn.BatchNormLayer |
| opencv_dnn.BNLLLayer |
| opencv_dnn.ConcatLayer |
| opencv_dnn.CropLayer |
| opencv_dnn.DetectionOutputLayer |
| opencv_dnn.Dict
\brief This class implements name-value dictionary, values are instances of DictValue.
|
| opencv_dnn.DictValue
\example samples/dnn/text_detection.cpp
|
| opencv_dnn.EltwiseLayer |
| opencv_dnn.ELULayer |
| opencv_dnn.FlattenLayer |
| opencv_dnn.InnerProductLayer |
| opencv_dnn.Layer
\brief This interface class allows to build new Layers - are building blocks of networks.
|
| opencv_dnn.LayerFactory.Constructor
Each Layer class must provide this function to the factory
|
| opencv_dnn.LayerParams
\brief This class provides all data needed to initialize layer.
|
| opencv_dnn.LRNLayer |
| opencv_dnn.LSTMLayer
LSTM recurrent layer
|
| opencv_dnn.MatPointerVector |
| opencv_dnn.MatPointerVector.Iterator |
| opencv_dnn.MatShapeVector |
| opencv_dnn.MatShapeVector.Iterator |
| opencv_dnn.MatShapeVectorVector |
| opencv_dnn.MatShapeVectorVector.Iterator |
| opencv_dnn.MaxUnpoolLayer |
| opencv_dnn.MVNLayer |
| opencv_dnn.Net
\brief This class allows to create and manipulate comprehensive artificial neural networks.
|
| opencv_dnn.NormalizeBBoxLayer
\brief \f$ L_p \f$ - normalization layer.
|
| opencv_dnn.PaddingLayer
\brief Adds extra values for specific axes.
|
| opencv_dnn.PermuteLayer |
| opencv_dnn.PoolingLayer |
| opencv_dnn.PowerLayer |
| opencv_dnn.PriorBoxLayer |
| opencv_dnn.ProposalLayer |
| opencv_dnn.RangeVectorVector |
| opencv_dnn.RegionLayer |
| opencv_dnn.ReLU6Layer |
| opencv_dnn.ReLULayer |
| opencv_dnn.ReorgLayer |
| opencv_dnn.ReshapeLayer |
| opencv_dnn.ResizeLayer
\brief Resize input 4-dimensional blob by nearest neighbor or bilinear strategy.
|
| opencv_dnn.RNNLayer
\brief Classical recurrent layer
|
| opencv_dnn.ScaleLayer |
| opencv_dnn.ShuffleChannelLayer
Permute channels of 4-dimensional input blob.
|
| opencv_dnn.SigmoidLayer |
| opencv_dnn.SliceLayer
Slice layer has several modes:
1.
|
| opencv_dnn.SoftmaxLayer |
| opencv_dnn.SplitLayer |
| opencv_dnn.TanHLayer |
| opencv_face.BasicFaceRecognizer
\addtogroup face
\{
|
| opencv_face.CParams
\addtogroup face
\{
|
| opencv_face.EigenFaceRecognizer |
| opencv_face.Facemark
\brief Abstract base class for all facemark models
|
| opencv_face.FacemarkAAM
\addtogroup face
\{
|
| opencv_face.FacemarkAAM.Config
\brief Optional parameter for fitting process.
|
| opencv_face.FacemarkAAM.Data
\brief Data container for the facemark::getData function
|
| opencv_face.FacemarkAAM.Model
\brief The model of AAM Algorithm
|
| opencv_face.FacemarkAAM.Model.Texture |
| opencv_face.FacemarkAAM.Params |
| opencv_face.FacemarkKazemi
\}
|
| opencv_face.FacemarkKazemi.Params |
| opencv_face.FacemarkLBF
\addtogroup face
\{
|
| opencv_face.FacemarkLBF.BBox |
| opencv_face.FacemarkLBF.Params |
| opencv_face.FacemarkTrain
\brief Abstract base class for trainable facemark models
|
| opencv_face.FaceRecognizer
\addtogroup face
\{
|
| opencv_face.FisherFaceRecognizer |
| opencv_face.LBPHFaceRecognizer |
| opencv_face.PredictCollector
\addtogroup face
\{
/** \brief Abstract base class for all strategies of prediction result handling
|
| opencv_face.StandardCollector
\brief Default predict collector
|
| opencv_face.StandardCollector.PredictResult |
| opencv_features2d.Accumulator
\} features2d_main
|
| opencv_features2d.AgastFeatureDetector
\} features2d_main
|
| opencv_features2d.AKAZE
\brief Class implementing the AKAZE keypoint detector and descriptor extractor, described in \cite ANB13.
|
| opencv_features2d.BFMatcher
\brief Brute-force descriptor matcher.
|
| opencv_features2d.BOWTrainer
\addtogroup features2d_category
/** \{
|
| opencv_features2d.BRISK
\addtogroup features2d_main
\{
|
| opencv_features2d.DescriptorMatcher
\addtogroup features2d_match
/** \{
|
| opencv_features2d.DrawMatchesFlags
\addtogroup features2d_draw
/** \{
|
| opencv_features2d.FastFeatureDetector
\} features2d_main
|
| opencv_features2d.Feature2D
\brief Abstract base class for 2D image feature detectors and descriptor extractors
|
| opencv_features2d.FlannBasedMatcher
\brief Flann-based descriptor matcher.
|
| opencv_features2d.GFTTDetector
\brief Wrapping class for feature detection using the goodFeaturesToTrack function.
|
| opencv_features2d.KAZE
\} features2d_main
|
| opencv_features2d.KeyPointsFilter
\brief A class filters a vector of keypoints.
|
| opencv_features2d.MSER
\brief Maximally stable extremal region extractor
|
| opencv_features2d.ORB
\brief Class implementing the ORB (*oriented BRIEF*) keypoint detector and descriptor extractor
|
| opencv_features2d.SimpleBlobDetector
\brief Class for extracting blobs from an image.
|
| opencv_features2d.SimpleBlobDetector.Params |
| opencv_flann.AutotunedIndexParams |
| opencv_flann.CompositeIndexParams |
| opencv_flann.HierarchicalClusteringIndexParams |
| opencv_flann.Index |
| opencv_flann.IndexParams |
| opencv_flann.KDTreeIndexParams |
| opencv_flann.KMeansIndexParams |
| opencv_flann.LinearIndexParams |
| opencv_flann.SearchParams |
| opencv_highgui.ButtonCallback
\brief Callback function for a button created by cv::createButton
|
| opencv_highgui.CvButtonCallback |
| opencv_highgui.CvMouseCallback |
| opencv_highgui.CvOpenGlDrawCallback |
| opencv_highgui.CvTrackbarCallback |
| opencv_highgui.CvTrackbarCallback2 |
| opencv_highgui.MouseCallback
\brief Callback function for mouse events.
|
| opencv_highgui.OpenGlDrawCallback
\brief Callback function defined to be called every frame.
|
| opencv_highgui.Pt2Func_int_byte__ |
| opencv_highgui.Pt2Func_int_ByteBuffer |
| opencv_highgui.Pt2Func_int_BytePointer |
| opencv_highgui.Pt2Func_int_PointerPointer |
| opencv_highgui.QtFont
\} highgui_opengl
|
| opencv_highgui.TrackbarCallback
\brief Callback function for Trackbar see cv::createTrackbar
|
| opencv_img_hash.AverageHash
\addtogroup img_hash
\{
|
| opencv_img_hash.BlockMeanHash
\brief Image hash based on block mean.
|
| opencv_img_hash.ColorMomentHash
\addtogroup img_hash
\{
|
| opencv_img_hash.ImgHashBase
\addtogroup img_hash
\{
|
| opencv_img_hash.MarrHildrethHash
\addtogroup img_hash
\{
|
| opencv_img_hash.PHash
\addtogroup img_hash
\{
|
| opencv_img_hash.RadialVarianceHash
\addtogroup img_hash
\{
|
| opencv_imgproc.CLAHE
\brief Base class for Contrast Limited Adaptive Histogram Equalization.
|
| opencv_imgproc.CvChainPtReader
Freeman chain reader state
|
| opencv_imgproc.CvConnectedComp
Connected component structure
|
| opencv_imgproc.CvContourScanner |
| opencv_imgproc.CvConvexityDefect
Convexity defect
|
| opencv_imgproc.CvDistanceFunction |
| opencv_imgproc.CvFont
Font structure
|
| opencv_imgproc.CvHuMoments
Hu invariants
|
| opencv_imgproc.CvMoments
Spatial and central moments
|
| opencv_imgproc.GeneralizedHough
finds arbitrary template in the grayscale image using Generalized Hough Transform
|
| opencv_imgproc.GeneralizedHoughBallard
Ballard, D.H.
|
| opencv_imgproc.GeneralizedHoughGuil
Guil, N., González-Linares, J.M.
|
| opencv_imgproc.LineIterator
\brief Line iterator
|
| opencv_imgproc.LineSegmentDetector
\brief Line segment detector class
|
| opencv_imgproc.Subdiv2D
\addtogroup imgproc_subdiv2d
\{
|
| opencv_ml.ANN_MLP
\brief Artificial Neural Networks - Multi-Layer Perceptrons.
|
| opencv_ml.Boost
\brief Boosted tree classifier derived from DTrees
|
| opencv_ml.DTrees
\brief The class represents a single decision tree or a collection of decision trees.
|
| opencv_ml.DTrees.Node
\brief The class represents a decision tree node.
|
| opencv_ml.DTrees.Split
\brief The class represents split in a decision tree.
|
| opencv_ml.EM
\brief The class implements the Expectation Maximization algorithm.
|
| opencv_ml.KNearest
\brief The class implements K-Nearest Neighbors model
|
| opencv_ml.LogisticRegression
\brief Implements Logistic Regression classifier.
|
| opencv_ml.NormalBayesClassifier
\brief Bayes classifier for normally distributed data.
|
| opencv_ml.ParamGrid
\brief The structure represents the logarithmic grid range of statmodel parameters.
|
| opencv_ml.RTrees
\brief The class implements the random forest predictor.
|
| opencv_ml.StatModel
\brief Base class for statistical models in OpenCV ML.
|
| opencv_ml.SVM
\brief Support Vector Machines.
|
| opencv_ml.SVM.Kernel |
| opencv_ml.SVMSGD
\brief Stochastic Gradient Descent SVM classifier
|
| opencv_ml.TrainData
\brief Class encapsulating training data.
|
| opencv_objdetect.BaseCascadeClassifier |
| opencv_objdetect.BaseCascadeClassifier.MaskGenerator |
| opencv_objdetect.CascadeClassifier
\brief Cascade classifier class for object detection.
|
| opencv_objdetect.CvAvgComp |
| opencv_objdetect.CvHaarClassifier |
| opencv_objdetect.CvHaarClassifierCascade |
| opencv_objdetect.CvHaarFeature |
| opencv_objdetect.CvHaarStageClassifier |
| opencv_objdetect.CvHidHaarClassifierCascade |
| opencv_objdetect.DetectionBasedTracker.ExtObject |
| opencv_objdetect.DetectionBasedTracker.IDetector |
| opencv_objdetect.DetectionBasedTracker.Parameters |
| opencv_objdetect.DetectionROI
struct for detection region of interest (ROI)
|
| opencv_objdetect.HOGDescriptor
\brief Implementation of HOG (Histogram of Oriented Gradients) descriptor and object detector.
|
| opencv_objdetect.QRCodeDetector |
| opencv_objdetect.SimilarRects
\addtogroup objdetect
\{
|
| opencv_optflow.DISOpticalFlow
\brief DIS optical flow algorithm.
|
| opencv_optflow.VariationalRefinement
\brief Variational optical flow refinement
|
| opencv_phase_unwrapping.HistogramPhaseUnwrapping
\addtogroup phase_unwrapping
\{
|
| opencv_phase_unwrapping.HistogramPhaseUnwrapping.Params
\brief Parameters of phaseUnwrapping constructor.
|
| opencv_phase_unwrapping.PhaseUnwrapping
\addtogroup phase_unwrapping
\{
|
| opencv_photo.AlignExposures
\brief The base class for algorithms that align images of the same scene with different exposures
|
| opencv_photo.AlignMTB
\brief 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.
|
| opencv_photo.CalibrateCRF
\brief The base class for camera response calibration algorithms.
|
| opencv_photo.CalibrateDebevec
\brief Inverse camera response function is extracted for each brightness value by minimizing an objective
function as linear system.
|
| opencv_photo.CalibrateRobertson
\brief Inverse camera response function is extracted for each brightness value by minimizing an objective
function as linear system.
|
| opencv_photo.MergeDebevec
\brief The resulting HDR image is calculated as weighted average of the exposures considering exposure
values and camera response.
|
| opencv_photo.MergeExposures
\brief The base class algorithms that can merge exposure sequence to a single image.
|
| opencv_photo.MergeMertens
\brief Pixels are weighted using contrast, saturation and well-exposedness measures, than images are
combined using laplacian pyramids.
|
| opencv_photo.MergeRobertson
\brief The resulting HDR image is calculated as weighted average of the exposures considering exposure
values and camera response.
|
| opencv_photo.Tonemap
\brief Base class for tonemapping algorithms - tools that are used to map HDR image to 8-bit range.
|
| opencv_photo.TonemapDrago
\brief Adaptive logarithmic mapping is a fast global tonemapping algorithm that scales the image in
logarithmic domain.
|
| opencv_photo.TonemapDurand
\brief 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.
|
| opencv_photo.TonemapMantiuk
\brief This algorithm transforms image to contrast using gradients on all levels of gaussian pyramid,
transforms contrast values to HVS response and scales the response.
|
| opencv_photo.TonemapReinhard
\brief This is a global tonemapping operator that models human visual system.
|
| opencv_plot.Plot2d
\addtogroup plot
\{
|
| opencv_saliency.MotionSaliency
Motion Saliency Base Class
|
| opencv_saliency.MotionSaliencyBinWangApr2014
\brief the Fast Self-tuning Background Subtraction Algorithm from \cite BinWangApr2014
|
| opencv_saliency.Objectness
Objectness Base Class
|
| opencv_saliency.ObjectnessBING
\brief the Binarized normed gradients algorithm from \cite BING
|
| opencv_saliency.Saliency
\addtogroup saliency
\{
|
| opencv_saliency.StaticSaliency
Static Saliency Base Class
|
| opencv_saliency.StaticSaliencyFineGrained
\brief the Fine Grained Saliency approach from \cite FGS
|
| opencv_saliency.StaticSaliencySpectralResidual
\brief the Spectral Residual approach from \cite SR
|
| opencv_shape.AffineTransformer
\brief Wrapper class for the OpenCV Affine Transformation algorithm.
|
| opencv_shape.HausdorffDistanceExtractor
\brief A simple Hausdorff distance measure between shapes defined by contours
|
| opencv_shape.HistogramCostExtractor
\addtogroup shape
\{
|
| opencv_shape.ShapeContextDistanceExtractor
\brief Implementation of the Shape Context descriptor and matching algorithm
|
| opencv_shape.ShapeDistanceExtractor
\brief Abstract base class for shape distance algorithms.
|
| opencv_shape.ShapeTransformer
\addtogroup shape
\{
|
| opencv_shape.ThinPlateSplineShapeTransformer
\brief Definition of the transformation
|
| opencv_stitching.AffineBasedEstimator
\brief Affine transformation based estimator.
|
| opencv_stitching.AffineBestOf2NearestMatcher
\brief Features matcher similar to cv::detail::BestOf2NearestMatcher which
finds two best matches for each feature and leaves the best one only if the
ratio between descriptor distances is greater than the threshold match_conf.
|
| opencv_stitching.AffineWarper
\brief Affine warper that uses rotations and translations
|
| opencv_stitching.AKAZEFeaturesFinder
\brief AKAZE features finder.
|
| opencv_stitching.BestOf2NearestMatcher
\brief Features matcher which finds two best matches for each feature and leaves the best one only if the
ratio between descriptor distances is greater than the threshold match_conf
|
| opencv_stitching.BestOf2NearestRangeMatcher |
| opencv_stitching.Blender
\addtogroup stitching_blend
\{
|
| opencv_stitching.BlocksGainCompensator
\brief Exposure compensator which tries to remove exposure related artifacts by adjusting image block
intensities, see \cite UES01 for details.
|
| opencv_stitching.BundleAdjusterAffine
\brief Bundle adjuster that expects affine transformation
represented in homogeneous coordinates in R for each camera param.
|
| opencv_stitching.BundleAdjusterAffinePartial
\brief Bundle adjuster that expects affine transformation with 4 DOF
represented in homogeneous coordinates in R for each camera param.
|
| opencv_stitching.BundleAdjusterBase
\brief Base class for all camera parameters refinement methods.
|
| opencv_stitching.BundleAdjusterRay
\brief Implementation of the camera parameters refinement algorithm which minimizes sum of the distances
between the rays passing through the camera center and a feature.
|
| opencv_stitching.BundleAdjusterReproj
\brief Implementation of the camera parameters refinement algorithm which minimizes sum of the reprojection
error squares
|
| opencv_stitching.CameraParams
\addtogroup stitching
\{
|
| opencv_stitching.CompressedRectilinearPortraitProjector |
| opencv_stitching.CompressedRectilinearPortraitWarper |
| opencv_stitching.CompressedRectilinearProjector |
| opencv_stitching.CompressedRectilinearWarper |
| opencv_stitching.CylindricalPortraitProjector |
| opencv_stitching.CylindricalProjector |
| opencv_stitching.CylindricalWarper
\brief Cylindrical warper factory class.
|
| opencv_stitching.DetailPlaneWarper
\brief Warper that maps an image onto the z = 1 plane.
|
| opencv_stitching.DetailPlaneWarperGpu |
| opencv_stitching.DisjointSets
\addtogroup stitching
\{
|
| opencv_stitching.DpSeamFinder |
| opencv_stitching.Estimator
\addtogroup stitching_rotation
\{
|
| opencv_stitching.ExposureCompensator
\addtogroup stitching_exposure
\{
|
| opencv_stitching.FeatherBlender
\brief Simple blender which mixes images at its borders.
|
| opencv_stitching.FeaturesFinder
\brief Feature finders base class
|
| opencv_stitching.FeaturesMatcher
\brief Feature matchers base class.
|
| opencv_stitching.FisheyeProjector |
| opencv_stitching.FisheyeWarper |
| opencv_stitching.GainCompensator
\brief Exposure compensator which tries to remove exposure related artifacts by adjusting image
intensities, see \cite BL07 and \cite WJ10 for details.
|
| opencv_stitching.Graph |
| opencv_stitching.GraphCutSeamFinder
\brief Minimum graph cut-based seam estimator.
|
| opencv_stitching.GraphCutSeamFinderBase
\brief Base class for all minimum graph-cut-based seam estimators.
|
| opencv_stitching.GraphEdge |
| opencv_stitching.HomographyBasedEstimator
\brief Homography based rotation estimator.
|
| opencv_stitching.ImageFeatures
\addtogroup stitching_match
\{
|
| opencv_stitching.MatchesInfo
\brief Structure containing information about matches between two images.
|
| opencv_stitching.MercatorProjector |
| opencv_stitching.MercatorWarper |
| opencv_stitching.MultiBandBlender
\brief Blender which uses multi-band blending algorithm (see \cite BA83).
|
| opencv_stitching.NoBundleAdjuster
\brief Stub bundle adjuster that does nothing.
|
| opencv_stitching.NoExposureCompensator
\brief Stub exposure compensator which does nothing.
|
| opencv_stitching.NoSeamFinder
\brief Stub seam estimator which does nothing.
|
| opencv_stitching.OrbFeaturesFinder
\brief ORB features finder.
|
| opencv_stitching.PairwiseSeamFinder
\brief Base class for all pairwise seam estimators.
|
| opencv_stitching.PaniniPortraitProjector |
| opencv_stitching.PaniniPortraitWarper |
| opencv_stitching.PaniniProjector |
| opencv_stitching.PaniniWarper |
| opencv_stitching.PlanePortraitProjector |
| opencv_stitching.PlaneProjector
\brief Base class for rotation-based warper using a detail::ProjectorBase_ derived class.
|
| opencv_stitching.PlaneWarper
\brief Plane warper factory class.
|
| opencv_stitching.ProjectorBase
\brief Base class for warping logic implementation.
|
| opencv_stitching.RotationWarper
\addtogroup stitching_warp
\{
|
| opencv_stitching.SeamFinder
\addtogroup stitching_seam
\{
|
| opencv_stitching.SiftFeaturesFinder
\brief SIFT features finder.
|
| opencv_stitching.SphericalPortraitProjector |
| opencv_stitching.SphericalProjector |
| opencv_stitching.SphericalWarper
\brief Spherical warper factory class
|
| opencv_stitching.StereographicProjector |
| opencv_stitching.StereographicWarper |
| opencv_stitching.Stitcher
\brief High level image stitcher.
|
| opencv_stitching.SurfFeaturesFinder
\brief SURF features finder.
|
| opencv_stitching.Timelapser
\addtogroup stitching
\{
|
| opencv_stitching.TimelapserCrop |
| opencv_stitching.TransverseMercatorProjector |
| opencv_stitching.TransverseMercatorWarper |
| opencv_stitching.VoronoiSeamFinder
\brief Voronoi diagram-based seam estimator.
|
| opencv_stitching.WarperCreator
\addtogroup stitching_warp
\{
|
| opencv_structured_light.GrayCodePattern
\addtogroup structured_light
\{
|
| opencv_structured_light.GrayCodePattern.Params
\brief Parameters of StructuredLightPattern constructor.
|
| opencv_structured_light.SinusoidalPattern
\brief Class implementing Fourier transform profilometry (FTP) , phase-shifting profilometry (PSP)
and Fourier-assisted phase-shifting profilometry (FAPS) based on \cite faps.
|
| opencv_structured_light.SinusoidalPattern.Params
\brief Parameters of SinusoidalPattern constructor
|
| opencv_structured_light.StructuredLightPattern
\brief Abstract base class for generating and decoding structured light patterns.
|
| opencv_superres.BroxOpticalFlow |
| opencv_superres.DenseOpticalFlowExt
\addtogroup superres
\{
|
| opencv_superres.FrameSource
\addtogroup superres
\{
|
| opencv_superres.PyrLKOpticalFlow |
| opencv_superres.SuperResDualTVL1OpticalFlow |
| opencv_superres.SuperResFarnebackOpticalFlow |
| opencv_superres.SuperResolution
\brief Base class for Super Resolution algorithms.
|
| opencv_text.BaseOCR |
| opencv_text.DoubleVector |
| opencv_text.DoubleVector.Iterator |
| opencv_text.ERFilter
\brief Base class for 1st and 2nd stages of Neumann and Matas scene text detection algorithm \cite Neumann12.
|
| opencv_text.ERFilter.Callback
\brief Callback with the classifier is made a class.
|
| opencv_text.ERStat
\addtogroup text_detect
\{
|
| opencv_text.ERStatVector |
| opencv_text.ERStatVector.Iterator |
| opencv_text.ERStatVectorVector |
| opencv_text.ERStatVectorVector.Iterator |
| opencv_text.IntDeque |
| opencv_text.IntDeque.Iterator |
| opencv_text.OCRBeamSearchDecoder
\brief OCRBeamSearchDecoder class provides an interface for OCR using Beam Search algorithm.
|
| opencv_text.OCRBeamSearchDecoder.ClassifierCallback
\brief Callback with the character classifier is made a class.
|
| opencv_text.OCRHMMDecoder
\brief OCRHMMDecoder class provides an interface for OCR using Hidden Markov Models.
|
| opencv_text.OCRHMMDecoder.ClassifierCallback
\brief Callback with the character classifier is made a class.
|
| opencv_text.OCRHolisticWordRecognizer
\brief OCRHolisticWordRecognizer class provides the functionallity of segmented wordspotting.
|
| opencv_text.OCRTesseract
\brief OCRTesseract class provides an interface with the tesseract-ocr API (v3.02.02) in C++.
|
| opencv_text.StdStringVector |
| opencv_text.StdStringVector.Iterator |
| opencv_text.TextDetector
\addtogroup text_detect
\{
|
| opencv_text.TextDetectorCNN
\brief TextDetectorCNN class provides the functionallity of text bounding box detection.
|
| opencv_tracking.AugmentedUnscentedKalmanFilterParams
\brief Augmented Unscented Kalman filter parameters.
|
| opencv_tracking.ClfMilBoost
\addtogroup tracking
\{
|
| opencv_tracking.ClfMilBoost.Params |
| opencv_tracking.ClfOnlineStump |
| opencv_tracking.ConfidenceMap |
| opencv_tracking.ConfidenceMapVector |
| opencv_tracking.ConfidenceMapVector.Iterator |
| opencv_tracking.CvFeatureEvaluator |
| opencv_tracking.CvFeatureParams |
| opencv_tracking.CvHaarEvaluator |
| opencv_tracking.CvHaarEvaluator.FeatureHaar |
| opencv_tracking.CvHaarFeatureParams |
| opencv_tracking.CvHOGEvaluator |
| opencv_tracking.CvHOGFeatureParams |
| opencv_tracking.CvLBPEvaluator |
| opencv_tracking.CvLBPFeatureParams |
| opencv_tracking.CvParams |
| opencv_tracking.EstimatedGaussDistribution |
| opencv_tracking.MultiTracker
\brief This class is used to track multiple objects using the specified tracker algorithm.
|
| opencv_tracking.MultiTracker_Alt
\brief Base abstract class for the long-term Multi Object Trackers:
|
| opencv_tracking.MultiTrackerTLD
\brief Multi Object Tracker for TLD.
|
| opencv_tracking.StringTrackerFeaturePairVector |
| opencv_tracking.StringTrackerSamplerAlgorithmPairVector |
| opencv_tracking.StrongClassifierDirectSelection
\addtogroup tracking
\{
|
| opencv_tracking.Tracker
\brief Base abstract class for the long-term tracker:
|
| opencv_tracking.TrackerBoosting
\brief This is a real-time object tracking based on a novel on-line version of the AdaBoost algorithm.
|
| opencv_tracking.TrackerBoosting.Params |
| opencv_tracking.TrackerCSRT
\brief Discriminative Correlation Filter Tracker with Channel and Spatial Reliability
|
| opencv_tracking.TrackerCSRT.Params |
| opencv_tracking.TrackerFeature
\brief Abstract base class for TrackerFeature that represents the feature.
|
| opencv_tracking.TrackerFeatureHAAR
\brief TrackerFeature based on HAAR features, used by TrackerMIL and many others algorithms
\note HAAR features implementation is copied from apps/traincascade and modified according to MIL
|
| opencv_tracking.TrackerFeatureHAAR.Params |
| opencv_tracking.TrackerFeatureHOG
\brief TrackerFeature based on HOG
|
| opencv_tracking.TrackerFeatureLBP
\brief TrackerFeature based on LBP
|
| opencv_tracking.TrackerFeatureSet
\brief Class that manages the extraction and selection of features
|
| opencv_tracking.TrackerGOTURN
\brief GOTURN (\cite GOTURN) is kind of trackers based on Convolutional Neural Networks (CNN).
|
| opencv_tracking.TrackerGOTURN.Params |
| opencv_tracking.TrackerKCF
\brief KCF is a novel tracking framework that utilizes properties of circulant matrix to enhance the processing speed.
|
| opencv_tracking.TrackerKCF.Arg0_Mat_Rect_Mat |
| opencv_tracking.TrackerKCF.Params |
| opencv_tracking.TrackerMedianFlow
\brief Median Flow tracker implementation.
|
| opencv_tracking.TrackerMedianFlow.Params |
| opencv_tracking.TrackerMIL
\brief The MIL algorithm trains a classifier in an online manner to separate the object from the
background.
|
| opencv_tracking.TrackerMIL.Params |
| opencv_tracking.TrackerMOSSE
\brief the MOSSE tracker
note, that this tracker works with grayscale images, if passed bgr ones, they will get converted internally.
|
| opencv_tracking.TrackerSampler
\brief Class that manages the sampler in order to select regions for the update the model of the tracker
|
| opencv_tracking.TrackerSamplerAlgorithm
\brief Abstract base class for TrackerSamplerAlgorithm that represents the algorithm for the specific
sampler.
|
| opencv_tracking.TrackerSamplerCS
\brief TrackerSampler based on CS (current state), used by algorithm TrackerBoosting
|
| opencv_tracking.TrackerSamplerCS.Params |
| opencv_tracking.TrackerSamplerCSC
\brief TrackerSampler based on CSC (current state centered), used by MIL algorithm TrackerMIL
|
| opencv_tracking.TrackerSamplerCSC.Params |
| opencv_tracking.TrackerSamplerPF.Params
\brief This structure contains all the parameters that can be varied during the course of sampling
algorithm.
|
| opencv_tracking.TrackerStateEstimator
\brief Abstract base class for TrackerStateEstimator that estimates the most likely target state.
|
| opencv_tracking.TrackerStateEstimatorMILBoosting
\brief TrackerStateEstimator based on Boosting
|
| opencv_tracking.TrackerStateEstimatorSVM
\brief TrackerStateEstimator based on SVM
|
| opencv_tracking.TrackerTargetState
\brief Abstract base class for TrackerTargetState that represents a possible state of the target.
|
| opencv_tracking.TrackerTLD
\brief TLD is a novel tracking framework that explicitly decomposes the long-term tracking task into
tracking, learning and detection.
|
| opencv_tracking.TrackerTLD.Params |
| opencv_tracking.TrackerVector |
| opencv_tracking.TrackerVector.Iterator |
| opencv_tracking.Trajectory |
| opencv_tracking.Trajectory.Iterator |
| opencv_tracking.UkfSystemModel
\brief Model of dynamical system for Unscented Kalman filter.
|
| opencv_tracking.UnscentedKalmanFilter
\brief The interface for Unscented Kalman filter and Augmented Unscented Kalman filter.
|
| opencv_tracking.UnscentedKalmanFilterParams
\brief Unscented Kalman filter parameters.
|
| opencv_tracking.WeakClassifierHaarFeature |
| opencv_video.BackgroundSubtractor
\addtogroup video_motion
\{
|
| opencv_video.BackgroundSubtractorKNN
\brief K-nearest neighbours - based Background/Foreground Segmentation Algorithm.
|
| opencv_video.BackgroundSubtractorMOG2
\brief Gaussian Mixture-based Background/Foreground Segmentation Algorithm.
|
| opencv_video.CvKalman |
| opencv_video.DenseOpticalFlow |
| opencv_video.DualTVL1OpticalFlow
\brief "Dual TV L1" Optical Flow Algorithm.
|
| opencv_video.FarnebackOpticalFlow
\brief Class computing a dense optical flow using the Gunnar Farneback's algorithm.
|
| opencv_video.KalmanFilter
\brief Kalman filter class.
|
| opencv_video.SparseOpticalFlow
\brief Base interface for sparse optical flow algorithms.
|
| opencv_video.SparsePyrLKOpticalFlow
\brief Class used for calculating a sparse optical flow.
|
| opencv_videoio.CvCapture
\brief "black box" capture structure
|
| opencv_videoio.CvVideoWriter
\brief "black box" video file writer structure
|
| opencv_videoio.VideoCapture
\brief Class for video capturing from video files, image sequences or cameras.
|
| opencv_videoio.VideoWriter
\brief Video writer class.
|
| opencv_videostab.ColorAverageInpainter |
| opencv_videostab.ColorInpainter |
| opencv_videostab.ConsistentMosaicInpainter |
| opencv_videostab.DeblurerBase |
| opencv_videostab.FastMarchingMethod
\addtogroup videostab_marching
\{
|
| opencv_videostab.GaussianMotionFilter |
| opencv_videostab.IDenseOptFlowEstimator |
| opencv_videostab.IFrameSource
\addtogroup videostab
\{
|
| opencv_videostab.ILog
\addtogroup videostab
\{
|
| opencv_videostab.ImageMotionEstimatorBase
\brief Base class for global 2D motion estimation methods which take frames as input.
|
| opencv_videostab.IMotionStabilizer
\addtogroup videostab_motion
\{
|
| opencv_videostab.InpainterBase
\addtogroup videostab
\{
|
| opencv_videostab.InpaintingPipeline |
| opencv_videostab.IOutlierRejector
\addtogroup videostab
\{
|
| opencv_videostab.ISparseOptFlowEstimator
\addtogroup videostab
\{
|
| opencv_videostab.LogToStdout |
| opencv_videostab.LpMotionStabilizer |
| opencv_videostab.MoreAccurateMotionWobbleSuppressor |
| opencv_videostab.MoreAccurateMotionWobbleSuppressorBase |
| opencv_videostab.MotionEstimatorBase
\brief Base class for all global motion estimation methods.
|
| opencv_videostab.MotionEstimatorL1
\brief Describes a global 2D motion estimation method which minimizes L1 error.
|
| opencv_videostab.MotionEstimatorRansacL2
\brief Describes a robust RANSAC-based global 2D motion estimation method which minimizes L2 error.
|
| opencv_videostab.MotionFilterBase |
| opencv_videostab.MotionInpainter |
| opencv_videostab.MotionStabilizationPipeline |
| opencv_videostab.NullDeblurer |
| opencv_videostab.NullFrameSource |
| opencv_videostab.NullInpainter |
| opencv_videostab.NullLog |
| opencv_videostab.NullOutlierRejector |
| opencv_videostab.NullWobbleSuppressor |
| opencv_videostab.OnePassStabilizer |
| opencv_videostab.PyrLkOptFlowEstimatorBase |
| opencv_videostab.RansacParams
\brief Describes RANSAC method parameters.
|
| opencv_videostab.SparsePyrLkOptFlowEstimator |
| opencv_videostab.StabilizerBase
\addtogroup videostab
\{
|
| opencv_videostab.TranslationBasedLocalOutlierRejector |
| opencv_videostab.TwoPassStabilizer |
| opencv_videostab.WeightingDeblurer |
| opencv_videostab.WobbleSuppressorBase
\addtogroup videostab
\{
|
| opencv_xfeatures2d.AffineFeature2D
\brief Class implementing affine adaptation for key points.
|
| opencv_xfeatures2d.BoostDesc
\brief Class implementing BoostDesc (Learning Image Descriptors with Boosting), described in
\cite Trzcinski13a and \cite Trzcinski13b.
|
| opencv_xfeatures2d.BriefDescriptorExtractor
\brief Class for computing BRIEF descriptors described in \cite calon2010 .
|
| opencv_xfeatures2d.DAISY
\brief Class implementing DAISY descriptor, described in \cite Tola10
|
| opencv_xfeatures2d.Elliptic_KeyPoint
\brief Elliptic region around an interest point.
|
| opencv_xfeatures2d.FREAK
\addtogroup xfeatures2d_experiment
\{
|
| opencv_xfeatures2d.HarrisLaplaceFeatureDetector
\brief Class implementing the Harris-Laplace feature detector as described in \cite Mikolajczyk2004.
|
| opencv_xfeatures2d.LATCH
latch Class for computing the LATCH descriptor.
|
| opencv_xfeatures2d.LUCID
\brief Class implementing the locally uniform comparison image descriptor, described in \cite LUCID
|
| opencv_xfeatures2d.MSDDetector
\brief Class implementing the MSD (*Maximal Self-Dissimilarity*) keypoint detector, described in \cite Tombari14.
|
| opencv_xfeatures2d.PCTSignatures
\brief Class implementing PCT (position-color-texture) signature extraction
as described in \cite KrulisLS16.
|
| opencv_xfeatures2d.PCTSignaturesSQFD
\brief Class implementing Signature Quadratic Form Distance (SQFD).
|
| opencv_xfeatures2d.SIFT
\addtogroup xfeatures2d_nonfree
\{
|
| opencv_xfeatures2d.StarDetector
\brief The class implements the keypoint detector introduced by \cite Agrawal08, synonym of StarDetector.
|
| opencv_xfeatures2d.SURF
\brief Class for extracting Speeded Up Robust Features from an image \cite Bay06 .
|
| opencv_xfeatures2d.VGG
\brief Class implementing VGG (Oxford Visual Geometry Group) descriptor trained end to end
using "Descriptor Learning Using Convex Optimisation" (DLCO) aparatus described in \cite Simonyan14.
|
| opencv_ximgproc.AdaptiveManifoldFilter
\brief Interface for Adaptive Manifold Filter realizations.
|
| opencv_ximgproc.DisparityFilter
\addtogroup ximgproc_filters
\{
|
| opencv_ximgproc.DisparityWLSFilter
\brief 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.
|
| opencv_ximgproc.DTFilter
\brief Interface for realizations of Domain Transform filter.
|
| opencv_ximgproc.EdgeAwareInterpolator
\brief Sparse match interpolation algorithm based on modified locally-weighted affine
estimator from \cite Revaud2015 and Fast Global Smoother as post-processing filter.
|
| opencv_ximgproc.FastGlobalSmootherFilter
\brief Interface for implementations of Fast Global Smoother filter.
|
| opencv_ximgproc.GraphSegmentation
\addtogroup ximgproc_segmentation
\{
|
| opencv_ximgproc.GuidedFilter
\brief Interface for realizations of Guided Filter.
|
| opencv_ximgproc.RFFeatureGetter
\addtogroup ximgproc_edge
\{
|
| opencv_ximgproc.SelectiveSearchSegmentation
\brief Selective search segmentation algorithm
The class implements the algorithm described in \cite uijlings2013selective.
|
| opencv_ximgproc.SelectiveSearchSegmentationStrategy
\brief Strategie for the selective search segmentation algorithm
The class implements a generic stragery for the algorithm described in \cite uijlings2013selective.
|
| opencv_ximgproc.SelectiveSearchSegmentationStrategyColor
\brief Color-based strategy for the selective search segmentation algorithm
The class is implemented from the algorithm described in \cite uijlings2013selective.
|
| opencv_ximgproc.SelectiveSearchSegmentationStrategyFill
\brief Fill-based strategy for the selective search segmentation algorithm
The class is implemented from the algorithm described in \cite uijlings2013selective.
|
| opencv_ximgproc.SelectiveSearchSegmentationStrategyMultiple
\brief Regroup multiple strategies for the selective search segmentation algorithm
|
| opencv_ximgproc.SelectiveSearchSegmentationStrategySize
\brief Size-based strategy for the selective search segmentation algorithm
The class is implemented from the algorithm described in \cite uijlings2013selective.
|
| opencv_ximgproc.SelectiveSearchSegmentationStrategyTexture
\brief Texture-based strategy for the selective search segmentation algorithm
The class is implemented from the algorithm described in \cite uijlings2013selective.
|
| opencv_ximgproc.SparseMatchInterpolator
\addtogroup ximgproc_filters
\{
|
| opencv_ximgproc.StructuredEdgeDetection
\brief Class implementing edge detection algorithm from \cite Dollar2013 :
|
| opencv_ximgproc.SuperpixelLSC
\addtogroup ximgproc_superpixel
\{
|
| opencv_ximgproc.SuperpixelSEEDS
\addtogroup ximgproc_superpixel
\{
|
| opencv_ximgproc.SuperpixelSLIC
\brief Class implementing the SLIC (Simple Linear Iterative Clustering) superpixels
algorithm described in \cite Achanta2012.
|
| opencv_xphoto.GrayworldWB
\brief Gray-world white balance algorithm
|
| opencv_xphoto.LearningBasedWB
\brief More sophisticated learning-based automatic white balance algorithm.
|
| opencv_xphoto.SimpleWB
\brief A simple white balance algorithm that works by independently stretching
each of the input image channels to the specified range.
|
| opencv_xphoto.WhiteBalancer
\addtogroup xphoto
\{
|
| Class and Description |
|---|
| opencv_calib3d.CvPOSITObject
\
Camera Calibration, Pose Estimation and Stereo *
\
|
| opencv_calib3d.CvStereoBMState |
| opencv_core.Algorithm
\brief This is a base class for all more or less complex algorithms in OpenCV
|
| opencv_core.CvBox2D
\sa RotatedRect
|
| opencv_core.CvFileStorage
"black box" file storage
|
| opencv_core.CvGraph
Graph is "derived" from the set (this is set a of vertices)
and includes another set (edges)
|
| opencv_core.CvGraphScanner |
| opencv_core.CvGraphVtx |
| opencv_core.CvHistogram |
| opencv_core.CvMat
Deprecated.
CvMat is now obsolete; consider using Mat instead.
|
| opencv_core.CvMatND
Deprecated.
consider using cv::Mat instead
|
| opencv_core.CvMemStorage |
| opencv_core.CvPoint
CvPoint and variants
|
| opencv_core.CvPoint2D32f |
| opencv_core.CvPoint2D64f |
| opencv_core.CvPoint3D32f |
| opencv_core.CvPoint3D64f |
| opencv_core.CvScalar
\sa Scalar_
|
| opencv_core.CvSeq
Pointer to the first sequence block.
|
| opencv_core.CvSet |
| opencv_core.CvSize
CvSize's & CvBox
|
| opencv_core.CvSize2D32f |
| opencv_core.CvSparseMat |
| opencv_core.IplConvKernel |
| opencv_core.IplImage
The IplImage is taken from the Intel Image Processing Library, in which the format is native.
|
| opencv_core.IplROI |
| opencv_core.Mat
\brief n-dimensional dense array class \anchor CVMat_Details
|
| opencv_core.Scalar
\brief Template class for a 4-element vector derived from Vec.
|
| opencv_imgproc.CvMoments
Spatial and central moments
|
| opencv_ml.ANN_MLP
\brief Artificial Neural Networks - Multi-Layer Perceptrons.
|
| opencv_ml.Boost
\brief Boosted tree classifier derived from DTrees
|
| opencv_ml.DTrees
\brief The class represents a single decision tree or a collection of decision trees.
|
| opencv_ml.EM
\brief The class implements the Expectation Maximization algorithm.
|
| opencv_ml.KNearest
\brief The class implements K-Nearest Neighbors model
|
| opencv_ml.LogisticRegression
\brief Implements Logistic Regression classifier.
|
| opencv_ml.NormalBayesClassifier
\brief Bayes classifier for normally distributed data.
|
| opencv_ml.RTrees
\brief The class implements the random forest predictor.
|
| opencv_ml.SVM
\brief Support Vector Machines.
|
| opencv_objdetect.CvHaarClassifierCascade |
| opencv_video.CvKalman |
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