Modifier and Type | Class and Description |
---|---|
class |
BackgroundSubtractorCNT
\brief Background subtraction based on counting.
|
class |
BackgroundSubtractorGMG
\brief Background Subtractor module based on the algorithm given in \cite Gold2012 .
|
class |
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.
|
class |
BackgroundSubtractorLSBP
\brief Background Subtraction using Local SVD Binary Pattern.
|
class |
SyntheticSequenceGenerator
\brief Synthetic frame sequence generator for testing background subtraction algorithms.
|
Modifier and Type | Class and Description |
---|---|
class |
Retina
\brief class which allows the Gipsa/Listic Labs model to be used with OpenCV.
|
class |
RetinaFastToneMapping
\addtogroup bioinspired
\{
|
class |
TransientAreasSegmentationModule
\brief class which provides a transient/moving areas segmentation module
|
Modifier and Type | Class and Description |
---|---|
class |
LMSolver
Levenberg-Marquardt solver.
|
class |
StereoBM
\brief Class for computing stereo correspondence using the block matching algorithm, introduced and
contributed to OpenCV by K.
|
class |
StereoMatcher
\brief The base class for stereo correspondence algorithms.
|
class |
StereoSGBM
\brief The class implements the modified H.
|
Modifier and Type | Class and Description |
---|---|
class |
ConjGradSolver
\brief This class is used to perform the non-linear non-constrained minimization of a function
with known gradient,
|
class |
DownhillSolver
\brief This class is used to perform the non-linear non-constrained minimization of a function,
|
class |
MinProblemSolver
\brief Basic interface for all solvers
|
Modifier and Type | Method and Description |
---|---|
Algorithm |
Algorithm.position(long position) |
Modifier and Type | Class and Description |
---|---|
class |
Convolution
\brief Base class for convolution (or cross-correlation) operator.
|
class |
DFT
\brief Base class for DFT operator as a cv::Algorithm.
|
class |
LookUpTable
\brief Base class for transform using lookup table.
|
Modifier and Type | Class and Description |
---|---|
class |
BackgroundSubtractorMOG
\brief Gaussian Mixture-based Background/Foreground Segmentation Algorithm.
|
Modifier and Type | Class and Description |
---|---|
class |
DescriptorMatcher
\brief Abstract base class for matching keypoint descriptors.
|
class |
Feature2DAsync
\brief Abstract base class for CUDA asynchronous 2D image feature detectors and descriptor extractors.
|
Modifier and Type | Class and Description |
---|---|
class |
Filter
\addtogroup cudafilters
\{
|
Modifier and Type | Class and Description |
---|---|
class |
CannyEdgeDetector
\} cudaimgproc_hist
|
class |
CornernessCriteria
\} cudaimgproc_hough
|
class |
CornersDetector
\brief Base class for Corners Detector.
|
class |
CudaCLAHE
\brief Base class for Contrast Limited Adaptive Histogram Equalization.
|
class |
HoughCirclesDetector
\brief Base class for circles detector algorithm.
|
class |
HoughLinesDetector
\addtogroup cudaimgproc_hough
\{
|
class |
HoughSegmentDetector
\brief Base class for line segments detector algorithm.
|
class |
TemplateMatching
\brief Base class for Template Matching.
|
Modifier and Type | Class and Description |
---|---|
class |
CudaCascadeClassifier
\brief Cascade classifier class used for object detection.
|
class |
HOG
\brief The class implements Histogram of Oriented Gradients (\cite Dalal2005) object detector.
|
Modifier and Type | Class and Description |
---|---|
class |
BroxOpticalFlow
\brief Class computing the optical flow for two images using Brox et al Optical Flow algorithm (\cite Brox2004).
|
class |
DenseOpticalFlow
\brief Base interface for dense optical flow algorithms.
|
class |
DensePyrLKOpticalFlow
\brief Class used for calculating a dense optical flow.
|
class |
FarnebackOpticalFlow
\brief Class computing a dense optical flow using the Gunnar Farneback's algorithm.
|
class |
NvidiaHWOpticalFlow
\brief Base Interface for optical flow algorithms using NVIDIA Optical Flow SDK.
|
class |
NvidiaOpticalFlow_1_0
\brief Class for computing the optical flow vectors between two images using NVIDIA Optical Flow hardware and Optical Flow SDK 1.0.
|
class |
OpticalFlowDual_TVL1
\brief Implementation of the Zach, Pock and Bischof Dual TV-L1 Optical Flow method.
|
class |
SparseOpticalFlow
\brief Base interface for sparse optical flow algorithms.
|
class |
SparsePyrLKOpticalFlow
\brief Class used for calculating a sparse optical flow.
|
Modifier and Type | Class and Description |
---|---|
class |
DisparityBilateralFilter
\brief Class refining a disparity map using joint bilateral filtering.
|
class |
StereoBeliefPropagation
\brief Class computing stereo correspondence using the belief propagation algorithm.
|
class |
StereoConstantSpaceBP
\brief Class computing stereo correspondence using the constant space belief propagation algorithm.
|
Modifier and Type | Class and Description |
---|---|
class |
AbsLayer |
class |
ActivationLayer |
class |
BaseConvolutionLayer |
class |
BatchNormLayer |
class |
BlankLayer
\addtogroup dnn
\{
|
class |
BNLLLayer |
class |
ChannelsPReLULayer |
class |
ConcatLayer |
class |
ConstLayer
Constant layer produces the same data blob at an every forward pass.
|
class |
ConvolutionLayer |
class |
CropAndResizeLayer |
class |
CropLayer |
class |
DeconvolutionLayer |
class |
DetectionOutputLayer |
class |
EltwiseLayer
\brief Element wise operation on inputs
|
class |
ELULayer |
class |
FlattenLayer |
class |
InnerProductLayer |
class |
InterpLayer
\brief Bilinear resize layer from https://github.com/cdmh/deeplab-public-ver2
It differs from \ref ResizeLayer in output shape and resize scales computations.
|
class |
Layer
\brief This interface class allows to build new Layers - are building blocks of networks.
|
class |
LRNLayer |
class |
LSTMLayer
LSTM recurrent layer
|
class |
MaxUnpoolLayer |
class |
MishLayer |
class |
MVNLayer |
class |
NormalizeBBoxLayer
\brief
L_p - normalization layer. |
class |
PaddingLayer
\brief Adds extra values for specific axes.
|
class |
PermuteLayer |
class |
PoolingLayer |
class |
PowerLayer |
class |
PriorBoxLayer |
class |
ProposalLayer |
class |
RegionLayer |
class |
ReLU6Layer |
class |
ReLULayer |
class |
ReorgLayer |
class |
ReshapeLayer |
class |
ResizeLayer
\brief Resize input 4-dimensional blob by nearest neighbor or bilinear strategy.
|
class |
RNNLayer
\brief Classical recurrent layer
|
class |
ScaleLayer |
class |
ShiftLayer |
class |
ShuffleChannelLayer
Permute channels of 4-dimensional input blob.
|
class |
SigmoidLayer |
class |
SliceLayer
Slice layer has several modes:
1.
|
class |
SoftmaxLayer |
class |
SplitLayer |
class |
SwishLayer |
class |
TanHLayer |
Modifier and Type | Class and Description |
---|---|
class |
BasicFaceRecognizer
\addtogroup face
\{
|
class |
EigenFaceRecognizer |
class |
Facemark
\brief Abstract base class for all facemark models
|
class |
FacemarkAAM
\addtogroup face
\{
|
class |
FacemarkKazemi |
class |
FacemarkLBF
\addtogroup face
\{
|
class |
FacemarkTrain
\brief Abstract base class for trainable facemark models
|
class |
FaceRecognizer
\addtogroup face
\{
|
class |
FisherFaceRecognizer |
class |
LBPHFaceRecognizer |
Modifier and Type | Class and Description |
---|---|
class |
AgastFeatureDetector
\} features2d_main
|
class |
AKAZE
\brief Class implementing the AKAZE keypoint detector and descriptor extractor, described in \cite ANB13.
|
class |
BFMatcher
\brief Brute-force descriptor matcher.
|
class |
BRISK
\addtogroup features2d_main
\{
|
class |
FastFeatureDetector
\} features2d_main
|
class |
Feature2D
\brief Abstract base class for 2D image feature detectors and descriptor extractors
|
class |
FlannBasedMatcher
\brief Flann-based descriptor matcher.
|
class |
GFTTDetector
\brief Wrapping class for feature detection using the goodFeaturesToTrack function.
|
class |
KAZE
\} features2d_main
|
class |
MSER
\brief Maximally stable extremal region extractor
|
class |
ORB
\brief Class implementing the ORB (*oriented BRIEF*) keypoint detector and descriptor extractor
|
class |
SimpleBlobDetector
\brief Class for extracting blobs from an image.
|
Modifier and Type | Class and Description |
---|---|
class |
AverageHash
\addtogroup img_hash
\{
|
class |
BlockMeanHash
\brief Image hash based on block mean.
|
class |
ColorMomentHash
\addtogroup img_hash
\{
|
class |
ImgHashBase
\addtogroup img_hash
\{
|
class |
MarrHildrethHash
\addtogroup img_hash
\{
|
class |
PHash
\addtogroup img_hash
\{
|
class |
RadialVarianceHash
\addtogroup img_hash
\{
|
Modifier and Type | Class and Description |
---|---|
class |
CLAHE
\} imgproc_shape
|
class |
GeneralizedHough
\brief finds arbitrary template in the grayscale image using Generalized Hough Transform
|
class |
GeneralizedHoughBallard
\brief finds arbitrary template in the grayscale image using Generalized Hough Transform
|
class |
GeneralizedHoughGuil
\brief finds arbitrary template in the grayscale image using Generalized Hough Transform
|
class |
LineSegmentDetector
\} imgproc_subdiv2d
|
Modifier and Type | Class and Description |
---|---|
class |
AbstractStatModel |
class |
ANN_MLP
\brief Artificial Neural Networks - Multi-Layer Perceptrons.
|
class |
Boost
\brief Boosted tree classifier derived from DTrees
|
class |
DTrees
\brief The class represents a single decision tree or a collection of decision trees.
|
class |
EM
\brief The class implements the Expectation Maximization algorithm.
|
class |
KNearest
\brief The class implements K-Nearest Neighbors model
|
class |
LogisticRegression
\brief Implements Logistic Regression classifier.
|
class |
NormalBayesClassifier
\brief Bayes classifier for normally distributed data.
|
class |
RTrees
\brief The class implements the random forest predictor.
|
class |
StatModel
\brief Base class for statistical models in OpenCV ML.
|
class |
SVM
\brief Support Vector Machines.
|
static class |
SVM.Kernel |
class |
SVMSGD
\brief Stochastic Gradient Descent SVM classifier
|
Modifier and Type | Class and Description |
---|---|
class |
BaseCascadeClassifier |
Modifier and Type | Class and Description |
---|---|
class |
DualTVL1OpticalFlow
\brief "Dual TV L1" Optical Flow Algorithm.
|
Modifier and Type | Class and Description |
---|---|
class |
HistogramPhaseUnwrapping
\addtogroup phase_unwrapping
\{
|
class |
PhaseUnwrapping
\addtogroup phase_unwrapping
\{
|
Modifier and Type | Class and Description |
---|---|
class |
AlignExposures
\brief The base class for algorithms that align images of the same scene with different exposures
|
class |
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.
|
class |
CalibrateCRF
\brief The base class for camera response calibration algorithms.
|
class |
CalibrateDebevec
\brief Inverse camera response function is extracted for each brightness value by minimizing an objective
function as linear system.
|
class |
CalibrateRobertson
\brief Inverse camera response function is extracted for each brightness value by minimizing an objective
function as linear system.
|
class |
MergeDebevec
\brief The resulting HDR image is calculated as weighted average of the exposures considering exposure
values and camera response.
|
class |
MergeExposures
\brief The base class algorithms that can merge exposure sequence to a single image.
|
class |
MergeMertens
\brief Pixels are weighted using contrast, saturation and well-exposedness measures, than images are
combined using laplacian pyramids.
|
class |
MergeRobertson
\brief The resulting HDR image is calculated as weighted average of the exposures considering exposure
values and camera response.
|
class |
Tonemap
\brief Base class for tonemapping algorithms - tools that are used to map HDR image to 8-bit range.
|
class |
TonemapDrago
\brief Adaptive logarithmic mapping is a fast global tonemapping algorithm that scales the image in
logarithmic domain.
|
class |
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.
|
class |
TonemapReinhard
\brief This is a global tonemapping operator that models human visual system.
|
Modifier and Type | Class and Description |
---|---|
class |
Plot2d
\addtogroup plot
\{
|
Modifier and Type | Class and Description |
---|---|
class |
QualityBase
\addtogroup quality
\{
|
class |
QualityBRISQUE
\brief BRISQUE (Blind/Referenceless Image Spatial Quality Evaluator) is a No Reference Image Quality Assessment (NR-IQA) algorithm.
|
class |
QualityGMSD
\brief Full reference GMSD algorithm
http://www4.comp.polyu.edu.hk/~cslzhang/IQA/GMSD/GMSD.htm
|
class |
QualityMSE
\brief Full reference mean square error algorithm https://en.wikipedia.org/wiki/Mean_squared_error
|
class |
QualityPSNR
\brief Full reference peak signal to noise ratio (PSNR) algorithm https://en.wikipedia.org/wiki/Peak_signal-to-noise_ratio
|
class |
QualitySSIM
\brief Full reference structural similarity algorithm https://en.wikipedia.org/wiki/Structural_similarity
|
Modifier and Type | Class and Description |
---|---|
class |
MotionSaliency
Motion Saliency Base Class
|
class |
MotionSaliencyBinWangApr2014
\brief the Fast Self-tuning Background Subtraction Algorithm from \cite BinWangApr2014
|
class |
Objectness
Objectness Base Class
|
class |
ObjectnessBING
\brief the Binarized normed gradients algorithm from \cite BING
|
class |
Saliency
\addtogroup saliency
\{
|
class |
StaticSaliency
Static Saliency Base Class
|
class |
StaticSaliencyFineGrained
\brief the Fine Grained Saliency approach from \cite FGS
|
class |
StaticSaliencySpectralResidual
\brief the Spectral Residual approach from \cite SR
|
Modifier and Type | Class and Description |
---|---|
class |
AffineTransformer
\brief Wrapper class for the OpenCV Affine Transformation algorithm.
|
class |
ChiHistogramCostExtractor
\brief An Chi based cost extraction.
|
class |
EMDHistogramCostExtractor
\brief An EMD based cost extraction.
|
class |
EMDL1HistogramCostExtractor
\brief An EMD-L1 based cost extraction.
|
class |
HausdorffDistanceExtractor
\brief A simple Hausdorff distance measure between shapes defined by contours
|
class |
HistogramCostExtractor
\addtogroup shape
\{
|
class |
NormHistogramCostExtractor
\brief A norm based cost extraction.
|
class |
ShapeContextDistanceExtractor
\brief Implementation of the Shape Context descriptor and matching algorithm
|
class |
ShapeDistanceExtractor
\brief Abstract base class for shape distance algorithms.
|
class |
ShapeTransformer
\addtogroup shape
\{
|
class |
ThinPlateSplineShapeTransformer
\brief Definition of the transformation
|
Modifier and Type | Class and Description |
---|---|
class |
GrayCodePattern
\addtogroup structured_light
\{
|
class |
SinusoidalPattern
\brief Class implementing Fourier transform profilometry (FTP) , phase-shifting profilometry (PSP)
and Fourier-assisted phase-shifting profilometry (FAPS) based on \cite faps.
|
class |
StructuredLightPattern
\brief Abstract base class for generating and decoding structured light patterns.
|
Modifier and Type | Class and Description |
---|---|
class |
DenseOpticalFlowExt
\addtogroup superres
\{
|
class |
PyrLKOpticalFlow |
class |
SuperResDualTVL1OpticalFlow |
class |
SuperResFarnebackOpticalFlow |
class |
SuperResolution
\brief Base class for Super Resolution algorithms.
|
Modifier and Type | Class and Description |
---|---|
class |
ERFilter
\brief Base class for 1st and 2nd stages of Neumann and Matas scene text detection algorithm \cite Neumann12.
|
Modifier and Type | Class and Description |
---|---|
class |
MultiTracker
\brief This class is used to track multiple objects using the specified tracker algorithm.
|
class |
Tracker
\brief Base abstract class for the long-term tracker:
|
class |
TrackerBoosting
\brief the Boosting tracker
|
class |
TrackerCSRT
\brief the CSRT tracker
|
class |
TrackerGOTURN
\brief the GOTURN (Generic Object Tracking Using Regression Networks) tracker
|
class |
TrackerKCF
\brief the KCF (Kernelized Correlation Filter) tracker
|
class |
TrackerMedianFlow
\brief the Median Flow tracker
|
class |
TrackerMIL
\brief The MIL algorithm trains a classifier in an online manner to separate the object from the
background.
|
class |
TrackerMOSSE
\brief the MOSSE (Minimum Output Sum of Squared %Error) tracker
|
class |
TrackerTLD
\brief the TLD (Tracking, learning and detection) tracker
|
Modifier and Type | Class and Description |
---|---|
class |
BackgroundSubtractor
\addtogroup video_motion
\{
|
class |
BackgroundSubtractorKNN
\brief K-nearest neighbours - based Background/Foreground Segmentation Algorithm.
|
class |
BackgroundSubtractorMOG2
\brief Gaussian Mixture-based Background/Foreground Segmentation Algorithm.
|
class |
DISOpticalFlow
\brief DIS optical flow algorithm.
|
class |
VariationalRefinement
\brief Variational optical flow refinement
|
Modifier and Type | Class and Description |
---|---|
class |
AffineFeature2D
\brief Class implementing affine adaptation for key points.
|
class |
BoostDesc
\brief Class implementing BoostDesc (Learning Image Descriptors with Boosting), described in
\cite Trzcinski13a and \cite Trzcinski13b.
|
class |
BriefDescriptorExtractor
\brief Class for computing BRIEF descriptors described in \cite calon2010 .
|
class |
DAISY
\brief Class implementing DAISY descriptor, described in \cite Tola10
|
class |
FREAK
\addtogroup xfeatures2d_experiment
\{
|
class |
HarrisLaplaceFeatureDetector
\brief Class implementing the Harris-Laplace feature detector as described in \cite Mikolajczyk2004.
|
class |
LATCH
latch Class for computing the LATCH descriptor.
|
class |
LUCID
\brief Class implementing the locally uniform comparison image descriptor, described in \cite LUCID
|
class |
MSDDetector
\brief Class implementing the MSD (*Maximal Self-Dissimilarity*) keypoint detector, described in \cite Tombari14.
|
class |
PCTSignatures
\brief Class implementing PCT (position-color-texture) signature extraction
as described in \cite KrulisLS16.
|
class |
PCTSignaturesSQFD
\brief Class implementing Signature Quadratic Form Distance (SQFD).
|
class |
SIFT
\brief Class for extracting keypoints and computing descriptors using the Scale Invariant Feature Transform
(SIFT) algorithm by D.
|
class |
StarDetector
\brief The class implements the keypoint detector introduced by \cite Agrawal08, synonym of StarDetector.
|
class |
SURF
\brief Class for extracting Speeded Up Robust Features from an image \cite Bay06 .
|
class |
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.
|
Modifier and Type | Class and Description |
---|---|
class |
AdaptiveManifoldFilter
\brief Interface for Adaptive Manifold Filter realizations.
|
class |
DisparityFilter
\addtogroup ximgproc_filters
\{
|
class |
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.
|
class |
DTFilter
\brief Interface for realizations of Domain Transform filter.
|
class |
EdgeAwareInterpolator
\brief Sparse match interpolation algorithm based on modified locally-weighted affine
estimator from \cite Revaud2015 and Fast Global Smoother as post-processing filter.
|
class |
FastBilateralSolverFilter
\brief Interface for implementations of Fast Bilateral Solver.
|
class |
FastGlobalSmootherFilter
\brief Interface for implementations of Fast Global Smoother filter.
|
class |
GraphSegmentation
\addtogroup ximgproc_segmentation
\{
|
class |
GuidedFilter
\brief Interface for realizations of Guided Filter.
|
class |
RFFeatureGetter
\addtogroup ximgproc_edge
\{
|
class |
RICInterpolator
\brief Sparse match interpolation algorithm based on modified piecewise locally-weighted affine
estimator called Robust Interpolation method of Correspondences or RIC from \cite Hu2017 and Variational
and Fast Global Smoother as post-processing filter.
|
class |
SelectiveSearchSegmentation
\brief Selective search segmentation algorithm
The class implements the algorithm described in \cite uijlings2013selective.
|
class |
SelectiveSearchSegmentationStrategy
\brief Strategie for the selective search segmentation algorithm
The class implements a generic stragery for the algorithm described in \cite uijlings2013selective.
|
class |
SelectiveSearchSegmentationStrategyColor
\brief Color-based strategy for the selective search segmentation algorithm
The class is implemented from the algorithm described in \cite uijlings2013selective.
|
class |
SelectiveSearchSegmentationStrategyFill
\brief Fill-based strategy for the selective search segmentation algorithm
The class is implemented from the algorithm described in \cite uijlings2013selective.
|
class |
SelectiveSearchSegmentationStrategyMultiple
\brief Regroup multiple strategies for the selective search segmentation algorithm
|
class |
SelectiveSearchSegmentationStrategySize
\brief Size-based strategy for the selective search segmentation algorithm
The class is implemented from the algorithm described in \cite uijlings2013selective.
|
class |
SelectiveSearchSegmentationStrategyTexture
\brief Texture-based strategy for the selective search segmentation algorithm
The class is implemented from the algorithm described in \cite uijlings2013selective.
|
class |
SparseMatchInterpolator
\addtogroup ximgproc_filters
\{
|
class |
StructuredEdgeDetection
\brief Class implementing edge detection algorithm from \cite Dollar2013 :
|
class |
SuperpixelLSC
\addtogroup ximgproc_superpixel
\{
|
class |
SuperpixelSEEDS
\addtogroup ximgproc_superpixel
\{
|
class |
SuperpixelSLIC
\brief Class implementing the SLIC (Simple Linear Iterative Clustering) superpixels
algorithm described in \cite Achanta2012.
|
Modifier and Type | Class and Description |
---|---|
class |
GrayworldWB
\brief Gray-world white balance algorithm
|
class |
LearningBasedWB
\brief More sophisticated learning-based automatic white balance algorithm.
|
class |
SimpleWB
\brief A simple white balance algorithm that works by independently stretching
each of the input image channels to the specified range.
|
class |
TonemapDurand
\addtogroup xphoto
\{
|
class |
WhiteBalancer
\addtogroup xphoto
\{
|
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