gpuimgproc module fixes
This commit is contained in:
Vladislav Vinogradov
@@ -48,31 +48,13 @@
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#endif
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#include "opencv2/core/gpumat.hpp"
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#include "opencv2/gpufilters.hpp"
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#include "opencv2/core/base.hpp"
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#include "opencv2/imgproc.hpp"
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#include "opencv2/gpufilters.hpp"
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namespace cv { namespace gpu {
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enum { ALPHA_OVER, ALPHA_IN, ALPHA_OUT, ALPHA_ATOP, ALPHA_XOR, ALPHA_PLUS, ALPHA_OVER_PREMUL, ALPHA_IN_PREMUL, ALPHA_OUT_PREMUL,
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ALPHA_ATOP_PREMUL, ALPHA_XOR_PREMUL, ALPHA_PLUS_PREMUL, ALPHA_PREMUL};
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//! Composite two images using alpha opacity values contained in each image
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//! Supports CV_8UC4, CV_16UC4, CV_32SC4 and CV_32FC4 types
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CV_EXPORTS void alphaComp(const GpuMat& img1, const GpuMat& img2, GpuMat& dst, int alpha_op, Stream& stream = Stream::Null());
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//! Does mean shift filtering on GPU.
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CV_EXPORTS void meanShiftFiltering(const GpuMat& src, GpuMat& dst, int sp, int sr,
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TermCriteria criteria = TermCriteria(TermCriteria::MAX_ITER + TermCriteria::EPS, 5, 1),
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Stream& stream = Stream::Null());
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//! Does mean shift procedure on GPU.
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CV_EXPORTS void meanShiftProc(const GpuMat& src, GpuMat& dstr, GpuMat& dstsp, int sp, int sr,
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TermCriteria criteria = TermCriteria(TermCriteria::MAX_ITER + TermCriteria::EPS, 5, 1),
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Stream& stream = Stream::Null());
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//! Does mean shift segmentation with elimination of small regions.
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CV_EXPORTS void meanShiftSegmentation(const GpuMat& src, Mat& dst, int sp, int sr, int minsize,
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TermCriteria criteria = TermCriteria(TermCriteria::MAX_ITER + TermCriteria::EPS, 5, 1));
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/////////////////////////// Color Processing ///////////////////////////
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//! converts image from one color space to another
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CV_EXPORTS void cvtColor(const GpuMat& src, GpuMat& dst, int code, int dcn = 0, Stream& stream = Stream::Null());
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@@ -107,41 +89,65 @@ CV_EXPORTS void swapChannels(GpuMat& image, const int dstOrder[4], Stream& strea
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//! Routines for correcting image color gamma
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CV_EXPORTS void gammaCorrection(const GpuMat& src, GpuMat& dst, bool forward = true, Stream& stream = Stream::Null());
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//! computes Harris cornerness criteria at each image pixel
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CV_EXPORTS void cornerHarris(const GpuMat& src, GpuMat& dst, int blockSize, int ksize, double k, int borderType = BORDER_REFLECT101);
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CV_EXPORTS void cornerHarris(const GpuMat& src, GpuMat& dst, GpuMat& Dx, GpuMat& Dy, int blockSize, int ksize, double k, int borderType = BORDER_REFLECT101);
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CV_EXPORTS void cornerHarris(const GpuMat& src, GpuMat& dst, GpuMat& Dx, GpuMat& Dy, GpuMat& buf, int blockSize, int ksize, double k,
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int borderType = BORDER_REFLECT101, Stream& stream = Stream::Null());
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enum { ALPHA_OVER, ALPHA_IN, ALPHA_OUT, ALPHA_ATOP, ALPHA_XOR, ALPHA_PLUS, ALPHA_OVER_PREMUL, ALPHA_IN_PREMUL, ALPHA_OUT_PREMUL,
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ALPHA_ATOP_PREMUL, ALPHA_XOR_PREMUL, ALPHA_PLUS_PREMUL, ALPHA_PREMUL};
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//! computes minimum eigen value of 2x2 derivative covariation matrix at each pixel - the cornerness criteria
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CV_EXPORTS void cornerMinEigenVal(const GpuMat& src, GpuMat& dst, int blockSize, int ksize, int borderType=BORDER_REFLECT101);
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CV_EXPORTS void cornerMinEigenVal(const GpuMat& src, GpuMat& dst, GpuMat& Dx, GpuMat& Dy, int blockSize, int ksize, int borderType=BORDER_REFLECT101);
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CV_EXPORTS void cornerMinEigenVal(const GpuMat& src, GpuMat& dst, GpuMat& Dx, GpuMat& Dy, GpuMat& buf, int blockSize, int ksize,
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int borderType=BORDER_REFLECT101, Stream& stream = Stream::Null());
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//! Composite two images using alpha opacity values contained in each image
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//! Supports CV_8UC4, CV_16UC4, CV_32SC4 and CV_32FC4 types
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CV_EXPORTS void alphaComp(const GpuMat& img1, const GpuMat& img2, GpuMat& dst, int alpha_op, Stream& stream = Stream::Null());
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struct CV_EXPORTS MatchTemplateBuf
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////////////////////////////// Histogram ///////////////////////////////
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//! Compute levels with even distribution. levels will have 1 row and nLevels cols and CV_32SC1 type.
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CV_EXPORTS void evenLevels(GpuMat& levels, int nLevels, int lowerLevel, int upperLevel);
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//! Calculates histogram with evenly distributed bins for signle channel source.
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//! Supports CV_8UC1, CV_16UC1 and CV_16SC1 source types.
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//! Output hist will have one row and histSize cols and CV_32SC1 type.
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CV_EXPORTS void histEven(const GpuMat& src, GpuMat& hist, int histSize, int lowerLevel, int upperLevel, Stream& stream = Stream::Null());
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CV_EXPORTS void histEven(const GpuMat& src, GpuMat& hist, GpuMat& buf, int histSize, int lowerLevel, int upperLevel, Stream& stream = Stream::Null());
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//! Calculates histogram with evenly distributed bins for four-channel source.
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//! All channels of source are processed separately.
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//! Supports CV_8UC4, CV_16UC4 and CV_16SC4 source types.
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//! Output hist[i] will have one row and histSize[i] cols and CV_32SC1 type.
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CV_EXPORTS void histEven(const GpuMat& src, GpuMat hist[4], int histSize[4], int lowerLevel[4], int upperLevel[4], Stream& stream = Stream::Null());
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CV_EXPORTS void histEven(const GpuMat& src, GpuMat hist[4], GpuMat& buf, int histSize[4], int lowerLevel[4], int upperLevel[4], Stream& stream = Stream::Null());
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//! Calculates histogram with bins determined by levels array.
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//! levels must have one row and CV_32SC1 type if source has integer type or CV_32FC1 otherwise.
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//! Supports CV_8UC1, CV_16UC1, CV_16SC1 and CV_32FC1 source types.
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//! Output hist will have one row and (levels.cols-1) cols and CV_32SC1 type.
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CV_EXPORTS void histRange(const GpuMat& src, GpuMat& hist, const GpuMat& levels, Stream& stream = Stream::Null());
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CV_EXPORTS void histRange(const GpuMat& src, GpuMat& hist, const GpuMat& levels, GpuMat& buf, Stream& stream = Stream::Null());
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//! Calculates histogram with bins determined by levels array.
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//! All levels must have one row and CV_32SC1 type if source has integer type or CV_32FC1 otherwise.
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//! All channels of source are processed separately.
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//! Supports CV_8UC4, CV_16UC4, CV_16SC4 and CV_32FC4 source types.
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//! Output hist[i] will have one row and (levels[i].cols-1) cols and CV_32SC1 type.
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CV_EXPORTS void histRange(const GpuMat& src, GpuMat hist[4], const GpuMat levels[4], Stream& stream = Stream::Null());
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CV_EXPORTS void histRange(const GpuMat& src, GpuMat hist[4], const GpuMat levels[4], GpuMat& buf, Stream& stream = Stream::Null());
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//! Calculates histogram for 8u one channel image
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//! Output hist will have one row, 256 cols and CV32SC1 type.
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CV_EXPORTS void calcHist(const GpuMat& src, GpuMat& hist, Stream& stream = Stream::Null());
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CV_EXPORTS void calcHist(const GpuMat& src, GpuMat& hist, GpuMat& buf, Stream& stream = Stream::Null());
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//! normalizes the grayscale image brightness and contrast by normalizing its histogram
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CV_EXPORTS void equalizeHist(const GpuMat& src, GpuMat& dst, Stream& stream = Stream::Null());
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CV_EXPORTS void equalizeHist(const GpuMat& src, GpuMat& dst, GpuMat& hist, Stream& stream = Stream::Null());
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CV_EXPORTS void equalizeHist(const GpuMat& src, GpuMat& dst, GpuMat& hist, GpuMat& buf, Stream& stream = Stream::Null());
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class CV_EXPORTS CLAHE : public cv::CLAHE
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{
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Size user_block_size;
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GpuMat imagef, templf;
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std::vector<GpuMat> images;
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std::vector<GpuMat> image_sums;
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std::vector<GpuMat> image_sqsums;
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public:
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using cv::CLAHE::apply;
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virtual void apply(InputArray src, OutputArray dst, Stream& stream) = 0;
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};
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CV_EXPORTS Ptr<cv::gpu::CLAHE> createCLAHE(double clipLimit = 40.0, Size tileGridSize = Size(8, 8));
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//! computes the proximity map for the raster template and the image where the template is searched for
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CV_EXPORTS void matchTemplate(const GpuMat& image, const GpuMat& templ, GpuMat& result, int method, Stream &stream = Stream::Null());
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//! computes the proximity map for the raster template and the image where the template is searched for
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CV_EXPORTS void matchTemplate(const GpuMat& image, const GpuMat& templ, GpuMat& result, int method, MatchTemplateBuf &buf, Stream& stream = Stream::Null());
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//! performs linear blending of two images
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//! to avoid accuracy errors sum of weigths shouldn't be very close to zero
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CV_EXPORTS void blendLinear(const GpuMat& img1, const GpuMat& img2, const GpuMat& weights1, const GpuMat& weights2,
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GpuMat& result, Stream& stream = Stream::Null());
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//! Performa bilateral filtering of passsed image
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CV_EXPORTS void bilateralFilter(const GpuMat& src, GpuMat& dst, int kernel_size, float sigma_color, float sigma_spatial,
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int borderMode = BORDER_DEFAULT, Stream& stream = Stream::Null());
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//////////////////////////////// Canny ////////////////////////////////
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struct CV_EXPORTS CannyBuf
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{
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@@ -160,7 +166,7 @@ CV_EXPORTS void Canny(const GpuMat& image, CannyBuf& buf, GpuMat& edges, double
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CV_EXPORTS void Canny(const GpuMat& dx, const GpuMat& dy, GpuMat& edges, double low_thresh, double high_thresh, bool L2gradient = false);
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CV_EXPORTS void Canny(const GpuMat& dx, const GpuMat& dy, CannyBuf& buf, GpuMat& edges, double low_thresh, double high_thresh, bool L2gradient = false);
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//! HoughLines
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/////////////////////////// Hough Transform ////////////////////////////
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struct HoughLinesBuf
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{
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@@ -172,13 +178,9 @@ CV_EXPORTS void HoughLines(const GpuMat& src, GpuMat& lines, float rho, float th
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CV_EXPORTS void HoughLines(const GpuMat& src, GpuMat& lines, HoughLinesBuf& buf, float rho, float theta, int threshold, bool doSort = false, int maxLines = 4096);
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CV_EXPORTS void HoughLinesDownload(const GpuMat& d_lines, OutputArray h_lines, OutputArray h_votes = noArray());
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//! HoughLinesP
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//! finds line segments in the black-n-white image using probabalistic Hough transform
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CV_EXPORTS void HoughLinesP(const GpuMat& image, GpuMat& lines, HoughLinesBuf& buf, float rho, float theta, int minLineLength, int maxLineGap, int maxLines = 4096);
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//! HoughCircles
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struct HoughCirclesBuf
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{
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GpuMat edges;
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@@ -223,50 +225,21 @@ private:
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CannyBuf cannyBuf_;
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};
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//! Compute levels with even distribution. levels will have 1 row and nLevels cols and CV_32SC1 type.
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CV_EXPORTS void evenLevels(GpuMat& levels, int nLevels, int lowerLevel, int upperLevel);
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//! Calculates histogram with evenly distributed bins for signle channel source.
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//! Supports CV_8UC1, CV_16UC1 and CV_16SC1 source types.
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//! Output hist will have one row and histSize cols and CV_32SC1 type.
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CV_EXPORTS void histEven(const GpuMat& src, GpuMat& hist, int histSize, int lowerLevel, int upperLevel, Stream& stream = Stream::Null());
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CV_EXPORTS void histEven(const GpuMat& src, GpuMat& hist, GpuMat& buf, int histSize, int lowerLevel, int upperLevel, Stream& stream = Stream::Null());
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//! Calculates histogram with evenly distributed bins for four-channel source.
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//! All channels of source are processed separately.
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//! Supports CV_8UC4, CV_16UC4 and CV_16SC4 source types.
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//! Output hist[i] will have one row and histSize[i] cols and CV_32SC1 type.
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CV_EXPORTS void histEven(const GpuMat& src, GpuMat hist[4], int histSize[4], int lowerLevel[4], int upperLevel[4], Stream& stream = Stream::Null());
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CV_EXPORTS void histEven(const GpuMat& src, GpuMat hist[4], GpuMat& buf, int histSize[4], int lowerLevel[4], int upperLevel[4], Stream& stream = Stream::Null());
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//! Calculates histogram with bins determined by levels array.
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//! levels must have one row and CV_32SC1 type if source has integer type or CV_32FC1 otherwise.
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//! Supports CV_8UC1, CV_16UC1, CV_16SC1 and CV_32FC1 source types.
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//! Output hist will have one row and (levels.cols-1) cols and CV_32SC1 type.
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CV_EXPORTS void histRange(const GpuMat& src, GpuMat& hist, const GpuMat& levels, Stream& stream = Stream::Null());
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CV_EXPORTS void histRange(const GpuMat& src, GpuMat& hist, const GpuMat& levels, GpuMat& buf, Stream& stream = Stream::Null());
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//! Calculates histogram with bins determined by levels array.
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//! All levels must have one row and CV_32SC1 type if source has integer type or CV_32FC1 otherwise.
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//! All channels of source are processed separately.
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//! Supports CV_8UC4, CV_16UC4, CV_16SC4 and CV_32FC4 source types.
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//! Output hist[i] will have one row and (levels[i].cols-1) cols and CV_32SC1 type.
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CV_EXPORTS void histRange(const GpuMat& src, GpuMat hist[4], const GpuMat levels[4], Stream& stream = Stream::Null());
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CV_EXPORTS void histRange(const GpuMat& src, GpuMat hist[4], const GpuMat levels[4], GpuMat& buf, Stream& stream = Stream::Null());
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////////////////////////// Corners Detection ///////////////////////////
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//! Calculates histogram for 8u one channel image
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//! Output hist will have one row, 256 cols and CV32SC1 type.
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CV_EXPORTS void calcHist(const GpuMat& src, GpuMat& hist, Stream& stream = Stream::Null());
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CV_EXPORTS void calcHist(const GpuMat& src, GpuMat& hist, GpuMat& buf, Stream& stream = Stream::Null());
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//! computes Harris cornerness criteria at each image pixel
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CV_EXPORTS void cornerHarris(const GpuMat& src, GpuMat& dst, int blockSize, int ksize, double k, int borderType = BORDER_REFLECT101);
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CV_EXPORTS void cornerHarris(const GpuMat& src, GpuMat& dst, GpuMat& Dx, GpuMat& Dy, int blockSize, int ksize, double k, int borderType = BORDER_REFLECT101);
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CV_EXPORTS void cornerHarris(const GpuMat& src, GpuMat& dst, GpuMat& Dx, GpuMat& Dy, GpuMat& buf, int blockSize, int ksize, double k,
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int borderType = BORDER_REFLECT101, Stream& stream = Stream::Null());
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//! normalizes the grayscale image brightness and contrast by normalizing its histogram
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CV_EXPORTS void equalizeHist(const GpuMat& src, GpuMat& dst, Stream& stream = Stream::Null());
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CV_EXPORTS void equalizeHist(const GpuMat& src, GpuMat& dst, GpuMat& hist, Stream& stream = Stream::Null());
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CV_EXPORTS void equalizeHist(const GpuMat& src, GpuMat& dst, GpuMat& hist, GpuMat& buf, Stream& stream = Stream::Null());
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//! computes minimum eigen value of 2x2 derivative covariation matrix at each pixel - the cornerness criteria
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CV_EXPORTS void cornerMinEigenVal(const GpuMat& src, GpuMat& dst, int blockSize, int ksize, int borderType=BORDER_REFLECT101);
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CV_EXPORTS void cornerMinEigenVal(const GpuMat& src, GpuMat& dst, GpuMat& Dx, GpuMat& Dy, int blockSize, int ksize, int borderType=BORDER_REFLECT101);
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CV_EXPORTS void cornerMinEigenVal(const GpuMat& src, GpuMat& dst, GpuMat& Dx, GpuMat& Dy, GpuMat& buf, int blockSize, int ksize,
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int borderType=BORDER_REFLECT101, Stream& stream = Stream::Null());
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class CV_EXPORTS CLAHE : public cv::CLAHE
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{
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public:
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using cv::CLAHE::apply;
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virtual void apply(InputArray src, OutputArray dst, Stream& stream) = 0;
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};
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CV_EXPORTS Ptr<cv::gpu::CLAHE> createCLAHE(double clipLimit = 40.0, Size tileGridSize = Size(8, 8));
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////////////////////////// Feature Detection ///////////////////////////
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class CV_EXPORTS GoodFeaturesToTrackDetector_GPU
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{
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@@ -315,6 +288,52 @@ inline GoodFeaturesToTrackDetector_GPU::GoodFeaturesToTrackDetector_GPU(int maxC
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harrisK = harrisK_;
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}
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///////////////////////////// Mean Shift //////////////////////////////
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//! Does mean shift filtering on GPU.
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CV_EXPORTS void meanShiftFiltering(const GpuMat& src, GpuMat& dst, int sp, int sr,
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TermCriteria criteria = TermCriteria(TermCriteria::MAX_ITER + TermCriteria::EPS, 5, 1),
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Stream& stream = Stream::Null());
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//! Does mean shift procedure on GPU.
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CV_EXPORTS void meanShiftProc(const GpuMat& src, GpuMat& dstr, GpuMat& dstsp, int sp, int sr,
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TermCriteria criteria = TermCriteria(TermCriteria::MAX_ITER + TermCriteria::EPS, 5, 1),
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Stream& stream = Stream::Null());
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//! Does mean shift segmentation with elimination of small regions.
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CV_EXPORTS void meanShiftSegmentation(const GpuMat& src, Mat& dst, int sp, int sr, int minsize,
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TermCriteria criteria = TermCriteria(TermCriteria::MAX_ITER + TermCriteria::EPS, 5, 1));
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/////////////////////////// Match Template ////////////////////////////
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struct CV_EXPORTS MatchTemplateBuf
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{
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Size user_block_size;
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GpuMat imagef, templf;
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std::vector<GpuMat> images;
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std::vector<GpuMat> image_sums;
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std::vector<GpuMat> image_sqsums;
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};
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//! computes the proximity map for the raster template and the image where the template is searched for
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CV_EXPORTS void matchTemplate(const GpuMat& image, const GpuMat& templ, GpuMat& result, int method, Stream &stream = Stream::Null());
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//! computes the proximity map for the raster template and the image where the template is searched for
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CV_EXPORTS void matchTemplate(const GpuMat& image, const GpuMat& templ, GpuMat& result, int method, MatchTemplateBuf &buf, Stream& stream = Stream::Null());
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////////////////////////// Bilateral Filter ///////////////////////////
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//! Performa bilateral filtering of passsed image
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CV_EXPORTS void bilateralFilter(const GpuMat& src, GpuMat& dst, int kernel_size, float sigma_color, float sigma_spatial,
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int borderMode = BORDER_DEFAULT, Stream& stream = Stream::Null());
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///////////////////////////// Blending ////////////////////////////////
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//! performs linear blending of two images
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//! to avoid accuracy errors sum of weigths shouldn't be very close to zero
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CV_EXPORTS void blendLinear(const GpuMat& img1, const GpuMat& img2, const GpuMat& weights1, const GpuMat& weights2,
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GpuMat& result, Stream& stream = Stream::Null());
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}} // namespace cv { namespace gpu {
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#endif /* __OPENCV_GPUIMGPROC_HPP__ */
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