mirror of
https://github.com/opencv/opencv.git
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added masks support for bitwise operations on GPU
This commit is contained in:
Alexey Spizhevoy
parent
3163cfb845
commit
732bd621bb
@ -474,53 +474,53 @@ namespace cv
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//! computes magnitude of each (x(i), y(i)) vector
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//! supports only floating-point source
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CV_EXPORTS void magnitude(const GpuMat& x, const GpuMat& y, GpuMat& magnitude);
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//! Async version
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//! async version
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CV_EXPORTS void magnitude(const GpuMat& x, const GpuMat& y, GpuMat& magnitude, const Stream& stream);
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//! computes squared magnitude of each (x(i), y(i)) vector
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//! supports only floating-point source
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CV_EXPORTS void magnitudeSqr(const GpuMat& x, const GpuMat& y, GpuMat& magnitude);
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//! Async version
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//! async version
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CV_EXPORTS void magnitudeSqr(const GpuMat& x, const GpuMat& y, GpuMat& magnitude, const Stream& stream);
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//! computes angle (angle(i)) of each (x(i), y(i)) vector
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//! supports only floating-point source
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CV_EXPORTS void phase(const GpuMat& x, const GpuMat& y, GpuMat& angle, bool angleInDegrees = false);
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//! Async version
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//! async version
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CV_EXPORTS void phase(const GpuMat& x, const GpuMat& y, GpuMat& angle, bool angleInDegrees, const Stream& stream);
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//! converts Cartesian coordinates to polar
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//! supports only floating-point source
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CV_EXPORTS void cartToPolar(const GpuMat& x, const GpuMat& y, GpuMat& magnitude, GpuMat& angle, bool angleInDegrees = false);
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//! Async version
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//! async version
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CV_EXPORTS void cartToPolar(const GpuMat& x, const GpuMat& y, GpuMat& magnitude, GpuMat& angle, bool angleInDegrees, const Stream& stream);
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//! converts polar coordinates to Cartesian
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//! supports only floating-point source
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CV_EXPORTS void polarToCart(const GpuMat& magnitude, const GpuMat& angle, GpuMat& x, GpuMat& y, bool angleInDegrees = false);
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//! Async version
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//! async version
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CV_EXPORTS void polarToCart(const GpuMat& magnitude, const GpuMat& angle, GpuMat& x, GpuMat& y, bool angleInDegrees, const Stream& stream);
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//! Perfroms per-elements bit-wise inversion
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CV_EXPORTS void bitwise_not(const GpuMat& src, GpuMat& dst);
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//! Async version
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CV_EXPORTS void bitwise_not(const GpuMat& src, GpuMat& dst, const Stream& stream);
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//! perfroms per-elements bit-wise inversion
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CV_EXPORTS void bitwise_not(const GpuMat& src, GpuMat& dst, const GpuMat& mask=GpuMat());
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//! async version
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CV_EXPORTS void bitwise_not(const GpuMat& src, GpuMat& dst, const GpuMat& mask, const Stream& stream);
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//! Calculates per-element bit-wise disjunction of two arrays
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CV_EXPORTS void bitwise_or(const GpuMat& src1, const GpuMat& src2, GpuMat& dst);
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//! Async version
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CV_EXPORTS void bitwise_or(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const Stream& stream);
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//! calculates per-element bit-wise disjunction of two arrays
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CV_EXPORTS void bitwise_or(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask=GpuMat());
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//! async version
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CV_EXPORTS void bitwise_or(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask, const Stream& stream);
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//! Calculates per-element bit-wise conjunction of two arrays
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CV_EXPORTS void bitwise_and(const GpuMat& src1, const GpuMat& src2, GpuMat& dst);
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//! Async version
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CV_EXPORTS void bitwise_and(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const Stream& stream);
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//! calculates per-element bit-wise conjunction of two arrays
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CV_EXPORTS void bitwise_and(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask=GpuMat());
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//! async version
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CV_EXPORTS void bitwise_and(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask, const Stream& stream);
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//! Calculates per-element bit-wise "exclusive or" operation
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CV_EXPORTS void bitwise_xor(const GpuMat& src1, const GpuMat& src2, GpuMat& dst);
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//! Async version
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CV_EXPORTS void bitwise_xor(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const Stream& stream);
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//! calculates per-element bit-wise "exclusive or" operation
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CV_EXPORTS void bitwise_xor(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask=GpuMat());
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//! async version
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CV_EXPORTS void bitwise_xor(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask, const Stream& stream);
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//! Logical operators
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CV_EXPORTS GpuMat operator ~ (const GpuMat& src);
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@ -551,7 +551,7 @@ namespace cv
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//! Supported types of input disparity: CV_8U, CV_16S.
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//! Output disparity has CV_8UC4 type in BGRA format (alpha = 255).
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CV_EXPORTS void drawColorDisp(const GpuMat& src_disp, GpuMat& dst_disp, int ndisp);
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//! Async version
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//! async version
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CV_EXPORTS void drawColorDisp(const GpuMat& src_disp, GpuMat& dst_disp, int ndisp, const Stream& stream);
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//! Reprojects disparity image to 3D space.
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@ -560,12 +560,12 @@ namespace cv
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//! Each element of this matrix will contain the 3D coordinates of the point (x,y,z,1), computed from the disparity map.
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//! Q is the 4x4 perspective transformation matrix that can be obtained with cvStereoRectify.
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CV_EXPORTS void reprojectImageTo3D(const GpuMat& disp, GpuMat& xyzw, const Mat& Q);
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//! Async version
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//! async version
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CV_EXPORTS void reprojectImageTo3D(const GpuMat& disp, GpuMat& xyzw, const Mat& Q, const Stream& stream);
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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);
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//! Async version
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//! async version
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CV_EXPORTS void cvtColor(const GpuMat& src, GpuMat& dst, int code, int dcn, const Stream& stream);
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//! applies fixed threshold to the image.
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@ -821,7 +821,7 @@ namespace cv
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//! Output disparity has CV_8U type.
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void operator() ( const GpuMat& left, const GpuMat& right, GpuMat& disparity);
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//! Async version
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//! async version
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void operator() ( const GpuMat& left, const GpuMat& right, GpuMat& disparity, const Stream & stream);
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//! Some heuristics that tries to estmate
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@ -876,7 +876,7 @@ namespace cv
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//! if disparity is empty output type will be CV_16S else output type will be disparity.type().
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void operator()(const GpuMat& left, const GpuMat& right, GpuMat& disparity);
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//! Async version
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//! async version
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void operator()(const GpuMat& left, const GpuMat& right, GpuMat& disparity, Stream& stream);
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@ -935,7 +935,7 @@ namespace cv
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//! if disparity is empty output type will be CV_16S else output type will be disparity.type().
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void operator()(const GpuMat& left, const GpuMat& right, GpuMat& disparity);
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//! Async version
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//! async version
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void operator()(const GpuMat& left, const GpuMat& right, GpuMat& disparity, Stream& stream);
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int ndisp;
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@ -991,7 +991,7 @@ namespace cv
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//! disparity must have CV_8U or CV_16S type, image must have CV_8UC1 or CV_8UC3 type.
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void operator()(const GpuMat& disparity, const GpuMat& image, GpuMat& dst);
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//! Async version
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//! async version
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void operator()(const GpuMat& disparity, const GpuMat& image, GpuMat& dst, Stream& stream);
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private:
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@ -81,14 +81,14 @@ void cv::gpu::cartToPolar(const GpuMat&, const GpuMat&, GpuMat&, GpuMat&, bool)
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void cv::gpu::cartToPolar(const GpuMat&, const GpuMat&, GpuMat&, GpuMat&, bool, const Stream&) { throw_nogpu(); }
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void cv::gpu::polarToCart(const GpuMat&, const GpuMat&, GpuMat&, GpuMat&, bool) { throw_nogpu(); }
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void cv::gpu::polarToCart(const GpuMat&, const GpuMat&, GpuMat&, GpuMat&, bool, const Stream&) { throw_nogpu(); }
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void cv::gpu::bitwise_not(const GpuMat&, GpuMat&) { throw_nogpu(); }
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void cv::gpu::bitwise_not(const GpuMat&, GpuMat&, const Stream& stream) { throw_nogpu(); }
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void cv::gpu::bitwise_or(const GpuMat&, const GpuMat&, GpuMat&) { throw_nogpu(); }
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void cv::gpu::bitwise_or(const GpuMat&, const GpuMat&, GpuMat&, const Stream& stream) { throw_nogpu(); }
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void cv::gpu::bitwise_and(const GpuMat&, const GpuMat&, GpuMat&) { throw_nogpu(); }
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void cv::gpu::bitwise_and(const GpuMat&, const GpuMat&, GpuMat&, const Stream& stream) { throw_nogpu(); }
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void cv::gpu::bitwise_xor(const GpuMat&, const GpuMat&, GpuMat&) { throw_nogpu(); }
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void cv::gpu::bitwise_xor(const GpuMat&, const GpuMat&, GpuMat&, const Stream& stream) { throw_nogpu(); }
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void cv::gpu::bitwise_not(const GpuMat&, GpuMat&, const GpuMat&) { throw_nogpu(); }
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void cv::gpu::bitwise_not(const GpuMat&, GpuMat&, const GpuMat&, const Stream&) { throw_nogpu(); }
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void cv::gpu::bitwise_or(const GpuMat&, const GpuMat&, GpuMat&, const GpuMat&) { throw_nogpu(); }
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void cv::gpu::bitwise_or(const GpuMat&, const GpuMat&, GpuMat&, const GpuMat&, const Stream&) { throw_nogpu(); }
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void cv::gpu::bitwise_and(const GpuMat&, const GpuMat&, GpuMat&, const GpuMat&) { throw_nogpu(); }
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void cv::gpu::bitwise_and(const GpuMat&, const GpuMat&, GpuMat&, const GpuMat&, const Stream&) { throw_nogpu(); }
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void cv::gpu::bitwise_xor(const GpuMat&, const GpuMat&, GpuMat&, const GpuMat&) { throw_nogpu(); }
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void cv::gpu::bitwise_xor(const GpuMat&, const GpuMat&, GpuMat&, const GpuMat&, const Stream&) { throw_nogpu(); }
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cv::gpu::GpuMat cv::gpu::operator ~ (const GpuMat&) { throw_nogpu(); return GpuMat(); }
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cv::gpu::GpuMat cv::gpu::operator | (const GpuMat&, const GpuMat&) { throw_nogpu(); return GpuMat(); }
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cv::gpu::GpuMat cv::gpu::operator & (const GpuMat&, const GpuMat&) { throw_nogpu(); return GpuMat(); }
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@ -873,10 +873,18 @@ void cv::gpu::polarToCart(const GpuMat& magnitude, const GpuMat& angle, GpuMat&
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namespace cv { namespace gpu { namespace mathfunc
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{
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void bitwise_not_caller(const DevMem2D src, int elemSize, PtrStep dst, cudaStream_t stream);
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void bitwise_or_caller(int cols, int rows, const PtrStep src1, const PtrStep src2, int elemSize, PtrStep dst, cudaStream_t stream);
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void bitwise_and_caller(int cols, int rows, const PtrStep src1, const PtrStep src2, int elemSize, PtrStep dst, cudaStream_t stream);
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void bitwise_xor_caller(int cols, int rows, const PtrStep src1, const PtrStep src2, int elemSize, PtrStep dst, cudaStream_t stream);
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void bitwise_not_caller(int rows, int cols, const PtrStep src, int elemSize, PtrStep dst, cudaStream_t stream);
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void bitwise_not_caller(int rows, int cols, const PtrStep src, int elemSize, PtrStep dst, const PtrStep mask, cudaStream_t stream);
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void bitwise_or_caller(int rows, int cols, const PtrStep src1, const PtrStep src2, int elemSize, PtrStep dst, cudaStream_t stream);
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void bitwise_or_caller(int rows, int cols, const PtrStep src1, const PtrStep src2, int elemSize, PtrStep dst, const PtrStep mask, cudaStream_t stream);
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void bitwise_and_caller(int rows, int cols, const PtrStep src1, const PtrStep src2, int elemSize, PtrStep dst, cudaStream_t stream);
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void bitwise_and_caller(int rows, int cols, const PtrStep src1, const PtrStep src2, int elemSize, PtrStep dst, const PtrStep mask, cudaStream_t stream);
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void bitwise_xor_caller(int rows, int cols, const PtrStep src1, const PtrStep src2, int elemSize, PtrStep dst, cudaStream_t stream);
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void bitwise_xor_caller(int rows, int cols, const PtrStep src1, const PtrStep src2, int elemSize, PtrStep dst, const PtrStep mask, cudaStream_t stream);
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template <int opid, typename Mask>
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void bitwise_bin_op(int rows, int cols, const PtrStep src1, const PtrStep src2, PtrStep dst, int elem_size, Mask mask, cudaStream_t stream);
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}}}
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namespace
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@ -884,75 +892,126 @@ namespace
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void bitwise_not_caller(const GpuMat& src, GpuMat& dst, cudaStream_t stream)
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{
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dst.create(src.size(), src.type());
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mathfunc::bitwise_not_caller(src, src.elemSize(), dst, stream);
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mathfunc::bitwise_not_caller(src.rows, src.cols, src, src.elemSize(), dst, stream);
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}
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void bitwise_not_caller(const GpuMat& src, GpuMat& dst, const GpuMat& mask, cudaStream_t stream)
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{
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CV_Assert(mask.type() == CV_8U && mask.size() == src.size());
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dst.create(src.size(), src.type());
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mathfunc::bitwise_not_caller(src.rows, src.cols, src, src.elemSize(), dst, mask, stream);
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}
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void bitwise_or_caller(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, cudaStream_t stream)
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{
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CV_Assert(src1.size() == src2.size());
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CV_Assert(src1.type() == src2.type());
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CV_Assert(src1.size() == src2.size() && src1.type() == src2.type());
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dst.create(src1.size(), src1.type());
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mathfunc::bitwise_or_caller(dst.cols, dst.rows, src1, src2, dst.elemSize(), dst, stream);
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mathfunc::bitwise_or_caller(dst.rows, dst.cols, src1, src2, dst.elemSize(), dst, stream);
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}
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void bitwise_or_caller(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask, cudaStream_t stream)
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{
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CV_Assert(src1.size() == src2.size() && src1.type() == src2.type());
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CV_Assert(mask.type() == CV_8U && mask.size() == src1.size());
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dst.create(src1.size(), src1.type());
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mathfunc::bitwise_or_caller(dst.rows, dst.cols, src1, src2, dst.elemSize(), dst, mask, stream);
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}
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void bitwise_and_caller(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, cudaStream_t stream)
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{
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CV_Assert(src1.size() == src2.size());
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CV_Assert(src1.type() == src2.type());
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CV_Assert(src1.size() == src2.size() && src1.type() == src2.type());
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dst.create(src1.size(), src1.type());
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mathfunc::bitwise_and_caller(dst.cols, dst.rows, src1, src2, dst.elemSize(), dst, stream);
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mathfunc::bitwise_and_caller(dst.rows, dst.cols, src1, src2, dst.elemSize(), dst, stream);
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}
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void bitwise_and_caller(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask, cudaStream_t stream)
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{
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CV_Assert(src1.size() == src2.size() && src1.type() == src2.type());
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CV_Assert(mask.type() == CV_8U && mask.size() == src1.size());
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dst.create(src1.size(), src1.type());
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mathfunc::bitwise_and_caller(dst.rows, dst.cols, src1, src2, dst.elemSize(), dst, mask, stream);
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}
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void bitwise_xor_caller(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, cudaStream_t stream)
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{
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CV_Assert(src1.size() == src2.size());
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CV_Assert(src1.type() == src2.type());
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dst.create(src1.size(), src1.type());
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mathfunc::bitwise_xor_caller(dst.cols, dst.rows, src1, src2, dst.elemSize(), dst, stream);
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mathfunc::bitwise_xor_caller(dst.rows, dst.cols, src1, src2, dst.elemSize(), dst, stream);
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}
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void bitwise_xor_caller(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask, cudaStream_t stream)
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{
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CV_Assert(src1.size() == src2.size() && src1.type() == src2.type());
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CV_Assert(mask.type() == CV_8U && mask.size() == src1.size());
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dst.create(src1.size(), src1.type());
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mathfunc::bitwise_xor_caller(dst.rows, dst.cols, src1, src2, dst.elemSize(), dst, mask, stream);
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}
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}
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void cv::gpu::bitwise_not(const GpuMat& src, GpuMat& dst)
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void cv::gpu::bitwise_not(const GpuMat& src, GpuMat& dst, const GpuMat& mask)
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{
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::bitwise_not_caller(src, dst, 0);
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if (mask.empty())
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::bitwise_not_caller(src, dst, 0);
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else
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::bitwise_not_caller(src, dst, mask, 0);
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}
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void cv::gpu::bitwise_not(const GpuMat& src, GpuMat& dst, const Stream& stream)
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void cv::gpu::bitwise_not(const GpuMat& src, GpuMat& dst, const GpuMat& mask, const Stream& stream)
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{
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::bitwise_not_caller(src, dst, StreamAccessor::getStream(stream));
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if (mask.empty())
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::bitwise_not_caller(src, dst, StreamAccessor::getStream(stream));
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else
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::bitwise_not_caller(src, dst, mask, StreamAccessor::getStream(stream));
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}
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void cv::gpu::bitwise_or(const GpuMat& src1, const GpuMat& src2, GpuMat& dst)
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void cv::gpu::bitwise_or(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask)
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{
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::bitwise_or_caller(src1, src2, dst, 0);
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if (mask.empty())
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::bitwise_or_caller(src1, src2, dst, 0);
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else
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::bitwise_or_caller(src1, src2, dst, mask, 0);
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}
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void cv::gpu::bitwise_or(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const Stream& stream)
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void cv::gpu::bitwise_or(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask, const Stream& stream)
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{
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::bitwise_or_caller(src1, src2, dst, StreamAccessor::getStream(stream));
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if (mask.empty())
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::bitwise_or_caller(src1, src2, dst, StreamAccessor::getStream(stream));
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else
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::bitwise_or_caller(src1, src2, dst, mask, StreamAccessor::getStream(stream));
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}
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void cv::gpu::bitwise_and(const GpuMat& src1, const GpuMat& src2, GpuMat& dst)
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void cv::gpu::bitwise_and(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask)
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{
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::bitwise_and_caller(src1, src2, dst, 0);
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if (mask.empty())
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::bitwise_and_caller(src1, src2, dst, 0);
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else
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::bitwise_and_caller(src1, src2, dst, mask, 0);
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}
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||||
|
||||
void cv::gpu::bitwise_and(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const Stream& stream)
|
||||
void cv::gpu::bitwise_and(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask, const Stream& stream)
|
||||
{
|
||||
::bitwise_and_caller(src1, src2, dst, StreamAccessor::getStream(stream));
|
||||
if (mask.empty())
|
||||
::bitwise_and_caller(src1, src2, dst, StreamAccessor::getStream(stream));
|
||||
else
|
||||
::bitwise_and_caller(src1, src2, dst, mask, StreamAccessor::getStream(stream));
|
||||
}
|
||||
|
||||
void cv::gpu::bitwise_xor(const GpuMat& src1, const GpuMat& src2, GpuMat& dst)
|
||||
void cv::gpu::bitwise_xor(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask)
|
||||
{
|
||||
::bitwise_xor_caller(src1, src2, dst, 0);
|
||||
if (mask.empty())
|
||||
::bitwise_xor_caller(src1, src2, dst, 0);
|
||||
else
|
||||
::bitwise_xor_caller(src1, src2, dst, mask, 0);
|
||||
}
|
||||
|
||||
void cv::gpu::bitwise_xor(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const Stream& stream)
|
||||
void cv::gpu::bitwise_xor(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const GpuMat& mask, const Stream& stream)
|
||||
{
|
||||
::bitwise_xor_caller(src1, src2, dst, StreamAccessor::getStream(stream));
|
||||
if (mask.empty())
|
||||
::bitwise_xor_caller(src1, src2, dst, StreamAccessor::getStream(stream));
|
||||
else
|
||||
::bitwise_xor_caller(src1, src2, dst, mask, StreamAccessor::getStream(stream));
|
||||
|
||||
}
|
||||
|
||||
cv::gpu::GpuMat cv::gpu::operator ~ (const GpuMat& src)
|
||||
|
||||
@ -243,100 +243,154 @@ namespace cv { namespace gpu { namespace mathfunc
|
||||
//////////////////////////////////////////////////////////////////////////////
|
||||
// Per-element bit-wise logical matrix operations
|
||||
|
||||
struct Mask8U
|
||||
{
|
||||
explicit Mask8U(PtrStep mask): mask(mask) {}
|
||||
__device__ bool operator()(int y, int x) { return mask.ptr(y)[x]; }
|
||||
PtrStep mask;
|
||||
};
|
||||
struct MaskTrue { __device__ bool operator()(int y, int x) { return true; } };
|
||||
|
||||
__global__ void bitwise_not_kernel(int cols, int rows, const PtrStep src, PtrStep dst)
|
||||
// Unary operations
|
||||
|
||||
enum { UN_OP_NOT };
|
||||
|
||||
template <typename T, int opid>
|
||||
struct UnOp { __device__ T operator()(T lhs, T rhs); };
|
||||
|
||||
template <typename T>
|
||||
struct UnOp<T, UN_OP_NOT>{ __device__ T operator()(T x) { return ~x; } };
|
||||
|
||||
template <typename T, int cn, typename UnOp, typename Mask>
|
||||
__global__ void bitwise_un_op(int rows, int cols, const PtrStep src, PtrStep dst, UnOp op, Mask mask)
|
||||
{
|
||||
const int x = blockDim.x * blockIdx.x + threadIdx.x;
|
||||
const int y = blockDim.y * blockIdx.y + threadIdx.y;
|
||||
|
||||
if (x < cols && y < rows)
|
||||
if (x < cols && y < rows && mask(y, x))
|
||||
{
|
||||
dst.ptr(y)[x] = ~src.ptr(y)[x];
|
||||
T* dsty = (T*)dst.ptr(y);
|
||||
const T* srcy = (const T*)src.ptr(y);
|
||||
|
||||
#pragma unroll
|
||||
for (int i = 0; i < cn; ++i)
|
||||
dsty[cn * x + i] = op(srcy[cn * x + i]);
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
void bitwise_not_caller(const DevMem2D src, int elemSize, PtrStep dst, cudaStream_t stream)
|
||||
template <int opid, typename Mask>
|
||||
void bitwise_un_op(int rows, int cols, const PtrStep src, PtrStep dst, int elem_size, Mask mask, cudaStream_t stream)
|
||||
{
|
||||
dim3 threads(16, 16, 1);
|
||||
dim3 grid(divUp(src.cols * elemSize, threads.x), divUp(src.rows, threads.y), 1);
|
||||
|
||||
bitwise_not_kernel<<<grid, threads, 0, stream>>>(src.cols * elemSize, src.rows, src, dst);
|
||||
|
||||
if (stream == 0)
|
||||
cudaSafeCall(cudaThreadSynchronize());
|
||||
dim3 threads(16, 16);
|
||||
dim3 grid(divUp(cols, threads.x), divUp(rows, threads.y));
|
||||
switch (elem_size)
|
||||
{
|
||||
case 1: bitwise_un_op<unsigned char, 1><<<grid, threads>>>(rows, cols, src, dst, UnOp<unsigned char, opid>(), mask); break;
|
||||
case 2: bitwise_un_op<unsigned short, 1><<<grid, threads>>>(rows, cols, src, dst, UnOp<unsigned short, opid>(), mask); break;
|
||||
case 3: bitwise_un_op<unsigned char, 3><<<grid, threads>>>(rows, cols, src, dst, UnOp<unsigned char, opid>(), mask); break;
|
||||
case 4: bitwise_un_op<unsigned int, 1><<<grid, threads>>>(rows, cols, src, dst, UnOp<unsigned int, opid>(), mask); break;
|
||||
case 6: bitwise_un_op<unsigned short, 3><<<grid, threads>>>(rows, cols, src, dst, UnOp<unsigned short, opid>(), mask); break;
|
||||
case 8: bitwise_un_op<unsigned int, 2><<<grid, threads>>>(rows, cols, src, dst, UnOp<unsigned int, opid>(), mask); break;
|
||||
case 12: bitwise_un_op<unsigned int, 3><<<grid, threads>>>(rows, cols, src, dst, UnOp<unsigned int, opid>(), mask); break;
|
||||
case 16: bitwise_un_op<unsigned int, 4><<<grid, threads>>>(rows, cols, src, dst, UnOp<unsigned int, opid>(), mask); break;
|
||||
case 24: bitwise_un_op<unsigned int, 6><<<grid, threads>>>(rows, cols, src, dst, UnOp<unsigned int, opid>(), mask); break;
|
||||
case 32: bitwise_un_op<unsigned int, 8><<<grid, threads>>>(rows, cols, src, dst, UnOp<unsigned int, opid>(), mask); break;
|
||||
}
|
||||
if (stream == 0) cudaSafeCall(cudaThreadSynchronize());
|
||||
}
|
||||
|
||||
void bitwise_not_caller(int rows, int cols,const PtrStep src, int elem_size, PtrStep dst, cudaStream_t stream)
|
||||
{
|
||||
bitwise_un_op<UN_OP_NOT>(rows, cols, src, dst, elem_size, MaskTrue(), stream);
|
||||
}
|
||||
|
||||
__global__ void bitwise_or_kernel(int cols, int rows, const PtrStep src1, const PtrStep src2, PtrStep dst)
|
||||
void bitwise_not_caller(int rows, int cols,const PtrStep src, int elem_size, PtrStep dst, const PtrStep mask, cudaStream_t stream)
|
||||
{
|
||||
bitwise_un_op<UN_OP_NOT>(rows, cols, src, dst, elem_size, Mask8U(mask), stream);
|
||||
}
|
||||
|
||||
// Binary operations
|
||||
|
||||
enum { BIN_OP_OR, BIN_OP_AND, BIN_OP_XOR };
|
||||
|
||||
template <typename T, int opid>
|
||||
struct BinOp { __device__ T operator()(T lhs, T rhs); };
|
||||
|
||||
template <typename T>
|
||||
struct BinOp<T, BIN_OP_OR>{ __device__ T operator()(T lhs, T rhs) { return lhs | rhs; } };
|
||||
|
||||
template <typename T>
|
||||
struct BinOp<T, BIN_OP_AND>{ __device__ T operator()(T lhs, T rhs) { return lhs & rhs; } };
|
||||
|
||||
template <typename T>
|
||||
struct BinOp<T, BIN_OP_XOR>{ __device__ T operator()(T lhs, T rhs) { return lhs ^ rhs; } };
|
||||
|
||||
template <typename T, int cn, typename BinOp, typename Mask>
|
||||
__global__ void bitwise_bin_op(int rows, int cols, const PtrStep src1, const PtrStep src2, PtrStep dst, BinOp op, Mask mask)
|
||||
{
|
||||
const int x = blockDim.x * blockIdx.x + threadIdx.x;
|
||||
const int y = blockDim.y * blockIdx.y + threadIdx.y;
|
||||
|
||||
if (x < cols && y < rows)
|
||||
if (x < cols && y < rows && mask(y, x))
|
||||
{
|
||||
dst.ptr(y)[x] = src1.ptr(y)[x] | src2.ptr(y)[x];
|
||||
T* dsty = (T*)dst.ptr(y);
|
||||
const T* src1y = (const T*)src1.ptr(y);
|
||||
const T* src2y = (const T*)src2.ptr(y);
|
||||
|
||||
#pragma unroll
|
||||
for (int i = 0; i < cn; ++i)
|
||||
dsty[cn * x + i] = op(src1y[cn * x + i], src2y[cn * x + i]);
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
void bitwise_or_caller(int cols, int rows, const PtrStep src1, const PtrStep src2, int elemSize, PtrStep dst, cudaStream_t stream)
|
||||
template <int opid, typename Mask>
|
||||
void bitwise_bin_op(int rows, int cols, const PtrStep src1, const PtrStep src2, PtrStep dst, int elem_size, Mask mask, cudaStream_t stream)
|
||||
{
|
||||
dim3 threads(16, 16, 1);
|
||||
dim3 grid(divUp(cols * elemSize, threads.x), divUp(rows, threads.y), 1);
|
||||
|
||||
bitwise_or_kernel<<<grid, threads, 0, stream>>>(cols * elemSize, rows, src1, src2, dst);
|
||||
|
||||
if (stream == 0)
|
||||
cudaSafeCall(cudaThreadSynchronize());
|
||||
}
|
||||
|
||||
|
||||
__global__ void bitwise_and_kernel(int cols, int rows, const PtrStep src1, const PtrStep src2, PtrStep dst)
|
||||
{
|
||||
const int x = blockDim.x * blockIdx.x + threadIdx.x;
|
||||
const int y = blockDim.y * blockIdx.y + threadIdx.y;
|
||||
|
||||
if (x < cols && y < rows)
|
||||
dim3 threads(16, 16);
|
||||
dim3 grid(divUp(cols, threads.x), divUp(rows, threads.y));
|
||||
switch (elem_size)
|
||||
{
|
||||
dst.ptr(y)[x] = src1.ptr(y)[x] & src2.ptr(y)[x];
|
||||
case 1: bitwise_bin_op<unsigned char, 1><<<grid, threads>>>(rows, cols, src1, src2, dst, BinOp<unsigned char, opid>(), mask); break;
|
||||
case 2: bitwise_bin_op<unsigned short, 1><<<grid, threads>>>(rows, cols, src1, src2, dst, BinOp<unsigned short, opid>(), mask); break;
|
||||
case 3: bitwise_bin_op<unsigned char, 3><<<grid, threads>>>(rows, cols, src1, src2, dst, BinOp<unsigned char, opid>(), mask); break;
|
||||
case 4: bitwise_bin_op<unsigned int, 1><<<grid, threads>>>(rows, cols, src1, src2, dst, BinOp<unsigned int, opid>(), mask); break;
|
||||
case 6: bitwise_bin_op<unsigned short, 3><<<grid, threads>>>(rows, cols, src1, src2, dst, BinOp<unsigned short, opid>(), mask); break;
|
||||
case 8: bitwise_bin_op<unsigned int, 2><<<grid, threads>>>(rows, cols, src1, src2, dst, BinOp<unsigned int, opid>(), mask); break;
|
||||
case 12: bitwise_bin_op<unsigned int, 3><<<grid, threads>>>(rows, cols, src1, src2, dst, BinOp<unsigned int, opid>(), mask); break;
|
||||
case 16: bitwise_bin_op<unsigned int, 4><<<grid, threads>>>(rows, cols, src1, src2, dst, BinOp<unsigned int, opid>(), mask); break;
|
||||
case 24: bitwise_bin_op<unsigned int, 6><<<grid, threads>>>(rows, cols, src1, src2, dst, BinOp<unsigned int, opid>(), mask); break;
|
||||
case 32: bitwise_bin_op<unsigned int, 8><<<grid, threads>>>(rows, cols, src1, src2, dst, BinOp<unsigned int, opid>(), mask); break;
|
||||
}
|
||||
if (stream == 0) cudaSafeCall(cudaThreadSynchronize());
|
||||
}
|
||||
|
||||
|
||||
void bitwise_and_caller(int cols, int rows, const PtrStep src1, const PtrStep src2, int elemSize, PtrStep dst, cudaStream_t stream)
|
||||
void bitwise_or_caller(int rows, int cols, const PtrStep src1, const PtrStep src2, int elem_size, PtrStep dst, cudaStream_t stream)
|
||||
{
|
||||
dim3 threads(16, 16, 1);
|
||||
dim3 grid(divUp(cols * elemSize, threads.x), divUp(rows, threads.y), 1);
|
||||
|
||||
bitwise_and_kernel<<<grid, threads, 0, stream>>>(cols * elemSize, rows, src1, src2, dst);
|
||||
|
||||
if (stream == 0)
|
||||
cudaSafeCall(cudaThreadSynchronize());
|
||||
bitwise_bin_op<BIN_OP_OR>(rows, cols, src1, src2, dst, elem_size, MaskTrue(), stream);
|
||||
}
|
||||
|
||||
|
||||
|
||||
__global__ void bitwise_xor_kernel(int cols, int rows, const PtrStep src1, const PtrStep src2, PtrStep dst)
|
||||
void bitwise_or_caller(int rows, int cols, const PtrStep src1, const PtrStep src2, int elem_size, PtrStep dst, const PtrStep mask, cudaStream_t stream)
|
||||
{
|
||||
const int x = blockDim.x * blockIdx.x + threadIdx.x;
|
||||
const int y = blockDim.y * blockIdx.y + threadIdx.y;
|
||||
|
||||
if (x < cols && y < rows)
|
||||
{
|
||||
dst.ptr(y)[x] = src1.ptr(y)[x] ^ src2.ptr(y)[x];
|
||||
}
|
||||
bitwise_bin_op<BIN_OP_OR>(rows, cols, src1, src2, dst, elem_size, Mask8U(mask), stream);
|
||||
}
|
||||
|
||||
|
||||
void bitwise_xor_caller(int cols, int rows, const PtrStep src1, const PtrStep src2, int elemSize, PtrStep dst, cudaStream_t stream)
|
||||
void bitwise_and_caller(int rows, int cols, const PtrStep src1, const PtrStep src2, int elem_size, PtrStep dst, cudaStream_t stream)
|
||||
{
|
||||
dim3 threads(16, 16, 1);
|
||||
dim3 grid(divUp(cols * elemSize, threads.x), divUp(rows, threads.y), 1);
|
||||
|
||||
bitwise_xor_kernel<<<grid, threads, 0, stream>>>(cols * elemSize, rows, src1, src2, dst);
|
||||
|
||||
if (stream == 0)
|
||||
cudaSafeCall(cudaThreadSynchronize());
|
||||
bitwise_bin_op<BIN_OP_AND>(rows, cols, src1, src2, dst, elem_size, MaskTrue(), stream);
|
||||
}
|
||||
|
||||
void bitwise_and_caller(int rows, int cols, const PtrStep src1, const PtrStep src2, int elem_size, PtrStep dst, const PtrStep mask, cudaStream_t stream)
|
||||
{
|
||||
bitwise_bin_op<BIN_OP_AND>(rows, cols, src1, src2, dst, elem_size, Mask8U(mask), stream);
|
||||
}
|
||||
|
||||
void bitwise_xor_caller(int rows, int cols, const PtrStep src1, const PtrStep src2, int elem_size, PtrStep dst, cudaStream_t stream)
|
||||
{
|
||||
bitwise_bin_op<BIN_OP_XOR>(rows, cols, src1, src2, dst, elem_size, MaskTrue(), stream);
|
||||
}
|
||||
|
||||
void bitwise_xor_caller(int rows, int cols, const PtrStep src1, const PtrStep src2, int elem_size, PtrStep dst, const PtrStep mask, cudaStream_t stream)
|
||||
{
|
||||
bitwise_bin_op<BIN_OP_XOR>(rows, cols, src1, src2, dst, elem_size, Mask8U(mask), stream);
|
||||
}
|
||||
}}}
|
||||
|
||||
@ -60,7 +60,7 @@ struct CV_GpuBitwiseTest: public CvTest
|
||||
int rows, cols;
|
||||
for (int depth = CV_8U; depth <= CV_64F; ++depth)
|
||||
for (int cn = 1; cn <= 4; ++cn)
|
||||
for (int attempt = 0; attempt < 5; ++attempt)
|
||||
for (int attempt = 0; attempt < 3; ++attempt)
|
||||
{
|
||||
rows = 1 + rand() % 100;
|
||||
cols = 1 + rand() % 100;
|
||||
@ -83,7 +83,12 @@ struct CV_GpuBitwiseTest: public CvTest
|
||||
}
|
||||
|
||||
Mat dst_gold = ~src;
|
||||
gpu::GpuMat dst = ~gpu::GpuMat(src);
|
||||
|
||||
gpu::GpuMat mask(src.size(), CV_8U);
|
||||
mask.setTo(Scalar(1));
|
||||
|
||||
gpu::GpuMat dst;
|
||||
gpu::bitwise_not(gpu::GpuMat(src), dst, mask);
|
||||
|
||||
CHECK(dst_gold.size() == dst.size(), CvTS::FAIL_INVALID_OUTPUT);
|
||||
CHECK(dst_gold.type() == dst.type(), CvTS::FAIL_INVALID_OUTPUT);
|
||||
@ -112,10 +117,23 @@ struct CV_GpuBitwiseTest: public CvTest
|
||||
|
||||
CHECK(dst_gold.size() == dst.size(), CvTS::FAIL_INVALID_OUTPUT);
|
||||
CHECK(dst_gold.type() == dst.type(), CvTS::FAIL_INVALID_OUTPUT);
|
||||
|
||||
Mat dsth(dst);
|
||||
for (int i = 0; i < dst_gold.rows; ++i)
|
||||
CHECK(memcmp(dst_gold.ptr(i), dsth.ptr(i), dst_gold.cols * dst_gold.elemSize()) == 0, CvTS::FAIL_INVALID_OUTPUT)
|
||||
|
||||
Mat mask(src1.size(), CV_8U);
|
||||
randu(mask, Scalar(0), Scalar(255));
|
||||
|
||||
Mat dst_gold2(dst_gold.size(), dst_gold.type()); dst_gold2.setTo(Scalar::all(0));
|
||||
gpu::GpuMat dst2(dst.size(), dst.type()); dst2.setTo(Scalar::all(0));
|
||||
bitwise_or(src1, src2, dst_gold2, mask);
|
||||
gpu::bitwise_or(gpu::GpuMat(src1), gpu::GpuMat(src2), dst2, gpu::GpuMat(mask));
|
||||
|
||||
CHECK(dst_gold2.size() == dst2.size(), CvTS::FAIL_INVALID_OUTPUT);
|
||||
CHECK(dst_gold2.type() == dst2.type(), CvTS::FAIL_INVALID_OUTPUT);
|
||||
dsth = dst2;
|
||||
for (int i = 0; i < dst_gold.rows; ++i)
|
||||
CHECK(memcmp(dst_gold2.ptr(i), dsth.ptr(i), dst_gold2.cols * dst_gold2.elemSize()) == 0, CvTS::FAIL_INVALID_OUTPUT)
|
||||
}
|
||||
|
||||
void test_bitwise_and(int rows, int cols, int type)
|
||||
@ -138,10 +156,24 @@ struct CV_GpuBitwiseTest: public CvTest
|
||||
|
||||
CHECK(dst_gold.size() == dst.size(), CvTS::FAIL_INVALID_OUTPUT);
|
||||
CHECK(dst_gold.type() == dst.type(), CvTS::FAIL_INVALID_OUTPUT);
|
||||
|
||||
Mat dsth(dst);
|
||||
for (int i = 0; i < dst_gold.rows; ++i)
|
||||
CHECK(memcmp(dst_gold.ptr(i), dsth.ptr(i), dst_gold.cols * dst_gold.elemSize()) == 0, CvTS::FAIL_INVALID_OUTPUT)
|
||||
|
||||
|
||||
Mat mask(src1.size(), CV_8U);
|
||||
randu(mask, Scalar(0), Scalar(255));
|
||||
|
||||
Mat dst_gold2(dst_gold.size(), dst_gold.type()); dst_gold2.setTo(Scalar::all(0));
|
||||
gpu::GpuMat dst2(dst.size(), dst.type()); dst2.setTo(Scalar::all(0));
|
||||
bitwise_and(src1, src2, dst_gold2, mask);
|
||||
gpu::bitwise_and(gpu::GpuMat(src1), gpu::GpuMat(src2), dst2, gpu::GpuMat(mask));
|
||||
|
||||
CHECK(dst_gold2.size() == dst2.size(), CvTS::FAIL_INVALID_OUTPUT);
|
||||
CHECK(dst_gold2.type() == dst2.type(), CvTS::FAIL_INVALID_OUTPUT);
|
||||
dsth = dst2;
|
||||
for (int i = 0; i < dst_gold.rows; ++i)
|
||||
CHECK(memcmp(dst_gold2.ptr(i), dsth.ptr(i), dst_gold2.cols * dst_gold2.elemSize()) == 0, CvTS::FAIL_INVALID_OUTPUT)
|
||||
}
|
||||
|
||||
void test_bitwise_xor(int rows, int cols, int type)
|
||||
@ -164,10 +196,24 @@ struct CV_GpuBitwiseTest: public CvTest
|
||||
|
||||
CHECK(dst_gold.size() == dst.size(), CvTS::FAIL_INVALID_OUTPUT);
|
||||
CHECK(dst_gold.type() == dst.type(), CvTS::FAIL_INVALID_OUTPUT);
|
||||
|
||||
Mat dsth(dst);
|
||||
for (int i = 0; i < dst_gold.rows; ++i)
|
||||
CHECK(memcmp(dst_gold.ptr(i), dsth.ptr(i), dst_gold.cols * dst_gold.elemSize()) == 0, CvTS::FAIL_INVALID_OUTPUT)
|
||||
|
||||
|
||||
Mat mask(src1.size(), CV_8U);
|
||||
randu(mask, Scalar(0), Scalar(255));
|
||||
|
||||
Mat dst_gold2(dst_gold.size(), dst_gold.type()); dst_gold2.setTo(Scalar::all(0));
|
||||
gpu::GpuMat dst2(dst.size(), dst.type()); dst2.setTo(Scalar::all(0));
|
||||
bitwise_xor(src1, src2, dst_gold2, mask);
|
||||
gpu::bitwise_xor(gpu::GpuMat(src1), gpu::GpuMat(src2), dst2, gpu::GpuMat(mask));
|
||||
|
||||
CHECK(dst_gold2.size() == dst2.size(), CvTS::FAIL_INVALID_OUTPUT);
|
||||
CHECK(dst_gold2.type() == dst2.type(), CvTS::FAIL_INVALID_OUTPUT);
|
||||
dsth = dst2;
|
||||
for (int i = 0; i < dst_gold.rows; ++i)
|
||||
CHECK(memcmp(dst_gold2.ptr(i), dsth.ptr(i), dst_gold2.cols * dst_gold2.elemSize()) == 0, CvTS::FAIL_INVALID_OUTPUT)
|
||||
}
|
||||
} gpu_bitwise_test;
|
||||
|
||||
|
||||
Loading…
Reference in New Issue
Block a user