| Modifier and Type | Method and Description |
|---|---|
static AffineTransformer |
opencv_shape.createAffineTransformer(boolean fullAffine)
Complete constructor
|
static AlignMTB |
opencv_photo.createAlignMTB() |
static AlignMTB |
opencv_photo.createAlignMTB(int max_bits,
int exclude_range,
boolean cut)
\brief Creates AlignMTB object
|
static AdaptiveManifoldFilter |
opencv_ximgproc.createAMFilter(double sigma_s,
double sigma_r) |
static AdaptiveManifoldFilter |
opencv_ximgproc.createAMFilter(double sigma_s,
double sigma_r,
boolean adjust_outliers)
\brief Factory method, create instance of AdaptiveManifoldFilter and produce some initialization routines.
|
static UnscentedKalmanFilter |
opencv_tracking.createAugmentedUnscentedKalmanFilter(AugmentedUnscentedKalmanFilterParams params)
\brief Augmented Unscented Kalman Filter factory method
|
static BackgroundSubtractorCNT |
opencv_bgsegm.createBackgroundSubtractorCNT() |
static BackgroundSubtractorCNT |
opencv_bgsegm.createBackgroundSubtractorCNT(int minPixelStability,
boolean useHistory,
int maxPixelStability,
boolean isParallel)
\brief Creates a CNT Background Subtractor
|
static BackgroundSubtractorGMG |
opencv_bgsegm.createBackgroundSubtractorGMG() |
static BackgroundSubtractorGMG |
opencv_bgsegm.createBackgroundSubtractorGMG(int initializationFrames,
double decisionThreshold)
\brief Creates a GMG Background Subtractor
|
static BackgroundSubtractorGSOC |
opencv_bgsegm.createBackgroundSubtractorGSOC() |
static BackgroundSubtractorGSOC |
opencv_bgsegm.createBackgroundSubtractorGSOC(int mc,
int nSamples,
float replaceRate,
float propagationRate,
int hitsThreshold,
float alpha,
float beta,
float blinkingSupressionDecay,
float blinkingSupressionMultiplier,
float noiseRemovalThresholdFacBG,
float noiseRemovalThresholdFacFG)
\brief Creates an instance of BackgroundSubtractorGSOC algorithm.
|
static BackgroundSubtractorKNN |
opencv_video.createBackgroundSubtractorKNN() |
static BackgroundSubtractorKNN |
opencv_video.createBackgroundSubtractorKNN(int history,
double dist2Threshold,
boolean detectShadows)
\brief Creates KNN Background Subtractor
|
static BackgroundSubtractorLSBP |
opencv_bgsegm.createBackgroundSubtractorLSBP() |
static BackgroundSubtractorLSBP |
opencv_bgsegm.createBackgroundSubtractorLSBP(int mc,
int nSamples,
int LSBPRadius,
float Tlower,
float Tupper,
float Tinc,
float Tdec,
float Rscale,
float Rincdec,
float noiseRemovalThresholdFacBG,
float noiseRemovalThresholdFacFG,
int LSBPthreshold,
int minCount)
\brief Creates an instance of BackgroundSubtractorLSBP algorithm.
|
static BackgroundSubtractorMOG |
opencv_cudabgsegm.createBackgroundSubtractorMOG() |
static BackgroundSubtractorMOG |
opencv_bgsegm.createBackgroundSubtractorMOG() |
static BackgroundSubtractorMOG |
opencv_cudabgsegm.createBackgroundSubtractorMOG(int history,
int nmixtures,
double backgroundRatio,
double noiseSigma)
\brief Creates mixture-of-gaussian background subtractor
|
static BackgroundSubtractorMOG |
opencv_bgsegm.createBackgroundSubtractorMOG(int history,
int nmixtures,
double backgroundRatio,
double noiseSigma)
\brief Creates mixture-of-gaussian background subtractor
|
static BackgroundSubtractorMOG2 |
opencv_video.createBackgroundSubtractorMOG2() |
static BackgroundSubtractorMOG2 |
opencv_cudabgsegm.createBackgroundSubtractorMOG2() |
static BackgroundSubtractorMOG2 |
opencv_video.createBackgroundSubtractorMOG2(int history,
double varThreshold,
boolean detectShadows)
\brief Creates MOG2 Background Subtractor
|
static BackgroundSubtractorMOG2 |
opencv_cudabgsegm.createBackgroundSubtractorMOG2(int history,
double varThreshold,
boolean detectShadows)
\brief Creates MOG2 Background Subtractor
|
static Filter |
opencv_cudafilters.createBoxFilter(int srcType,
int dstType,
Size ksize) |
static Filter |
opencv_cudafilters.createBoxFilter(int srcType,
int dstType,
Size ksize,
Point anchor,
int borderMode,
Scalar borderVal)
\brief Creates a normalized 2D box filter.
|
static Filter |
opencv_cudafilters.createBoxMaxFilter(int srcType,
Size ksize) |
static Filter |
opencv_cudafilters.createBoxMaxFilter(int srcType,
Size ksize,
Point anchor,
int borderMode,
Scalar borderVal)
\brief Creates the maximum filter.
|
static Filter |
opencv_cudafilters.createBoxMinFilter(int srcType,
Size ksize) |
static Filter |
opencv_cudafilters.createBoxMinFilter(int srcType,
Size ksize,
Point anchor,
int borderMode,
Scalar borderVal)
\brief Creates the minimum filter.
|
static CalibrateDebevec |
opencv_photo.createCalibrateDebevec() |
static CalibrateDebevec |
opencv_photo.createCalibrateDebevec(int samples,
float lambda,
boolean random)
\brief Creates CalibrateDebevec object
|
static CalibrateRobertson |
opencv_photo.createCalibrateRobertson() |
static CalibrateRobertson |
opencv_photo.createCalibrateRobertson(int max_iter,
float threshold)
\brief Creates CalibrateRobertson object
|
static CannyEdgeDetector |
opencv_cudaimgproc.createCannyEdgeDetector(double low_thresh,
double high_thresh) |
static CannyEdgeDetector |
opencv_cudaimgproc.createCannyEdgeDetector(double low_thresh,
double high_thresh,
int apperture_size,
boolean L2gradient)
\brief Creates implementation for cuda::CannyEdgeDetector .
|
static HistogramCostExtractor |
opencv_shape.createChiHistogramCostExtractor() |
static HistogramCostExtractor |
opencv_shape.createChiHistogramCostExtractor(int nDummies,
float defaultCost) |
static CLAHE |
opencv_imgproc.createCLAHE() |
static CudaCLAHE |
opencv_cudaimgproc.createCLAHE() |
static CLAHE |
opencv_imgproc.createCLAHE(double clipLimit,
Size tileGridSize)
\brief Creates a smart pointer to a cv::CLAHE class and initializes it.
|
static CudaCLAHE |
opencv_cudaimgproc.createCLAHE(double clipLimit,
Size tileGridSize)
\brief Creates implementation for cuda::CLAHE .
|
static Filter |
opencv_cudafilters.createColumnSumFilter(int srcType,
int dstType,
int ksize) |
static Filter |
opencv_cudafilters.createColumnSumFilter(int srcType,
int dstType,
int ksize,
int anchor,
int borderMode,
Scalar borderVal)
\brief Creates a vertical 1D box filter.
|
static ContourFitting |
opencv_ximgproc.createContourFitting() |
static ContourFitting |
opencv_ximgproc.createContourFitting(int ctr,
int fd)
\brief create ContourFitting algorithm object
|
static Convolution |
opencv_cudaarithm.createConvolution() |
static Convolution |
opencv_cudaarithm.createConvolution(Size user_block_size)
\brief Creates implementation for cuda::Convolution .
|
static Filter |
opencv_cudafilters.createDerivFilter(int srcType,
int dstType,
int dx,
int dy,
int ksize) |
static Filter |
opencv_cudafilters.createDerivFilter(int srcType,
int dstType,
int dx,
int dy,
int ksize,
boolean normalize,
double scale,
int rowBorderMode,
int columnBorderMode)
\brief Creates a generalized Deriv operator.
|
static DFT |
opencv_cudaarithm.createDFT(Size dft_size,
int flags)
\brief Creates implementation for cuda::DFT.
|
static DisparityBilateralFilter |
opencv_cudastereo.createDisparityBilateralFilter() |
static DisparityBilateralFilter |
opencv_cudastereo.createDisparityBilateralFilter(int ndisp,
int radius,
int iters)
\brief Creates DisparityBilateralFilter object.
|
static DisparityWLSFilter |
opencv_ximgproc.createDisparityWLSFilter(StereoMatcher matcher_left)
\brief Convenience factory method that creates an instance of DisparityWLSFilter and sets up all the relevant
filter parameters automatically based on the matcher instance.
|
static DisparityWLSFilter |
opencv_ximgproc.createDisparityWLSFilterGeneric(boolean use_confidence)
\brief More generic factory method, create instance of DisparityWLSFilter and execute basic
initialization routines.
|
static DTFilter |
opencv_ximgproc.createDTFilter(GpuMat guide,
double sigmaSpatial,
double sigmaColor) |
static DTFilter |
opencv_ximgproc.createDTFilter(GpuMat guide,
double sigmaSpatial,
double sigmaColor,
int mode,
int numIters) |
static DTFilter |
opencv_ximgproc.createDTFilter(Mat guide,
double sigmaSpatial,
double sigmaColor) |
static DTFilter |
opencv_ximgproc.createDTFilter(Mat guide,
double sigmaSpatial,
double sigmaColor,
int mode,
int numIters)
\brief Factory method, create instance of DTFilter and produce initialization routines.
|
static DTFilter |
opencv_ximgproc.createDTFilter(UMat guide,
double sigmaSpatial,
double sigmaColor) |
static DTFilter |
opencv_ximgproc.createDTFilter(UMat guide,
double sigmaSpatial,
double sigmaColor,
int mode,
int numIters) |
static EdgeAwareInterpolator |
opencv_ximgproc.createEdgeAwareInterpolator()
\brief Factory method that creates an instance of the
EdgeAwareInterpolator.
|
static EdgeBoxes |
opencv_ximgproc.createEdgeBoxes() |
static EdgeBoxes |
opencv_ximgproc.createEdgeBoxes(float alpha,
float beta,
float eta,
float minScore,
int maxBoxes,
float edgeMinMag,
float edgeMergeThr,
float clusterMinMag,
float maxAspectRatio,
float minBoxArea,
float gamma,
float kappa)
\brief Creates a Edgeboxes
|
static HistogramCostExtractor |
opencv_shape.createEMDHistogramCostExtractor() |
static HistogramCostExtractor |
opencv_shape.createEMDHistogramCostExtractor(int flag,
int nDummies,
float defaultCost) |
static HistogramCostExtractor |
opencv_shape.createEMDL1HistogramCostExtractor() |
static HistogramCostExtractor |
opencv_shape.createEMDL1HistogramCostExtractor(int nDummies,
float defaultCost) |
static ERFilter |
opencv_text.createERFilterNM1(BytePointer filename) |
static ERFilter |
opencv_text.createERFilterNM1(BytePointer filename,
int thresholdDelta,
float minArea,
float maxArea,
float minProbability,
boolean nonMaxSuppression,
float minProbabilityDiff)
\brief Reads an Extremal Region Filter for the 1st stage classifier of N&M algorithm
from the provided path e.g.
|
static ERFilter |
opencv_text.createERFilterNM1(ERFilter.Callback cb) |
static ERFilter |
opencv_text.createERFilterNM1(ERFilter.Callback cb,
int thresholdDelta,
float minArea,
float maxArea,
float minProbability,
boolean nonMaxSuppression,
float minProbabilityDiff)
\brief Create an Extremal Region Filter for the 1st stage classifier of N&M algorithm \cite Neumann12.
|
static ERFilter |
opencv_text.createERFilterNM1(String filename) |
static ERFilter |
opencv_text.createERFilterNM1(String filename,
int thresholdDelta,
float minArea,
float maxArea,
float minProbability,
boolean nonMaxSuppression,
float minProbabilityDiff) |
static ERFilter |
opencv_text.createERFilterNM2(BytePointer filename) |
static ERFilter |
opencv_text.createERFilterNM2(BytePointer filename,
float minProbability)
\brief Reads an Extremal Region Filter for the 2nd stage classifier of N&M algorithm
from the provided path e.g.
|
static ERFilter |
opencv_text.createERFilterNM2(ERFilter.Callback cb) |
static ERFilter |
opencv_text.createERFilterNM2(ERFilter.Callback cb,
float minProbability)
\brief Create an Extremal Region Filter for the 2nd stage classifier of N&M algorithm \cite Neumann12.
|
static ERFilter |
opencv_text.createERFilterNM2(String filename) |
static ERFilter |
opencv_text.createERFilterNM2(String filename,
float minProbability) |
static BaseCascadeClassifier.MaskGenerator |
opencv_objdetect.createFaceDetectionMaskGenerator() |
static Facemark |
opencv_face.createFacemarkAAM()
construct an AAM facemark detector
|
static Facemark |
opencv_face.createFacemarkKazemi()
construct a Kazemi facemark detector
|
static Facemark |
opencv_face.createFacemarkLBF()
construct an LBF facemark detector
|
static FastBilateralSolverFilter |
opencv_ximgproc.createFastBilateralSolverFilter(GpuMat guide,
double sigma_spatial,
double sigma_luma,
double sigma_chroma) |
static FastBilateralSolverFilter |
opencv_ximgproc.createFastBilateralSolverFilter(GpuMat guide,
double sigma_spatial,
double sigma_luma,
double sigma_chroma,
double lambda,
int num_iter,
double max_tol) |
static FastBilateralSolverFilter |
opencv_ximgproc.createFastBilateralSolverFilter(Mat guide,
double sigma_spatial,
double sigma_luma,
double sigma_chroma) |
static FastBilateralSolverFilter |
opencv_ximgproc.createFastBilateralSolverFilter(Mat guide,
double sigma_spatial,
double sigma_luma,
double sigma_chroma,
double lambda,
int num_iter,
double max_tol)
\brief Factory method, create instance of FastBilateralSolverFilter and execute the initialization routines.
|
static FastBilateralSolverFilter |
opencv_ximgproc.createFastBilateralSolverFilter(UMat guide,
double sigma_spatial,
double sigma_luma,
double sigma_chroma) |
static FastBilateralSolverFilter |
opencv_ximgproc.createFastBilateralSolverFilter(UMat guide,
double sigma_spatial,
double sigma_luma,
double sigma_chroma,
double lambda,
int num_iter,
double max_tol) |
static FastGlobalSmootherFilter |
opencv_ximgproc.createFastGlobalSmootherFilter(GpuMat guide,
double lambda,
double sigma_color) |
static FastGlobalSmootherFilter |
opencv_ximgproc.createFastGlobalSmootherFilter(GpuMat guide,
double lambda,
double sigma_color,
double lambda_attenuation,
int num_iter) |
static FastGlobalSmootherFilter |
opencv_ximgproc.createFastGlobalSmootherFilter(Mat guide,
double lambda,
double sigma_color) |
static FastGlobalSmootherFilter |
opencv_ximgproc.createFastGlobalSmootherFilter(Mat guide,
double lambda,
double sigma_color,
double lambda_attenuation,
int num_iter)
\brief Factory method, create instance of FastGlobalSmootherFilter and execute the initialization routines.
|
static FastGlobalSmootherFilter |
opencv_ximgproc.createFastGlobalSmootherFilter(UMat guide,
double lambda,
double sigma_color) |
static FastGlobalSmootherFilter |
opencv_ximgproc.createFastGlobalSmootherFilter(UMat guide,
double lambda,
double sigma_color,
double lambda_attenuation,
int num_iter) |
static FastLineDetector |
opencv_ximgproc.createFastLineDetector() |
static FastLineDetector |
opencv_ximgproc.createFastLineDetector(int length_threshold,
float distance_threshold,
double canny_th1,
double canny_th2,
int canny_aperture_size,
boolean do_merge)
\brief Creates a smart pointer to a FastLineDetector object and initializes it
|
static FrameSource |
opencv_superres.createFrameSource_Camera() |
static FrameSource |
opencv_superres.createFrameSource_Camera(int deviceId) |
static FrameSource |
opencv_superres.createFrameSource_Empty()
\defgroup superres Super Resolution
|
static FrameSource |
opencv_superres.createFrameSource_Video_CUDA(BytePointer fileName) |
static FrameSource |
opencv_superres.createFrameSource_Video_CUDA(String fileName) |
static FrameSource |
opencv_superres.createFrameSource_Video(BytePointer fileName) |
static FrameSource |
opencv_superres.createFrameSource_Video(String fileName) |
static Filter |
opencv_cudafilters.createGaussianFilter(int srcType,
int dstType,
Size ksize,
double sigma1) |
static Filter |
opencv_cudafilters.createGaussianFilter(int srcType,
int dstType,
Size ksize,
double sigma1,
double sigma2,
int rowBorderMode,
int columnBorderMode)
\brief Creates a Gaussian filter.
|
static GeneralizedHoughBallard |
opencv_imgproc.createGeneralizedHoughBallard()
\brief Creates a smart pointer to a cv::GeneralizedHoughBallard class and initializes it.
|
static GeneralizedHoughBallard |
opencv_cudaimgproc.createGeneralizedHoughBallard()
\brief Creates implementation for generalized hough transform from \cite Ballard1981 .
|
static GeneralizedHoughGuil |
opencv_imgproc.createGeneralizedHoughGuil()
\brief Creates a smart pointer to a cv::GeneralizedHoughGuil class and initializes it.
|
static GeneralizedHoughGuil |
opencv_cudaimgproc.createGeneralizedHoughGuil()
\brief Creates implementation for generalized hough transform from \cite Guil1999 .
|
static CornersDetector |
opencv_cudaimgproc.createGoodFeaturesToTrackDetector(int srcType) |
static CornersDetector |
opencv_cudaimgproc.createGoodFeaturesToTrackDetector(int srcType,
int maxCorners,
double qualityLevel,
double minDistance,
int blockSize,
boolean useHarrisDetector,
double harrisK)
\brief Creates implementation for cuda::CornersDetector .
|
static GraphSegmentation |
opencv_ximgproc.createGraphSegmentation() |
static GraphSegmentation |
opencv_ximgproc.createGraphSegmentation(double sigma,
float k,
int min_size)
\brief Creates a graph based segmentor
|
static GrayworldWB |
opencv_xphoto.createGrayworldWB()
\brief Creates an instance of GrayworldWB
|
static GuidedFilter |
opencv_ximgproc.createGuidedFilter(GpuMat guide,
int radius,
double eps) |
static GuidedFilter |
opencv_ximgproc.createGuidedFilter(GpuMat guide,
int radius,
double eps,
double scale) |
static GuidedFilter |
opencv_ximgproc.createGuidedFilter(Mat guide,
int radius,
double eps) |
static GuidedFilter |
opencv_ximgproc.createGuidedFilter(Mat guide,
int radius,
double eps,
double scale)
\brief Factory method, create instance of GuidedFilter and produce initialization routines.
|
static GuidedFilter |
opencv_ximgproc.createGuidedFilter(UMat guide,
int radius,
double eps) |
static GuidedFilter |
opencv_ximgproc.createGuidedFilter(UMat guide,
int radius,
double eps,
double scale) |
static CornernessCriteria |
opencv_cudaimgproc.createHarrisCorner(int srcType,
int blockSize,
int ksize,
double k) |
static CornernessCriteria |
opencv_cudaimgproc.createHarrisCorner(int srcType,
int blockSize,
int ksize,
double k,
int borderType)
\brief Creates implementation for Harris cornerness criteria.
|
static HausdorffDistanceExtractor |
opencv_shape.createHausdorffDistanceExtractor() |
static HausdorffDistanceExtractor |
opencv_shape.createHausdorffDistanceExtractor(int distanceFlag,
float rankProp) |
static HoughCirclesDetector |
opencv_cudaimgproc.createHoughCirclesDetector(float dp,
float minDist,
int cannyThreshold,
int votesThreshold,
int minRadius,
int maxRadius) |
static HoughCirclesDetector |
opencv_cudaimgproc.createHoughCirclesDetector(float dp,
float minDist,
int cannyThreshold,
int votesThreshold,
int minRadius,
int maxRadius,
int maxCircles)
\brief Creates implementation for cuda::HoughCirclesDetector .
|
static HoughLinesDetector |
opencv_cudaimgproc.createHoughLinesDetector(float rho,
float theta,
int threshold) |
static HoughLinesDetector |
opencv_cudaimgproc.createHoughLinesDetector(float rho,
float theta,
int threshold,
boolean doSort,
int maxLines)
\brief Creates implementation for cuda::HoughLinesDetector .
|
static HoughSegmentDetector |
opencv_cudaimgproc.createHoughSegmentDetector(float rho,
float theta,
int minLineLength,
int maxLineGap) |
static HoughSegmentDetector |
opencv_cudaimgproc.createHoughSegmentDetector(float rho,
float theta,
int minLineLength,
int maxLineGap,
int maxLines,
int threshold)
\brief Creates implementation for cuda::HoughSegmentDetector .
|
static Filter |
opencv_cudafilters.createLaplacianFilter(int srcType,
int dstType) |
static Filter |
opencv_cudafilters.createLaplacianFilter(int srcType,
int dstType,
int ksize,
double scale,
int borderMode,
Scalar borderVal)
\brief Creates a Laplacian operator.
|
static LearningBasedWB |
opencv_xphoto.createLearningBasedWB() |
static LearningBasedWB |
opencv_xphoto.createLearningBasedWB(BytePointer path_to_model)
\brief Creates an instance of LearningBasedWB
|
static LearningBasedWB |
opencv_xphoto.createLearningBasedWB(String path_to_model) |
static Filter |
opencv_cudafilters.createLinearFilter(int srcType,
int dstType,
GpuMat kernel) |
static Filter |
opencv_cudafilters.createLinearFilter(int srcType,
int dstType,
GpuMat kernel,
Point anchor,
int borderMode,
Scalar borderVal) |
static Filter |
opencv_cudafilters.createLinearFilter(int srcType,
int dstType,
Mat kernel) |
static Filter |
opencv_cudafilters.createLinearFilter(int srcType,
int dstType,
Mat kernel,
Point anchor,
int borderMode,
Scalar borderVal)
\brief Creates a non-separable linear 2D filter.
|
static Filter |
opencv_cudafilters.createLinearFilter(int srcType,
int dstType,
UMat kernel) |
static Filter |
opencv_cudafilters.createLinearFilter(int srcType,
int dstType,
UMat kernel,
Point anchor,
int borderMode,
Scalar borderVal) |
static LineSegmentDetector |
opencv_imgproc.createLineSegmentDetector() |
static LineSegmentDetector |
opencv_imgproc.createLineSegmentDetector(int refine,
double scale,
double sigma_scale,
double quant,
double ang_th,
double log_eps,
double density_th,
int n_bins)
\brief Creates a smart pointer to a LineSegmentDetector object and initializes it.
|
static LookUpTable |
opencv_cudaarithm.createLookUpTable(GpuMat lut) |
static LookUpTable |
opencv_cudaarithm.createLookUpTable(Mat lut)
\brief Creates implementation for cuda::LookUpTable .
|
static LookUpTable |
opencv_cudaarithm.createLookUpTable(UMat lut) |
static Filter |
opencv_cudafilters.createMedianFilter(int srcType,
int windowSize) |
static Filter |
opencv_cudafilters.createMedianFilter(int srcType,
int windowSize,
int partition)
\}
|
static MergeDebevec |
opencv_photo.createMergeDebevec()
\brief Creates MergeDebevec object
|
static MergeMertens |
opencv_photo.createMergeMertens() |
static MergeMertens |
opencv_photo.createMergeMertens(float contrast_weight,
float saturation_weight,
float exposure_weight)
\brief Creates MergeMertens object
|
static MergeRobertson |
opencv_photo.createMergeRobertson()
\brief Creates MergeRobertson object
|
static CornernessCriteria |
opencv_cudaimgproc.createMinEigenValCorner(int srcType,
int blockSize,
int ksize) |
static CornernessCriteria |
opencv_cudaimgproc.createMinEigenValCorner(int srcType,
int blockSize,
int ksize,
int borderType)
\brief Creates implementation for the minimum eigen value of a 2x2 derivative covariation matrix (the
cornerness criteria).
|
static Filter |
opencv_cudafilters.createMorphologyFilter(int op,
int srcType,
GpuMat kernel) |
static Filter |
opencv_cudafilters.createMorphologyFilter(int op,
int srcType,
GpuMat kernel,
Point anchor,
int iterations) |
static Filter |
opencv_cudafilters.createMorphologyFilter(int op,
int srcType,
Mat kernel) |
static Filter |
opencv_cudafilters.createMorphologyFilter(int op,
int srcType,
Mat kernel,
Point anchor,
int iterations)
\brief Creates a 2D morphological filter.
|
static Filter |
opencv_cudafilters.createMorphologyFilter(int op,
int srcType,
UMat kernel) |
static Filter |
opencv_cudafilters.createMorphologyFilter(int op,
int srcType,
UMat kernel,
Point anchor,
int iterations) |
static HistogramCostExtractor |
opencv_shape.createNormHistogramCostExtractor() |
static HistogramCostExtractor |
opencv_shape.createNormHistogramCostExtractor(int flag,
int nDummies,
float defaultCost)
\}
|
static BroxOpticalFlow |
opencv_superres.createOptFlow_Brox_CUDA() |
static DenseOpticalFlow |
opencv_optflow.createOptFlow_DeepFlow()
\brief DeepFlow optical flow algorithm implementation.
|
static SuperResDualTVL1OpticalFlow |
opencv_superres.createOptFlow_DualTVL1_CUDA() |
static SuperResDualTVL1OpticalFlow |
opencv_superres.createOptFlow_DualTVL1() |
static DualTVL1OpticalFlow |
opencv_optflow.createOptFlow_DualTVL1()
\brief Creates instance of cv::DenseOpticalFlow
|
static SuperResFarnebackOpticalFlow |
opencv_superres.createOptFlow_Farneback_CUDA() |
static SuperResFarnebackOpticalFlow |
opencv_superres.createOptFlow_Farneback()
\} superres
|
static DenseOpticalFlow |
opencv_optflow.createOptFlow_Farneback()
Additional interface to the Farneback's algorithm - calcOpticalFlowFarneback()
|
static PyrLKOpticalFlow |
opencv_superres.createOptFlow_PyrLK_CUDA() |
static DenseOpticalFlow |
opencv_optflow.createOptFlow_SimpleFlow()
Additional interface to the SimpleFlow algorithm - calcOpticalFlowSF()
|
static DenseOpticalFlow |
opencv_optflow.createOptFlow_SparseToDense()
Additional interface to the SparseToDenseFlow algorithm - calcOpticalFlowSparseToDense()
|
static RFFeatureGetter |
opencv_ximgproc.createRFFeatureGetter()
\file
\date Jun 17, 2014
|
static RICInterpolator |
opencv_ximgproc.createRICInterpolator()
\brief Factory method that creates an instance of the
RICInterpolator.
|
static StereoMatcher |
opencv_ximgproc.createRightMatcher(StereoMatcher matcher_left)
\brief Convenience method to set up the matcher for computing the right-view disparity map
that is required in case of filtering with confidence.
|
static Filter |
opencv_cudafilters.createRowSumFilter(int srcType,
int dstType,
int ksize) |
static Filter |
opencv_cudafilters.createRowSumFilter(int srcType,
int dstType,
int ksize,
int anchor,
int borderMode,
Scalar borderVal)
\brief Creates a horizontal 1D box filter.
|
static Filter |
opencv_cudafilters.createScharrFilter(int srcType,
int dstType,
int dx,
int dy) |
static Filter |
opencv_cudafilters.createScharrFilter(int srcType,
int dstType,
int dx,
int dy,
double scale,
int rowBorderMode,
int columnBorderMode)
\brief Creates a vertical or horizontal Scharr operator.
|
static SelectiveSearchSegmentation |
opencv_ximgproc.createSelectiveSearchSegmentation()
\brief Create a new SelectiveSearchSegmentation class.
|
static SelectiveSearchSegmentationStrategyColor |
opencv_ximgproc.createSelectiveSearchSegmentationStrategyColor()
\brief Create a new color-based strategy
|
static SelectiveSearchSegmentationStrategyFill |
opencv_ximgproc.createSelectiveSearchSegmentationStrategyFill()
\brief Create a new fill-based strategy
|
static SelectiveSearchSegmentationStrategyMultiple |
opencv_ximgproc.createSelectiveSearchSegmentationStrategyMultiple()
\brief Create a new multiple strategy
|
static SelectiveSearchSegmentationStrategyMultiple |
opencv_ximgproc.createSelectiveSearchSegmentationStrategyMultiple(SelectiveSearchSegmentationStrategy s1)
\brief Create a new multiple strategy and set one subtrategy
|
static SelectiveSearchSegmentationStrategyMultiple |
opencv_ximgproc.createSelectiveSearchSegmentationStrategyMultiple(SelectiveSearchSegmentationStrategy s1,
SelectiveSearchSegmentationStrategy s2)
\brief Create a new multiple strategy and set two subtrategies, with equal weights
|
static SelectiveSearchSegmentationStrategyMultiple |
opencv_ximgproc.createSelectiveSearchSegmentationStrategyMultiple(SelectiveSearchSegmentationStrategy s1,
SelectiveSearchSegmentationStrategy s2,
SelectiveSearchSegmentationStrategy s3)
\brief Create a new multiple strategy and set three subtrategies, with equal weights
|
static SelectiveSearchSegmentationStrategyMultiple |
opencv_ximgproc.createSelectiveSearchSegmentationStrategyMultiple(SelectiveSearchSegmentationStrategy s1,
SelectiveSearchSegmentationStrategy s2,
SelectiveSearchSegmentationStrategy s3,
SelectiveSearchSegmentationStrategy s4)
\brief Create a new multiple strategy and set four subtrategies, with equal weights
|
static SelectiveSearchSegmentationStrategySize |
opencv_ximgproc.createSelectiveSearchSegmentationStrategySize()
\brief Create a new size-based strategy
|
static SelectiveSearchSegmentationStrategyTexture |
opencv_ximgproc.createSelectiveSearchSegmentationStrategyTexture()
\brief Create a new size-based strategy
|
static Filter |
opencv_cudafilters.createSeparableLinearFilter(int srcType,
int dstType,
GpuMat rowKernel,
GpuMat columnKernel) |
static Filter |
opencv_cudafilters.createSeparableLinearFilter(int srcType,
int dstType,
GpuMat rowKernel,
GpuMat columnKernel,
Point anchor,
int rowBorderMode,
int columnBorderMode) |
static Filter |
opencv_cudafilters.createSeparableLinearFilter(int srcType,
int dstType,
Mat rowKernel,
Mat columnKernel) |
static Filter |
opencv_cudafilters.createSeparableLinearFilter(int srcType,
int dstType,
Mat rowKernel,
Mat columnKernel,
Point anchor,
int rowBorderMode,
int columnBorderMode)
\brief Creates a separable linear filter.
|
static Filter |
opencv_cudafilters.createSeparableLinearFilter(int srcType,
int dstType,
UMat rowKernel,
UMat columnKernel) |
static Filter |
opencv_cudafilters.createSeparableLinearFilter(int srcType,
int dstType,
UMat rowKernel,
UMat columnKernel,
Point anchor,
int rowBorderMode,
int columnBorderMode) |
static ShapeContextDistanceExtractor |
opencv_shape.createShapeContextDistanceExtractor() |
static ShapeContextDistanceExtractor |
opencv_shape.createShapeContextDistanceExtractor(int nAngularBins,
int nRadialBins,
float innerRadius,
float outerRadius,
int iterations,
HistogramCostExtractor comparer,
ShapeTransformer transformer)
\}
|
static SimpleWB |
opencv_xphoto.createSimpleWB()
\brief Creates an instance of SimpleWB
|
static Filter |
opencv_cudafilters.createSobelFilter(int srcType,
int dstType,
int dx,
int dy) |
static Filter |
opencv_cudafilters.createSobelFilter(int srcType,
int dstType,
int dx,
int dy,
int ksize,
double scale,
int rowBorderMode,
int columnBorderMode)
\brief Creates a Sobel operator.
|
static StereoBeliefPropagation |
opencv_cudastereo.createStereoBeliefPropagation() |
static StereoBeliefPropagation |
opencv_cudastereo.createStereoBeliefPropagation(int ndisp,
int iters,
int levels,
int msg_type)
\brief Creates StereoBeliefPropagation object.
|
static StereoBM |
opencv_cudastereo.createStereoBM() |
static StereoBM |
opencv_cudastereo.createStereoBM(int numDisparities,
int blockSize)
\brief Creates StereoBM object.
|
static StereoConstantSpaceBP |
opencv_cudastereo.createStereoConstantSpaceBP() |
static StereoConstantSpaceBP |
opencv_cudastereo.createStereoConstantSpaceBP(int ndisp,
int iters,
int levels,
int nr_plane,
int msg_type)
\brief Creates StereoConstantSpaceBP object.
|
static StereoSGM |
opencv_cudastereo.createStereoSGM() |
static StereoSGM |
opencv_cudastereo.createStereoSGM(int minDisparity,
int numDisparities,
int P1,
int P2,
int uniquenessRatio,
int mode)
\brief Creates StereoSGM object.
|
static Stitcher |
opencv_stitching.createStitcher() |
static Stitcher |
opencv_stitching.createStitcher(boolean try_use_gpu)
Deprecated.
use Stitcher::create
|
static Stitcher |
opencv_stitching.createStitcherScans() |
static Stitcher |
opencv_stitching.createStitcherScans(boolean try_use_gpu)
Deprecated.
use Stitcher::create
|
static StructuredEdgeDetection |
opencv_ximgproc.createStructuredEdgeDetection(BytePointer model) |
static StructuredEdgeDetection |
opencv_ximgproc.createStructuredEdgeDetection(BytePointer model,
RFFeatureGetter howToGetFeatures)
The only constructor
|
static StructuredEdgeDetection |
opencv_ximgproc.createStructuredEdgeDetection(String model) |
static StructuredEdgeDetection |
opencv_ximgproc.createStructuredEdgeDetection(String model,
RFFeatureGetter howToGetFeatures) |
static SuperpixelLSC |
opencv_ximgproc.createSuperpixelLSC(GpuMat image) |
static SuperpixelLSC |
opencv_ximgproc.createSuperpixelLSC(GpuMat image,
int region_size,
float ratio) |
static SuperpixelLSC |
opencv_ximgproc.createSuperpixelLSC(Mat image) |
static SuperpixelLSC |
opencv_ximgproc.createSuperpixelLSC(Mat image,
int region_size,
float ratio)
\brief Class implementing the LSC (Linear Spectral Clustering) superpixels
|
static SuperpixelLSC |
opencv_ximgproc.createSuperpixelLSC(UMat image) |
static SuperpixelLSC |
opencv_ximgproc.createSuperpixelLSC(UMat image,
int region_size,
float ratio) |
static SuperpixelSEEDS |
opencv_ximgproc.createSuperpixelSEEDS(int image_width,
int image_height,
int image_channels,
int num_superpixels,
int num_levels) |
static SuperpixelSEEDS |
opencv_ximgproc.createSuperpixelSEEDS(int image_width,
int image_height,
int image_channels,
int num_superpixels,
int num_levels,
int prior,
int histogram_bins,
boolean double_step)
\brief Initializes a SuperpixelSEEDS object.
|
static SuperpixelSLIC |
opencv_ximgproc.createSuperpixelSLIC(GpuMat image) |
static SuperpixelSLIC |
opencv_ximgproc.createSuperpixelSLIC(GpuMat image,
int algorithm,
int region_size,
float ruler) |
static SuperpixelSLIC |
opencv_ximgproc.createSuperpixelSLIC(Mat image) |
static SuperpixelSLIC |
opencv_ximgproc.createSuperpixelSLIC(Mat image,
int algorithm,
int region_size,
float ruler)
\brief Initialize a SuperpixelSLIC object
|
static SuperpixelSLIC |
opencv_ximgproc.createSuperpixelSLIC(UMat image) |
static SuperpixelSLIC |
opencv_ximgproc.createSuperpixelSLIC(UMat image,
int algorithm,
int region_size,
float ruler) |
static SuperResolution |
opencv_superres.createSuperResolution_BTVL1_CUDA() |
static SuperResolution |
opencv_superres.createSuperResolution_BTVL1()
\brief Create Bilateral TV-L1 Super Resolution.
|
static SyntheticSequenceGenerator |
opencv_bgsegm.createSyntheticSequenceGenerator(GpuMat background,
GpuMat object) |
static SyntheticSequenceGenerator |
opencv_bgsegm.createSyntheticSequenceGenerator(GpuMat background,
GpuMat object,
double amplitude,
double wavelength,
double wavespeed,
double objspeed) |
static SyntheticSequenceGenerator |
opencv_bgsegm.createSyntheticSequenceGenerator(Mat background,
Mat object) |
static SyntheticSequenceGenerator |
opencv_bgsegm.createSyntheticSequenceGenerator(Mat background,
Mat object,
double amplitude,
double wavelength,
double wavespeed,
double objspeed)
\brief Creates an instance of SyntheticSequenceGenerator.
|
static SyntheticSequenceGenerator |
opencv_bgsegm.createSyntheticSequenceGenerator(UMat background,
UMat object) |
static SyntheticSequenceGenerator |
opencv_bgsegm.createSyntheticSequenceGenerator(UMat background,
UMat object,
double amplitude,
double wavelength,
double wavespeed,
double objspeed) |
static TemplateMatching |
opencv_cudaimgproc.createTemplateMatching(int srcType,
int method) |
static TemplateMatching |
opencv_cudaimgproc.createTemplateMatching(int srcType,
int method,
Size user_block_size)
\brief Creates implementation for cuda::TemplateMatching .
|
static ThinPlateSplineShapeTransformer |
opencv_shape.createThinPlateSplineShapeTransformer() |
static ThinPlateSplineShapeTransformer |
opencv_shape.createThinPlateSplineShapeTransformer(double regularizationParameter)
Complete constructor
|
static Tonemap |
opencv_photo.createTonemap() |
static Tonemap |
opencv_photo.createTonemap(float gamma)
\brief Creates simple linear mapper with gamma correction
|
static TonemapDrago |
opencv_photo.createTonemapDrago() |
static TonemapDrago |
opencv_photo.createTonemapDrago(float gamma,
float saturation,
float bias)
\brief Creates TonemapDrago object
|
static TonemapDurand |
opencv_xphoto.createTonemapDurand() |
static TonemapDurand |
opencv_xphoto.createTonemapDurand(float gamma,
float contrast,
float saturation,
float sigma_color,
float sigma_space)
\brief Creates TonemapDurand object
|
static TonemapMantiuk |
opencv_photo.createTonemapMantiuk() |
static TonemapMantiuk |
opencv_photo.createTonemapMantiuk(float gamma,
float scale,
float saturation)
\brief Creates TonemapMantiuk object
|
static TonemapReinhard |
opencv_photo.createTonemapReinhard() |
static TonemapReinhard |
opencv_photo.createTonemapReinhard(float gamma,
float intensity,
float light_adapt,
float color_adapt)
\brief Creates TonemapReinhard object
|
static ITrackerByMatching |
opencv_tracking.createTrackerByMatching() |
static ITrackerByMatching |
opencv_tracking.createTrackerByMatching(TrackerParams params)
\brief The factory to create Tracker-by-Matching algorithm implementation.
|
static UnscentedKalmanFilter |
opencv_tracking.createUnscentedKalmanFilter(UnscentedKalmanFilterParams params)
\brief Unscented Kalman Filter factory method
|
static VideoReader |
opencv_cudacodec.createVideoReader(BytePointer filename) |
static VideoReader |
opencv_cudacodec.createVideoReader(BytePointer filename,
int[] sourceParams,
VideoReaderInitParams params) |
static VideoReader |
opencv_cudacodec.createVideoReader(BytePointer filename,
IntBuffer sourceParams,
VideoReaderInitParams params) |
static VideoReader |
opencv_cudacodec.createVideoReader(BytePointer filename,
IntPointer sourceParams,
VideoReaderInitParams params)
\brief Creates video reader.
|
static VideoReader |
opencv_cudacodec.createVideoReader(RawVideoSource source) |
static VideoReader |
opencv_cudacodec.createVideoReader(RawVideoSource source,
VideoReaderInitParams params)
\overload
|
static VideoReader |
opencv_cudacodec.createVideoReader(String filename) |
static VideoReader |
opencv_cudacodec.createVideoReader(String filename,
int[] sourceParams,
VideoReaderInitParams params) |
static VideoReader |
opencv_cudacodec.createVideoReader(String filename,
IntBuffer sourceParams,
VideoReaderInitParams params) |
static VideoReader |
opencv_cudacodec.createVideoReader(String filename,
IntPointer sourceParams,
VideoReaderInitParams params) |
static VideoWriter |
opencv_cudacodec.createVideoWriter(BytePointer fileName,
Size frameSize) |
static VideoWriter |
opencv_cudacodec.createVideoWriter(BytePointer fileName,
Size frameSize,
int codec,
double fps,
int colorFormat,
EncoderCallback encoderCallback,
Stream stream)
\brief Creates video writer.
|
static VideoWriter |
opencv_cudacodec.createVideoWriter(BytePointer fileName,
Size frameSize,
int codec,
double fps,
int colorFormat,
EncoderParams params) |
static VideoWriter |
opencv_cudacodec.createVideoWriter(BytePointer fileName,
Size frameSize,
int codec,
double fps,
int colorFormat,
EncoderParams params,
EncoderCallback encoderCallback,
Stream stream)
\brief Creates video writer.
|
static VideoWriter |
opencv_cudacodec.createVideoWriter(String fileName,
Size frameSize) |
static VideoWriter |
opencv_cudacodec.createVideoWriter(String fileName,
Size frameSize,
int codec,
double fps,
int colorFormat,
EncoderCallback encoderCallback,
Stream stream) |
static VideoWriter |
opencv_cudacodec.createVideoWriter(String fileName,
Size frameSize,
int codec,
double fps,
int colorFormat,
EncoderParams params) |
static VideoWriter |
opencv_cudacodec.createVideoWriter(String fileName,
Size frameSize,
int codec,
double fps,
int colorFormat,
EncoderParams params,
EncoderCallback encoderCallback,
Stream stream) |
static Formatted |
opencv_core.format(GpuMat mtx,
int fmt) |
static Formatted |
opencv_core.format(Mat mtx,
int fmt) |
static Formatted |
opencv_core.format(UMat mtx,
int fmt) |
opencv_imgcodecs.ImageCollection.Impl |
opencv_imgcodecs.ImageCollection.getImpl() |
static ERFilter.Callback |
opencv_text.loadClassifierNM1(BytePointer filename)
\brief Allow to implicitly load the default classifier when creating an ERFilter object.
|
static ERFilter.Callback |
opencv_text.loadClassifierNM1(String filename) |
static ERFilter.Callback |
opencv_text.loadClassifierNM2(BytePointer filename)
\brief Allow to implicitly load the default classifier when creating an ERFilter object.
|
static ERFilter.Callback |
opencv_text.loadClassifierNM2(String filename) |
static OCRBeamSearchDecoder.ClassifierCallback |
opencv_text.loadOCRBeamSearchClassifierCNN(BytePointer filename)
\brief Allow to implicitly load the default character classifier when creating an OCRBeamSearchDecoder object.
|
static OCRBeamSearchDecoder.ClassifierCallback |
opencv_text.loadOCRBeamSearchClassifierCNN(String filename) |
static OCRHMMDecoder.ClassifierCallback |
opencv_text.loadOCRHMMClassifier(BytePointer filename,
int classifier)
\brief Allow to implicitly load the default character classifier when creating an OCRHMMDecoder object.
|
static OCRHMMDecoder.ClassifierCallback |
opencv_text.loadOCRHMMClassifier(String filename,
int classifier) |
static OCRHMMDecoder.ClassifierCallback |
opencv_text.loadOCRHMMClassifierCNN(BytePointer filename)
Deprecated.
use loadOCRHMMClassifier instead
|
static OCRHMMDecoder.ClassifierCallback |
opencv_text.loadOCRHMMClassifierCNN(String filename) |
static OCRHMMDecoder.ClassifierCallback |
opencv_text.loadOCRHMMClassifierNM(BytePointer filename)
Deprecated.
loadOCRHMMClassifier instead
|
static OCRHMMDecoder.ClassifierCallback |
opencv_text.loadOCRHMMClassifierNM(String filename) |
| Modifier and Type | Method and Description |
|---|---|
static double |
opencv_aruco.calibrateCameraAruco(GpuMatVector corners,
GpuMat ids,
GpuMat counter,
Board board,
Size imageSize,
GpuMat cameraMatrix,
GpuMat distCoeffs) |
static double |
opencv_aruco.calibrateCameraAruco(GpuMatVector corners,
GpuMat ids,
GpuMat counter,
Board board,
Size imageSize,
GpuMat cameraMatrix,
GpuMat distCoeffs,
GpuMatVector rvecs,
GpuMatVector tvecs,
int flags,
TermCriteria criteria) |
static double |
opencv_aruco.calibrateCameraAruco(GpuMatVector corners,
Mat ids,
Mat counter,
Board board,
Size imageSize,
Mat cameraMatrix,
Mat distCoeffs) |
static double |
opencv_aruco.calibrateCameraAruco(GpuMatVector corners,
Mat ids,
Mat counter,
Board board,
Size imageSize,
Mat cameraMatrix,
Mat distCoeffs,
GpuMatVector rvecs,
GpuMatVector tvecs,
int flags,
TermCriteria criteria) |
static double |
opencv_aruco.calibrateCameraAruco(GpuMatVector corners,
UMat ids,
UMat counter,
Board board,
Size imageSize,
UMat cameraMatrix,
UMat distCoeffs) |
static double |
opencv_aruco.calibrateCameraAruco(GpuMatVector corners,
UMat ids,
UMat counter,
Board board,
Size imageSize,
UMat cameraMatrix,
UMat distCoeffs,
GpuMatVector rvecs,
GpuMatVector tvecs,
int flags,
TermCriteria criteria) |
static double |
opencv_aruco.calibrateCameraAruco(MatVector corners,
GpuMat ids,
GpuMat counter,
Board board,
Size imageSize,
GpuMat cameraMatrix,
GpuMat distCoeffs) |
static double |
opencv_aruco.calibrateCameraAruco(MatVector corners,
GpuMat ids,
GpuMat counter,
Board board,
Size imageSize,
GpuMat cameraMatrix,
GpuMat distCoeffs,
MatVector rvecs,
MatVector tvecs,
int flags,
TermCriteria criteria) |
static double |
opencv_aruco.calibrateCameraAruco(MatVector corners,
Mat ids,
Mat counter,
Board board,
Size imageSize,
Mat cameraMatrix,
Mat distCoeffs) |
static double |
opencv_aruco.calibrateCameraAruco(MatVector corners,
Mat ids,
Mat counter,
Board board,
Size imageSize,
Mat cameraMatrix,
Mat distCoeffs,
MatVector rvecs,
MatVector tvecs,
int flags,
TermCriteria criteria)
Deprecated.
Use Board::matchImagePoints and cv::solvePnP
|
static double |
opencv_aruco.calibrateCameraAruco(MatVector corners,
UMat ids,
UMat counter,
Board board,
Size imageSize,
UMat cameraMatrix,
UMat distCoeffs) |
static double |
opencv_aruco.calibrateCameraAruco(MatVector corners,
UMat ids,
UMat counter,
Board board,
Size imageSize,
UMat cameraMatrix,
UMat distCoeffs,
MatVector rvecs,
MatVector tvecs,
int flags,
TermCriteria criteria) |
static double |
opencv_aruco.calibrateCameraAruco(UMatVector corners,
GpuMat ids,
GpuMat counter,
Board board,
Size imageSize,
GpuMat cameraMatrix,
GpuMat distCoeffs) |
static double |
opencv_aruco.calibrateCameraAruco(UMatVector corners,
GpuMat ids,
GpuMat counter,
Board board,
Size imageSize,
GpuMat cameraMatrix,
GpuMat distCoeffs,
UMatVector rvecs,
UMatVector tvecs,
int flags,
TermCriteria criteria) |
static double |
opencv_aruco.calibrateCameraAruco(UMatVector corners,
Mat ids,
Mat counter,
Board board,
Size imageSize,
Mat cameraMatrix,
Mat distCoeffs) |
static double |
opencv_aruco.calibrateCameraAruco(UMatVector corners,
Mat ids,
Mat counter,
Board board,
Size imageSize,
Mat cameraMatrix,
Mat distCoeffs,
UMatVector rvecs,
UMatVector tvecs,
int flags,
TermCriteria criteria) |
static double |
opencv_aruco.calibrateCameraAruco(UMatVector corners,
UMat ids,
UMat counter,
Board board,
Size imageSize,
UMat cameraMatrix,
UMat distCoeffs) |
static double |
opencv_aruco.calibrateCameraAruco(UMatVector corners,
UMat ids,
UMat counter,
Board board,
Size imageSize,
UMat cameraMatrix,
UMat distCoeffs,
UMatVector rvecs,
UMatVector tvecs,
int flags,
TermCriteria criteria) |
static double |
opencv_aruco.calibrateCameraArucoExtended(GpuMatVector corners,
GpuMat ids,
GpuMat counter,
Board board,
Size imageSize,
GpuMat cameraMatrix,
GpuMat distCoeffs,
GpuMatVector rvecs,
GpuMatVector tvecs,
GpuMat stdDeviationsIntrinsics,
GpuMat stdDeviationsExtrinsics,
GpuMat perViewErrors) |
static double |
opencv_aruco.calibrateCameraArucoExtended(GpuMatVector corners,
GpuMat ids,
GpuMat counter,
Board board,
Size imageSize,
GpuMat cameraMatrix,
GpuMat distCoeffs,
GpuMatVector rvecs,
GpuMatVector tvecs,
GpuMat stdDeviationsIntrinsics,
GpuMat stdDeviationsExtrinsics,
GpuMat perViewErrors,
int flags,
TermCriteria criteria) |
static double |
opencv_aruco.calibrateCameraArucoExtended(GpuMatVector corners,
Mat ids,
Mat counter,
Board board,
Size imageSize,
Mat cameraMatrix,
Mat distCoeffs,
GpuMatVector rvecs,
GpuMatVector tvecs,
Mat stdDeviationsIntrinsics,
Mat stdDeviationsExtrinsics,
Mat perViewErrors) |
static double |
opencv_aruco.calibrateCameraArucoExtended(GpuMatVector corners,
Mat ids,
Mat counter,
Board board,
Size imageSize,
Mat cameraMatrix,
Mat distCoeffs,
GpuMatVector rvecs,
GpuMatVector tvecs,
Mat stdDeviationsIntrinsics,
Mat stdDeviationsExtrinsics,
Mat perViewErrors,
int flags,
TermCriteria criteria) |
static double |
opencv_aruco.calibrateCameraArucoExtended(GpuMatVector corners,
UMat ids,
UMat counter,
Board board,
Size imageSize,
UMat cameraMatrix,
UMat distCoeffs,
GpuMatVector rvecs,
GpuMatVector tvecs,
UMat stdDeviationsIntrinsics,
UMat stdDeviationsExtrinsics,
UMat perViewErrors) |
static double |
opencv_aruco.calibrateCameraArucoExtended(GpuMatVector corners,
UMat ids,
UMat counter,
Board board,
Size imageSize,
UMat cameraMatrix,
UMat distCoeffs,
GpuMatVector rvecs,
GpuMatVector tvecs,
UMat stdDeviationsIntrinsics,
UMat stdDeviationsExtrinsics,
UMat perViewErrors,
int flags,
TermCriteria criteria) |
static double |
opencv_aruco.calibrateCameraArucoExtended(MatVector corners,
GpuMat ids,
GpuMat counter,
Board board,
Size imageSize,
GpuMat cameraMatrix,
GpuMat distCoeffs,
MatVector rvecs,
MatVector tvecs,
GpuMat stdDeviationsIntrinsics,
GpuMat stdDeviationsExtrinsics,
GpuMat perViewErrors) |
static double |
opencv_aruco.calibrateCameraArucoExtended(MatVector corners,
GpuMat ids,
GpuMat counter,
Board board,
Size imageSize,
GpuMat cameraMatrix,
GpuMat distCoeffs,
MatVector rvecs,
MatVector tvecs,
GpuMat stdDeviationsIntrinsics,
GpuMat stdDeviationsExtrinsics,
GpuMat perViewErrors,
int flags,
TermCriteria criteria) |
static double |
opencv_aruco.calibrateCameraArucoExtended(MatVector corners,
Mat ids,
Mat counter,
Board board,
Size imageSize,
Mat cameraMatrix,
Mat distCoeffs,
MatVector rvecs,
MatVector tvecs,
Mat stdDeviationsIntrinsics,
Mat stdDeviationsExtrinsics,
Mat perViewErrors) |
static double |
opencv_aruco.calibrateCameraArucoExtended(MatVector corners,
Mat ids,
Mat counter,
Board board,
Size imageSize,
Mat cameraMatrix,
Mat distCoeffs,
MatVector rvecs,
MatVector tvecs,
Mat stdDeviationsIntrinsics,
Mat stdDeviationsExtrinsics,
Mat perViewErrors,
int flags,
TermCriteria criteria)
Deprecated.
Use Board::matchImagePoints and cv::solvePnP
|
static double |
opencv_aruco.calibrateCameraArucoExtended(MatVector corners,
UMat ids,
UMat counter,
Board board,
Size imageSize,
UMat cameraMatrix,
UMat distCoeffs,
MatVector rvecs,
MatVector tvecs,
UMat stdDeviationsIntrinsics,
UMat stdDeviationsExtrinsics,
UMat perViewErrors) |
static double |
opencv_aruco.calibrateCameraArucoExtended(MatVector corners,
UMat ids,
UMat counter,
Board board,
Size imageSize,
UMat cameraMatrix,
UMat distCoeffs,
MatVector rvecs,
MatVector tvecs,
UMat stdDeviationsIntrinsics,
UMat stdDeviationsExtrinsics,
UMat perViewErrors,
int flags,
TermCriteria criteria) |
static double |
opencv_aruco.calibrateCameraArucoExtended(UMatVector corners,
GpuMat ids,
GpuMat counter,
Board board,
Size imageSize,
GpuMat cameraMatrix,
GpuMat distCoeffs,
UMatVector rvecs,
UMatVector tvecs,
GpuMat stdDeviationsIntrinsics,
GpuMat stdDeviationsExtrinsics,
GpuMat perViewErrors) |
static double |
opencv_aruco.calibrateCameraArucoExtended(UMatVector corners,
GpuMat ids,
GpuMat counter,
Board board,
Size imageSize,
GpuMat cameraMatrix,
GpuMat distCoeffs,
UMatVector rvecs,
UMatVector tvecs,
GpuMat stdDeviationsIntrinsics,
GpuMat stdDeviationsExtrinsics,
GpuMat perViewErrors,
int flags,
TermCriteria criteria) |
static double |
opencv_aruco.calibrateCameraArucoExtended(UMatVector corners,
Mat ids,
Mat counter,
Board board,
Size imageSize,
Mat cameraMatrix,
Mat distCoeffs,
UMatVector rvecs,
UMatVector tvecs,
Mat stdDeviationsIntrinsics,
Mat stdDeviationsExtrinsics,
Mat perViewErrors) |
static double |
opencv_aruco.calibrateCameraArucoExtended(UMatVector corners,
Mat ids,
Mat counter,
Board board,
Size imageSize,
Mat cameraMatrix,
Mat distCoeffs,
UMatVector rvecs,
UMatVector tvecs,
Mat stdDeviationsIntrinsics,
Mat stdDeviationsExtrinsics,
Mat perViewErrors,
int flags,
TermCriteria criteria) |
static double |
opencv_aruco.calibrateCameraArucoExtended(UMatVector corners,
UMat ids,
UMat counter,
Board board,
Size imageSize,
UMat cameraMatrix,
UMat distCoeffs,
UMatVector rvecs,
UMatVector tvecs,
UMat stdDeviationsIntrinsics,
UMat stdDeviationsExtrinsics,
UMat perViewErrors) |
static double |
opencv_aruco.calibrateCameraArucoExtended(UMatVector corners,
UMat ids,
UMat counter,
Board board,
Size imageSize,
UMat cameraMatrix,
UMat distCoeffs,
UMatVector rvecs,
UMatVector tvecs,
UMat stdDeviationsIntrinsics,
UMat stdDeviationsExtrinsics,
UMat perViewErrors,
int flags,
TermCriteria criteria) |
static double |
opencv_aruco.calibrateCameraCharuco(GpuMatVector charucoCorners,
GpuMatVector charucoIds,
CharucoBoard board,
Size imageSize,
GpuMat cameraMatrix,
GpuMat distCoeffs) |
static double |
opencv_aruco.calibrateCameraCharuco(GpuMatVector charucoCorners,
GpuMatVector charucoIds,
CharucoBoard board,
Size imageSize,
GpuMat cameraMatrix,
GpuMat distCoeffs,
GpuMatVector rvecs,
GpuMatVector tvecs,
int flags,
TermCriteria criteria) |
static double |
opencv_aruco.calibrateCameraCharuco(GpuMatVector charucoCorners,
GpuMatVector charucoIds,
CharucoBoard board,
Size imageSize,
Mat cameraMatrix,
Mat distCoeffs) |
static double |
opencv_aruco.calibrateCameraCharuco(GpuMatVector charucoCorners,
GpuMatVector charucoIds,
CharucoBoard board,
Size imageSize,
Mat cameraMatrix,
Mat distCoeffs,
GpuMatVector rvecs,
GpuMatVector tvecs,
int flags,
TermCriteria criteria) |
static double |
opencv_aruco.calibrateCameraCharuco(GpuMatVector charucoCorners,
GpuMatVector charucoIds,
CharucoBoard board,
Size imageSize,
UMat cameraMatrix,
UMat distCoeffs) |
static double |
opencv_aruco.calibrateCameraCharuco(GpuMatVector charucoCorners,
GpuMatVector charucoIds,
CharucoBoard board,
Size imageSize,
UMat cameraMatrix,
UMat distCoeffs,
GpuMatVector rvecs,
GpuMatVector tvecs,
int flags,
TermCriteria criteria) |
static double |
opencv_aruco.calibrateCameraCharuco(MatVector charucoCorners,
MatVector charucoIds,
CharucoBoard board,
Size imageSize,
GpuMat cameraMatrix,
GpuMat distCoeffs) |
static double |
opencv_aruco.calibrateCameraCharuco(MatVector charucoCorners,
MatVector charucoIds,
CharucoBoard board,
Size imageSize,
GpuMat cameraMatrix,
GpuMat distCoeffs,
MatVector rvecs,
MatVector tvecs,
int flags,
TermCriteria criteria) |
static double |
opencv_aruco.calibrateCameraCharuco(MatVector charucoCorners,
MatVector charucoIds,
CharucoBoard board,
Size imageSize,
Mat cameraMatrix,
Mat distCoeffs) |
static double |
opencv_aruco.calibrateCameraCharuco(MatVector charucoCorners,
MatVector charucoIds,
CharucoBoard board,
Size imageSize,
Mat cameraMatrix,
Mat distCoeffs,
MatVector rvecs,
MatVector tvecs,
int flags,
TermCriteria criteria)
Deprecated.
Use CharucoBoard::matchImagePoints and cv::solvePnP
|
static double |
opencv_aruco.calibrateCameraCharuco(MatVector charucoCorners,
MatVector charucoIds,
CharucoBoard board,
Size imageSize,
UMat cameraMatrix,
UMat distCoeffs) |
static double |
opencv_aruco.calibrateCameraCharuco(MatVector charucoCorners,
MatVector charucoIds,
CharucoBoard board,
Size imageSize,
UMat cameraMatrix,
UMat distCoeffs,
MatVector rvecs,
MatVector tvecs,
int flags,
TermCriteria criteria) |
static double |
opencv_aruco.calibrateCameraCharuco(UMatVector charucoCorners,
UMatVector charucoIds,
CharucoBoard board,
Size imageSize,
GpuMat cameraMatrix,
GpuMat distCoeffs) |
static double |
opencv_aruco.calibrateCameraCharuco(UMatVector charucoCorners,
UMatVector charucoIds,
CharucoBoard board,
Size imageSize,
GpuMat cameraMatrix,
GpuMat distCoeffs,
UMatVector rvecs,
UMatVector tvecs,
int flags,
TermCriteria criteria) |
static double |
opencv_aruco.calibrateCameraCharuco(UMatVector charucoCorners,
UMatVector charucoIds,
CharucoBoard board,
Size imageSize,
Mat cameraMatrix,
Mat distCoeffs) |
static double |
opencv_aruco.calibrateCameraCharuco(UMatVector charucoCorners,
UMatVector charucoIds,
CharucoBoard board,
Size imageSize,
Mat cameraMatrix,
Mat distCoeffs,
UMatVector rvecs,
UMatVector tvecs,
int flags,
TermCriteria criteria) |
static double |
opencv_aruco.calibrateCameraCharuco(UMatVector charucoCorners,
UMatVector charucoIds,
CharucoBoard board,
Size imageSize,
UMat cameraMatrix,
UMat distCoeffs) |
static double |
opencv_aruco.calibrateCameraCharuco(UMatVector charucoCorners,
UMatVector charucoIds,
CharucoBoard board,
Size imageSize,
UMat cameraMatrix,
UMat distCoeffs,
UMatVector rvecs,
UMatVector tvecs,
int flags,
TermCriteria criteria) |
static double |
opencv_aruco.calibrateCameraCharucoExtended(GpuMatVector charucoCorners,
GpuMatVector charucoIds,
CharucoBoard board,
Size imageSize,
GpuMat cameraMatrix,
GpuMat distCoeffs,
GpuMatVector rvecs,
GpuMatVector tvecs,
GpuMat stdDeviationsIntrinsics,
GpuMat stdDeviationsExtrinsics,
GpuMat perViewErrors) |
static double |
opencv_aruco.calibrateCameraCharucoExtended(GpuMatVector charucoCorners,
GpuMatVector charucoIds,
CharucoBoard board,
Size imageSize,
GpuMat cameraMatrix,
GpuMat distCoeffs,
GpuMatVector rvecs,
GpuMatVector tvecs,
GpuMat stdDeviationsIntrinsics,
GpuMat stdDeviationsExtrinsics,
GpuMat perViewErrors,
int flags,
TermCriteria criteria) |
static double |
opencv_aruco.calibrateCameraCharucoExtended(GpuMatVector charucoCorners,
GpuMatVector charucoIds,
CharucoBoard board,
Size imageSize,
Mat cameraMatrix,
Mat distCoeffs,
GpuMatVector rvecs,
GpuMatVector tvecs,
Mat stdDeviationsIntrinsics,
Mat stdDeviationsExtrinsics,
Mat perViewErrors) |
static double |
opencv_aruco.calibrateCameraCharucoExtended(GpuMatVector charucoCorners,
GpuMatVector charucoIds,
CharucoBoard board,
Size imageSize,
Mat cameraMatrix,
Mat distCoeffs,
GpuMatVector rvecs,
GpuMatVector tvecs,
Mat stdDeviationsIntrinsics,
Mat stdDeviationsExtrinsics,
Mat perViewErrors,
int flags,
TermCriteria criteria) |
static double |
opencv_aruco.calibrateCameraCharucoExtended(GpuMatVector charucoCorners,
GpuMatVector charucoIds,
CharucoBoard board,
Size imageSize,
UMat cameraMatrix,
UMat distCoeffs,
GpuMatVector rvecs,
GpuMatVector tvecs,
UMat stdDeviationsIntrinsics,
UMat stdDeviationsExtrinsics,
UMat perViewErrors) |
static double |
opencv_aruco.calibrateCameraCharucoExtended(GpuMatVector charucoCorners,
GpuMatVector charucoIds,
CharucoBoard board,
Size imageSize,
UMat cameraMatrix,
UMat distCoeffs,
GpuMatVector rvecs,
GpuMatVector tvecs,
UMat stdDeviationsIntrinsics,
UMat stdDeviationsExtrinsics,
UMat perViewErrors,
int flags,
TermCriteria criteria) |
static double |
opencv_aruco.calibrateCameraCharucoExtended(MatVector charucoCorners,
MatVector charucoIds,
CharucoBoard board,
Size imageSize,
GpuMat cameraMatrix,
GpuMat distCoeffs,
MatVector rvecs,
MatVector tvecs,
GpuMat stdDeviationsIntrinsics,
GpuMat stdDeviationsExtrinsics,
GpuMat perViewErrors) |
static double |
opencv_aruco.calibrateCameraCharucoExtended(MatVector charucoCorners,
MatVector charucoIds,
CharucoBoard board,
Size imageSize,
GpuMat cameraMatrix,
GpuMat distCoeffs,
MatVector rvecs,
MatVector tvecs,
GpuMat stdDeviationsIntrinsics,
GpuMat stdDeviationsExtrinsics,
GpuMat perViewErrors,
int flags,
TermCriteria criteria) |
static double |
opencv_aruco.calibrateCameraCharucoExtended(MatVector charucoCorners,
MatVector charucoIds,
CharucoBoard board,
Size imageSize,
Mat cameraMatrix,
Mat distCoeffs,
MatVector rvecs,
MatVector tvecs,
Mat stdDeviationsIntrinsics,
Mat stdDeviationsExtrinsics,
Mat perViewErrors) |
static double |
opencv_aruco.calibrateCameraCharucoExtended(MatVector charucoCorners,
MatVector charucoIds,
CharucoBoard board,
Size imageSize,
Mat cameraMatrix,
Mat distCoeffs,
MatVector rvecs,
MatVector tvecs,
Mat stdDeviationsIntrinsics,
Mat stdDeviationsExtrinsics,
Mat perViewErrors,
int flags,
TermCriteria criteria)
Deprecated.
Use CharucoBoard::matchImagePoints and cv::solvePnP
|
static double |
opencv_aruco.calibrateCameraCharucoExtended(MatVector charucoCorners,
MatVector charucoIds,
CharucoBoard board,
Size imageSize,
UMat cameraMatrix,
UMat distCoeffs,
MatVector rvecs,
MatVector tvecs,
UMat stdDeviationsIntrinsics,
UMat stdDeviationsExtrinsics,
UMat perViewErrors) |
static double |
opencv_aruco.calibrateCameraCharucoExtended(MatVector charucoCorners,
MatVector charucoIds,
CharucoBoard board,
Size imageSize,
UMat cameraMatrix,
UMat distCoeffs,
MatVector rvecs,
MatVector tvecs,
UMat stdDeviationsIntrinsics,
UMat stdDeviationsExtrinsics,
UMat perViewErrors,
int flags,
TermCriteria criteria) |
static double |
opencv_aruco.calibrateCameraCharucoExtended(UMatVector charucoCorners,
UMatVector charucoIds,
CharucoBoard board,
Size imageSize,
GpuMat cameraMatrix,
GpuMat distCoeffs,
UMatVector rvecs,
UMatVector tvecs,
GpuMat stdDeviationsIntrinsics,
GpuMat stdDeviationsExtrinsics,
GpuMat perViewErrors) |
static double |
opencv_aruco.calibrateCameraCharucoExtended(UMatVector charucoCorners,
UMatVector charucoIds,
CharucoBoard board,
Size imageSize,
GpuMat cameraMatrix,
GpuMat distCoeffs,
UMatVector rvecs,
UMatVector tvecs,
GpuMat stdDeviationsIntrinsics,
GpuMat stdDeviationsExtrinsics,
GpuMat perViewErrors,
int flags,
TermCriteria criteria) |
static double |
opencv_aruco.calibrateCameraCharucoExtended(UMatVector charucoCorners,
UMatVector charucoIds,
CharucoBoard board,
Size imageSize,
Mat cameraMatrix,
Mat distCoeffs,
UMatVector rvecs,
UMatVector tvecs,
Mat stdDeviationsIntrinsics,
Mat stdDeviationsExtrinsics,
Mat perViewErrors) |
static double |
opencv_aruco.calibrateCameraCharucoExtended(UMatVector charucoCorners,
UMatVector charucoIds,
CharucoBoard board,
Size imageSize,
Mat cameraMatrix,
Mat distCoeffs,
UMatVector rvecs,
UMatVector tvecs,
Mat stdDeviationsIntrinsics,
Mat stdDeviationsExtrinsics,
Mat perViewErrors,
int flags,
TermCriteria criteria) |
static double |
opencv_aruco.calibrateCameraCharucoExtended(UMatVector charucoCorners,
UMatVector charucoIds,
CharucoBoard board,
Size imageSize,
UMat cameraMatrix,
UMat distCoeffs,
UMatVector rvecs,
UMatVector tvecs,
UMat stdDeviationsIntrinsics,
UMat stdDeviationsExtrinsics,
UMat perViewErrors) |
static double |
opencv_aruco.calibrateCameraCharucoExtended(UMatVector charucoCorners,
UMatVector charucoIds,
CharucoBoard board,
Size imageSize,
UMat cameraMatrix,
UMat distCoeffs,
UMatVector rvecs,
UMatVector tvecs,
UMat stdDeviationsIntrinsics,
UMat stdDeviationsExtrinsics,
UMat perViewErrors,
int flags,
TermCriteria criteria) |
static void |
opencv_stitching.computeImageFeatures(Feature2D featuresFinder,
GpuMatVector images,
ImageFeaturesVector features) |
static void |
opencv_stitching.computeImageFeatures(Feature2D featuresFinder,
GpuMatVector images,
ImageFeaturesVector features,
GpuMatVector masks) |
static void |
opencv_stitching.computeImageFeatures(Feature2D featuresFinder,
MatVector images,
ImageFeaturesVector features) |
static void |
opencv_stitching.computeImageFeatures(Feature2D featuresFinder,
MatVector images,
ImageFeaturesVector features,
MatVector masks)
\brief
|
static void |
opencv_stitching.computeImageFeatures(Feature2D featuresFinder,
UMatVector images,
ImageFeaturesVector features) |
static void |
opencv_stitching.computeImageFeatures(Feature2D featuresFinder,
UMatVector images,
ImageFeaturesVector features,
UMatVector masks) |
static void |
opencv_stitching.computeImageFeatures2(Feature2D featuresFinder,
GpuMat image,
ImageFeatures features) |
static void |
opencv_stitching.computeImageFeatures2(Feature2D featuresFinder,
GpuMat image,
ImageFeatures features,
GpuMat mask) |
static void |
opencv_stitching.computeImageFeatures2(Feature2D featuresFinder,
Mat image,
ImageFeatures features) |
static void |
opencv_stitching.computeImageFeatures2(Feature2D featuresFinder,
Mat image,
ImageFeatures features,
Mat mask)
\brief
|
static void |
opencv_stitching.computeImageFeatures2(Feature2D featuresFinder,
UMat image,
ImageFeatures features) |
static void |
opencv_stitching.computeImageFeatures2(Feature2D featuresFinder,
UMat image,
ImageFeatures features,
UMat mask) |
static DisparityWLSFilter |
opencv_ximgproc.createDisparityWLSFilter(StereoMatcher matcher_left)
\brief Convenience factory method that creates an instance of DisparityWLSFilter and sets up all the relevant
filter parameters automatically based on the matcher instance.
|
static ERFilter |
opencv_text.createERFilterNM1(ERFilter.Callback cb) |
static ERFilter |
opencv_text.createERFilterNM1(ERFilter.Callback cb,
int thresholdDelta,
float minArea,
float maxArea,
float minProbability,
boolean nonMaxSuppression,
float minProbabilityDiff)
\brief Create an Extremal Region Filter for the 1st stage classifier of N&M algorithm \cite Neumann12.
|
static ERFilter |
opencv_text.createERFilterNM2(ERFilter.Callback cb) |
static ERFilter |
opencv_text.createERFilterNM2(ERFilter.Callback cb,
float minProbability)
\brief Create an Extremal Region Filter for the 2nd stage classifier of N&M algorithm \cite Neumann12.
|
static StereoMatcher |
opencv_ximgproc.createRightMatcher(StereoMatcher matcher_left)
\brief Convenience method to set up the matcher for computing the right-view disparity map
that is required in case of filtering with confidence.
|
static SelectiveSearchSegmentationStrategyMultiple |
opencv_ximgproc.createSelectiveSearchSegmentationStrategyMultiple(SelectiveSearchSegmentationStrategy s1)
\brief Create a new multiple strategy and set one subtrategy
|
static SelectiveSearchSegmentationStrategyMultiple |
opencv_ximgproc.createSelectiveSearchSegmentationStrategyMultiple(SelectiveSearchSegmentationStrategy s1,
SelectiveSearchSegmentationStrategy s2)
\brief Create a new multiple strategy and set two subtrategies, with equal weights
|
static SelectiveSearchSegmentationStrategyMultiple |
opencv_ximgproc.createSelectiveSearchSegmentationStrategyMultiple(SelectiveSearchSegmentationStrategy s1,
SelectiveSearchSegmentationStrategy s2)
\brief Create a new multiple strategy and set two subtrategies, with equal weights
|
static SelectiveSearchSegmentationStrategyMultiple |
opencv_ximgproc.createSelectiveSearchSegmentationStrategyMultiple(SelectiveSearchSegmentationStrategy s1,
SelectiveSearchSegmentationStrategy s2,
SelectiveSearchSegmentationStrategy s3)
\brief Create a new multiple strategy and set three subtrategies, with equal weights
|
static SelectiveSearchSegmentationStrategyMultiple |
opencv_ximgproc.createSelectiveSearchSegmentationStrategyMultiple(SelectiveSearchSegmentationStrategy s1,
SelectiveSearchSegmentationStrategy s2,
SelectiveSearchSegmentationStrategy s3)
\brief Create a new multiple strategy and set three subtrategies, with equal weights
|
static SelectiveSearchSegmentationStrategyMultiple |
opencv_ximgproc.createSelectiveSearchSegmentationStrategyMultiple(SelectiveSearchSegmentationStrategy s1,
SelectiveSearchSegmentationStrategy s2,
SelectiveSearchSegmentationStrategy s3)
\brief Create a new multiple strategy and set three subtrategies, with equal weights
|
static SelectiveSearchSegmentationStrategyMultiple |
opencv_ximgproc.createSelectiveSearchSegmentationStrategyMultiple(SelectiveSearchSegmentationStrategy s1,
SelectiveSearchSegmentationStrategy s2,
SelectiveSearchSegmentationStrategy s3,
SelectiveSearchSegmentationStrategy s4)
\brief Create a new multiple strategy and set four subtrategies, with equal weights
|
static SelectiveSearchSegmentationStrategyMultiple |
opencv_ximgproc.createSelectiveSearchSegmentationStrategyMultiple(SelectiveSearchSegmentationStrategy s1,
SelectiveSearchSegmentationStrategy s2,
SelectiveSearchSegmentationStrategy s3,
SelectiveSearchSegmentationStrategy s4)
\brief Create a new multiple strategy and set four subtrategies, with equal weights
|
static SelectiveSearchSegmentationStrategyMultiple |
opencv_ximgproc.createSelectiveSearchSegmentationStrategyMultiple(SelectiveSearchSegmentationStrategy s1,
SelectiveSearchSegmentationStrategy s2,
SelectiveSearchSegmentationStrategy s3,
SelectiveSearchSegmentationStrategy s4)
\brief Create a new multiple strategy and set four subtrategies, with equal weights
|
static SelectiveSearchSegmentationStrategyMultiple |
opencv_ximgproc.createSelectiveSearchSegmentationStrategyMultiple(SelectiveSearchSegmentationStrategy s1,
SelectiveSearchSegmentationStrategy s2,
SelectiveSearchSegmentationStrategy s3,
SelectiveSearchSegmentationStrategy s4)
\brief Create a new multiple strategy and set four subtrategies, with equal weights
|
static ShapeContextDistanceExtractor |
opencv_shape.createShapeContextDistanceExtractor(int nAngularBins,
int nRadialBins,
float innerRadius,
float outerRadius,
int iterations,
HistogramCostExtractor comparer,
ShapeTransformer transformer)
\}
|
static ShapeContextDistanceExtractor |
opencv_shape.createShapeContextDistanceExtractor(int nAngularBins,
int nRadialBins,
float innerRadius,
float outerRadius,
int iterations,
HistogramCostExtractor comparer,
ShapeTransformer transformer)
\}
|
static StructuredEdgeDetection |
opencv_ximgproc.createStructuredEdgeDetection(BytePointer model,
RFFeatureGetter howToGetFeatures)
The only constructor
|
static StructuredEdgeDetection |
opencv_ximgproc.createStructuredEdgeDetection(String model,
RFFeatureGetter howToGetFeatures) |
static VideoReader |
opencv_cudacodec.createVideoReader(RawVideoSource source) |
static VideoReader |
opencv_cudacodec.createVideoReader(RawVideoSource source,
VideoReaderInitParams params)
\overload
|
static VideoWriter |
opencv_cudacodec.createVideoWriter(BytePointer fileName,
Size frameSize,
int codec,
double fps,
int colorFormat,
EncoderCallback encoderCallback,
Stream stream)
\brief Creates video writer.
|
static VideoWriter |
opencv_cudacodec.createVideoWriter(BytePointer fileName,
Size frameSize,
int codec,
double fps,
int colorFormat,
EncoderParams params,
EncoderCallback encoderCallback,
Stream stream)
\brief Creates video writer.
|
static VideoWriter |
opencv_cudacodec.createVideoWriter(String fileName,
Size frameSize,
int codec,
double fps,
int colorFormat,
EncoderCallback encoderCallback,
Stream stream) |
static VideoWriter |
opencv_cudacodec.createVideoWriter(String fileName,
Size frameSize,
int codec,
double fps,
int colorFormat,
EncoderParams params,
EncoderCallback encoderCallback,
Stream stream) |
static void |
opencv_aruco.detectCharucoDiamond(GpuMat image,
GpuMatVector markerCorners,
GpuMat markerIds,
float squareMarkerLengthRate,
GpuMatVector diamondCorners,
GpuMat diamondIds,
GpuMat cameraMatrix,
GpuMat distCoeffs,
Dictionary dictionary) |
static void |
opencv_aruco.detectCharucoDiamond(GpuMat image,
MatVector markerCorners,
GpuMat markerIds,
float squareMarkerLengthRate,
MatVector diamondCorners,
GpuMat diamondIds,
GpuMat cameraMatrix,
GpuMat distCoeffs,
Dictionary dictionary) |
static void |
opencv_aruco.detectCharucoDiamond(GpuMat image,
UMatVector markerCorners,
GpuMat markerIds,
float squareMarkerLengthRate,
UMatVector diamondCorners,
GpuMat diamondIds,
GpuMat cameraMatrix,
GpuMat distCoeffs,
Dictionary dictionary) |
static void |
opencv_aruco.detectCharucoDiamond(Mat image,
GpuMatVector markerCorners,
Mat markerIds,
float squareMarkerLengthRate,
GpuMatVector diamondCorners,
Mat diamondIds,
Mat cameraMatrix,
Mat distCoeffs,
Dictionary dictionary) |
static void |
opencv_aruco.detectCharucoDiamond(Mat image,
MatVector markerCorners,
Mat markerIds,
float squareMarkerLengthRate,
MatVector diamondCorners,
Mat diamondIds,
Mat cameraMatrix,
Mat distCoeffs,
Dictionary dictionary)
Deprecated.
Use CharucoDetector::detectDiamonds
|
static void |
opencv_aruco.detectCharucoDiamond(Mat image,
UMatVector markerCorners,
Mat markerIds,
float squareMarkerLengthRate,
UMatVector diamondCorners,
Mat diamondIds,
Mat cameraMatrix,
Mat distCoeffs,
Dictionary dictionary) |
static void |
opencv_aruco.detectCharucoDiamond(UMat image,
GpuMatVector markerCorners,
UMat markerIds,
float squareMarkerLengthRate,
GpuMatVector diamondCorners,
UMat diamondIds,
UMat cameraMatrix,
UMat distCoeffs,
Dictionary dictionary) |
static void |
opencv_aruco.detectCharucoDiamond(UMat image,
MatVector markerCorners,
UMat markerIds,
float squareMarkerLengthRate,
MatVector diamondCorners,
UMat diamondIds,
UMat cameraMatrix,
UMat distCoeffs,
Dictionary dictionary) |
static void |
opencv_aruco.detectCharucoDiamond(UMat image,
UMatVector markerCorners,
UMat markerIds,
float squareMarkerLengthRate,
UMatVector diamondCorners,
UMat diamondIds,
UMat cameraMatrix,
UMat distCoeffs,
Dictionary dictionary) |
static void |
opencv_aruco.detectMarkers(GpuMat image,
Dictionary dictionary,
GpuMatVector corners,
GpuMat ids) |
static void |
opencv_aruco.detectMarkers(GpuMat image,
Dictionary dictionary,
GpuMatVector corners,
GpuMat ids,
DetectorParameters parameters,
GpuMatVector rejectedImgPoints) |
static void |
opencv_aruco.detectMarkers(GpuMat image,
Dictionary dictionary,
GpuMatVector corners,
GpuMat ids,
DetectorParameters parameters,
GpuMatVector rejectedImgPoints) |
static void |
opencv_aruco.detectMarkers(GpuMat image,
Dictionary dictionary,
MatVector corners,
GpuMat ids) |
static void |
opencv_aruco.detectMarkers(GpuMat image,
Dictionary dictionary,
MatVector corners,
GpuMat ids,
DetectorParameters parameters,
MatVector rejectedImgPoints) |
static void |
opencv_aruco.detectMarkers(GpuMat image,
Dictionary dictionary,
MatVector corners,
GpuMat ids,
DetectorParameters parameters,
MatVector rejectedImgPoints) |
static void |
opencv_aruco.detectMarkers(GpuMat image,
Dictionary dictionary,
UMatVector corners,
GpuMat ids) |
static void |
opencv_aruco.detectMarkers(GpuMat image,
Dictionary dictionary,
UMatVector corners,
GpuMat ids,
DetectorParameters parameters,
UMatVector rejectedImgPoints) |
static void |
opencv_aruco.detectMarkers(GpuMat image,
Dictionary dictionary,
UMatVector corners,
GpuMat ids,
DetectorParameters parameters,
UMatVector rejectedImgPoints) |
static void |
opencv_aruco.detectMarkers(Mat image,
Dictionary dictionary,
GpuMatVector corners,
Mat ids) |
static void |
opencv_aruco.detectMarkers(Mat image,
Dictionary dictionary,
GpuMatVector corners,
Mat ids,
DetectorParameters parameters,
GpuMatVector rejectedImgPoints) |
static void |
opencv_aruco.detectMarkers(Mat image,
Dictionary dictionary,
GpuMatVector corners,
Mat ids,
DetectorParameters parameters,
GpuMatVector rejectedImgPoints) |
static void |
opencv_aruco.detectMarkers(Mat image,
Dictionary dictionary,
MatVector corners,
Mat ids) |
static void |
opencv_aruco.detectMarkers(Mat image,
Dictionary dictionary,
MatVector corners,
Mat ids,
DetectorParameters parameters,
MatVector rejectedImgPoints)
Deprecated.
Use class ArucoDetector::detectMarkers
|
static void |
opencv_aruco.detectMarkers(Mat image,
Dictionary dictionary,
MatVector corners,
Mat ids,
DetectorParameters parameters,
MatVector rejectedImgPoints)
Deprecated.
Use class ArucoDetector::detectMarkers
|
static void |
opencv_aruco.detectMarkers(Mat image,
Dictionary dictionary,
UMatVector corners,
Mat ids) |
static void |
opencv_aruco.detectMarkers(Mat image,
Dictionary dictionary,
UMatVector corners,
Mat ids,
DetectorParameters parameters,
UMatVector rejectedImgPoints) |
static void |
opencv_aruco.detectMarkers(Mat image,
Dictionary dictionary,
UMatVector corners,
Mat ids,
DetectorParameters parameters,
UMatVector rejectedImgPoints) |
static void |
opencv_aruco.detectMarkers(UMat image,
Dictionary dictionary,
GpuMatVector corners,
UMat ids) |
static void |
opencv_aruco.detectMarkers(UMat image,
Dictionary dictionary,
GpuMatVector corners,
UMat ids,
DetectorParameters parameters,
GpuMatVector rejectedImgPoints) |
static void |
opencv_aruco.detectMarkers(UMat image,
Dictionary dictionary,
GpuMatVector corners,
UMat ids,
DetectorParameters parameters,
GpuMatVector rejectedImgPoints) |
static void |
opencv_aruco.detectMarkers(UMat image,
Dictionary dictionary,
MatVector corners,
UMat ids) |
static void |
opencv_aruco.detectMarkers(UMat image,
Dictionary dictionary,
MatVector corners,
UMat ids,
DetectorParameters parameters,
MatVector rejectedImgPoints) |
static void |
opencv_aruco.detectMarkers(UMat image,
Dictionary dictionary,
MatVector corners,
UMat ids,
DetectorParameters parameters,
MatVector rejectedImgPoints) |
static void |
opencv_aruco.detectMarkers(UMat image,
Dictionary dictionary,
UMatVector corners,
UMat ids) |
static void |
opencv_aruco.detectMarkers(UMat image,
Dictionary dictionary,
UMatVector corners,
UMat ids,
DetectorParameters parameters,
UMatVector rejectedImgPoints) |
static void |
opencv_aruco.detectMarkers(UMat image,
Dictionary dictionary,
UMatVector corners,
UMat ids,
DetectorParameters parameters,
UMatVector rejectedImgPoints) |
static void |
opencv_text.detectRegions(GpuMat image,
ERFilter er_filter1,
ERFilter er_filter2,
PointVectorVector regions) |
static void |
opencv_text.detectRegions(GpuMat image,
ERFilter er_filter1,
ERFilter er_filter2,
PointVectorVector regions) |
static void |
opencv_text.detectRegions(GpuMat image,
ERFilter er_filter1,
ERFilter er_filter2,
RectVector groups_rects) |
static void |
opencv_text.detectRegions(GpuMat image,
ERFilter er_filter1,
ERFilter er_filter2,
RectVector groups_rects) |
static void |
opencv_text.detectRegions(GpuMat image,
ERFilter er_filter1,
ERFilter er_filter2,
RectVector groups_rects,
int method,
BytePointer filename,
float minProbability) |
static void |
opencv_text.detectRegions(GpuMat image,
ERFilter er_filter1,
ERFilter er_filter2,
RectVector groups_rects,
int method,
BytePointer filename,
float minProbability) |
static void |
opencv_text.detectRegions(GpuMat image,
ERFilter er_filter1,
ERFilter er_filter2,
RectVector groups_rects,
int method,
String filename,
float minProbability) |
static void |
opencv_text.detectRegions(GpuMat image,
ERFilter er_filter1,
ERFilter er_filter2,
RectVector groups_rects,
int method,
String filename,
float minProbability) |
static void |
opencv_text.detectRegions(Mat image,
ERFilter er_filter1,
ERFilter er_filter2,
PointVectorVector regions) |
static void |
opencv_text.detectRegions(Mat image,
ERFilter er_filter1,
ERFilter er_filter2,
PointVectorVector regions) |
static void |
opencv_text.detectRegions(Mat image,
ERFilter er_filter1,
ERFilter er_filter2,
RectVector groups_rects) |
static void |
opencv_text.detectRegions(Mat image,
ERFilter er_filter1,
ERFilter er_filter2,
RectVector groups_rects) |
static void |
opencv_text.detectRegions(Mat image,
ERFilter er_filter1,
ERFilter er_filter2,
RectVector groups_rects,
int method,
BytePointer filename,
float minProbability)
\brief Extracts text regions from image.
|
static void |
opencv_text.detectRegions(Mat image,
ERFilter er_filter1,
ERFilter er_filter2,
RectVector groups_rects,
int method,
BytePointer filename,
float minProbability)
\brief Extracts text regions from image.
|
static void |
opencv_text.detectRegions(Mat image,
ERFilter er_filter1,
ERFilter er_filter2,
RectVector groups_rects,
int method,
String filename,
float minProbability) |
static void |
opencv_text.detectRegions(Mat image,
ERFilter er_filter1,
ERFilter er_filter2,
RectVector groups_rects,
int method,
String filename,
float minProbability) |
static void |
opencv_text.detectRegions(UMat image,
ERFilter er_filter1,
ERFilter er_filter2,
PointVectorVector regions) |
static void |
opencv_text.detectRegions(UMat image,
ERFilter er_filter1,
ERFilter er_filter2,
PointVectorVector regions) |
static void |
opencv_text.detectRegions(UMat image,
ERFilter er_filter1,
ERFilter er_filter2,
RectVector groups_rects) |
static void |
opencv_text.detectRegions(UMat image,
ERFilter er_filter1,
ERFilter er_filter2,
RectVector groups_rects) |
static void |
opencv_text.detectRegions(UMat image,
ERFilter er_filter1,
ERFilter er_filter2,
RectVector groups_rects,
int method,
BytePointer filename,
float minProbability) |
static void |
opencv_text.detectRegions(UMat image,
ERFilter er_filter1,
ERFilter er_filter2,
RectVector groups_rects,
int method,
BytePointer filename,
float minProbability) |
static void |
opencv_text.detectRegions(UMat image,
ERFilter er_filter1,
ERFilter er_filter2,
RectVector groups_rects,
int method,
String filename,
float minProbability) |
static void |
opencv_text.detectRegions(UMat image,
ERFilter er_filter1,
ERFilter er_filter2,
RectVector groups_rects,
int method,
String filename,
float minProbability) |
static void |
opencv_aruco.drawCharucoDiamond(Dictionary dictionary,
Scalar4i ids,
int squareLength,
int markerLength,
GpuMat img) |
static void |
opencv_aruco.drawCharucoDiamond(Dictionary dictionary,
Scalar4i ids,
int squareLength,
int markerLength,
GpuMat img,
int marginSize,
int borderBits) |
static void |
opencv_aruco.drawCharucoDiamond(Dictionary dictionary,
Scalar4i ids,
int squareLength,
int markerLength,
Mat img) |
static void |
opencv_aruco.drawCharucoDiamond(Dictionary dictionary,
Scalar4i ids,
int squareLength,
int markerLength,
Mat img,
int marginSize,
int borderBits)
Deprecated.
Use CharucoBoard::generateImage()
|
static void |
opencv_aruco.drawCharucoDiamond(Dictionary dictionary,
Scalar4i ids,
int squareLength,
int markerLength,
UMat img) |
static void |
opencv_aruco.drawCharucoDiamond(Dictionary dictionary,
Scalar4i ids,
int squareLength,
int markerLength,
UMat img,
int marginSize,
int borderBits) |
static void |
opencv_aruco.drawPlanarBoard(Board board,
Size outSize,
GpuMat img,
int marginSize,
int borderBits) |
static void |
opencv_aruco.drawPlanarBoard(Board board,
Size outSize,
Mat img,
int marginSize,
int borderBits)
Deprecated.
Use Board::generateImage
|
static void |
opencv_aruco.drawPlanarBoard(Board board,
Size outSize,
UMat img,
int marginSize,
int borderBits) |
static int |
opencv_aruco.estimatePoseBoard(GpuMatVector corners,
GpuMat ids,
Board board,
GpuMat cameraMatrix,
GpuMat distCoeffs,
GpuMat rvec,
GpuMat tvec) |
static int |
opencv_aruco.estimatePoseBoard(GpuMatVector corners,
GpuMat ids,
Board board,
GpuMat cameraMatrix,
GpuMat distCoeffs,
GpuMat rvec,
GpuMat tvec,
boolean useExtrinsicGuess) |
static int |
opencv_aruco.estimatePoseBoard(GpuMatVector corners,
Mat ids,
Board board,
Mat cameraMatrix,
Mat distCoeffs,
Mat rvec,
Mat tvec) |
static int |
opencv_aruco.estimatePoseBoard(GpuMatVector corners,
Mat ids,
Board board,
Mat cameraMatrix,
Mat distCoeffs,
Mat rvec,
Mat tvec,
boolean useExtrinsicGuess) |
static int |
opencv_aruco.estimatePoseBoard(GpuMatVector corners,
UMat ids,
Board board,
UMat cameraMatrix,
UMat distCoeffs,
UMat rvec,
UMat tvec) |
static int |
opencv_aruco.estimatePoseBoard(GpuMatVector corners,
UMat ids,
Board board,
UMat cameraMatrix,
UMat distCoeffs,
UMat rvec,
UMat tvec,
boolean useExtrinsicGuess) |
static int |
opencv_aruco.estimatePoseBoard(MatVector corners,
GpuMat ids,
Board board,
GpuMat cameraMatrix,
GpuMat distCoeffs,
GpuMat rvec,
GpuMat tvec) |
static int |
opencv_aruco.estimatePoseBoard(MatVector corners,
GpuMat ids,
Board board,
GpuMat cameraMatrix,
GpuMat distCoeffs,
GpuMat rvec,
GpuMat tvec,
boolean useExtrinsicGuess) |
static int |
opencv_aruco.estimatePoseBoard(MatVector corners,
Mat ids,
Board board,
Mat cameraMatrix,
Mat distCoeffs,
Mat rvec,
Mat tvec) |
static int |
opencv_aruco.estimatePoseBoard(MatVector corners,
Mat ids,
Board board,
Mat cameraMatrix,
Mat distCoeffs,
Mat rvec,
Mat tvec,
boolean useExtrinsicGuess)
Deprecated.
Use Board::matchImagePoints and cv::solvePnP
|
static int |
opencv_aruco.estimatePoseBoard(MatVector corners,
UMat ids,
Board board,
UMat cameraMatrix,
UMat distCoeffs,
UMat rvec,
UMat tvec) |
static int |
opencv_aruco.estimatePoseBoard(MatVector corners,
UMat ids,
Board board,
UMat cameraMatrix,
UMat distCoeffs,
UMat rvec,
UMat tvec,
boolean useExtrinsicGuess) |
static int |
opencv_aruco.estimatePoseBoard(UMatVector corners,
GpuMat ids,
Board board,
GpuMat cameraMatrix,
GpuMat distCoeffs,
GpuMat rvec,
GpuMat tvec) |
static int |
opencv_aruco.estimatePoseBoard(UMatVector corners,
GpuMat ids,
Board board,
GpuMat cameraMatrix,
GpuMat distCoeffs,
GpuMat rvec,
GpuMat tvec,
boolean useExtrinsicGuess) |
static int |
opencv_aruco.estimatePoseBoard(UMatVector corners,
Mat ids,
Board board,
Mat cameraMatrix,
Mat distCoeffs,
Mat rvec,
Mat tvec) |
static int |
opencv_aruco.estimatePoseBoard(UMatVector corners,
Mat ids,
Board board,
Mat cameraMatrix,
Mat distCoeffs,
Mat rvec,
Mat tvec,
boolean useExtrinsicGuess) |
static int |
opencv_aruco.estimatePoseBoard(UMatVector corners,
UMat ids,
Board board,
UMat cameraMatrix,
UMat distCoeffs,
UMat rvec,
UMat tvec) |
static int |
opencv_aruco.estimatePoseBoard(UMatVector corners,
UMat ids,
Board board,
UMat cameraMatrix,
UMat distCoeffs,
UMat rvec,
UMat tvec,
boolean useExtrinsicGuess) |
static boolean |
opencv_aruco.estimatePoseCharucoBoard(GpuMat charucoCorners,
GpuMat charucoIds,
CharucoBoard board,
GpuMat cameraMatrix,
GpuMat distCoeffs,
GpuMat rvec,
GpuMat tvec) |
static boolean |
opencv_aruco.estimatePoseCharucoBoard(GpuMat charucoCorners,
GpuMat charucoIds,
CharucoBoard board,
GpuMat cameraMatrix,
GpuMat distCoeffs,
GpuMat rvec,
GpuMat tvec,
boolean useExtrinsicGuess) |
static boolean |
opencv_aruco.estimatePoseCharucoBoard(Mat charucoCorners,
Mat charucoIds,
CharucoBoard board,
Mat cameraMatrix,
Mat distCoeffs,
Mat rvec,
Mat tvec) |
static boolean |
opencv_aruco.estimatePoseCharucoBoard(Mat charucoCorners,
Mat charucoIds,
CharucoBoard board,
Mat cameraMatrix,
Mat distCoeffs,
Mat rvec,
Mat tvec,
boolean useExtrinsicGuess)
Deprecated.
Use CharucoBoard::matchImagePoints and cv::solvePnP
|
static boolean |
opencv_aruco.estimatePoseCharucoBoard(UMat charucoCorners,
UMat charucoIds,
CharucoBoard board,
UMat cameraMatrix,
UMat distCoeffs,
UMat rvec,
UMat tvec) |
static boolean |
opencv_aruco.estimatePoseCharucoBoard(UMat charucoCorners,
UMat charucoIds,
CharucoBoard board,
UMat cameraMatrix,
UMat distCoeffs,
UMat rvec,
UMat tvec,
boolean useExtrinsicGuess) |
static void |
opencv_aruco.estimatePoseSingleMarkers(GpuMatVector corners,
float markerLength,
GpuMat cameraMatrix,
GpuMat distCoeffs,
GpuMat rvecs,
GpuMat tvecs,
GpuMat objPoints,
EstimateParameters estimateParameters) |
static void |
opencv_aruco.estimatePoseSingleMarkers(GpuMatVector corners,
float markerLength,
Mat cameraMatrix,
Mat distCoeffs,
Mat rvecs,
Mat tvecs,
Mat objPoints,
EstimateParameters estimateParameters) |
static void |
opencv_aruco.estimatePoseSingleMarkers(GpuMatVector corners,
float markerLength,
UMat cameraMatrix,
UMat distCoeffs,
UMat rvecs,
UMat tvecs,
UMat objPoints,
EstimateParameters estimateParameters) |
static void |
opencv_aruco.estimatePoseSingleMarkers(MatVector corners,
float markerLength,
GpuMat cameraMatrix,
GpuMat distCoeffs,
GpuMat rvecs,
GpuMat tvecs,
GpuMat objPoints,
EstimateParameters estimateParameters) |
static void |
opencv_aruco.estimatePoseSingleMarkers(MatVector corners,
float markerLength,
Mat cameraMatrix,
Mat distCoeffs,
Mat rvecs,
Mat tvecs,
Mat objPoints,
EstimateParameters estimateParameters)
Deprecated.
Use cv::solvePnP
|
static void |
opencv_aruco.estimatePoseSingleMarkers(MatVector corners,
float markerLength,
UMat cameraMatrix,
UMat distCoeffs,
UMat rvecs,
UMat tvecs,
UMat objPoints,
EstimateParameters estimateParameters) |
static void |
opencv_aruco.estimatePoseSingleMarkers(UMatVector corners,
float markerLength,
GpuMat cameraMatrix,
GpuMat distCoeffs,
GpuMat rvecs,
GpuMat tvecs,
GpuMat objPoints,
EstimateParameters estimateParameters) |
static void |
opencv_aruco.estimatePoseSingleMarkers(UMatVector corners,
float markerLength,
Mat cameraMatrix,
Mat distCoeffs,
Mat rvecs,
Mat tvecs,
Mat objPoints,
EstimateParameters estimateParameters) |
static void |
opencv_aruco.estimatePoseSingleMarkers(UMatVector corners,
float markerLength,
UMat cameraMatrix,
UMat distCoeffs,
UMat rvecs,
UMat tvecs,
UMat objPoints,
EstimateParameters estimateParameters) |
static void |
opencv_features2d.evaluateFeatureDetector(Mat img1,
Mat img2,
Mat H1to2,
KeyPointVector keypoints1,
KeyPointVector keypoints2,
float[] repeatability,
int[] correspCount,
Feature2D fdetector) |
static void |
opencv_features2d.evaluateFeatureDetector(Mat img1,
Mat img2,
Mat H1to2,
KeyPointVector keypoints1,
KeyPointVector keypoints2,
FloatBuffer repeatability,
IntBuffer correspCount,
Feature2D fdetector) |
static void |
opencv_features2d.evaluateFeatureDetector(Mat img1,
Mat img2,
Mat H1to2,
KeyPointVector keypoints1,
KeyPointVector keypoints2,
FloatPointer repeatability,
IntPointer correspCount,
Feature2D fdetector)
\addtogroup features2d_main
/** \{
|
static boolean |
opencv_calib3d.findCirclesGrid(GpuMat image,
Size patternSize,
GpuMat centers,
int flags,
Feature2D blobDetector) |
static boolean |
opencv_calib3d.findCirclesGrid(GpuMat image,
Size patternSize,
GpuMat centers,
int flags,
Feature2D blobDetector,
CirclesGridFinderParameters parameters) |
static boolean |
opencv_calib3d.findCirclesGrid(Mat image,
Size patternSize,
Mat centers,
int flags,
Feature2D blobDetector)
\overload
|
static boolean |
opencv_calib3d.findCirclesGrid(Mat image,
Size patternSize,
Mat centers,
int flags,
Feature2D blobDetector,
CirclesGridFinderParameters parameters)
\brief Finds centers in the grid of circles.
|
static boolean |
opencv_calib3d.findCirclesGrid(UMat image,
Size patternSize,
UMat centers,
int flags,
Feature2D blobDetector) |
static boolean |
opencv_calib3d.findCirclesGrid(UMat image,
Size patternSize,
UMat centers,
int flags,
Feature2D blobDetector,
CirclesGridFinderParameters parameters) |
static void |
opencv_aruco.getBoardObjectAndImagePoints(Board board,
GpuMatVector detectedCorners,
GpuMat detectedIds,
GpuMat objPoints,
GpuMat imgPoints) |
static void |
opencv_aruco.getBoardObjectAndImagePoints(Board board,
GpuMatVector detectedCorners,
Mat detectedIds,
Mat objPoints,
Mat imgPoints) |
static void |
opencv_aruco.getBoardObjectAndImagePoints(Board board,
GpuMatVector detectedCorners,
UMat detectedIds,
UMat objPoints,
UMat imgPoints) |
static void |
opencv_aruco.getBoardObjectAndImagePoints(Board board,
MatVector detectedCorners,
GpuMat detectedIds,
GpuMat objPoints,
GpuMat imgPoints) |
static void |
opencv_aruco.getBoardObjectAndImagePoints(Board board,
MatVector detectedCorners,
Mat detectedIds,
Mat objPoints,
Mat imgPoints)
Deprecated.
Use Board::matchImagePoints
|
static void |
opencv_aruco.getBoardObjectAndImagePoints(Board board,
MatVector detectedCorners,
UMat detectedIds,
UMat objPoints,
UMat imgPoints) |
static void |
opencv_aruco.getBoardObjectAndImagePoints(Board board,
UMatVector detectedCorners,
GpuMat detectedIds,
GpuMat objPoints,
GpuMat imgPoints) |
static void |
opencv_aruco.getBoardObjectAndImagePoints(Board board,
UMatVector detectedCorners,
Mat detectedIds,
Mat objPoints,
Mat imgPoints) |
static void |
opencv_aruco.getBoardObjectAndImagePoints(Board board,
UMatVector detectedCorners,
UMat detectedIds,
UMat objPoints,
UMat imgPoints) |
static int |
opencv_aruco.interpolateCornersCharuco(GpuMatVector markerCorners,
GpuMat markerIds,
GpuMat image,
CharucoBoard board,
GpuMat charucoCorners,
GpuMat charucoIds) |
static int |
opencv_aruco.interpolateCornersCharuco(GpuMatVector markerCorners,
GpuMat markerIds,
GpuMat image,
CharucoBoard board,
GpuMat charucoCorners,
GpuMat charucoIds,
GpuMat cameraMatrix,
GpuMat distCoeffs,
int minMarkers) |
static int |
opencv_aruco.interpolateCornersCharuco(GpuMatVector markerCorners,
Mat markerIds,
Mat image,
CharucoBoard board,
Mat charucoCorners,
Mat charucoIds) |
static int |
opencv_aruco.interpolateCornersCharuco(GpuMatVector markerCorners,
Mat markerIds,
Mat image,
CharucoBoard board,
Mat charucoCorners,
Mat charucoIds,
Mat cameraMatrix,
Mat distCoeffs,
int minMarkers) |
static int |
opencv_aruco.interpolateCornersCharuco(GpuMatVector markerCorners,
UMat markerIds,
UMat image,
CharucoBoard board,
UMat charucoCorners,
UMat charucoIds) |
static int |
opencv_aruco.interpolateCornersCharuco(GpuMatVector markerCorners,
UMat markerIds,
UMat image,
CharucoBoard board,
UMat charucoCorners,
UMat charucoIds,
UMat cameraMatrix,
UMat distCoeffs,
int minMarkers) |
static int |
opencv_aruco.interpolateCornersCharuco(MatVector markerCorners,
GpuMat markerIds,
GpuMat image,
CharucoBoard board,
GpuMat charucoCorners,
GpuMat charucoIds) |
static int |
opencv_aruco.interpolateCornersCharuco(MatVector markerCorners,
GpuMat markerIds,
GpuMat image,
CharucoBoard board,
GpuMat charucoCorners,
GpuMat charucoIds,
GpuMat cameraMatrix,
GpuMat distCoeffs,
int minMarkers) |
static int |
opencv_aruco.interpolateCornersCharuco(MatVector markerCorners,
Mat markerIds,
Mat image,
CharucoBoard board,
Mat charucoCorners,
Mat charucoIds) |
static int |
opencv_aruco.interpolateCornersCharuco(MatVector markerCorners,
Mat markerIds,
Mat image,
CharucoBoard board,
Mat charucoCorners,
Mat charucoIds,
Mat cameraMatrix,
Mat distCoeffs,
int minMarkers)
Deprecated.
Use CharucoDetector::detectBoard
|
static int |
opencv_aruco.interpolateCornersCharuco(MatVector markerCorners,
UMat markerIds,
UMat image,
CharucoBoard board,
UMat charucoCorners,
UMat charucoIds) |
static int |
opencv_aruco.interpolateCornersCharuco(MatVector markerCorners,
UMat markerIds,
UMat image,
CharucoBoard board,
UMat charucoCorners,
UMat charucoIds,
UMat cameraMatrix,
UMat distCoeffs,
int minMarkers) |
static int |
opencv_aruco.interpolateCornersCharuco(UMatVector markerCorners,
GpuMat markerIds,
GpuMat image,
CharucoBoard board,
GpuMat charucoCorners,
GpuMat charucoIds) |
static int |
opencv_aruco.interpolateCornersCharuco(UMatVector markerCorners,
GpuMat markerIds,
GpuMat image,
CharucoBoard board,
GpuMat charucoCorners,
GpuMat charucoIds,
GpuMat cameraMatrix,
GpuMat distCoeffs,
int minMarkers) |
static int |
opencv_aruco.interpolateCornersCharuco(UMatVector markerCorners,
Mat markerIds,
Mat image,
CharucoBoard board,
Mat charucoCorners,
Mat charucoIds) |
static int |
opencv_aruco.interpolateCornersCharuco(UMatVector markerCorners,
Mat markerIds,
Mat image,
CharucoBoard board,
Mat charucoCorners,
Mat charucoIds,
Mat cameraMatrix,
Mat distCoeffs,
int minMarkers) |
static int |
opencv_aruco.interpolateCornersCharuco(UMatVector markerCorners,
UMat markerIds,
UMat image,
CharucoBoard board,
UMat charucoCorners,
UMat charucoIds) |
static int |
opencv_aruco.interpolateCornersCharuco(UMatVector markerCorners,
UMat markerIds,
UMat image,
CharucoBoard board,
UMat charucoCorners,
UMat charucoIds,
UMat cameraMatrix,
UMat distCoeffs,
int minMarkers) |
static int |
opencv_core.print(Formatted fmtd) |
static int |
opencv_core.print(Formatted fmtd,
Pointer stream) |
static void |
opencv_aruco.refineDetectedMarkers(GpuMat image,
Board board,
GpuMatVector detectedCorners,
GpuMat detectedIds,
GpuMatVector rejectedCorners) |
static void |
opencv_aruco.refineDetectedMarkers(GpuMat image,
Board board,
GpuMatVector detectedCorners,
GpuMat detectedIds,
GpuMatVector rejectedCorners,
GpuMat cameraMatrix,
GpuMat distCoeffs,
float minRepDistance,
float errorCorrectionRate,
boolean checkAllOrders,
GpuMat recoveredIdxs,
DetectorParameters parameters) |
static void |
opencv_aruco.refineDetectedMarkers(GpuMat image,
Board board,
GpuMatVector detectedCorners,
GpuMat detectedIds,
GpuMatVector rejectedCorners,
GpuMat cameraMatrix,
GpuMat distCoeffs,
float minRepDistance,
float errorCorrectionRate,
boolean checkAllOrders,
GpuMat recoveredIdxs,
DetectorParameters parameters) |
static void |
opencv_aruco.refineDetectedMarkers(GpuMat image,
Board board,
MatVector detectedCorners,
GpuMat detectedIds,
MatVector rejectedCorners) |
static void |
opencv_aruco.refineDetectedMarkers(GpuMat image,
Board board,
MatVector detectedCorners,
GpuMat detectedIds,
MatVector rejectedCorners,
GpuMat cameraMatrix,
GpuMat distCoeffs,
float minRepDistance,
float errorCorrectionRate,
boolean checkAllOrders,
GpuMat recoveredIdxs,
DetectorParameters parameters) |
static void |
opencv_aruco.refineDetectedMarkers(GpuMat image,
Board board,
MatVector detectedCorners,
GpuMat detectedIds,
MatVector rejectedCorners,
GpuMat cameraMatrix,
GpuMat distCoeffs,
float minRepDistance,
float errorCorrectionRate,
boolean checkAllOrders,
GpuMat recoveredIdxs,
DetectorParameters parameters) |
static void |
opencv_aruco.refineDetectedMarkers(GpuMat image,
Board board,
UMatVector detectedCorners,
GpuMat detectedIds,
UMatVector rejectedCorners) |
static void |
opencv_aruco.refineDetectedMarkers(GpuMat image,
Board board,
UMatVector detectedCorners,
GpuMat detectedIds,
UMatVector rejectedCorners,
GpuMat cameraMatrix,
GpuMat distCoeffs,
float minRepDistance,
float errorCorrectionRate,
boolean checkAllOrders,
GpuMat recoveredIdxs,
DetectorParameters parameters) |
static void |
opencv_aruco.refineDetectedMarkers(GpuMat image,
Board board,
UMatVector detectedCorners,
GpuMat detectedIds,
UMatVector rejectedCorners,
GpuMat cameraMatrix,
GpuMat distCoeffs,
float minRepDistance,
float errorCorrectionRate,
boolean checkAllOrders,
GpuMat recoveredIdxs,
DetectorParameters parameters) |
static void |
opencv_aruco.refineDetectedMarkers(Mat image,
Board board,
GpuMatVector detectedCorners,
Mat detectedIds,
GpuMatVector rejectedCorners) |
static void |
opencv_aruco.refineDetectedMarkers(Mat image,
Board board,
GpuMatVector detectedCorners,
Mat detectedIds,
GpuMatVector rejectedCorners,
Mat cameraMatrix,
Mat distCoeffs,
float minRepDistance,
float errorCorrectionRate,
boolean checkAllOrders,
Mat recoveredIdxs,
DetectorParameters parameters) |
static void |
opencv_aruco.refineDetectedMarkers(Mat image,
Board board,
GpuMatVector detectedCorners,
Mat detectedIds,
GpuMatVector rejectedCorners,
Mat cameraMatrix,
Mat distCoeffs,
float minRepDistance,
float errorCorrectionRate,
boolean checkAllOrders,
Mat recoveredIdxs,
DetectorParameters parameters) |
static void |
opencv_aruco.refineDetectedMarkers(Mat image,
Board board,
MatVector detectedCorners,
Mat detectedIds,
MatVector rejectedCorners) |
static void |
opencv_aruco.refineDetectedMarkers(Mat image,
Board board,
MatVector detectedCorners,
Mat detectedIds,
MatVector rejectedCorners,
Mat cameraMatrix,
Mat distCoeffs,
float minRepDistance,
float errorCorrectionRate,
boolean checkAllOrders,
Mat recoveredIdxs,
DetectorParameters parameters)
Deprecated.
Use class ArucoDetector::refineDetectedMarkers
|
static void |
opencv_aruco.refineDetectedMarkers(Mat image,
Board board,
MatVector detectedCorners,
Mat detectedIds,
MatVector rejectedCorners,
Mat cameraMatrix,
Mat distCoeffs,
float minRepDistance,
float errorCorrectionRate,
boolean checkAllOrders,
Mat recoveredIdxs,
DetectorParameters parameters)
Deprecated.
Use class ArucoDetector::refineDetectedMarkers
|
static void |
opencv_aruco.refineDetectedMarkers(Mat image,
Board board,
UMatVector detectedCorners,
Mat detectedIds,
UMatVector rejectedCorners) |
static void |
opencv_aruco.refineDetectedMarkers(Mat image,
Board board,
UMatVector detectedCorners,
Mat detectedIds,
UMatVector rejectedCorners,
Mat cameraMatrix,
Mat distCoeffs,
float minRepDistance,
float errorCorrectionRate,
boolean checkAllOrders,
Mat recoveredIdxs,
DetectorParameters parameters) |
static void |
opencv_aruco.refineDetectedMarkers(Mat image,
Board board,
UMatVector detectedCorners,
Mat detectedIds,
UMatVector rejectedCorners,
Mat cameraMatrix,
Mat distCoeffs,
float minRepDistance,
float errorCorrectionRate,
boolean checkAllOrders,
Mat recoveredIdxs,
DetectorParameters parameters) |
static void |
opencv_aruco.refineDetectedMarkers(UMat image,
Board board,
GpuMatVector detectedCorners,
UMat detectedIds,
GpuMatVector rejectedCorners) |
static void |
opencv_aruco.refineDetectedMarkers(UMat image,
Board board,
GpuMatVector detectedCorners,
UMat detectedIds,
GpuMatVector rejectedCorners,
UMat cameraMatrix,
UMat distCoeffs,
float minRepDistance,
float errorCorrectionRate,
boolean checkAllOrders,
UMat recoveredIdxs,
DetectorParameters parameters) |
static void |
opencv_aruco.refineDetectedMarkers(UMat image,
Board board,
GpuMatVector detectedCorners,
UMat detectedIds,
GpuMatVector rejectedCorners,
UMat cameraMatrix,
UMat distCoeffs,
float minRepDistance,
float errorCorrectionRate,
boolean checkAllOrders,
UMat recoveredIdxs,
DetectorParameters parameters) |
static void |
opencv_aruco.refineDetectedMarkers(UMat image,
Board board,
MatVector detectedCorners,
UMat detectedIds,
MatVector rejectedCorners) |
static void |
opencv_aruco.refineDetectedMarkers(UMat image,
Board board,
MatVector detectedCorners,
UMat detectedIds,
MatVector rejectedCorners,
UMat cameraMatrix,
UMat distCoeffs,
float minRepDistance,
float errorCorrectionRate,
boolean checkAllOrders,
UMat recoveredIdxs,
DetectorParameters parameters) |
static void |
opencv_aruco.refineDetectedMarkers(UMat image,
Board board,
MatVector detectedCorners,
UMat detectedIds,
MatVector rejectedCorners,
UMat cameraMatrix,
UMat distCoeffs,
float minRepDistance,
float errorCorrectionRate,
boolean checkAllOrders,
UMat recoveredIdxs,
DetectorParameters parameters) |
static void |
opencv_aruco.refineDetectedMarkers(UMat image,
Board board,
UMatVector detectedCorners,
UMat detectedIds,
UMatVector rejectedCorners) |
static void |
opencv_aruco.refineDetectedMarkers(UMat image,
Board board,
UMatVector detectedCorners,
UMat detectedIds,
UMatVector rejectedCorners,
UMat cameraMatrix,
UMat distCoeffs,
float minRepDistance,
float errorCorrectionRate,
boolean checkAllOrders,
UMat recoveredIdxs,
DetectorParameters parameters) |
static void |
opencv_aruco.refineDetectedMarkers(UMat image,
Board board,
UMatVector detectedCorners,
UMat detectedIds,
UMatVector rejectedCorners,
UMat cameraMatrix,
UMat distCoeffs,
float minRepDistance,
float errorCorrectionRate,
boolean checkAllOrders,
UMat recoveredIdxs,
DetectorParameters parameters) |
static BytePointer |
opencv_core.shiftLeft(BytePointer out,
Formatted fmtd) |
static String |
opencv_core.shiftLeft(String out,
Formatted fmtd) |
static boolean |
opencv_aruco.testCharucoCornersCollinear(CharucoBoard board,
GpuMat charucoIds) |
static boolean |
opencv_aruco.testCharucoCornersCollinear(CharucoBoard board,
Mat charucoIds)
Deprecated.
Use CharucoBoard::checkCharucoCornersCollinear
|
static boolean |
opencv_aruco.testCharucoCornersCollinear(CharucoBoard board,
UMat charucoIds) |
| Modifier and Type | Method and Description |
|---|---|
static TransientAreasSegmentationModule |
TransientAreasSegmentationModule.create(Size inputSize)
\brief allocator
|
static RetinaFastToneMapping |
RetinaFastToneMapping.create(Size inputSize) |
static Retina |
Retina.create(Size inputSize)
\overload
|
static Retina |
Retina.create(Size inputSize,
boolean colorMode) |
static Retina |
Retina.create(Size inputSize,
boolean colorMode,
int colorSamplingMethod,
boolean useRetinaLogSampling,
float reductionFactor,
float samplingStrength)
\brief Constructors from standardized interfaces : retreive a smart pointer to a Retina instance
|
| Modifier and Type | Method and Description |
|---|---|
static StereoSGBM |
StereoSGBM.create() |
static StereoBM |
StereoBM.create() |
static StereoBM |
StereoBM.create(int numDisparities,
int blockSize)
\brief Creates StereoBM object
|
static StereoSGBM |
StereoSGBM.create(int minDisparity,
int numDisparities,
int blockSize,
int P1,
int P2,
int disp12MaxDiff,
int preFilterCap,
int uniquenessRatio,
int speckleWindowSize,
int speckleRange,
int mode)
\brief Creates StereoSGBM object
|
static LMSolver |
LMSolver.create(LMSolver.Callback cb,
int maxIters)
Creates Levenberg-Marquard solver
|
static LMSolver |
LMSolver.create(LMSolver.Callback cb,
int maxIters,
double eps) |
CvMat |
CvLevMarq.err() |
CvMat |
CvLevMarq.J() |
CvMat |
CvLevMarq.JtErr() |
CvMat |
CvLevMarq.JtJ() |
CvMat |
CvLevMarq.JtJN() |
CvMat |
CvLevMarq.JtJV() |
CvMat |
CvLevMarq.JtJW() |
CvMat |
CvLevMarq.mask() |
CvMat |
CvLevMarq.param() |
CvMat |
CvLevMarq.prevParam() |
| Modifier and Type | Method and Description |
|---|---|
static LMSolver |
LMSolver.create(LMSolver.Callback cb,
int maxIters)
Creates Levenberg-Marquard solver
|
static LMSolver |
LMSolver.create(LMSolver.Callback cb,
int maxIters,
double eps) |
| Modifier and Type | Method and Description |
|---|---|
static DownhillSolver |
DownhillSolver.create() |
static ConjGradSolver |
ConjGradSolver.create() |
static DFT1D |
DFT1D.create(int len,
int count,
int depth,
int flags) |
static DCT2D |
DCT2D.create(int width,
int height,
int depth,
int flags) |
static DFT1D |
DFT1D.create(int len,
int count,
int depth,
int flags,
boolean[] useBuffer) |
static DFT1D |
DFT1D.create(int len,
int count,
int depth,
int flags,
BoolPointer useBuffer) |
static DFT2D |
DFT2D.create(int width,
int height,
int depth,
int src_channels,
int dst_channels,
int flags) |
static DFT2D |
DFT2D.create(int width,
int height,
int depth,
int src_channels,
int dst_channels,
int flags,
int nonzero_rows) |
static DownhillSolver |
DownhillSolver.create(MinProblemSolver.Function f,
GpuMat initStep,
TermCriteria termcrit) |
static DownhillSolver |
DownhillSolver.create(MinProblemSolver.Function f,
Mat initStep,
TermCriteria termcrit)
\brief This function returns the reference to the ready-to-use DownhillSolver object.
|
static ConjGradSolver |
ConjGradSolver.create(MinProblemSolver.Function f,
TermCriteria termcrit)
\brief This function returns the reference to the ready-to-use ConjGradSolver object.
|
static DownhillSolver |
DownhillSolver.create(MinProblemSolver.Function f,
UMat initStep,
TermCriteria termcrit) |
Formatted |
Formatter.format(Mat mtx) |
static Formatter |
Formatter.get() |
static Formatter |
Formatter.get(int fmt) |
GpuMat.Allocator |
BufferPool.getAllocator()
Returns the allocator associated with the stream.
|
MinProblemSolver.Function |
MinProblemSolver.getFunction()
\brief Getter for the optimized function.
|
| Modifier and Type | Method and Description |
|---|---|
static DownhillSolver |
DownhillSolver.create(MinProblemSolver.Function f,
GpuMat initStep,
TermCriteria termcrit) |
static DownhillSolver |
DownhillSolver.create(MinProblemSolver.Function f,
Mat initStep,
TermCriteria termcrit)
\brief This function returns the reference to the ready-to-use DownhillSolver object.
|
static ConjGradSolver |
ConjGradSolver.create(MinProblemSolver.Function f,
TermCriteria termcrit)
\brief This function returns the reference to the ready-to-use ConjGradSolver object.
|
static DownhillSolver |
DownhillSolver.create(MinProblemSolver.Function f,
UMat initStep,
TermCriteria termcrit) |
void |
MinProblemSolver.setFunction(MinProblemSolver.Function f)
\brief Setter for the optimized function.
|
| Constructor and Description |
|---|
Stream(GpuMat.Allocator allocator)
creates a new asynchronous stream with custom allocator
|
| Modifier and Type | Method and Description |
|---|---|
static ORB |
ORB.create() |
static FastFeatureDetector |
FastFeatureDetector.create() |
static FastFeatureDetector |
FastFeatureDetector.create(int threshold,
boolean nonmaxSuppression,
int type,
int max_npoints) |
static ORB |
ORB.create(int nfeatures,
float scaleFactor,
int nlevels,
int edgeThreshold,
int firstLevel,
int WTA_K,
int scoreType,
int patchSize,
int fastThreshold,
boolean blurForDescriptor) |
static DescriptorMatcher |
DescriptorMatcher.createBFMatcher() |
static DescriptorMatcher |
DescriptorMatcher.createBFMatcher(int normType)
\brief Brute-force descriptor matcher.
|
| Modifier and Type | Method and Description |
|---|---|
static HOG |
HOG.create() |
static CudaCascadeClassifier |
CudaCascadeClassifier.create(BytePointer filename)
\brief Loads the classifier from a file.
|
static CudaCascadeClassifier |
CudaCascadeClassifier.create(FileStorage file)
\overload
|
static HOG |
HOG.create(Size win_size,
Size block_size,
Size block_stride,
Size cell_size,
int nbins)
\brief Creates the HOG descriptor and detector.
|
static CudaCascadeClassifier |
CudaCascadeClassifier.create(String filename) |
| Modifier and Type | Method and Description |
|---|---|
static SparsePyrLKOpticalFlow |
SparsePyrLKOpticalFlow.create() |
static OpticalFlowDual_TVL1 |
OpticalFlowDual_TVL1.create() |
static FarnebackOpticalFlow |
FarnebackOpticalFlow.create() |
static DensePyrLKOpticalFlow |
DensePyrLKOpticalFlow.create() |
static BroxOpticalFlow |
BroxOpticalFlow.create() |
static OpticalFlowDual_TVL1 |
OpticalFlowDual_TVL1.create(double tau,
double lambda,
double theta,
int nscales,
int warps,
double epsilon,
int iterations,
double scaleStep,
double gamma,
boolean useInitialFlow) |
static BroxOpticalFlow |
BroxOpticalFlow.create(double alpha,
double gamma,
double scale_factor,
int inner_iterations,
int outer_iterations,
int solver_iterations) |
static FarnebackOpticalFlow |
FarnebackOpticalFlow.create(int numLevels,
double pyrScale,
boolean fastPyramids,
int winSize,
int numIters,
int polyN,
double polySigma,
int flags) |
static NvidiaOpticalFlow_2_0 |
NvidiaOpticalFlow_2_0.create(Size imageSize) |
static NvidiaOpticalFlow_1_0 |
NvidiaOpticalFlow_1_0.create(Size imageSize) |
static NvidiaOpticalFlow_1_0 |
NvidiaOpticalFlow_1_0.create(Size imageSize,
int perfPreset,
boolean enableTemporalHints,
boolean enableExternalHints,
boolean enableCostBuffer,
int gpuId,
Stream inputStream,
Stream outputStream)
\brief Instantiate NVIDIA Optical Flow
|
static SparsePyrLKOpticalFlow |
SparsePyrLKOpticalFlow.create(Size winSize,
int maxLevel,
int iters,
boolean useInitialFlow) |
static DensePyrLKOpticalFlow |
DensePyrLKOpticalFlow.create(Size winSize,
int maxLevel,
int iters,
boolean useInitialFlow) |
static NvidiaOpticalFlow_2_0 |
NvidiaOpticalFlow_2_0.create(Size imageSize,
int perfPreset,
int outputGridSize,
int hintGridSize,
boolean enableTemporalHints,
boolean enableExternalHints,
boolean enableCostBuffer,
int gpuId,
Stream inputStream,
Stream outputStream)
\brief Instantiate NVIDIA Optical Flow
|
static NvidiaOpticalFlow_2_0 |
NvidiaOpticalFlow_2_0.create(Size imageSize,
RectVector roiData) |
static NvidiaOpticalFlow_2_0 |
NvidiaOpticalFlow_2_0.create(Size imageSize,
RectVector roiData,
int perfPreset,
int outputGridSize,
int hintGridSize,
boolean enableTemporalHints,
boolean enableExternalHints,
boolean enableCostBuffer,
int gpuId,
Stream inputStream,
Stream outputStream)
\brief Instantiate NVIDIA Optical Flow with ROI Feature
|
| Modifier and Type | Method and Description |
|---|---|
Layer |
LayerFactory.Constructor.call(LayerParams params) |
static TileLayer |
TileLayer.create(LayerParams params) |
static ThresholdedReluLayer |
ThresholdedReluLayer.create(LayerParams params) |
static TanLayer |
TanLayer.create(LayerParams params) |
static TanHLayer |
TanHLayer.create(LayerParams params) |
static SwishLayer |
SwishLayer.create(LayerParams params) |
static SqrtLayer |
SqrtLayer.create(LayerParams params) |
static SplitLayer |
SplitLayer.create(LayerParams params) |
static SoftsignLayer |
SoftsignLayer.create(LayerParams params) |
static SoftplusLayer |
SoftplusLayer.create(LayerParams params) |
static SoftmaxLayerInt8 |
SoftmaxLayerInt8.create(LayerParams params) |
static SoftmaxLayer |
SoftmaxLayer.create(LayerParams params) |
static SliceLayer |
SliceLayer.create(LayerParams params) |
static SinLayer |
SinLayer.create(LayerParams params) |
static SinhLayer |
SinhLayer.create(LayerParams params) |
static SignLayer |
SignLayer.create(LayerParams params) |
static SigmoidLayer |
SigmoidLayer.create(LayerParams params) |
static Layer |
ShuffleChannelLayer.create(LayerParams params) |
static ShrinkLayer |
ShrinkLayer.create(LayerParams params) |
static Layer |
ShiftLayerInt8.create(LayerParams params) |
static Layer |
ShiftLayer.create(LayerParams params) |
static SeluLayer |
SeluLayer.create(LayerParams params) |
static ScatterNDLayer |
ScatterNDLayer.create(LayerParams params) |
static ScatterLayer |
ScatterLayer.create(LayerParams params) |
static ScaleLayerInt8 |
ScaleLayerInt8.create(LayerParams params) |
static ScaleLayer |
ScaleLayer.create(LayerParams params) |
static RoundLayer |
RoundLayer.create(LayerParams params) |
static RNNLayer |
RNNLayer.create(LayerParams params)
Creates instance of RNNLayer
|
static ResizeLayer |
ResizeLayer.create(LayerParams params) |
static ReshapeLayer |
ReshapeLayer.create(LayerParams params) |
static RequantizeLayer |
RequantizeLayer.create(LayerParams params) |
static ReorgLayer |
ReorgLayer.create(LayerParams params) |
static ReLULayer |
ReLULayer.create(LayerParams params) |
static ReLU6Layer |
ReLU6Layer.create(LayerParams params) |
static RegionLayer |
RegionLayer.create(LayerParams params) |
static ReduceLayer |
ReduceLayer.create(LayerParams params) |
static ReciprocalLayer |
ReciprocalLayer.create(LayerParams params) |
static QuantizeLayer |
QuantizeLayer.create(LayerParams params) |
static ProposalLayer |
ProposalLayer.create(LayerParams params) |
static PriorBoxLayer |
PriorBoxLayer.create(LayerParams params) |
static PowerLayer |
PowerLayer.create(LayerParams params) |
static PoolingLayerInt8 |
PoolingLayerInt8.create(LayerParams params) |
static PoolingLayer |
PoolingLayer.create(LayerParams params) |
static PermuteLayer |
PermuteLayer.create(LayerParams params) |
static PaddingLayer |
PaddingLayer.create(LayerParams params) |
static NotLayer |
NotLayer.create(LayerParams params) |
static NormalizeBBoxLayer |
NormalizeBBoxLayer.create(LayerParams params) |
static NaryEltwiseLayer |
NaryEltwiseLayer.create(LayerParams params) |
static MVNLayer |
MVNLayer.create(LayerParams params) |
static MishLayer |
MishLayer.create(LayerParams params) |
static MaxUnpoolLayer |
MaxUnpoolLayer.create(LayerParams params) |
static MatMulLayer |
MatMulLayer.create(LayerParams params) |
static LSTMLayer |
LSTMLayer.create(LayerParams params)
Creates instance of LSTM layer
|
static LRNLayer |
LRNLayer.create(LayerParams params) |
static LogLayer |
LogLayer.create(LayerParams params) |
static LayerNormLayer |
LayerNormLayer.create(LayerParams params) |
static Layer |
InterpLayer.create(LayerParams params) |
static InstanceNormLayer |
InstanceNormLayer.create(LayerParams params) |
static InnerProductLayerInt8 |
InnerProductLayerInt8.create(LayerParams params) |
static InnerProductLayer |
InnerProductLayer.create(LayerParams params) |
static HardSwishLayer |
HardSwishLayer.create(LayerParams params) |
static HardSigmoidLayer |
HardSigmoidLayer.create(LayerParams params) |
static GRULayer |
GRULayer.create(LayerParams params)
Creates instance of GRU layer
|
static GroupNormLayer |
GroupNormLayer.create(LayerParams params) |
static GemmLayer |
GemmLayer.create(LayerParams params) |
static GeluLayer |
GeluLayer.create(LayerParams params) |
static GeluApproximationLayer |
GeluApproximationLayer.create(LayerParams params) |
static GatherLayer |
GatherLayer.create(LayerParams params) |
static GatherElementsLayer |
GatherElementsLayer.create(LayerParams params) |
static FlowWarpLayer |
FlowWarpLayer.create(LayerParams params) |
static FloorLayer |
FloorLayer.create(LayerParams params) |
static FlattenLayer |
FlattenLayer.create(LayerParams params) |
static ExpLayer |
ExpLayer.create(LayerParams params) |
static ExpandLayer |
ExpandLayer.create(LayerParams params) |
static ErfLayer |
ErfLayer.create(LayerParams params) |
static ELULayer |
ELULayer.create(LayerParams params) |
static EltwiseLayerInt8 |
EltwiseLayerInt8.create(LayerParams params) |
static EltwiseLayer |
EltwiseLayer.create(LayerParams params) |
static EinsumLayer |
EinsumLayer.create(LayerParams params) |
static DetectionOutputLayer |
DetectionOutputLayer.create(LayerParams params) |
static DequantizeLayer |
DequantizeLayer.create(LayerParams params) |
static BaseConvolutionLayer |
DeconvolutionLayer.create(LayerParams params) |
static DataAugmentationLayer |
DataAugmentationLayer.create(LayerParams params) |
static CumSumLayer |
CumSumLayer.create(LayerParams params) |
static Layer |
CropLayer.create(LayerParams params) |
static Layer |
CropAndResizeLayer.create(LayerParams params) |
static CosLayer |
CosLayer.create(LayerParams params) |
static CoshLayer |
CoshLayer.create(LayerParams params) |
static CorrelationLayer |
CorrelationLayer.create(LayerParams params) |
static BaseConvolutionLayer |
ConvolutionLayerInt8.create(LayerParams params) |
static BaseConvolutionLayer |
ConvolutionLayer.create(LayerParams params) |
static Layer |
ConstLayer.create(LayerParams params) |
static ConcatLayer |
ConcatLayer.create(LayerParams params) |
static Layer |
CompareLayer.create(LayerParams params) |
static Layer |
ChannelsPReLULayer.create(LayerParams params) |
static CeluLayer |
CeluLayer.create(LayerParams params) |
static CeilLayer |
CeilLayer.create(LayerParams params) |
static BNLLLayer |
BNLLLayer.create(LayerParams params) |
static Layer |
BlankLayer.create(LayerParams params) |
static BatchNormLayerInt8 |
BatchNormLayerInt8.create(LayerParams params) |
static BatchNormLayer |
BatchNormLayer.create(LayerParams params) |
static AttentionLayer |
AttentionLayer.create(LayerParams params) |
static AtanLayer |
AtanLayer.create(LayerParams params) |
static AtanhLayer |
AtanhLayer.create(LayerParams params) |
static AsinLayer |
AsinLayer.create(LayerParams params) |
static AsinhLayer |
AsinhLayer.create(LayerParams params) |
static ArgLayer |
ArgLayer.create(LayerParams params) |
static ActivationLayerInt8 |
ActivationLayerInt8.create(LayerParams params) |
static AcosLayer |
AcosLayer.create(LayerParams params) |
static AcoshLayer |
AcoshLayer.create(LayerParams params) |
static AccumLayer |
AccumLayer.create(LayerParams params) |
static AbsLayer |
AbsLayer.create(LayerParams params) |
static Layer |
LayerFactory.createLayerInstance(BytePointer type,
LayerParams params)
\brief Creates instance of registered layer.
|
static Layer |
LayerFactory.createLayerInstance(String type,
LayerParams params) |
Layer |
Net.getLayer(BytePointer layerName)
Deprecated.
Use int getLayerId(const String &layer)
|
Layer |
Net.getLayer(DictValue layerId)
Deprecated.
to be removed
|
Layer |
Net.getLayer(int layerId)
\brief Returns pointer to layer with specified id or name which the network use.
|
Layer |
Net.getLayer(String layerName) |
BackendNode |
Layer.tryAttach(BackendNode node)
\brief Implement layers fusing.
|
| Modifier and Type | Method and Description |
|---|---|
void |
Layer.applyHalideScheduler(BackendNode node,
MatPointerVector inputs,
MatVector outputs,
int targetId)
\brief Automatic Halide scheduling based on layer hyper-parameters.
|
boolean |
Layer.setActivation(ActivationLayer layer)
\brief Tries to attach to the layer the subsequent activation layer, i.e.
|
BackendNode |
Layer.tryAttach(BackendNode node)
\brief Implement layers fusing.
|
boolean |
Layer.tryFuse(Layer top)
\brief Try to fuse current layer with a next one
|
| Modifier and Type | Method and Description |
|---|---|
static DnnSuperResImpl |
DnnSuperResImpl.create()
\brief Empty constructor for python
|
| Modifier and Type | Method and Description |
|---|---|
static StandardCollector |
StandardCollector.create() |
static LBPHFaceRecognizer |
LBPHFaceRecognizer.create() |
static FisherFaceRecognizer |
FisherFaceRecognizer.create() |
static FacemarkLBF |
FacemarkLBF.create() |
static FacemarkKazemi |
FacemarkKazemi.create() |
static FacemarkAAM |
FacemarkAAM.create() |
static EigenFaceRecognizer |
EigenFaceRecognizer.create() |
static StandardCollector |
StandardCollector.create(double threshold)
\brief Static constructor
|
static FacemarkAAM |
FacemarkAAM.create(FacemarkAAM.Params parameters)
initializer
|
static FacemarkKazemi |
FacemarkKazemi.create(FacemarkKazemi.Params parameters) |
static FacemarkLBF |
FacemarkLBF.create(FacemarkLBF.Params parameters) |
static FisherFaceRecognizer |
FisherFaceRecognizer.create(int num_components,
double threshold) |
static EigenFaceRecognizer |
EigenFaceRecognizer.create(int num_components,
double threshold) |
static LBPHFaceRecognizer |
LBPHFaceRecognizer.create(int radius,
int neighbors,
int grid_x,
int grid_y,
double threshold) |
| Modifier and Type | Method and Description |
|---|---|
void |
FaceRecognizer.predict_collect(GpuMat src,
PredictCollector collector) |
void |
FaceRecognizer.predict_collect(Mat src,
PredictCollector collector)
\brief - if implemented - send all result of prediction to collector that can be used for somehow custom result handling
|
void |
FaceRecognizer.predict_collect(UMat src,
PredictCollector collector) |
| Modifier and Type | Method and Description |
|---|---|
DescriptorMatcher |
FlannBasedMatcher.clone() |
DescriptorMatcher |
DescriptorMatcher.clone() |
DescriptorMatcher |
BFMatcher.clone() |
DescriptorMatcher |
FlannBasedMatcher.clone(boolean emptyTrainData) |
DescriptorMatcher |
DescriptorMatcher.clone(boolean emptyTrainData)
\brief Clones the matcher.
|
DescriptorMatcher |
BFMatcher.clone(boolean emptyTrainData) |
static SimpleBlobDetector |
SimpleBlobDetector.create() |
static SIFT |
SIFT.create() |
static ORB |
ORB.create() |
static MSER |
MSER.create() |
static KAZE |
KAZE.create() |
static GFTTDetector |
GFTTDetector.create() |
static FlannBasedMatcher |
FlannBasedMatcher.create() |
static FastFeatureDetector |
FastFeatureDetector.create() |
static BRISK |
BRISK.create() |
static BFMatcher |
BFMatcher.create() |
static AKAZE |
AKAZE.create() |
static AgastFeatureDetector |
AgastFeatureDetector.create() |
static KAZE |
KAZE.create(boolean extended,
boolean upright,
float threshold,
int nOctaves,
int nOctaveLayers,
int diffusivity)
\brief The KAZE constructor
|
static DescriptorMatcher |
DescriptorMatcher.create(BytePointer descriptorMatcherType)
\brief Creates a descriptor matcher of a given type with the default parameters (using default
constructor).
|
static AffineFeature |
AffineFeature.create(Feature2D backend) |
static AffineFeature |
AffineFeature.create(Feature2D backend,
int maxTilt,
int minTilt,
float tiltStep,
float rotateStepBase) |
static BRISK |
BRISK.create(float[] radiusList,
int[] numberList) |
static BRISK |
BRISK.create(float[] radiusList,
int[] numberList,
float dMax,
float dMin,
int[] indexChange) |
static BRISK |
BRISK.create(FloatBuffer radiusList,
IntBuffer numberList) |
static BRISK |
BRISK.create(FloatBuffer radiusList,
IntBuffer numberList,
float dMax,
float dMin,
IntBuffer indexChange) |
static BRISK |
BRISK.create(FloatPointer radiusList,
IntPointer numberList) |
static BRISK |
BRISK.create(FloatPointer radiusList,
IntPointer numberList,
float dMax,
float dMin,
IntPointer indexChange)
\brief The BRISK constructor for a custom pattern
|
static DescriptorMatcher |
DescriptorMatcher.create(int matcherType) |
static BFMatcher |
BFMatcher.create(int normType,
boolean crossCheck)
\brief Brute-force matcher create method.
|
static FastFeatureDetector |
FastFeatureDetector.create(int threshold,
boolean nonmaxSuppression,
int type) |
static AgastFeatureDetector |
AgastFeatureDetector.create(int threshold,
boolean nonmaxSuppression,
int type) |
static GFTTDetector |
GFTTDetector.create(int maxCorners,
double qualityLevel,
double minDistance,
int blockSize,
boolean useHarrisDetector,
double k) |
static GFTTDetector |
GFTTDetector.create(int maxCorners,
double qualityLevel,
double minDistance,
int blockSize,
int gradiantSize) |
static GFTTDetector |
GFTTDetector.create(int maxCorners,
double qualityLevel,
double minDistance,
int blockSize,
int gradiantSize,
boolean useHarrisDetector,
double k) |
static ORB |
ORB.create(int nfeatures,
float scaleFactor,
int nlevels,
int edgeThreshold,
int firstLevel,
int WTA_K,
int scoreType,
int patchSize,
int fastThreshold)
\brief The ORB constructor
|
static SIFT |
SIFT.create(int nfeatures,
int nOctaveLayers,
double contrastThreshold,
double edgeThreshold,
double sigma,
boolean enable_precise_upscale) |
static SIFT |
SIFT.create(int nfeatures,
int nOctaveLayers,
double contrastThreshold,
double edgeThreshold,
double sigma,
int descriptorType) |
static SIFT |
SIFT.create(int nfeatures,
int nOctaveLayers,
double contrastThreshold,
double edgeThreshold,
double sigma,
int descriptorType,
boolean enable_precise_upscale)
\brief Create SIFT with specified descriptorType.
|
static BRISK |
BRISK.create(int thresh,
int octaves,
float patternScale)
\brief The BRISK constructor
|
static BRISK |
BRISK.create(int thresh,
int octaves,
float[] radiusList,
int[] numberList) |
static BRISK |
BRISK.create(int thresh,
int octaves,
float[] radiusList,
int[] numberList,
float dMax,
float dMin,
int[] indexChange) |
static BRISK |
BRISK.create(int thresh,
int octaves,
FloatBuffer radiusList,
IntBuffer numberList) |
static BRISK |
BRISK.create(int thresh,
int octaves,
FloatBuffer radiusList,
IntBuffer numberList,
float dMax,
float dMin,
IntBuffer indexChange) |
static BRISK |
BRISK.create(int thresh,
int octaves,
FloatPointer radiusList,
IntPointer numberList) |
static BRISK |
BRISK.create(int thresh,
int octaves,
FloatPointer radiusList,
IntPointer numberList,
float dMax,
float dMin,
IntPointer indexChange)
\brief The BRISK constructor for a custom pattern, detection threshold and octaves
|
static MSER |
MSER.create(int delta,
int min_area,
int max_area,
double max_variation,
double min_diversity,
int max_evolution,
double area_threshold,
double min_margin,
int edge_blur_size)
\brief Full constructor for %MSER detector
|
static AKAZE |
AKAZE.create(int descriptor_type,
int descriptor_size,
int descriptor_channels,
float threshold,
int nOctaves,
int nOctaveLayers,
int diffusivity,
int max_points)
\brief The AKAZE constructor
|
static SimpleBlobDetector |
SimpleBlobDetector.create(SimpleBlobDetector.Params parameters) |
static DescriptorMatcher |
DescriptorMatcher.create(String descriptorMatcherType) |
| Modifier and Type | Method and Description |
|---|---|
static AffineFeature |
AffineFeature.create(Feature2D backend) |
static AffineFeature |
AffineFeature.create(Feature2D backend,
int maxTilt,
int minTilt,
float tiltStep,
float rotateStepBase) |
| Constructor and Description |
|---|
BOWImgDescriptorExtractor(DescriptorMatcher dmatcher)
\overload
|
BOWImgDescriptorExtractor(Feature2D dextractor,
DescriptorMatcher dmatcher)
\brief The constructor.
|
BOWImgDescriptorExtractor(Feature2D dextractor,
DescriptorMatcher dmatcher)
\brief The constructor.
|
FlannBasedMatcher(IndexParams indexParams,
SearchParams searchParams) |
FlannBasedMatcher(IndexParams indexParams,
SearchParams searchParams) |
| Modifier and Type | Method and Description |
|---|---|
static RadialVarianceHash |
RadialVarianceHash.create() |
static PHash |
PHash.create() |
static MarrHildrethHash |
MarrHildrethHash.create() |
static ColorMomentHash |
ColorMomentHash.create() |
static BlockMeanHash |
BlockMeanHash.create() |
static AverageHash |
AverageHash.create() |
static RadialVarianceHash |
RadialVarianceHash.create(double sigma,
int numOfAngleLine) |
static MarrHildrethHash |
MarrHildrethHash.create(float alpha,
float scale) |
static BlockMeanHash |
BlockMeanHash.create(int mode) |
| Modifier and Type | Method and Description |
|---|---|
static DetectorParameters |
DetectorParameters.create() |
static CCheckerDetector |
CCheckerDetector.create()
\brief Returns the implementation of the CCheckerDetector.
|
static CChecker |
CChecker.create()
\brief Create a new CChecker object.
|
static CCheckerDraw |
CCheckerDraw.create(CChecker pChecker) |
static CCheckerDraw |
CCheckerDraw.create(CChecker pChecker,
Scalar color,
int thickness)
\brief Create a new CCheckerDraw object.
|
CChecker |
CCheckerVector.Iterator.get() |
CChecker |
CCheckerVector.get(long i) |
CChecker |
CCheckerDetector.getBestColorChecker()
\brief Get the best color checker.
|
| Modifier and Type | Method and Description |
|---|---|
static CCheckerDraw |
CCheckerDraw.create(CChecker pChecker) |
static CCheckerDraw |
CCheckerDraw.create(CChecker pChecker,
Scalar color,
int thickness)
\brief Create a new CCheckerDraw object.
|
CCheckerVector.Iterator |
CCheckerVector.insert(CCheckerVector.Iterator pos,
CChecker value) |
boolean |
CCheckerDetector.process(GpuMat image,
int chartType,
int nc,
boolean useNet,
DetectorParameters params) |
boolean |
CCheckerDetector.process(Mat image,
int chartType,
int nc,
boolean useNet,
DetectorParameters params)
\brief Find the ColorCharts in the given image.
|
boolean |
CCheckerDetector.process(UMat image,
int chartType,
int nc,
boolean useNet,
DetectorParameters params) |
boolean |
CCheckerDetector.processWithROI(GpuMat image,
int chartType,
RectVector regionsOfInterest,
int nc,
boolean useNet,
DetectorParameters params) |
boolean |
CCheckerDetector.processWithROI(Mat image,
int chartType,
RectVector regionsOfInterest,
int nc,
boolean useNet,
DetectorParameters params)
\brief Find the ColorCharts in the given image.
|
boolean |
CCheckerDetector.processWithROI(UMat image,
int chartType,
RectVector regionsOfInterest,
int nc,
boolean useNet,
DetectorParameters params) |
| Modifier and Type | Method and Description |
|---|---|
static SVMSGD |
SVMSGD.create()
\brief Creates empty model.
|
static SVM |
SVM.create()
Creates empty model.
|
static RTrees |
RTrees.create()
Creates the empty model.
|
static ParamGrid |
ParamGrid.create() |
static NormalBayesClassifier |
NormalBayesClassifier.create()
Creates empty model
Use StatModel::train to train the model after creation.
|
static LogisticRegression |
LogisticRegression.create()
\brief Creates empty model.
|
static KNearest |
KNearest.create()
\brief Creates the empty model
|
static EM |
EM.create()
Creates empty %EM model.
|
static DTrees |
DTrees.create()
\brief Creates the empty model
|
static Boost |
Boost.create()
Creates the empty model.
|
static ANN_MLP |
ANN_MLP.create()
\brief Creates empty model
|
static ParamGrid |
ParamGrid.create(double minVal,
double maxVal,
double logstep)
\brief Creates a ParamGrid Ptr that can be given to the %SVM::trainAuto method
|
static TrainData |
TrainData.create(GpuMat samples,
int layout,
GpuMat responses) |
static TrainData |
TrainData.create(GpuMat samples,
int layout,
GpuMat responses,
GpuMat varIdx,
GpuMat sampleIdx,
GpuMat sampleWeights,
GpuMat varType) |
static TrainData |
TrainData.create(Mat samples,
int layout,
Mat responses) |
static TrainData |
TrainData.create(Mat samples,
int layout,
Mat responses,
Mat varIdx,
Mat sampleIdx,
Mat sampleWeights,
Mat varType)
\brief Creates training data from in-memory arrays.
|
static TrainData |
TrainData.create(UMat samples,
int layout,
UMat responses) |
static TrainData |
TrainData.create(UMat samples,
int layout,
UMat responses,
UMat varIdx,
UMat sampleIdx,
UMat sampleWeights,
UMat varType) |
static ParamGrid |
SVM.getDefaultGridPtr(int param_id)
\brief Generates a grid for %SVM parameters.
|
static SVMSGD |
SVMSGD.load(BytePointer filepath) |
static SVM |
SVM.load(BytePointer filepath)
\brief Loads and creates a serialized svm from a file
Use SVM::save to serialize and store an SVM to disk.
|
static RTrees |
RTrees.load(BytePointer filepath) |
static NormalBayesClassifier |
NormalBayesClassifier.load(BytePointer filepath) |
static LogisticRegression |
LogisticRegression.load(BytePointer filepath) |
static KNearest |
KNearest.load(BytePointer filepath)
\brief Loads and creates a serialized knearest from a file
Use KNearest::save to serialize and store an KNearest to disk.
|
static EM |
EM.load(BytePointer filepath) |
static DTrees |
DTrees.load(BytePointer filepath) |
static Boost |
Boost.load(BytePointer filepath) |
static ANN_MLP |
ANN_MLP.load(BytePointer filepath)
\brief Loads and creates a serialized ANN from a file
Use ANN::save to serialize and store an ANN to disk.
|
static SVMSGD |
SVMSGD.load(BytePointer filepath,
BytePointer nodeName)
\brief Loads and creates a serialized SVMSGD from a file
Use SVMSGD::save to serialize and store an SVMSGD to disk.
|
static RTrees |
RTrees.load(BytePointer filepath,
BytePointer nodeName)
\brief Loads and creates a serialized RTree from a file
Use RTree::save to serialize and store an RTree to disk.
|
static NormalBayesClassifier |
NormalBayesClassifier.load(BytePointer filepath,
BytePointer nodeName)
\brief Loads and creates a serialized NormalBayesClassifier from a file
Use NormalBayesClassifier::save to serialize and store an NormalBayesClassifier to disk.
|
static LogisticRegression |
LogisticRegression.load(BytePointer filepath,
BytePointer nodeName)
\brief Loads and creates a serialized LogisticRegression from a file
Use LogisticRegression::save to serialize and store an LogisticRegression to disk.
|
static EM |
EM.load(BytePointer filepath,
BytePointer nodeName)
\brief Loads and creates a serialized EM from a file
Use EM::save to serialize and store an EM to disk.
|
static DTrees |
DTrees.load(BytePointer filepath,
BytePointer nodeName)
\brief Loads and creates a serialized DTrees from a file
Use DTree::save to serialize and store an DTree to disk.
|
static Boost |
Boost.load(BytePointer filepath,
BytePointer nodeName)
\brief Loads and creates a serialized Boost from a file
Use Boost::save to serialize and store an RTree to disk.
|
static SVMSGD |
SVMSGD.load(String filepath) |
static SVM |
SVM.load(String filepath) |
static RTrees |
RTrees.load(String filepath) |
static NormalBayesClassifier |
NormalBayesClassifier.load(String filepath) |
static LogisticRegression |
LogisticRegression.load(String filepath) |
static KNearest |
KNearest.load(String filepath) |
static EM |
EM.load(String filepath) |
static DTrees |
DTrees.load(String filepath) |
static Boost |
Boost.load(String filepath) |
static ANN_MLP |
ANN_MLP.load(String filepath) |
static SVMSGD |
SVMSGD.load(String filepath,
String nodeName) |
static RTrees |
RTrees.load(String filepath,
String nodeName) |
static NormalBayesClassifier |
NormalBayesClassifier.load(String filepath,
String nodeName) |
static LogisticRegression |
LogisticRegression.load(String filepath,
String nodeName) |
static EM |
EM.load(String filepath,
String nodeName) |
static DTrees |
DTrees.load(String filepath,
String nodeName) |
static Boost |
Boost.load(String filepath,
String nodeName) |
static ANN_MLP |
AbstractStatModel.loadANN_MLP(BytePointer filename,
BytePointer objname) |
static ANN_MLP |
AbstractStatModel.loadANN_MLP(String filename,
String objname) |
static Boost |
AbstractStatModel.loadBoost(BytePointer filename,
BytePointer objname) |
static Boost |
AbstractStatModel.loadBoost(String filename,
String objname) |
static DTrees |
AbstractStatModel.loadDTrees(BytePointer filename,
BytePointer objname) |
static DTrees |
AbstractStatModel.loadDTrees(String filename,
String objname) |
static EM |
AbstractStatModel.loadEM(BytePointer filename,
BytePointer objname) |
static EM |
AbstractStatModel.loadEM(String filename,
String objname) |
static TrainData |
TrainData.loadFromCSV(BytePointer filename,
int headerLineCount) |
static TrainData |
TrainData.loadFromCSV(BytePointer filename,
int headerLineCount,
int responseStartIdx,
int responseEndIdx,
BytePointer varTypeSpec,
byte delimiter,
byte missch)
\brief Reads the dataset from a .csv file and returns the ready-to-use training data.
|
static TrainData |
TrainData.loadFromCSV(String filename,
int headerLineCount) |
static TrainData |
TrainData.loadFromCSV(String filename,
int headerLineCount,
int responseStartIdx,
int responseEndIdx,
String varTypeSpec,
byte delimiter,
byte missch) |
static KNearest |
AbstractStatModel.loadKNearest(BytePointer filename,
BytePointer objname) |
static KNearest |
AbstractStatModel.loadKNearest(String filename,
String objname) |
static LogisticRegression |
AbstractStatModel.loadLogisticRegression(BytePointer filename,
BytePointer objname) |
static LogisticRegression |
AbstractStatModel.loadLogisticRegression(String filename,
String objname) |
static NormalBayesClassifier |
AbstractStatModel.loadNormalBayesClassifier(BytePointer filename,
BytePointer objname) |
static NormalBayesClassifier |
AbstractStatModel.loadNormalBayesClassifier(String filename,
String objname) |
static RTrees |
AbstractStatModel.loadRTrees(BytePointer filename,
BytePointer objname) |
static RTrees |
AbstractStatModel.loadRTrees(String filename,
String objname) |
static SVM |
AbstractStatModel.loadSVM(BytePointer filename,
BytePointer objname) |
static SVM |
AbstractStatModel.loadSVM(String filename,
String objname) |
| Modifier and Type | Method and Description |
|---|---|
float |
StatModel.calcError(TrainData data,
boolean test,
GpuMat resp) |
float |
StatModel.calcError(TrainData data,
boolean test,
Mat resp)
\brief Computes error on the training or test dataset
|
float |
StatModel.calcError(TrainData data,
boolean test,
UMat resp) |
void |
SVM.setCustomKernel(SVM.Kernel _kernel)
Initialize with custom kernel.
|
boolean |
StatModel.train(TrainData trainData) |
boolean |
StatModel.train(TrainData trainData,
int flags)
\brief Trains the statistical model
|
boolean |
SVM.trainAuto(GpuMat samples,
int layout,
GpuMat responses,
int kFold,
ParamGrid Cgrid,
ParamGrid gammaGrid,
ParamGrid pGrid,
ParamGrid nuGrid,
ParamGrid coeffGrid,
ParamGrid degreeGrid,
boolean balanced) |
boolean |
SVM.trainAuto(GpuMat samples,
int layout,
GpuMat responses,
int kFold,
ParamGrid Cgrid,
ParamGrid gammaGrid,
ParamGrid pGrid,
ParamGrid nuGrid,
ParamGrid coeffGrid,
ParamGrid degreeGrid,
boolean balanced) |
boolean |
SVM.trainAuto(GpuMat samples,
int layout,
GpuMat responses,
int kFold,
ParamGrid Cgrid,
ParamGrid gammaGrid,
ParamGrid pGrid,
ParamGrid nuGrid,
ParamGrid coeffGrid,
ParamGrid degreeGrid,
boolean balanced) |
boolean |
SVM.trainAuto(GpuMat samples,
int layout,
GpuMat responses,
int kFold,
ParamGrid Cgrid,
ParamGrid gammaGrid,
ParamGrid pGrid,
ParamGrid nuGrid,
ParamGrid coeffGrid,
ParamGrid degreeGrid,
boolean balanced) |
boolean |
SVM.trainAuto(GpuMat samples,
int layout,
GpuMat responses,
int kFold,
ParamGrid Cgrid,
ParamGrid gammaGrid,
ParamGrid pGrid,
ParamGrid nuGrid,
ParamGrid coeffGrid,
ParamGrid degreeGrid,
boolean balanced) |
boolean |
SVM.trainAuto(GpuMat samples,
int layout,
GpuMat responses,
int kFold,
ParamGrid Cgrid,
ParamGrid gammaGrid,
ParamGrid pGrid,
ParamGrid nuGrid,
ParamGrid coeffGrid,
ParamGrid degreeGrid,
boolean balanced) |
boolean |
SVM.trainAuto(Mat samples,
int layout,
Mat responses,
int kFold,
ParamGrid Cgrid,
ParamGrid gammaGrid,
ParamGrid pGrid,
ParamGrid nuGrid,
ParamGrid coeffGrid,
ParamGrid degreeGrid,
boolean balanced)
\brief Trains an %SVM with optimal parameters
|
boolean |
SVM.trainAuto(Mat samples,
int layout,
Mat responses,
int kFold,
ParamGrid Cgrid,
ParamGrid gammaGrid,
ParamGrid pGrid,
ParamGrid nuGrid,
ParamGrid coeffGrid,
ParamGrid degreeGrid,
boolean balanced)
\brief Trains an %SVM with optimal parameters
|
boolean |
SVM.trainAuto(Mat samples,
int layout,
Mat responses,
int kFold,
ParamGrid Cgrid,
ParamGrid gammaGrid,
ParamGrid pGrid,
ParamGrid nuGrid,
ParamGrid coeffGrid,
ParamGrid degreeGrid,
boolean balanced)
\brief Trains an %SVM with optimal parameters
|
boolean |
SVM.trainAuto(Mat samples,
int layout,
Mat responses,
int kFold,
ParamGrid Cgrid,
ParamGrid gammaGrid,
ParamGrid pGrid,
ParamGrid nuGrid,
ParamGrid coeffGrid,
ParamGrid degreeGrid,
boolean balanced)
\brief Trains an %SVM with optimal parameters
|
boolean |
SVM.trainAuto(Mat samples,
int layout,
Mat responses,
int kFold,
ParamGrid Cgrid,
ParamGrid gammaGrid,
ParamGrid pGrid,
ParamGrid nuGrid,
ParamGrid coeffGrid,
ParamGrid degreeGrid,
boolean balanced)
\brief Trains an %SVM with optimal parameters
|
boolean |
SVM.trainAuto(Mat samples,
int layout,
Mat responses,
int kFold,
ParamGrid Cgrid,
ParamGrid gammaGrid,
ParamGrid pGrid,
ParamGrid nuGrid,
ParamGrid coeffGrid,
ParamGrid degreeGrid,
boolean balanced)
\brief Trains an %SVM with optimal parameters
|
boolean |
SVM.trainAuto(TrainData data) |
boolean |
SVM.trainAuto(TrainData data,
int kFold,
ParamGrid Cgrid,
ParamGrid gammaGrid,
ParamGrid pGrid,
ParamGrid nuGrid,
ParamGrid coeffGrid,
ParamGrid degreeGrid,
boolean balanced)
\brief Trains an %SVM with optimal parameters.
|
boolean |
SVM.trainAuto(UMat samples,
int layout,
UMat responses,
int kFold,
ParamGrid Cgrid,
ParamGrid gammaGrid,
ParamGrid pGrid,
ParamGrid nuGrid,
ParamGrid coeffGrid,
ParamGrid degreeGrid,
boolean balanced) |
boolean |
SVM.trainAuto(UMat samples,
int layout,
UMat responses,
int kFold,
ParamGrid Cgrid,
ParamGrid gammaGrid,
ParamGrid pGrid,
ParamGrid nuGrid,
ParamGrid coeffGrid,
ParamGrid degreeGrid,
boolean balanced) |
boolean |
SVM.trainAuto(UMat samples,
int layout,
UMat responses,
int kFold,
ParamGrid Cgrid,
ParamGrid gammaGrid,
ParamGrid pGrid,
ParamGrid nuGrid,
ParamGrid coeffGrid,
ParamGrid degreeGrid,
boolean balanced) |
boolean |
SVM.trainAuto(UMat samples,
int layout,
UMat responses,
int kFold,
ParamGrid Cgrid,
ParamGrid gammaGrid,
ParamGrid pGrid,
ParamGrid nuGrid,
ParamGrid coeffGrid,
ParamGrid degreeGrid,
boolean balanced) |
boolean |
SVM.trainAuto(UMat samples,
int layout,
UMat responses,
int kFold,
ParamGrid Cgrid,
ParamGrid gammaGrid,
ParamGrid pGrid,
ParamGrid nuGrid,
ParamGrid coeffGrid,
ParamGrid degreeGrid,
boolean balanced) |
boolean |
SVM.trainAuto(UMat samples,
int layout,
UMat responses,
int kFold,
ParamGrid Cgrid,
ParamGrid gammaGrid,
ParamGrid pGrid,
ParamGrid nuGrid,
ParamGrid coeffGrid,
ParamGrid degreeGrid,
boolean balanced) |