public class opencv_cudaimgproc extends opencv_cudaimgproc
Modifier and Type | Field and Description |
---|---|
static int |
ALPHA_ATOP
enum cv::cuda::AlphaCompTypes
|
static int |
ALPHA_ATOP_PREMUL
enum cv::cuda::AlphaCompTypes
|
static int |
ALPHA_IN
enum cv::cuda::AlphaCompTypes
|
static int |
ALPHA_IN_PREMUL
enum cv::cuda::AlphaCompTypes
|
static int |
ALPHA_OUT
enum cv::cuda::AlphaCompTypes
|
static int |
ALPHA_OUT_PREMUL
enum cv::cuda::AlphaCompTypes
|
static int |
ALPHA_OVER
enum cv::cuda::AlphaCompTypes
|
static int |
ALPHA_OVER_PREMUL
enum cv::cuda::AlphaCompTypes
|
static int |
ALPHA_PLUS
enum cv::cuda::AlphaCompTypes
|
static int |
ALPHA_PLUS_PREMUL
enum cv::cuda::AlphaCompTypes
|
static int |
ALPHA_PREMUL
enum cv::cuda::AlphaCompTypes
|
static int |
ALPHA_XOR
enum cv::cuda::AlphaCompTypes
|
static int |
ALPHA_XOR_PREMUL
enum cv::cuda::AlphaCompTypes
|
static int |
COLOR_BayerBG2BGR_MHT
enum cv::cuda::DemosaicTypes
|
static int |
COLOR_BayerBG2GRAY_MHT
enum cv::cuda::DemosaicTypes
|
static int |
COLOR_BayerBG2RGB_MHT
enum cv::cuda::DemosaicTypes
|
static int |
COLOR_BayerGB2BGR_MHT
enum cv::cuda::DemosaicTypes
|
static int |
COLOR_BayerGB2GRAY_MHT
enum cv::cuda::DemosaicTypes
|
static int |
COLOR_BayerGB2RGB_MHT
enum cv::cuda::DemosaicTypes
|
static int |
COLOR_BayerGR2BGR_MHT
enum cv::cuda::DemosaicTypes
|
static int |
COLOR_BayerGR2GRAY_MHT
enum cv::cuda::DemosaicTypes
|
static int |
COLOR_BayerGR2RGB_MHT
enum cv::cuda::DemosaicTypes
|
static int |
COLOR_BayerRG2BGR_MHT
enum cv::cuda::DemosaicTypes
|
static int |
COLOR_BayerRG2GRAY_MHT
enum cv::cuda::DemosaicTypes
|
static int |
COLOR_BayerRG2RGB_MHT
enum cv::cuda::DemosaicTypes
|
Constructor and Description |
---|
opencv_cudaimgproc() |
Modifier and Type | Method and Description |
---|---|
static void |
alphaComp(GpuMat img1,
GpuMat img2,
GpuMat dst,
int alpha_op) |
static void |
alphaComp(GpuMat img1,
GpuMat img2,
GpuMat dst,
int alpha_op,
Stream stream) |
static void |
alphaComp(Mat img1,
Mat img2,
Mat dst,
int alpha_op) |
static void |
alphaComp(Mat img1,
Mat img2,
Mat dst,
int alpha_op,
Stream stream)
\brief Composites two images using alpha opacity values contained in each image.
|
static void |
alphaComp(UMat img1,
UMat img2,
UMat dst,
int alpha_op) |
static void |
alphaComp(UMat img1,
UMat img2,
UMat dst,
int alpha_op,
Stream stream) |
static void |
bilateralFilter(GpuMat src,
GpuMat dst,
int kernel_size,
float sigma_color,
float sigma_spatial) |
static void |
bilateralFilter(GpuMat src,
GpuMat dst,
int kernel_size,
float sigma_color,
float sigma_spatial,
int borderMode,
Stream stream) |
static void |
bilateralFilter(Mat src,
Mat dst,
int kernel_size,
float sigma_color,
float sigma_spatial) |
static void |
bilateralFilter(Mat src,
Mat dst,
int kernel_size,
float sigma_color,
float sigma_spatial,
int borderMode,
Stream stream)
\brief Performs bilateral filtering of passed image
|
static void |
bilateralFilter(UMat src,
UMat dst,
int kernel_size,
float sigma_color,
float sigma_spatial) |
static void |
bilateralFilter(UMat src,
UMat dst,
int kernel_size,
float sigma_color,
float sigma_spatial,
int borderMode,
Stream stream) |
static void |
blendLinear(GpuMat img1,
GpuMat img2,
GpuMat weights1,
GpuMat weights2,
GpuMat result) |
static void |
blendLinear(GpuMat img1,
GpuMat img2,
GpuMat weights1,
GpuMat weights2,
GpuMat result,
Stream stream) |
static void |
blendLinear(Mat img1,
Mat img2,
Mat weights1,
Mat weights2,
Mat result) |
static void |
blendLinear(Mat img1,
Mat img2,
Mat weights1,
Mat weights2,
Mat result,
Stream stream)
\brief Performs linear blending of two images.
|
static void |
blendLinear(UMat img1,
UMat img2,
UMat weights1,
UMat weights2,
UMat result) |
static void |
blendLinear(UMat img1,
UMat img2,
UMat weights1,
UMat weights2,
UMat result,
Stream stream) |
static void |
calcHist(GpuMat src,
GpuMat hist) |
static void |
calcHist(GpuMat src,
GpuMat mask,
GpuMat hist) |
static void |
calcHist(GpuMat src,
GpuMat mask,
GpuMat hist,
Stream stream) |
static void |
calcHist(GpuMat src,
GpuMat hist,
Stream stream) |
static void |
calcHist(Mat src,
Mat hist) |
static void |
calcHist(Mat src,
Mat mask,
Mat hist) |
static void |
calcHist(Mat src,
Mat mask,
Mat hist,
Stream stream)
\brief Calculates histogram for one channel 8-bit image confined in given mask.
|
static void |
calcHist(Mat src,
Mat hist,
Stream stream)
\} cudaimgproc_color
|
static void |
calcHist(UMat src,
UMat hist) |
static void |
calcHist(UMat src,
UMat hist,
Stream stream) |
static void |
calcHist(UMat src,
UMat mask,
UMat hist) |
static void |
calcHist(UMat src,
UMat mask,
UMat hist,
Stream stream) |
static CannyEdgeDetector |
createCannyEdgeDetector(double low_thresh,
double high_thresh) |
static CannyEdgeDetector |
createCannyEdgeDetector(double low_thresh,
double high_thresh,
int apperture_size,
boolean L2gradient)
\brief Creates implementation for cuda::CannyEdgeDetector .
|
static CudaCLAHE |
createCLAHE() |
static CudaCLAHE |
createCLAHE(double clipLimit,
Size tileGridSize)
\brief Creates implementation for cuda::CLAHE .
|
static GeneralizedHoughBallard |
createGeneralizedHoughBallard()
\brief Creates implementation for generalized hough transform from \cite Ballard1981 .
|
static GeneralizedHoughGuil |
createGeneralizedHoughGuil()
\brief Creates implementation for generalized hough transform from \cite Guil1999 .
|
static CornersDetector |
createGoodFeaturesToTrackDetector(int srcType) |
static CornersDetector |
createGoodFeaturesToTrackDetector(int srcType,
int maxCorners,
double qualityLevel,
double minDistance,
int blockSize,
boolean useHarrisDetector,
double harrisK)
\brief Creates implementation for cuda::CornersDetector .
|
static CornernessCriteria |
createHarrisCorner(int srcType,
int blockSize,
int ksize,
double k) |
static CornernessCriteria |
createHarrisCorner(int srcType,
int blockSize,
int ksize,
double k,
int borderType)
\brief Creates implementation for Harris cornerness criteria.
|
static HoughCirclesDetector |
createHoughCirclesDetector(float dp,
float minDist,
int cannyThreshold,
int votesThreshold,
int minRadius,
int maxRadius) |
static HoughCirclesDetector |
createHoughCirclesDetector(float dp,
float minDist,
int cannyThreshold,
int votesThreshold,
int minRadius,
int maxRadius,
int maxCircles)
\brief Creates implementation for cuda::HoughCirclesDetector .
|
static HoughLinesDetector |
createHoughLinesDetector(float rho,
float theta,
int threshold) |
static HoughLinesDetector |
createHoughLinesDetector(float rho,
float theta,
int threshold,
boolean doSort,
int maxLines)
\brief Creates implementation for cuda::HoughLinesDetector .
|
static HoughSegmentDetector |
createHoughSegmentDetector(float rho,
float theta,
int minLineLength,
int maxLineGap) |
static HoughSegmentDetector |
createHoughSegmentDetector(float rho,
float theta,
int minLineLength,
int maxLineGap,
int maxLines)
\brief Creates implementation for cuda::HoughSegmentDetector .
|
static CornernessCriteria |
createMinEigenValCorner(int srcType,
int blockSize,
int ksize) |
static CornernessCriteria |
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 TemplateMatching |
createTemplateMatching(int srcType,
int method) |
static TemplateMatching |
createTemplateMatching(int srcType,
int method,
Size user_block_size)
\brief Creates implementation for cuda::TemplateMatching .
|
static void |
cvtColor(GpuMat src,
GpuMat dst,
int code) |
static void |
cvtColor(GpuMat src,
GpuMat dst,
int code,
int dcn,
Stream stream) |
static void |
cvtColor(Mat src,
Mat dst,
int code) |
static void |
cvtColor(Mat src,
Mat dst,
int code,
int dcn,
Stream stream)
\addtogroup cudaimgproc
\{
|
static void |
cvtColor(UMat src,
UMat dst,
int code) |
static void |
cvtColor(UMat src,
UMat dst,
int code,
int dcn,
Stream stream) |
static void |
demosaicing(GpuMat src,
GpuMat dst,
int code) |
static void |
demosaicing(GpuMat src,
GpuMat dst,
int code,
int dcn,
Stream stream) |
static void |
demosaicing(Mat src,
Mat dst,
int code) |
static void |
demosaicing(Mat src,
Mat dst,
int code,
int dcn,
Stream stream)
\brief Converts an image from Bayer pattern to RGB or grayscale.
|
static void |
demosaicing(UMat src,
UMat dst,
int code) |
static void |
demosaicing(UMat src,
UMat dst,
int code,
int dcn,
Stream stream) |
static void |
equalizeHist(GpuMat src,
GpuMat dst) |
static void |
equalizeHist(GpuMat src,
GpuMat dst,
Stream stream) |
static void |
equalizeHist(Mat src,
Mat dst) |
static void |
equalizeHist(Mat src,
Mat dst,
Stream stream)
\brief Equalizes the histogram of a grayscale image.
|
static void |
equalizeHist(UMat src,
UMat dst) |
static void |
equalizeHist(UMat src,
UMat dst,
Stream stream) |
static void |
evenLevels(GpuMat levels,
int nLevels,
int lowerLevel,
int upperLevel) |
static void |
evenLevels(GpuMat levels,
int nLevels,
int lowerLevel,
int upperLevel,
Stream stream) |
static void |
evenLevels(Mat levels,
int nLevels,
int lowerLevel,
int upperLevel) |
static void |
evenLevels(Mat levels,
int nLevels,
int lowerLevel,
int upperLevel,
Stream stream)
\brief Computes levels with even distribution.
|
static void |
evenLevels(UMat levels,
int nLevels,
int lowerLevel,
int upperLevel) |
static void |
evenLevels(UMat levels,
int nLevels,
int lowerLevel,
int upperLevel,
Stream stream) |
static void |
gammaCorrection(GpuMat src,
GpuMat dst) |
static void |
gammaCorrection(GpuMat src,
GpuMat dst,
boolean forward,
Stream stream) |
static void |
gammaCorrection(Mat src,
Mat dst) |
static void |
gammaCorrection(Mat src,
Mat dst,
boolean forward,
Stream stream)
\brief Routines for correcting image color gamma.
|
static void |
gammaCorrection(UMat src,
UMat dst) |
static void |
gammaCorrection(UMat src,
UMat dst,
boolean forward,
Stream stream) |
static void |
histEven(GpuMat src,
GpuMat hist,
int[] histSize,
int[] lowerLevel,
int[] upperLevel) |
static void |
histEven(GpuMat src,
GpuMat hist,
int[] histSize,
int[] lowerLevel,
int[] upperLevel,
Stream stream) |
static void |
histEven(GpuMat src,
GpuMat hist,
IntBuffer histSize,
IntBuffer lowerLevel,
IntBuffer upperLevel) |
static void |
histEven(GpuMat src,
GpuMat hist,
IntBuffer histSize,
IntBuffer lowerLevel,
IntBuffer upperLevel,
Stream stream) |
static void |
histEven(GpuMat src,
GpuMat hist,
int histSize,
int lowerLevel,
int upperLevel) |
static void |
histEven(GpuMat src,
GpuMat hist,
int histSize,
int lowerLevel,
int upperLevel,
Stream stream) |
static void |
histEven(GpuMat src,
GpuMat hist,
IntPointer histSize,
IntPointer lowerLevel,
IntPointer upperLevel) |
static void |
histEven(GpuMat src,
GpuMat hist,
IntPointer histSize,
IntPointer lowerLevel,
IntPointer upperLevel,
Stream stream) |
static void |
histEven(Mat src,
GpuMat hist,
int[] histSize,
int[] lowerLevel,
int[] upperLevel) |
static void |
histEven(Mat src,
GpuMat hist,
int[] histSize,
int[] lowerLevel,
int[] upperLevel,
Stream stream) |
static void |
histEven(Mat src,
GpuMat hist,
IntBuffer histSize,
IntBuffer lowerLevel,
IntBuffer upperLevel) |
static void |
histEven(Mat src,
GpuMat hist,
IntBuffer histSize,
IntBuffer lowerLevel,
IntBuffer upperLevel,
Stream stream) |
static void |
histEven(Mat src,
GpuMat hist,
IntPointer histSize,
IntPointer lowerLevel,
IntPointer upperLevel) |
static void |
histEven(Mat src,
GpuMat hist,
IntPointer histSize,
IntPointer lowerLevel,
IntPointer upperLevel,
Stream stream)
\overload
|
static void |
histEven(Mat src,
Mat hist,
int histSize,
int lowerLevel,
int upperLevel) |
static void |
histEven(Mat src,
Mat hist,
int histSize,
int lowerLevel,
int upperLevel,
Stream stream)
\brief Calculates a histogram with evenly distributed bins.
|
static void |
histEven(UMat src,
GpuMat hist,
int[] histSize,
int[] lowerLevel,
int[] upperLevel) |
static void |
histEven(UMat src,
GpuMat hist,
int[] histSize,
int[] lowerLevel,
int[] upperLevel,
Stream stream) |
static void |
histEven(UMat src,
GpuMat hist,
IntBuffer histSize,
IntBuffer lowerLevel,
IntBuffer upperLevel) |
static void |
histEven(UMat src,
GpuMat hist,
IntBuffer histSize,
IntBuffer lowerLevel,
IntBuffer upperLevel,
Stream stream) |
static void |
histEven(UMat src,
GpuMat hist,
IntPointer histSize,
IntPointer lowerLevel,
IntPointer upperLevel) |
static void |
histEven(UMat src,
GpuMat hist,
IntPointer histSize,
IntPointer lowerLevel,
IntPointer upperLevel,
Stream stream) |
static void |
histEven(UMat src,
UMat hist,
int histSize,
int lowerLevel,
int upperLevel) |
static void |
histEven(UMat src,
UMat hist,
int histSize,
int lowerLevel,
int upperLevel,
Stream stream) |
static void |
histRange(GpuMat src,
GpuMat hist,
GpuMat levels) |
static void |
histRange(GpuMat src,
GpuMat hist,
GpuMat levels,
Stream stream) |
static void |
histRange(Mat src,
GpuMat hist,
GpuMat levels) |
static void |
histRange(Mat src,
GpuMat hist,
GpuMat levels,
Stream stream)
\overload
|
static void |
histRange(Mat src,
Mat hist,
Mat levels) |
static void |
histRange(Mat src,
Mat hist,
Mat levels,
Stream stream)
\brief Calculates a histogram with bins determined by the levels array.
|
static void |
histRange(UMat src,
GpuMat hist,
GpuMat levels) |
static void |
histRange(UMat src,
GpuMat hist,
GpuMat levels,
Stream stream) |
static void |
histRange(UMat src,
UMat hist,
UMat levels) |
static void |
histRange(UMat src,
UMat hist,
UMat levels,
Stream stream) |
static void |
meanShiftFiltering(GpuMat src,
GpuMat dst,
int sp,
int sr) |
static void |
meanShiftFiltering(GpuMat src,
GpuMat dst,
int sp,
int sr,
TermCriteria criteria,
Stream stream) |
static void |
meanShiftFiltering(Mat src,
Mat dst,
int sp,
int sr) |
static void |
meanShiftFiltering(Mat src,
Mat dst,
int sp,
int sr,
TermCriteria criteria,
Stream stream)
\} cudaimgproc_feature
|
static void |
meanShiftFiltering(UMat src,
UMat dst,
int sp,
int sr) |
static void |
meanShiftFiltering(UMat src,
UMat dst,
int sp,
int sr,
TermCriteria criteria,
Stream stream) |
static void |
meanShiftProc(GpuMat src,
GpuMat dstr,
GpuMat dstsp,
int sp,
int sr) |
static void |
meanShiftProc(GpuMat src,
GpuMat dstr,
GpuMat dstsp,
int sp,
int sr,
TermCriteria criteria,
Stream stream) |
static void |
meanShiftProc(Mat src,
Mat dstr,
Mat dstsp,
int sp,
int sr) |
static void |
meanShiftProc(Mat src,
Mat dstr,
Mat dstsp,
int sp,
int sr,
TermCriteria criteria,
Stream stream)
\brief Performs a mean-shift procedure and stores information about processed points (their colors and
positions) in two images.
|
static void |
meanShiftProc(UMat src,
UMat dstr,
UMat dstsp,
int sp,
int sr) |
static void |
meanShiftProc(UMat src,
UMat dstr,
UMat dstsp,
int sp,
int sr,
TermCriteria criteria,
Stream stream) |
static void |
meanShiftSegmentation(GpuMat src,
GpuMat dst,
int sp,
int sr,
int minsize) |
static void |
meanShiftSegmentation(GpuMat src,
GpuMat dst,
int sp,
int sr,
int minsize,
TermCriteria criteria,
Stream stream) |
static void |
meanShiftSegmentation(Mat src,
Mat dst,
int sp,
int sr,
int minsize) |
static void |
meanShiftSegmentation(Mat src,
Mat dst,
int sp,
int sr,
int minsize,
TermCriteria criteria,
Stream stream)
\brief Performs a mean-shift segmentation of the source image and eliminates small segments.
|
static void |
meanShiftSegmentation(UMat src,
UMat dst,
int sp,
int sr,
int minsize) |
static void |
meanShiftSegmentation(UMat src,
UMat dst,
int sp,
int sr,
int minsize,
TermCriteria criteria,
Stream stream) |
static void |
swapChannels(GpuMat image,
int[] dstOrder) |
static void |
swapChannels(GpuMat image,
int[] dstOrder,
Stream stream) |
static void |
swapChannels(GpuMat image,
IntBuffer dstOrder) |
static void |
swapChannels(GpuMat image,
IntBuffer dstOrder,
Stream stream) |
static void |
swapChannels(GpuMat image,
IntPointer dstOrder) |
static void |
swapChannels(GpuMat image,
IntPointer dstOrder,
Stream stream) |
static void |
swapChannels(Mat image,
int[] dstOrder) |
static void |
swapChannels(Mat image,
int[] dstOrder,
Stream stream) |
static void |
swapChannels(Mat image,
IntBuffer dstOrder) |
static void |
swapChannels(Mat image,
IntBuffer dstOrder,
Stream stream) |
static void |
swapChannels(Mat image,
IntPointer dstOrder) |
static void |
swapChannels(Mat image,
IntPointer dstOrder,
Stream stream)
\brief Exchanges the color channels of an image in-place.
|
static void |
swapChannels(UMat image,
int[] dstOrder) |
static void |
swapChannels(UMat image,
int[] dstOrder,
Stream stream) |
static void |
swapChannels(UMat image,
IntBuffer dstOrder) |
static void |
swapChannels(UMat image,
IntBuffer dstOrder,
Stream stream) |
static void |
swapChannels(UMat image,
IntPointer dstOrder) |
static void |
swapChannels(UMat image,
IntPointer dstOrder,
Stream stream) |
map
public static final int COLOR_BayerBG2BGR_MHT
public static final int COLOR_BayerGB2BGR_MHT
public static final int COLOR_BayerRG2BGR_MHT
public static final int COLOR_BayerGR2BGR_MHT
public static final int COLOR_BayerBG2RGB_MHT
public static final int COLOR_BayerGB2RGB_MHT
public static final int COLOR_BayerRG2RGB_MHT
public static final int COLOR_BayerGR2RGB_MHT
public static final int COLOR_BayerBG2GRAY_MHT
public static final int COLOR_BayerGB2GRAY_MHT
public static final int COLOR_BayerRG2GRAY_MHT
public static final int COLOR_BayerGR2GRAY_MHT
public static final int ALPHA_OVER
public static final int ALPHA_IN
public static final int ALPHA_OUT
public static final int ALPHA_ATOP
public static final int ALPHA_XOR
public static final int ALPHA_PLUS
public static final int ALPHA_OVER_PREMUL
public static final int ALPHA_IN_PREMUL
public static final int ALPHA_OUT_PREMUL
public static final int ALPHA_ATOP_PREMUL
public static final int ALPHA_XOR_PREMUL
public static final int ALPHA_PLUS_PREMUL
public static final int ALPHA_PREMUL
@Namespace(value="cv::cuda") public static void cvtColor(@ByVal Mat src, @ByVal Mat dst, int code, int dcn, @ByRef(nullValue="cv::cuda::Stream::Null()") Stream stream)
/////////////////////////// Color Processing ///////////////////////////
\addtogroup cudaimgproc_color \{
/** \brief Converts an image from one color space to another.
src
- Source image with CV_8U , CV_16U , or CV_32F depth and 1, 3, or 4 channels.dst
- Destination image.code
- Color space conversion code. For details, see cvtColor .dcn
- Number of channels in the destination image. If the parameter is 0, the number of the
channels is derived automatically from src and the code .stream
- Stream for the asynchronous version.
3-channel color spaces (like HSV, XYZ, and so on) can be stored in a 4-channel image for better performance.
cvtColor
@Namespace(value="cv::cuda") public static void cvtColor(@ByVal Mat src, @ByVal Mat dst, int code)
@Namespace(value="cv::cuda") public static void cvtColor(@ByVal UMat src, @ByVal UMat dst, int code, int dcn, @ByRef(nullValue="cv::cuda::Stream::Null()") Stream stream)
@Namespace(value="cv::cuda") public static void cvtColor(@ByVal UMat src, @ByVal UMat dst, int code)
@Namespace(value="cv::cuda") public static void cvtColor(@ByVal GpuMat src, @ByVal GpuMat dst, int code, int dcn, @ByRef(nullValue="cv::cuda::Stream::Null()") Stream stream)
@Namespace(value="cv::cuda") public static void cvtColor(@ByVal GpuMat src, @ByVal GpuMat dst, int code)
@Namespace(value="cv::cuda") public static void demosaicing(@ByVal Mat src, @ByVal Mat dst, int code, int dcn, @ByRef(nullValue="cv::cuda::Stream::Null()") Stream stream)
src
- Source image (8-bit or 16-bit single channel).dst
- Destination image.code
- Color space conversion code (see the description below).dcn
- Number of channels in the destination image. If the parameter is 0, the number of the
channels is derived automatically from src and the code .stream
- Stream for the asynchronous version.
The function can do the following transformations:
- Demosaicing using bilinear interpolation
> - COLOR_BayerBG2GRAY , COLOR_BayerGB2GRAY , COLOR_BayerRG2GRAY , COLOR_BayerGR2GRAY > - COLOR_BayerBG2BGR , COLOR_BayerGB2BGR , COLOR_BayerRG2BGR , COLOR_BayerGR2BGR
- Demosaicing using Malvar-He-Cutler algorithm (\cite MHT2011)
> - COLOR_BayerBG2GRAY_MHT , COLOR_BayerGB2GRAY_MHT , COLOR_BayerRG2GRAY_MHT , > COLOR_BayerGR2GRAY_MHT > - COLOR_BayerBG2BGR_MHT , COLOR_BayerGB2BGR_MHT , COLOR_BayerRG2BGR_MHT , > COLOR_BayerGR2BGR_MHT
cvtColor
@Namespace(value="cv::cuda") public static void demosaicing(@ByVal Mat src, @ByVal Mat dst, int code)
@Namespace(value="cv::cuda") public static void demosaicing(@ByVal UMat src, @ByVal UMat dst, int code, int dcn, @ByRef(nullValue="cv::cuda::Stream::Null()") Stream stream)
@Namespace(value="cv::cuda") public static void demosaicing(@ByVal UMat src, @ByVal UMat dst, int code)
@Namespace(value="cv::cuda") public static void demosaicing(@ByVal GpuMat src, @ByVal GpuMat dst, int code, int dcn, @ByRef(nullValue="cv::cuda::Stream::Null()") Stream stream)
@Namespace(value="cv::cuda") public static void demosaicing(@ByVal GpuMat src, @ByVal GpuMat dst, int code)
@Namespace(value="cv::cuda") public static void swapChannels(@ByVal Mat image, @Const IntPointer dstOrder, @ByRef(nullValue="cv::cuda::Stream::Null()") Stream stream)
image
- Source image. Supports only CV_8UC4 type.dstOrder
- Integer array describing how channel values are permutated. The n-th entry of the
array contains the number of the channel that is stored in the n-th channel of the output image.
E.g. Given an RGBA image, aDstOrder = [3,2,1,0] converts this to ABGR channel order.stream
- Stream for the asynchronous version.
The methods support arbitrary permutations of the original channels, including replication.
@Namespace(value="cv::cuda") public static void swapChannels(@ByVal Mat image, @Const IntPointer dstOrder)
@Namespace(value="cv::cuda") public static void swapChannels(@ByVal Mat image, @Const IntBuffer dstOrder, @ByRef(nullValue="cv::cuda::Stream::Null()") Stream stream)
@Namespace(value="cv::cuda") public static void swapChannels(@ByVal Mat image, @Const IntBuffer dstOrder)
@Namespace(value="cv::cuda") public static void swapChannels(@ByVal Mat image, @Const int[] dstOrder, @ByRef(nullValue="cv::cuda::Stream::Null()") Stream stream)
@Namespace(value="cv::cuda") public static void swapChannels(@ByVal Mat image, @Const int[] dstOrder)
@Namespace(value="cv::cuda") public static void swapChannels(@ByVal UMat image, @Const IntPointer dstOrder, @ByRef(nullValue="cv::cuda::Stream::Null()") Stream stream)
@Namespace(value="cv::cuda") public static void swapChannels(@ByVal UMat image, @Const IntPointer dstOrder)
@Namespace(value="cv::cuda") public static void swapChannels(@ByVal UMat image, @Const IntBuffer dstOrder, @ByRef(nullValue="cv::cuda::Stream::Null()") Stream stream)
@Namespace(value="cv::cuda") public static void swapChannels(@ByVal UMat image, @Const IntBuffer dstOrder)
@Namespace(value="cv::cuda") public static void swapChannels(@ByVal UMat image, @Const int[] dstOrder, @ByRef(nullValue="cv::cuda::Stream::Null()") Stream stream)
@Namespace(value="cv::cuda") public static void swapChannels(@ByVal UMat image, @Const int[] dstOrder)
@Namespace(value="cv::cuda") public static void swapChannels(@ByVal GpuMat image, @Const IntPointer dstOrder, @ByRef(nullValue="cv::cuda::Stream::Null()") Stream stream)
@Namespace(value="cv::cuda") public static void swapChannels(@ByVal GpuMat image, @Const IntPointer dstOrder)
@Namespace(value="cv::cuda") public static void swapChannels(@ByVal GpuMat image, @Const IntBuffer dstOrder, @ByRef(nullValue="cv::cuda::Stream::Null()") Stream stream)
@Namespace(value="cv::cuda") public static void swapChannels(@ByVal GpuMat image, @Const IntBuffer dstOrder)
@Namespace(value="cv::cuda") public static void swapChannels(@ByVal GpuMat image, @Const int[] dstOrder, @ByRef(nullValue="cv::cuda::Stream::Null()") Stream stream)
@Namespace(value="cv::cuda") public static void swapChannels(@ByVal GpuMat image, @Const int[] dstOrder)
@Namespace(value="cv::cuda") public static void gammaCorrection(@ByVal Mat src, @ByVal Mat dst, @Cast(value="bool") boolean forward, @ByRef(nullValue="cv::cuda::Stream::Null()") Stream stream)
src
- Source image (3- or 4-channel 8 bit).dst
- Destination image.forward
- true for forward gamma correction or false for inverse gamma correction.stream
- Stream for the asynchronous version.@Namespace(value="cv::cuda") public static void gammaCorrection(@ByVal Mat src, @ByVal Mat dst)
@Namespace(value="cv::cuda") public static void gammaCorrection(@ByVal UMat src, @ByVal UMat dst, @Cast(value="bool") boolean forward, @ByRef(nullValue="cv::cuda::Stream::Null()") Stream stream)
@Namespace(value="cv::cuda") public static void gammaCorrection(@ByVal UMat src, @ByVal UMat dst)
@Namespace(value="cv::cuda") public static void gammaCorrection(@ByVal GpuMat src, @ByVal GpuMat dst, @Cast(value="bool") boolean forward, @ByRef(nullValue="cv::cuda::Stream::Null()") Stream stream)
@Namespace(value="cv::cuda") public static void gammaCorrection(@ByVal GpuMat src, @ByVal GpuMat dst)
@Namespace(value="cv::cuda") public static void alphaComp(@ByVal Mat img1, @ByVal Mat img2, @ByVal Mat dst, int alpha_op, @ByRef(nullValue="cv::cuda::Stream::Null()") Stream stream)
img1
- First image. Supports CV_8UC4 , CV_16UC4 , CV_32SC4 and CV_32FC4 types.img2
- Second image. Must have the same size and the same type as img1 .dst
- Destination image.alpha_op
- Flag specifying the alpha-blending operation:
- **ALPHA_OVER**
- **ALPHA_IN**
- **ALPHA_OUT**
- **ALPHA_ATOP**
- **ALPHA_XOR**
- **ALPHA_PLUS**
- **ALPHA_OVER_PREMUL**
- **ALPHA_IN_PREMUL**
- **ALPHA_OUT_PREMUL**
- **ALPHA_ATOP_PREMUL**
- **ALPHA_XOR_PREMUL**
- **ALPHA_PLUS_PREMUL**
- **ALPHA_PREMUL**stream
- Stream for the asynchronous version.
\note - An example demonstrating the use of alphaComp can be found at opencv_source_code/samples/gpu/alpha_comp.cpp
@Namespace(value="cv::cuda") public static void alphaComp(@ByVal Mat img1, @ByVal Mat img2, @ByVal Mat dst, int alpha_op)
@Namespace(value="cv::cuda") public static void alphaComp(@ByVal UMat img1, @ByVal UMat img2, @ByVal UMat dst, int alpha_op, @ByRef(nullValue="cv::cuda::Stream::Null()") Stream stream)
@Namespace(value="cv::cuda") public static void alphaComp(@ByVal UMat img1, @ByVal UMat img2, @ByVal UMat dst, int alpha_op)
@Namespace(value="cv::cuda") public static void alphaComp(@ByVal GpuMat img1, @ByVal GpuMat img2, @ByVal GpuMat dst, int alpha_op, @ByRef(nullValue="cv::cuda::Stream::Null()") Stream stream)
@Namespace(value="cv::cuda") public static void alphaComp(@ByVal GpuMat img1, @ByVal GpuMat img2, @ByVal GpuMat dst, int alpha_op)
@Namespace(value="cv::cuda") public static void calcHist(@ByVal Mat src, @ByVal Mat hist, @ByRef(nullValue="cv::cuda::Stream::Null()") Stream stream)
////////////////////////////// Histogram ///////////////////////////////
\addtogroup cudaimgproc_hist \{
/** \brief Calculates histogram for one channel 8-bit image.
src
- Source image with CV_8UC1 type.hist
- Destination histogram with one row, 256 columns, and the CV_32SC1 type.stream
- Stream for the asynchronous version.@Namespace(value="cv::cuda") public static void calcHist(@ByVal UMat src, @ByVal UMat hist, @ByRef(nullValue="cv::cuda::Stream::Null()") Stream stream)
@Namespace(value="cv::cuda") public static void calcHist(@ByVal UMat src, @ByVal UMat hist)
@Namespace(value="cv::cuda") public static void calcHist(@ByVal GpuMat src, @ByVal GpuMat hist, @ByRef(nullValue="cv::cuda::Stream::Null()") Stream stream)
@Namespace(value="cv::cuda") public static void calcHist(@ByVal GpuMat src, @ByVal GpuMat hist)
@Namespace(value="cv::cuda") public static void calcHist(@ByVal Mat src, @ByVal Mat mask, @ByVal Mat hist, @ByRef(nullValue="cv::cuda::Stream::Null()") Stream stream)
src
- Source image with CV_8UC1 type.hist
- Destination histogram with one row, 256 columns, and the CV_32SC1 type.mask
- A mask image same size as src and of type CV_8UC1.stream
- Stream for the asynchronous version.@Namespace(value="cv::cuda") public static void calcHist(@ByVal Mat src, @ByVal Mat mask, @ByVal Mat hist)
@Namespace(value="cv::cuda") public static void calcHist(@ByVal UMat src, @ByVal UMat mask, @ByVal UMat hist, @ByRef(nullValue="cv::cuda::Stream::Null()") Stream stream)
@Namespace(value="cv::cuda") public static void calcHist(@ByVal UMat src, @ByVal UMat mask, @ByVal UMat hist)
@Namespace(value="cv::cuda") public static void calcHist(@ByVal GpuMat src, @ByVal GpuMat mask, @ByVal GpuMat hist, @ByRef(nullValue="cv::cuda::Stream::Null()") Stream stream)
@Namespace(value="cv::cuda") public static void calcHist(@ByVal GpuMat src, @ByVal GpuMat mask, @ByVal GpuMat hist)
@Namespace(value="cv::cuda") public static void equalizeHist(@ByVal Mat src, @ByVal Mat dst, @ByRef(nullValue="cv::cuda::Stream::Null()") Stream stream)
src
- Source image with CV_8UC1 type.dst
- Destination image.stream
- Stream for the asynchronous version.
equalizeHist
@Namespace(value="cv::cuda") public static void equalizeHist(@ByVal Mat src, @ByVal Mat dst)
@Namespace(value="cv::cuda") public static void equalizeHist(@ByVal UMat src, @ByVal UMat dst, @ByRef(nullValue="cv::cuda::Stream::Null()") Stream stream)
@Namespace(value="cv::cuda") public static void equalizeHist(@ByVal UMat src, @ByVal UMat dst)
@Namespace(value="cv::cuda") public static void equalizeHist(@ByVal GpuMat src, @ByVal GpuMat dst, @ByRef(nullValue="cv::cuda::Stream::Null()") Stream stream)
@Namespace(value="cv::cuda") public static void equalizeHist(@ByVal GpuMat src, @ByVal GpuMat dst)
@Namespace(value="cv::cuda") @opencv_core.Ptr public static CudaCLAHE createCLAHE(double clipLimit, @ByVal(nullValue="cv::Size(8, 8)") Size tileGridSize)
clipLimit
- Threshold for contrast limiting.tileGridSize
- Size of grid for histogram equalization. Input image will be divided into
equally sized rectangular tiles. tileGridSize defines the number of tiles in row and column.@Namespace(value="cv::cuda") @opencv_core.Ptr public static CudaCLAHE createCLAHE()
@Namespace(value="cv::cuda") public static void evenLevels(@ByVal Mat levels, int nLevels, int lowerLevel, int upperLevel, @ByRef(nullValue="cv::cuda::Stream::Null()") Stream stream)
levels
- Destination array. levels has 1 row, nLevels columns, and the CV_32SC1 type.nLevels
- Number of computed levels. nLevels must be at least 2.lowerLevel
- Lower boundary value of the lowest level.upperLevel
- Upper boundary value of the greatest level.stream
- Stream for the asynchronous version.@Namespace(value="cv::cuda") public static void evenLevels(@ByVal Mat levels, int nLevels, int lowerLevel, int upperLevel)
@Namespace(value="cv::cuda") public static void evenLevels(@ByVal UMat levels, int nLevels, int lowerLevel, int upperLevel, @ByRef(nullValue="cv::cuda::Stream::Null()") Stream stream)
@Namespace(value="cv::cuda") public static void evenLevels(@ByVal UMat levels, int nLevels, int lowerLevel, int upperLevel)
@Namespace(value="cv::cuda") public static void evenLevels(@ByVal GpuMat levels, int nLevels, int lowerLevel, int upperLevel, @ByRef(nullValue="cv::cuda::Stream::Null()") Stream stream)
@Namespace(value="cv::cuda") public static void evenLevels(@ByVal GpuMat levels, int nLevels, int lowerLevel, int upperLevel)
@Namespace(value="cv::cuda") public static void histEven(@ByVal Mat src, @ByVal Mat hist, int histSize, int lowerLevel, int upperLevel, @ByRef(nullValue="cv::cuda::Stream::Null()") Stream stream)
src
- Source image. CV_8U, CV_16U, or CV_16S depth and 1 or 4 channels are supported. For
a four-channel image, all channels are processed separately.hist
- Destination histogram with one row, histSize columns, and the CV_32S type.histSize
- Size of the histogram.lowerLevel
- Lower boundary of lowest-level bin.upperLevel
- Upper boundary of highest-level bin.stream
- Stream for the asynchronous version.@Namespace(value="cv::cuda") public static void histEven(@ByVal Mat src, @ByVal Mat hist, int histSize, int lowerLevel, int upperLevel)
@Namespace(value="cv::cuda") public static void histEven(@ByVal UMat src, @ByVal UMat hist, int histSize, int lowerLevel, int upperLevel, @ByRef(nullValue="cv::cuda::Stream::Null()") Stream stream)
@Namespace(value="cv::cuda") public static void histEven(@ByVal UMat src, @ByVal UMat hist, int histSize, int lowerLevel, int upperLevel)
@Namespace(value="cv::cuda") public static void histEven(@ByVal GpuMat src, @ByVal GpuMat hist, int histSize, int lowerLevel, int upperLevel, @ByRef(nullValue="cv::cuda::Stream::Null()") Stream stream)
@Namespace(value="cv::cuda") public static void histEven(@ByVal GpuMat src, @ByVal GpuMat hist, int histSize, int lowerLevel, int upperLevel)
@Namespace(value="cv::cuda") public static void histEven(@ByVal Mat src, GpuMat hist, IntPointer histSize, IntPointer lowerLevel, IntPointer upperLevel, @ByRef(nullValue="cv::cuda::Stream::Null()") Stream stream)
@Namespace(value="cv::cuda") public static void histEven(@ByVal Mat src, GpuMat hist, IntPointer histSize, IntPointer lowerLevel, IntPointer upperLevel)
@Namespace(value="cv::cuda") public static void histEven(@ByVal Mat src, GpuMat hist, IntBuffer histSize, IntBuffer lowerLevel, IntBuffer upperLevel, @ByRef(nullValue="cv::cuda::Stream::Null()") Stream stream)
@Namespace(value="cv::cuda") public static void histEven(@ByVal Mat src, GpuMat hist, IntBuffer histSize, IntBuffer lowerLevel, IntBuffer upperLevel)
@Namespace(value="cv::cuda") public static void histEven(@ByVal Mat src, GpuMat hist, int[] histSize, int[] lowerLevel, int[] upperLevel, @ByRef(nullValue="cv::cuda::Stream::Null()") Stream stream)
@Namespace(value="cv::cuda") public static void histEven(@ByVal Mat src, GpuMat hist, int[] histSize, int[] lowerLevel, int[] upperLevel)
@Namespace(value="cv::cuda") public static void histEven(@ByVal UMat src, GpuMat hist, IntPointer histSize, IntPointer lowerLevel, IntPointer upperLevel, @ByRef(nullValue="cv::cuda::Stream::Null()") Stream stream)
@Namespace(value="cv::cuda") public static void histEven(@ByVal UMat src, GpuMat hist, IntPointer histSize, IntPointer lowerLevel, IntPointer upperLevel)
@Namespace(value="cv::cuda") public static void histEven(@ByVal UMat src, GpuMat hist, IntBuffer histSize, IntBuffer lowerLevel, IntBuffer upperLevel, @ByRef(nullValue="cv::cuda::Stream::Null()") Stream stream)
@Namespace(value="cv::cuda") public static void histEven(@ByVal UMat src, GpuMat hist, IntBuffer histSize, IntBuffer lowerLevel, IntBuffer upperLevel)
@Namespace(value="cv::cuda") public static void histEven(@ByVal UMat src, GpuMat hist, int[] histSize, int[] lowerLevel, int[] upperLevel, @ByRef(nullValue="cv::cuda::Stream::Null()") Stream stream)
@Namespace(value="cv::cuda") public static void histEven(@ByVal UMat src, GpuMat hist, int[] histSize, int[] lowerLevel, int[] upperLevel)
@Namespace(value="cv::cuda") public static void histEven(@ByVal GpuMat src, GpuMat hist, IntPointer histSize, IntPointer lowerLevel, IntPointer upperLevel, @ByRef(nullValue="cv::cuda::Stream::Null()") Stream stream)
@Namespace(value="cv::cuda") public static void histEven(@ByVal GpuMat src, GpuMat hist, IntPointer histSize, IntPointer lowerLevel, IntPointer upperLevel)
@Namespace(value="cv::cuda") public static void histEven(@ByVal GpuMat src, GpuMat hist, IntBuffer histSize, IntBuffer lowerLevel, IntBuffer upperLevel, @ByRef(nullValue="cv::cuda::Stream::Null()") Stream stream)
@Namespace(value="cv::cuda") public static void histEven(@ByVal GpuMat src, GpuMat hist, IntBuffer histSize, IntBuffer lowerLevel, IntBuffer upperLevel)
@Namespace(value="cv::cuda") public static void histEven(@ByVal GpuMat src, GpuMat hist, int[] histSize, int[] lowerLevel, int[] upperLevel, @ByRef(nullValue="cv::cuda::Stream::Null()") Stream stream)
@Namespace(value="cv::cuda") public static void histEven(@ByVal GpuMat src, GpuMat hist, int[] histSize, int[] lowerLevel, int[] upperLevel)
@Namespace(value="cv::cuda") public static void histRange(@ByVal Mat src, @ByVal Mat hist, @ByVal Mat levels, @ByRef(nullValue="cv::cuda::Stream::Null()") Stream stream)
src
- Source image. CV_8U , CV_16U , or CV_16S depth and 1 or 4 channels are supported.
For a four-channel image, all channels are processed separately.hist
- Destination histogram with one row, (levels.cols-1) columns, and the CV_32SC1 type.levels
- Number of levels in the histogram.stream
- Stream for the asynchronous version.@Namespace(value="cv::cuda") public static void histRange(@ByVal Mat src, @ByVal Mat hist, @ByVal Mat levels)
@Namespace(value="cv::cuda") public static void histRange(@ByVal UMat src, @ByVal UMat hist, @ByVal UMat levels, @ByRef(nullValue="cv::cuda::Stream::Null()") Stream stream)
@Namespace(value="cv::cuda") public static void histRange(@ByVal UMat src, @ByVal UMat hist, @ByVal UMat levels)
@Namespace(value="cv::cuda") public static void histRange(@ByVal GpuMat src, @ByVal GpuMat hist, @ByVal GpuMat levels, @ByRef(nullValue="cv::cuda::Stream::Null()") Stream stream)
@Namespace(value="cv::cuda") public static void histRange(@ByVal GpuMat src, @ByVal GpuMat hist, @ByVal GpuMat levels)
@Namespace(value="cv::cuda") public static void histRange(@ByVal Mat src, GpuMat hist, @Const GpuMat levels, @ByRef(nullValue="cv::cuda::Stream::Null()") Stream stream)
@Namespace(value="cv::cuda") public static void histRange(@ByVal Mat src, GpuMat hist, @Const GpuMat levels)
@Namespace(value="cv::cuda") public static void histRange(@ByVal UMat src, GpuMat hist, @Const GpuMat levels, @ByRef(nullValue="cv::cuda::Stream::Null()") Stream stream)
@Namespace(value="cv::cuda") public static void histRange(@ByVal UMat src, GpuMat hist, @Const GpuMat levels)
@Namespace(value="cv::cuda") @opencv_core.Ptr public static CannyEdgeDetector createCannyEdgeDetector(double low_thresh, double high_thresh, int apperture_size, @Cast(value="bool") boolean L2gradient)
low_thresh
- First threshold for the hysteresis procedure.high_thresh
- Second threshold for the hysteresis procedure.apperture_size
- Aperture size for the Sobel operator.L2gradient
- Flag indicating whether a more accurate L_2
norm
=\sqrt{(dI/dx)^2 + (dI/dy)^2}
should be used to compute the image gradient magnitude (
L2gradient=true ), or a faster default L_1
norm =|dI/dx|+|dI/dy|
is enough ( L2gradient=false
).@Namespace(value="cv::cuda") @opencv_core.Ptr public static CannyEdgeDetector createCannyEdgeDetector(double low_thresh, double high_thresh)
@Namespace(value="cv::cuda") @opencv_core.Ptr public static HoughLinesDetector createHoughLinesDetector(float rho, float theta, int threshold, @Cast(value="bool") boolean doSort, int maxLines)
rho
- Distance resolution of the accumulator in pixels.theta
- Angle resolution of the accumulator in radians.threshold
- Accumulator threshold parameter. Only those lines are returned that get enough
votes ( >\texttt{threshold}
).doSort
- Performs lines sort by votes.maxLines
- Maximum number of output lines.@Namespace(value="cv::cuda") @opencv_core.Ptr public static HoughLinesDetector createHoughLinesDetector(float rho, float theta, int threshold)
@Namespace(value="cv::cuda") @opencv_core.Ptr public static HoughSegmentDetector createHoughSegmentDetector(float rho, float theta, int minLineLength, int maxLineGap, int maxLines)
rho
- Distance resolution of the accumulator in pixels.theta
- Angle resolution of the accumulator in radians.minLineLength
- Minimum line length. Line segments shorter than that are rejected.maxLineGap
- Maximum allowed gap between points on the same line to link them.maxLines
- Maximum number of output lines.@Namespace(value="cv::cuda") @opencv_core.Ptr public static HoughSegmentDetector createHoughSegmentDetector(float rho, float theta, int minLineLength, int maxLineGap)
@Namespace(value="cv::cuda") @opencv_core.Ptr public static HoughCirclesDetector createHoughCirclesDetector(float dp, float minDist, int cannyThreshold, int votesThreshold, int minRadius, int maxRadius, int maxCircles)
dp
- Inverse ratio of the accumulator resolution to the image resolution. For example, if
dp=1 , the accumulator has the same resolution as the input image. If dp=2 , the accumulator has
half as big width and height.minDist
- Minimum distance between the centers of the detected circles. If the parameter is
too small, multiple neighbor circles may be falsely detected in addition to a true one. If it is
too large, some circles may be missed.cannyThreshold
- The higher threshold of the two passed to Canny edge detector (the lower one
is twice smaller).votesThreshold
- The accumulator threshold for the circle centers at the detection stage. The
smaller it is, the more false circles may be detected.minRadius
- Minimum circle radius.maxRadius
- Maximum circle radius.maxCircles
- Maximum number of output circles.@Namespace(value="cv::cuda") @opencv_core.Ptr public static HoughCirclesDetector createHoughCirclesDetector(float dp, float minDist, int cannyThreshold, int votesThreshold, int minRadius, int maxRadius)
@Namespace(value="cv::cuda") @opencv_core.Ptr public static GeneralizedHoughBallard createGeneralizedHoughBallard()
@Namespace(value="cv::cuda") @opencv_core.Ptr public static GeneralizedHoughGuil createGeneralizedHoughGuil()
@Namespace(value="cv::cuda") @opencv_core.Ptr public static CornernessCriteria createHarrisCorner(int srcType, int blockSize, int ksize, double k, int borderType)
srcType
- Input source type. Only CV_8UC1 and CV_32FC1 are supported for now.blockSize
- Neighborhood size.ksize
- Aperture parameter for the Sobel operator.k
- Harris detector free parameter.borderType
- Pixel extrapolation method. Only BORDER_REFLECT101 and BORDER_REPLICATE are
supported for now.
cornerHarris
@Namespace(value="cv::cuda") @opencv_core.Ptr public static CornernessCriteria createHarrisCorner(int srcType, int blockSize, int ksize, double k)
@Namespace(value="cv::cuda") @opencv_core.Ptr public static CornernessCriteria createMinEigenValCorner(int srcType, int blockSize, int ksize, int borderType)
srcType
- Input source type. Only CV_8UC1 and CV_32FC1 are supported for now.blockSize
- Neighborhood size.ksize
- Aperture parameter for the Sobel operator.borderType
- Pixel extrapolation method. Only BORDER_REFLECT101 and BORDER_REPLICATE are
supported for now.
cornerMinEigenVal
@Namespace(value="cv::cuda") @opencv_core.Ptr public static CornernessCriteria createMinEigenValCorner(int srcType, int blockSize, int ksize)
@Namespace(value="cv::cuda") @opencv_core.Ptr public static CornersDetector createGoodFeaturesToTrackDetector(int srcType, int maxCorners, double qualityLevel, double minDistance, int blockSize, @Cast(value="bool") boolean useHarrisDetector, double harrisK)
srcType
- Input source type. Only CV_8UC1 and CV_32FC1 are supported for now.maxCorners
- Maximum number of corners to return. If there are more corners than are found,
the strongest of them is returned.qualityLevel
- Parameter characterizing the minimal accepted quality of image corners. The
parameter value is multiplied by the best corner quality measure, which is the minimal eigenvalue
(see cornerMinEigenVal ) or the Harris function response (see cornerHarris ). The corners with the
quality measure less than the product are rejected. For example, if the best corner has the
quality measure = 1500, and the qualityLevel=0.01 , then all the corners with the quality measure
less than 15 are rejected.minDistance
- Minimum possible Euclidean distance between the returned corners.blockSize
- Size of an average block for computing a derivative covariation matrix over each
pixel neighborhood. See cornerEigenValsAndVecs .useHarrisDetector
- Parameter indicating whether to use a Harris detector (see cornerHarris)
or cornerMinEigenVal.harrisK
- Free parameter of the Harris detector.@Namespace(value="cv::cuda") @opencv_core.Ptr public static CornersDetector createGoodFeaturesToTrackDetector(int srcType)
@Namespace(value="cv::cuda") public static void meanShiftFiltering(@ByVal Mat src, @ByVal Mat dst, int sp, int sr, @ByVal(nullValue="cv::TermCriteria(cv::TermCriteria::MAX_ITER + cv::TermCriteria::EPS, 5, 1)") TermCriteria criteria, @ByRef(nullValue="cv::cuda::Stream::Null()") Stream stream)
///////////////////////////// Mean Shift //////////////////////////////
/** \brief Performs mean-shift filtering for each point of the source image.
src
- Source image. Only CV_8UC4 images are supported for now.dst
- Destination image containing the color of mapped points. It has the same size and type
as src .sp
- Spatial window radius.sr
- Color window radius.criteria
- Termination criteria. See TermCriteria.stream
- Stream for the asynchronous version.
It maps each point of the source image into another point. As a result, you have a new color and new position of each point.
@Namespace(value="cv::cuda") public static void meanShiftFiltering(@ByVal Mat src, @ByVal Mat dst, int sp, int sr)
@Namespace(value="cv::cuda") public static void meanShiftFiltering(@ByVal UMat src, @ByVal UMat dst, int sp, int sr, @ByVal(nullValue="cv::TermCriteria(cv::TermCriteria::MAX_ITER + cv::TermCriteria::EPS, 5, 1)") TermCriteria criteria, @ByRef(nullValue="cv::cuda::Stream::Null()") Stream stream)
@Namespace(value="cv::cuda") public static void meanShiftFiltering(@ByVal UMat src, @ByVal UMat dst, int sp, int sr)
@Namespace(value="cv::cuda") public static void meanShiftFiltering(@ByVal GpuMat src, @ByVal GpuMat dst, int sp, int sr, @ByVal(nullValue="cv::TermCriteria(cv::TermCriteria::MAX_ITER + cv::TermCriteria::EPS, 5, 1)") TermCriteria criteria, @ByRef(nullValue="cv::cuda::Stream::Null()") Stream stream)
@Namespace(value="cv::cuda") public static void meanShiftFiltering(@ByVal GpuMat src, @ByVal GpuMat dst, int sp, int sr)
@Namespace(value="cv::cuda") public static void meanShiftProc(@ByVal Mat src, @ByVal Mat dstr, @ByVal Mat dstsp, int sp, int sr, @ByVal(nullValue="cv::TermCriteria(cv::TermCriteria::MAX_ITER + cv::TermCriteria::EPS, 5, 1)") TermCriteria criteria, @ByRef(nullValue="cv::cuda::Stream::Null()") Stream stream)
src
- Source image. Only CV_8UC4 images are supported for now.dstr
- Destination image containing the color of mapped points. The size and type is the same
as src .dstsp
- Destination image containing the position of mapped points. The size is the same as
src size. The type is CV_16SC2 .sp
- Spatial window radius.sr
- Color window radius.criteria
- Termination criteria. See TermCriteria.stream
- Stream for the asynchronous version.
cuda::meanShiftFiltering
@Namespace(value="cv::cuda") public static void meanShiftProc(@ByVal Mat src, @ByVal Mat dstr, @ByVal Mat dstsp, int sp, int sr)
@Namespace(value="cv::cuda") public static void meanShiftProc(@ByVal UMat src, @ByVal UMat dstr, @ByVal UMat dstsp, int sp, int sr, @ByVal(nullValue="cv::TermCriteria(cv::TermCriteria::MAX_ITER + cv::TermCriteria::EPS, 5, 1)") TermCriteria criteria, @ByRef(nullValue="cv::cuda::Stream::Null()") Stream stream)
@Namespace(value="cv::cuda") public static void meanShiftProc(@ByVal UMat src, @ByVal UMat dstr, @ByVal UMat dstsp, int sp, int sr)
@Namespace(value="cv::cuda") public static void meanShiftProc(@ByVal GpuMat src, @ByVal GpuMat dstr, @ByVal GpuMat dstsp, int sp, int sr, @ByVal(nullValue="cv::TermCriteria(cv::TermCriteria::MAX_ITER + cv::TermCriteria::EPS, 5, 1)") TermCriteria criteria, @ByRef(nullValue="cv::cuda::Stream::Null()") Stream stream)
@Namespace(value="cv::cuda") public static void meanShiftProc(@ByVal GpuMat src, @ByVal GpuMat dstr, @ByVal GpuMat dstsp, int sp, int sr)
@Namespace(value="cv::cuda") public static void meanShiftSegmentation(@ByVal Mat src, @ByVal Mat dst, int sp, int sr, int minsize, @ByVal(nullValue="cv::TermCriteria(cv::TermCriteria::MAX_ITER + cv::TermCriteria::EPS, 5, 1)") TermCriteria criteria, @ByRef(nullValue="cv::cuda::Stream::Null()") Stream stream)
src
- Source image. Only CV_8UC4 images are supported for now.dst
- Segmented image with the same size and type as src (host or gpu memory).sp
- Spatial window radius.sr
- Color window radius.minsize
- Minimum segment size. Smaller segments are merged.criteria
- Termination criteria. See TermCriteria.stream
- Stream for the asynchronous version.@Namespace(value="cv::cuda") public static void meanShiftSegmentation(@ByVal Mat src, @ByVal Mat dst, int sp, int sr, int minsize)
@Namespace(value="cv::cuda") public static void meanShiftSegmentation(@ByVal UMat src, @ByVal UMat dst, int sp, int sr, int minsize, @ByVal(nullValue="cv::TermCriteria(cv::TermCriteria::MAX_ITER + cv::TermCriteria::EPS, 5, 1)") TermCriteria criteria, @ByRef(nullValue="cv::cuda::Stream::Null()") Stream stream)
@Namespace(value="cv::cuda") public static void meanShiftSegmentation(@ByVal UMat src, @ByVal UMat dst, int sp, int sr, int minsize)
@Namespace(value="cv::cuda") public static void meanShiftSegmentation(@ByVal GpuMat src, @ByVal GpuMat dst, int sp, int sr, int minsize, @ByVal(nullValue="cv::TermCriteria(cv::TermCriteria::MAX_ITER + cv::TermCriteria::EPS, 5, 1)") TermCriteria criteria, @ByRef(nullValue="cv::cuda::Stream::Null()") Stream stream)
@Namespace(value="cv::cuda") public static void meanShiftSegmentation(@ByVal GpuMat src, @ByVal GpuMat dst, int sp, int sr, int minsize)
@Namespace(value="cv::cuda") @opencv_core.Ptr public static TemplateMatching createTemplateMatching(int srcType, int method, @ByVal(nullValue="cv::Size()") Size user_block_size)
srcType
- Input source type. CV_32F and CV_8U depth images (1..4 channels) are supported
for now.method
- Specifies the way to compare the template with the image.user_block_size
- You can use field user_block_size to set specific block size. If you
leave its default value Size(0,0) then automatic estimation of block size will be used (which is
optimized for speed). By varying user_block_size you can reduce memory requirements at the cost
of speed.
The following methods are supported for the CV_8U depth images for now:
- CV_TM_SQDIFF - CV_TM_SQDIFF_NORMED - CV_TM_CCORR - CV_TM_CCORR_NORMED - CV_TM_CCOEFF - CV_TM_CCOEFF_NORMED
The following methods are supported for the CV_32F images for now:
- CV_TM_SQDIFF - CV_TM_CCORR
matchTemplate
@Namespace(value="cv::cuda") @opencv_core.Ptr public static TemplateMatching createTemplateMatching(int srcType, int method)
@Namespace(value="cv::cuda") public static void bilateralFilter(@ByVal Mat src, @ByVal Mat dst, int kernel_size, float sigma_color, float sigma_spatial, int borderMode, @ByRef(nullValue="cv::cuda::Stream::Null()") Stream stream)
src
- Source image. Supports only (channels != 2 && depth() != CV_8S && depth() != CV_32S
&& depth() != CV_64F).dst
- Destination imagwe.kernel_size
- Kernel window size.sigma_color
- Filter sigma in the color space.sigma_spatial
- Filter sigma in the coordinate space.borderMode
- Border type. See borderInterpolate for details. BORDER_REFLECT101 ,
BORDER_REPLICATE , BORDER_CONSTANT , BORDER_REFLECT and BORDER_WRAP are supported for now.stream
- Stream for the asynchronous version.
bilateralFilter
@Namespace(value="cv::cuda") public static void bilateralFilter(@ByVal Mat src, @ByVal Mat dst, int kernel_size, float sigma_color, float sigma_spatial)
@Namespace(value="cv::cuda") public static void bilateralFilter(@ByVal UMat src, @ByVal UMat dst, int kernel_size, float sigma_color, float sigma_spatial, int borderMode, @ByRef(nullValue="cv::cuda::Stream::Null()") Stream stream)
@Namespace(value="cv::cuda") public static void bilateralFilter(@ByVal UMat src, @ByVal UMat dst, int kernel_size, float sigma_color, float sigma_spatial)
@Namespace(value="cv::cuda") public static void bilateralFilter(@ByVal GpuMat src, @ByVal GpuMat dst, int kernel_size, float sigma_color, float sigma_spatial, int borderMode, @ByRef(nullValue="cv::cuda::Stream::Null()") Stream stream)
@Namespace(value="cv::cuda") public static void bilateralFilter(@ByVal GpuMat src, @ByVal GpuMat dst, int kernel_size, float sigma_color, float sigma_spatial)
@Namespace(value="cv::cuda") public static void blendLinear(@ByVal Mat img1, @ByVal Mat img2, @ByVal Mat weights1, @ByVal Mat weights2, @ByVal Mat result, @ByRef(nullValue="cv::cuda::Stream::Null()") Stream stream)
img1
- First image. Supports only CV_8U and CV_32F depth.img2
- Second image. Must have the same size and the same type as img1 .weights1
- Weights for first image. Must have tha same size as img1 . Supports only CV_32F
type.weights2
- Weights for second image. Must have tha same size as img2 . Supports only CV_32F
type.result
- Destination image.stream
- Stream for the asynchronous version.@Namespace(value="cv::cuda") public static void blendLinear(@ByVal Mat img1, @ByVal Mat img2, @ByVal Mat weights1, @ByVal Mat weights2, @ByVal Mat result)
@Namespace(value="cv::cuda") public static void blendLinear(@ByVal UMat img1, @ByVal UMat img2, @ByVal UMat weights1, @ByVal UMat weights2, @ByVal UMat result, @ByRef(nullValue="cv::cuda::Stream::Null()") Stream stream)
@Namespace(value="cv::cuda") public static void blendLinear(@ByVal UMat img1, @ByVal UMat img2, @ByVal UMat weights1, @ByVal UMat weights2, @ByVal UMat result)
@Namespace(value="cv::cuda") public static void blendLinear(@ByVal GpuMat img1, @ByVal GpuMat img2, @ByVal GpuMat weights1, @ByVal GpuMat weights2, @ByVal GpuMat result, @ByRef(nullValue="cv::cuda::Stream::Null()") Stream stream)
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