| Class | Description |
|---|---|
| cvkernels | |
| cvkernels.KernelData | |
| opencv_aruco | |
| 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 | |
| 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 | |
| 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 | |
| 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 | |
| opencv_core.Algorithm |
\brief This is a base class for all more or less complex algorithms in OpenCV
|
| opencv_core.Arrays | |
| opencv_core.AutoLock | |
| opencv_core.Buffer |
\cond IGNORED
|
| opencv_core.BufferPool |
\brief BufferPool for use with CUDA streams
|
| 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.Event.Impl | |
| 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.Kernel.Impl | |
| 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.Mutex.Impl | |
| 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.PtrOwner | |
| 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.RefOrVoid.type | |
| 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.Impl |
returns true if stream object is not default (!= 0)
|
| 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.Timer | |
| 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_core.WriteStructContext |
\cond IGNORED
|
| opencv_cudaarithm | |
| 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 | |
| opencv_cudafilters.Filter |
\addtogroup cudafilters
\{
|
| opencv_cudaimgproc | |
| 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 | |
| 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 | |
| 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_cudawarping | |
| opencv_dnn | |
| 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.BlankLayer |
\}
|
| opencv_dnn.BNLLLayer | |
| opencv_dnn.ChannelsPReLULayer | |
| opencv_dnn.ConcatLayer | |
| opencv_dnn.ConvolutionLayer | |
| opencv_dnn.CropAndResizeLayer | |
| opencv_dnn.CropLayer | |
| opencv_dnn.DeconvolutionLayer | |
| 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.InterpLayer |
\brief Bilinear resize layer from https://github.com/cdmh/deeplab-public
It differs from \ref ResizeLayer in output shape and resize scales computations.
|
| opencv_dnn.Layer |
\brief This interface class allows to build new Layers - are building blocks of networks.
|
| opencv_dnn.LayerFactory |
\addtogroup dnn
\{
\defgroup dnnLayerFactory Utilities for New Layers Registration
\{
|
| 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.ShiftLayer | |
| 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 | |
| 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 | |
| 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.BOWImgDescriptorExtractor |
\brief Class to compute an image descriptor using the *bag of visual words*.
|
| opencv_features2d.BOWKMeansTrainer |
\brief kmeans -based class to train visual vocabulary using the *bag of visual words* approach.
|
| 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 | |
| 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.LshIndexParams | |
| opencv_flann.SavedIndexParams | |
| opencv_flann.SearchParams | |
| opencv_highgui | |
| 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 | |
| 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.ImgHashBase.ImgHashImpl | |
| opencv_img_hash.MarrHildrethHash |
\addtogroup img_hash
\{
|
| opencv_img_hash.PHash |
\addtogroup img_hash
\{
|
| opencv_img_hash.RadialVarianceHash |
\addtogroup img_hash
\{
|
| opencv_imgcodecs | |
| opencv_imgproc | |
| 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.CvFeatureTree | |
| opencv_imgproc.CvFont |
Font structure
|
| opencv_imgproc.CvHuMoments |
Hu invariants
|
| opencv_imgproc.CvLSH | |
| opencv_imgproc.CvLSHOperations | |
| 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_java |
This is only a placeholder to facilitate loading the
opencv_java module with JavaCPP. |
| opencv_ml | |
| opencv_ml.ANN_MLP |
\brief Artificial Neural Networks - Multi-Layer Perceptrons.
|
| opencv_ml.ANN_MLP_ANNEAL |
\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 | |
| 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 |
\addtogroup objdetect
\{
|
| 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 | |
| opencv_optflow.DISOpticalFlow |
\brief DIS optical flow algorithm.
|
| opencv_optflow.VariationalRefinement |
\brief Variational optical flow refinement
|
| opencv_phase_unwrapping | |
| 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 | |
| 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 | |
| opencv_plot.Plot2d |
\addtogroup plot
\{
|
| opencv_saliency | |
| 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 | |
| opencv_shape.AffineTransformer |
\brief Wrapper class for the OpenCV Affine Transformation algorithm.
|
| opencv_shape.ChiHistogramCostExtractor |
\brief An Chi based cost extraction.
|
| opencv_shape.EMDHistogramCostExtractor |
\brief An EMD based cost extraction.
|
| opencv_shape.EMDL1HistogramCostExtractor |
\brief An EMD-L1 based cost extraction.
|
| opencv_shape.HausdorffDistanceExtractor |
\brief A simple Hausdorff distance measure between shapes defined by contours
|
| opencv_shape.HistogramCostExtractor |
\addtogroup shape
\{
|
| opencv_shape.NormHistogramCostExtractor |
\brief A norm based cost extraction.
|
| 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 | |
| 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.CylindricalPortraitWarper | |
| opencv_stitching.CylindricalProjector | |
| opencv_stitching.CylindricalWarper |
\brief Cylindrical warper factory class.
|
| opencv_stitching.DetailCompressedRectilinearPortraitWarper | |
| opencv_stitching.DetailCompressedRectilinearWarper | |
| opencv_stitching.DetailCylindricalWarper |
\brief Warper that maps an image onto the x\*x + z\*z = 1 cylinder.
|
| opencv_stitching.DetailCylindricalWarperGpu | |
| opencv_stitching.DetailFisheyeWarper | |
| opencv_stitching.DetailMercatorWarper | |
| opencv_stitching.DetailPaniniPortraitWarper | |
| opencv_stitching.DetailPaniniWarper | |
| opencv_stitching.DetailPlaneWarper |
\brief Warper that maps an image onto the z = 1 plane.
|
| opencv_stitching.DetailPlaneWarperGpu | |
| opencv_stitching.DetailSphericalWarper |
\brief Warper that maps an image onto the unit sphere located at the origin.
|
| opencv_stitching.DetailSphericalWarperGpu | |
| opencv_stitching.DetailStereographicWarper | |
| opencv_stitching.DetailTransverseMercatorWarper | |
| 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.PlanePortraitWarper | |
| 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.SphericalPortraitWarper | |
| 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 | |
| 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 | |
| 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 | |
| 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 | |
| opencv_tracking.AugmentedUnscentedKalmanFilterParams |
\brief Augmented Unscented Kalman filter parameters.
|
| opencv_tracking.BaseClassifier | |
| opencv_tracking.ClassifierThreshold | |
| 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.Detector | |
| 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.TrackerFeatureFeature2d |
\brief TrackerFeature based on Feature2D
|
| 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.TrackerModel |
\brief Abstract class that represents the model of the target.
|
| 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 |
\brief This sampler is based on particle filtering.
|
| 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.TrackerStateEstimatorAdaBoosting |
\brief TrackerStateEstimatorAdaBoosting based on ADA-Boosting
|
| opencv_tracking.TrackerStateEstimatorAdaBoosting.TrackerAdaBoostingTargetState |
\brief Implementation of the target state for TrackerAdaBoostingTargetState
|
| opencv_tracking.TrackerStateEstimatorMILBoosting |
\brief TrackerStateEstimator based on Boosting
|
| opencv_tracking.TrackerStateEstimatorMILBoosting.TrackerMILTargetState |
Implementation of the target state for TrackerStateEstimatorMILBoosting
|
| 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 | |
| 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 | |
| opencv_videoio.CvCapture |
\brief "black box" capture structure
|
| opencv_videoio.CvVideoWriter |
\brief "black box" video file writer structure
|
| opencv_videoio.IVideoCapture |
\} Images
|
| opencv_videoio.IVideoWriter | |
| opencv_videoio.VideoCapture |
\brief Class for video capturing from video files, image sequences or cameras.
|
| opencv_videoio.VideoWriter |
\brief Video writer class.
|
| opencv_videostab | |
| opencv_videostab.ColorAverageInpainter | |
| opencv_videostab.ColorInpainter | |
| opencv_videostab.ConsistentMosaicInpainter | |
| opencv_videostab.DeblurerBase | |
| opencv_videostab.FastMarchingMethod |
\addtogroup videostab_marching
\{
|
| opencv_videostab.FromFileMotionReader | |
| 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.KeypointBasedMotionEstimator |
\brief Describes a global 2D motion estimation method which uses keypoints detection and optical flow for
matching.
|
| 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.ToFileMotionWriter | |
| opencv_videostab.TranslationBasedLocalOutlierRejector | |
| opencv_videostab.TwoPassStabilizer | |
| opencv_videostab.VideoFileSource | |
| opencv_videostab.WeightingDeblurer | |
| opencv_videostab.WobbleSuppressorBase |
\addtogroup videostab
\{
|
| opencv_xfeatures2d | |
| 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 | |
| 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 | |
| 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
\{
|
Copyright © 2018. All rights reserved.