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refactoring: moved gpu reduction-based functions into separated file
This commit is contained in:
Alexey Spizhevoy
parent
1922e50f19
commit
df8529377b
@ -360,66 +360,17 @@ namespace cv
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friend struct StreamAccessor;
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};
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////////////////////////////// Arithmetics ///////////////////////////////////
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//! transposes the matrix
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//! supports CV_8UC1, CV_8SC1, CV_8UC4, CV_8SC4, CV_16UC2, CV_16SC2, CV_32SC1, CV_32FC1 type
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CV_EXPORTS void transpose(const GpuMat& src1, GpuMat& dst);
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//! computes mean value and standard deviation of all or selected array elements
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//! supports only CV_8UC1 type
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CV_EXPORTS void meanStdDev(const GpuMat& mtx, Scalar& mean, Scalar& stddev);
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//! computes norm of array
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//! supports NORM_INF, NORM_L1, NORM_L2
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//! supports only CV_8UC1 type
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CV_EXPORTS double norm(const GpuMat& src1, int normType=NORM_L2);
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//! computes norm of the difference between two arrays
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//! supports NORM_INF, NORM_L1, NORM_L2
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//! supports only CV_8UC1 type
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CV_EXPORTS double norm(const GpuMat& src1, const GpuMat& src2, int normType=NORM_L2);
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//! reverses the order of the rows, columns or both in a matrix
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//! supports CV_8UC1, CV_8UC4 types
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CV_EXPORTS void flip(const GpuMat& a, GpuMat& b, int flipCode);
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//! computes sum of array elements
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//! supports only single channel images
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CV_EXPORTS Scalar sum(const GpuMat& src);
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//! computes sum of array elements
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//! supports only single channel images
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CV_EXPORTS Scalar sum(const GpuMat& src, GpuMat& buf);
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//! computes squared sum of array elements
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//! supports only single channel images
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CV_EXPORTS Scalar sqrSum(const GpuMat& src);
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//! computes squared sum of array elements
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//! supports only single channel images
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CV_EXPORTS Scalar sqrSum(const GpuMat& src, GpuMat& buf);
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//! finds global minimum and maximum array elements and returns their values
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CV_EXPORTS void minMax(const GpuMat& src, double* minVal, double* maxVal=0, const GpuMat& mask=GpuMat());
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//! finds global minimum and maximum array elements and returns their values
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CV_EXPORTS void minMax(const GpuMat& src, double* minVal, double* maxVal, const GpuMat& mask, GpuMat& buf);
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//! finds global minimum and maximum array elements and returns their values with locations
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CV_EXPORTS void minMaxLoc(const GpuMat& src, double* minVal, double* maxVal=0, Point* minLoc=0, Point* maxLoc=0,
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const GpuMat& mask=GpuMat());
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//! finds global minimum and maximum array elements and returns their values with locations
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CV_EXPORTS void minMaxLoc(const GpuMat& src, double* minVal, double* maxVal, Point* minLoc, Point* maxLoc,
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const GpuMat& mask, GpuMat& valbuf, GpuMat& locbuf);
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//! counts non-zero array elements
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CV_EXPORTS int countNonZero(const GpuMat& src);
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//! counts non-zero array elements
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CV_EXPORTS int countNonZero(const GpuMat& src, GpuMat& buf);
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//! transforms 8-bit unsigned integers using lookup table: dst(i)=lut(src(i))
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//! destination array will have the depth type as lut and the same channels number as source
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//! supports CV_8UC1, CV_8UC3 types
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@ -487,25 +438,6 @@ namespace cv
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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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//! computes per-element minimum of two arrays (dst = min(src1, src2))
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CV_EXPORTS void min(const GpuMat& src1, const GpuMat& src2, GpuMat& dst);
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//! Async version
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CV_EXPORTS void min(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const Stream& stream);
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//! computes per-element minimum of array and scalar (dst = min(src1, src2))
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CV_EXPORTS void min(const GpuMat& src1, double src2, GpuMat& dst);
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//! Async version
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CV_EXPORTS void min(const GpuMat& src1, double src2, GpuMat& dst, const Stream& stream);
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//! computes per-element maximum of two arrays (dst = max(src1, src2))
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CV_EXPORTS void max(const GpuMat& src1, const GpuMat& src2, GpuMat& dst);
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//! Async version
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CV_EXPORTS void max(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const Stream& stream);
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//! computes per-element maximum of array and scalar (dst = max(src1, src2))
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CV_EXPORTS void max(const GpuMat& src1, double src2, GpuMat& dst);
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//! Async version
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CV_EXPORTS void max(const GpuMat& src1, double src2, GpuMat& dst, const Stream& stream);
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//////////////////////////// Per-element operations ////////////////////////////////////
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@ -576,6 +508,26 @@ namespace cv
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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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//! computes per-element minimum of two arrays (dst = min(src1, src2))
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CV_EXPORTS void min(const GpuMat& src1, const GpuMat& src2, GpuMat& dst);
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//! Async version
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CV_EXPORTS void min(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const Stream& stream);
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//! computes per-element minimum of array and scalar (dst = min(src1, src2))
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CV_EXPORTS void min(const GpuMat& src1, double src2, GpuMat& dst);
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//! Async version
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CV_EXPORTS void min(const GpuMat& src1, double src2, GpuMat& dst, const Stream& stream);
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//! computes per-element maximum of two arrays (dst = max(src1, src2))
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CV_EXPORTS void max(const GpuMat& src1, const GpuMat& src2, GpuMat& dst);
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//! Async version
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CV_EXPORTS void max(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const Stream& stream);
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//! computes per-element maximum of array and scalar (dst = max(src1, src2))
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CV_EXPORTS void max(const GpuMat& src1, double src2, GpuMat& dst);
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//! Async version
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CV_EXPORTS void max(const GpuMat& src1, double src2, GpuMat& dst, const Stream& stream);
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////////////////////////////// Image processing //////////////////////////////
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@ -663,15 +615,66 @@ namespace cv
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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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//! 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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//! 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);
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////////////////////////////// Matrix reductions //////////////////////////////
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//! computes mean value and standard deviation of all or selected array elements
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//! supports only CV_8UC1 type
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CV_EXPORTS void meanStdDev(const GpuMat& mtx, Scalar& mean, Scalar& stddev);
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//! computes norm of array
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//! supports NORM_INF, NORM_L1, NORM_L2
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//! supports only CV_8UC1 type
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CV_EXPORTS double norm(const GpuMat& src1, int normType=NORM_L2);
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//! computes norm of the difference between two arrays
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//! supports NORM_INF, NORM_L1, NORM_L2
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//! supports only CV_8UC1 type
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CV_EXPORTS double norm(const GpuMat& src1, const GpuMat& src2, int normType=NORM_L2);
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//! computes sum of array elements
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//! supports only single channel images
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CV_EXPORTS Scalar sum(const GpuMat& src);
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//! computes sum of array elements
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//! supports only single channel images
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CV_EXPORTS Scalar sum(const GpuMat& src, GpuMat& buf);
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//! computes squared sum of array elements
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//! supports only single channel images
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CV_EXPORTS Scalar sqrSum(const GpuMat& src);
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//! computes squared sum of array elements
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//! supports only single channel images
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CV_EXPORTS Scalar sqrSum(const GpuMat& src, GpuMat& buf);
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//! finds global minimum and maximum array elements and returns their values
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CV_EXPORTS void minMax(const GpuMat& src, double* minVal, double* maxVal=0, const GpuMat& mask=GpuMat());
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//! finds global minimum and maximum array elements and returns their values
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CV_EXPORTS void minMax(const GpuMat& src, double* minVal, double* maxVal, const GpuMat& mask, GpuMat& buf);
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//! finds global minimum and maximum array elements and returns their values with locations
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CV_EXPORTS void minMaxLoc(const GpuMat& src, double* minVal, double* maxVal=0, Point* minLoc=0, Point* maxLoc=0,
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const GpuMat& mask=GpuMat());
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//! finds global minimum and maximum array elements and returns their values with locations
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CV_EXPORTS void minMaxLoc(const GpuMat& src, double* minVal, double* maxVal, Point* minLoc, Point* maxLoc,
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const GpuMat& mask, GpuMat& valbuf, GpuMat& locbuf);
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//! counts non-zero array elements
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CV_EXPORTS int countNonZero(const GpuMat& src);
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//! counts non-zero array elements
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CV_EXPORTS int countNonZero(const GpuMat& src, GpuMat& buf);
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//////////////////////////////// Filter Engine ////////////////////////////////
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/*!
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@ -49,20 +49,7 @@ using namespace std;
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#if !defined (HAVE_CUDA)
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void cv::gpu::transpose(const GpuMat&, GpuMat&) { throw_nogpu(); }
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void cv::gpu::meanStdDev(const GpuMat&, Scalar&, Scalar&) { throw_nogpu(); }
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double cv::gpu::norm(const GpuMat&, int) { throw_nogpu(); return 0.0; }
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double cv::gpu::norm(const GpuMat&, const GpuMat&, int) { throw_nogpu(); return 0.0; }
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void cv::gpu::flip(const GpuMat&, GpuMat&, int) { throw_nogpu(); }
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Scalar cv::gpu::sum(const GpuMat&) { throw_nogpu(); return Scalar(); }
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Scalar cv::gpu::sum(const GpuMat&, GpuMat&) { throw_nogpu(); return Scalar(); }
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Scalar cv::gpu::sqrSum(const GpuMat&) { throw_nogpu(); return Scalar(); }
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Scalar cv::gpu::sqrSum(const GpuMat&, GpuMat&) { throw_nogpu(); return Scalar(); }
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void cv::gpu::minMax(const GpuMat&, double*, double*, const GpuMat&) { throw_nogpu(); }
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void cv::gpu::minMax(const GpuMat&, double*, double*, const GpuMat&, GpuMat&) { throw_nogpu(); }
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void cv::gpu::minMaxLoc(const GpuMat&, double*, double*, Point*, Point*, const GpuMat&) { throw_nogpu(); }
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void cv::gpu::minMaxLoc(const GpuMat&, double*, double*, Point*, Point*, const GpuMat&, GpuMat&, GpuMat&) { throw_nogpu(); }
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int cv::gpu::countNonZero(const GpuMat&) { throw_nogpu(); return 0; }
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int cv::gpu::countNonZero(const GpuMat&, GpuMat&) { throw_nogpu(); return 0; }
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void cv::gpu::LUT(const GpuMat&, const Mat&, GpuMat&) { throw_nogpu(); }
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void cv::gpu::exp(const GpuMat&, GpuMat&) { throw_nogpu(); }
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void cv::gpu::log(const GpuMat&, GpuMat&) { throw_nogpu(); }
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@ -78,14 +65,6 @@ 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::min(const GpuMat&, const GpuMat&, GpuMat&) { throw_nogpu(); }
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void cv::gpu::min(const GpuMat&, const GpuMat&, GpuMat&, const Stream&) { throw_nogpu(); }
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void cv::gpu::min(const GpuMat&, double, GpuMat&) { throw_nogpu(); }
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void cv::gpu::min(const GpuMat&, double, GpuMat&, const Stream&) { throw_nogpu(); }
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void cv::gpu::max(const GpuMat&, const GpuMat&, GpuMat&) { throw_nogpu(); }
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void cv::gpu::max(const GpuMat&, const GpuMat&, GpuMat&, const Stream&) { throw_nogpu(); }
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void cv::gpu::max(const GpuMat&, double, GpuMat&) { throw_nogpu(); }
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void cv::gpu::max(const GpuMat&, double, GpuMat&, const Stream&) { throw_nogpu(); }
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#else /* !defined (HAVE_CUDA) */
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@ -118,54 +97,6 @@ void cv::gpu::transpose(const GpuMat& src, GpuMat& dst)
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}
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}
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////////////////////////////////////////////////////////////////////////
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// meanStdDev
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void cv::gpu::meanStdDev(const GpuMat& src, Scalar& mean, Scalar& stddev)
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{
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CV_Assert(src.type() == CV_8UC1);
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NppiSize sz;
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sz.width = src.cols;
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sz.height = src.rows;
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nppSafeCall( nppiMean_StdDev_8u_C1R(src.ptr<Npp8u>(), src.step, sz, mean.val, stddev.val) );
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}
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////////////////////////////////////////////////////////////////////////
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// norm
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double cv::gpu::norm(const GpuMat& src1, int normType)
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{
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return norm(src1, GpuMat(src1.size(), src1.type(), Scalar::all(0.0)), normType);
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}
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double cv::gpu::norm(const GpuMat& src1, const GpuMat& src2, int normType)
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{
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CV_DbgAssert(src1.size() == src2.size() && src1.type() == src2.type());
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CV_Assert(src1.type() == CV_8UC1);
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CV_Assert(normType == NORM_INF || normType == NORM_L1 || normType == NORM_L2);
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typedef NppStatus (*npp_norm_diff_func_t)(const Npp8u* pSrc1, int nSrcStep1, const Npp8u* pSrc2, int nSrcStep2,
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NppiSize oSizeROI, Npp64f* pRetVal);
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static const npp_norm_diff_func_t npp_norm_diff_func[] = {nppiNormDiff_Inf_8u_C1R, nppiNormDiff_L1_8u_C1R, nppiNormDiff_L2_8u_C1R};
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NppiSize sz;
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sz.width = src1.cols;
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sz.height = src1.rows;
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int funcIdx = normType >> 1;
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double retVal;
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nppSafeCall( npp_norm_diff_func[funcIdx](src1.ptr<Npp8u>(), src1.step,
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src2.ptr<Npp8u>(), src2.step,
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sz, &retVal) );
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return retVal;
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}
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////////////////////////////////////////////////////////////////////////
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// flip
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@ -193,305 +124,6 @@ void cv::gpu::flip(const GpuMat& src, GpuMat& dst, int flipCode)
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}
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}
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////////////////////////////////////////////////////////////////////////
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// sum
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namespace cv { namespace gpu { namespace mathfunc
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{
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template <typename T>
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void sum_caller(const DevMem2D src, PtrStep buf, double* sum, int cn);
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template <typename T>
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void sum_multipass_caller(const DevMem2D src, PtrStep buf, double* sum, int cn);
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template <typename T>
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void sqsum_caller(const DevMem2D src, PtrStep buf, double* sum, int cn);
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template <typename T>
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void sqsum_multipass_caller(const DevMem2D src, PtrStep buf, double* sum, int cn);
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namespace sum
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{
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void get_buf_size_required(int cols, int rows, int cn, int& bufcols, int& bufrows);
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}
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}}}
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Scalar cv::gpu::sum(const GpuMat& src)
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{
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GpuMat buf;
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return sum(src, buf);
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}
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Scalar cv::gpu::sum(const GpuMat& src, GpuMat& buf)
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{
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using namespace mathfunc;
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typedef void (*Caller)(const DevMem2D, PtrStep, double*, int);
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static const Caller callers[2][7] =
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{ { sum_multipass_caller<unsigned char>, sum_multipass_caller<char>,
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sum_multipass_caller<unsigned short>, sum_multipass_caller<short>,
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sum_multipass_caller<int>, sum_multipass_caller<float>, 0 },
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{ sum_caller<unsigned char>, sum_caller<char>,
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sum_caller<unsigned short>, sum_caller<short>,
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sum_caller<int>, sum_caller<float>, 0 } };
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Size bufSize;
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sum::get_buf_size_required(src.cols, src.rows, src.channels(), bufSize.width, bufSize.height);
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buf.create(bufSize, CV_8U);
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Caller caller = callers[hasAtomicsSupport(getDevice())][src.depth()];
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if (!caller) CV_Error(CV_StsBadArg, "sum: unsupported type");
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double result[4];
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caller(src, buf, result, src.channels());
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return Scalar(result[0], result[1], result[2], result[3]);
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}
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Scalar cv::gpu::sqrSum(const GpuMat& src)
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{
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GpuMat buf;
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return sqrSum(src, buf);
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}
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Scalar cv::gpu::sqrSum(const GpuMat& src, GpuMat& buf)
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{
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using namespace mathfunc;
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typedef void (*Caller)(const DevMem2D, PtrStep, double*, int);
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static const Caller callers[2][7] =
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{ { sqsum_multipass_caller<unsigned char>, sqsum_multipass_caller<char>,
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sqsum_multipass_caller<unsigned short>, sqsum_multipass_caller<short>,
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sqsum_multipass_caller<int>, sqsum_multipass_caller<float>, 0 },
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{ sqsum_caller<unsigned char>, sqsum_caller<char>,
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sqsum_caller<unsigned short>, sqsum_caller<short>,
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sqsum_caller<int>, sqsum_caller<float>, 0 } };
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Size bufSize;
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sum::get_buf_size_required(src.cols, src.rows, src.channels(), bufSize.width, bufSize.height);
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buf.create(bufSize, CV_8U);
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Caller caller = callers[hasAtomicsSupport(getDevice())][src.depth()];
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if (!caller) CV_Error(CV_StsBadArg, "sqrSum: unsupported type");
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double result[4];
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caller(src, buf, result, src.channels());
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return Scalar(result[0], result[1], result[2], result[3]);
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}
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////////////////////////////////////////////////////////////////////////
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||||
// minMax
|
||||
|
||||
namespace cv { namespace gpu { namespace mathfunc { namespace minmax {
|
||||
|
||||
void get_buf_size_required(int cols, int rows, int elem_size, int& bufcols, int& bufrows);
|
||||
|
||||
template <typename T>
|
||||
void min_max_caller(const DevMem2D src, double* minval, double* maxval, PtrStep buf);
|
||||
|
||||
template <typename T>
|
||||
void min_max_mask_caller(const DevMem2D src, const PtrStep mask, double* minval, double* maxval, PtrStep buf);
|
||||
|
||||
template <typename T>
|
||||
void min_max_multipass_caller(const DevMem2D src, double* minval, double* maxval, PtrStep buf);
|
||||
|
||||
template <typename T>
|
||||
void min_max_mask_multipass_caller(const DevMem2D src, const PtrStep mask, double* minval, double* maxval, PtrStep buf);
|
||||
|
||||
}}}}
|
||||
|
||||
void cv::gpu::minMax(const GpuMat& src, double* minVal, double* maxVal, const GpuMat& mask)
|
||||
{
|
||||
GpuMat buf;
|
||||
minMax(src, minVal, maxVal, mask, buf);
|
||||
}
|
||||
|
||||
void cv::gpu::minMax(const GpuMat& src, double* minVal, double* maxVal, const GpuMat& mask, GpuMat& buf)
|
||||
{
|
||||
using namespace mathfunc::minmax;
|
||||
|
||||
typedef void (*Caller)(const DevMem2D, double*, double*, PtrStep);
|
||||
typedef void (*MaskedCaller)(const DevMem2D, const PtrStep, double*, double*, PtrStep);
|
||||
|
||||
static const Caller callers[2][7] =
|
||||
{ { min_max_multipass_caller<unsigned char>, min_max_multipass_caller<char>,
|
||||
min_max_multipass_caller<unsigned short>, min_max_multipass_caller<short>,
|
||||
min_max_multipass_caller<int>, min_max_multipass_caller<float>, 0 },
|
||||
{ min_max_caller<unsigned char>, min_max_caller<char>,
|
||||
min_max_caller<unsigned short>, min_max_caller<short>,
|
||||
min_max_caller<int>, min_max_caller<float>, min_max_caller<double> } };
|
||||
|
||||
static const MaskedCaller masked_callers[2][7] =
|
||||
{ { min_max_mask_multipass_caller<unsigned char>, min_max_mask_multipass_caller<char>,
|
||||
min_max_mask_multipass_caller<unsigned short>, min_max_mask_multipass_caller<short>,
|
||||
min_max_mask_multipass_caller<int>, min_max_mask_multipass_caller<float>, 0 },
|
||||
{ min_max_mask_caller<unsigned char>, min_max_mask_caller<char>,
|
||||
min_max_mask_caller<unsigned short>, min_max_mask_caller<short>,
|
||||
min_max_mask_caller<int>, min_max_mask_caller<float>,
|
||||
min_max_mask_caller<double> } };
|
||||
|
||||
|
||||
CV_Assert(src.channels() == 1);
|
||||
CV_Assert(mask.empty() || (mask.type() == CV_8U && src.size() == mask.size()));
|
||||
CV_Assert(src.type() != CV_64F || hasNativeDoubleSupport(getDevice()));
|
||||
|
||||
double minVal_; if (!minVal) minVal = &minVal_;
|
||||
double maxVal_; if (!maxVal) maxVal = &maxVal_;
|
||||
|
||||
Size bufSize;
|
||||
get_buf_size_required(src.cols, src.rows, src.elemSize(), bufSize.width, bufSize.height);
|
||||
buf.create(bufSize, CV_8U);
|
||||
|
||||
if (mask.empty())
|
||||
{
|
||||
Caller caller = callers[hasAtomicsSupport(getDevice())][src.type()];
|
||||
if (!caller) CV_Error(CV_StsBadArg, "minMax: unsupported type");
|
||||
caller(src, minVal, maxVal, buf);
|
||||
}
|
||||
else
|
||||
{
|
||||
MaskedCaller caller = masked_callers[hasAtomicsSupport(getDevice())][src.type()];
|
||||
if (!caller) CV_Error(CV_StsBadArg, "minMax: unsupported type");
|
||||
caller(src, mask, minVal, maxVal, buf);
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
////////////////////////////////////////////////////////////////////////
|
||||
// minMaxLoc
|
||||
|
||||
namespace cv { namespace gpu { namespace mathfunc { namespace minmaxloc {
|
||||
|
||||
void get_buf_size_required(int cols, int rows, int elem_size, int& b1cols,
|
||||
int& b1rows, int& b2cols, int& b2rows);
|
||||
|
||||
template <typename T>
|
||||
void min_max_loc_caller(const DevMem2D src, double* minval, double* maxval,
|
||||
int minloc[2], int maxloc[2], PtrStep valbuf, PtrStep locbuf);
|
||||
|
||||
template <typename T>
|
||||
void min_max_loc_mask_caller(const DevMem2D src, const PtrStep mask, double* minval, double* maxval,
|
||||
int minloc[2], int maxloc[2], PtrStep valbuf, PtrStep locbuf);
|
||||
|
||||
template <typename T>
|
||||
void min_max_loc_multipass_caller(const DevMem2D src, double* minval, double* maxval,
|
||||
int minloc[2], int maxloc[2], PtrStep valbuf, PtrStep locbuf);
|
||||
|
||||
template <typename T>
|
||||
void min_max_loc_mask_multipass_caller(const DevMem2D src, const PtrStep mask, double* minval, double* maxval,
|
||||
int minloc[2], int maxloc[2], PtrStep valbuf, PtrStep locbuf);
|
||||
|
||||
|
||||
}}}}
|
||||
|
||||
void cv::gpu::minMaxLoc(const GpuMat& src, double* minVal, double* maxVal, Point* minLoc, Point* maxLoc, const GpuMat& mask)
|
||||
{
|
||||
GpuMat valbuf, locbuf;
|
||||
minMaxLoc(src, minVal, maxVal, minLoc, maxLoc, mask, valbuf, locbuf);
|
||||
}
|
||||
|
||||
void cv::gpu::minMaxLoc(const GpuMat& src, double* minVal, double* maxVal, Point* minLoc, Point* maxLoc,
|
||||
const GpuMat& mask, GpuMat& valbuf, GpuMat& locbuf)
|
||||
{
|
||||
using namespace mathfunc::minmaxloc;
|
||||
|
||||
typedef void (*Caller)(const DevMem2D, double*, double*, int[2], int[2], PtrStep, PtrStep);
|
||||
typedef void (*MaskedCaller)(const DevMem2D, const PtrStep, double*, double*, int[2], int[2], PtrStep, PtrStep);
|
||||
|
||||
static const Caller callers[2][7] =
|
||||
{ { min_max_loc_multipass_caller<unsigned char>, min_max_loc_multipass_caller<char>,
|
||||
min_max_loc_multipass_caller<unsigned short>, min_max_loc_multipass_caller<short>,
|
||||
min_max_loc_multipass_caller<int>, min_max_loc_multipass_caller<float>, 0 },
|
||||
{ min_max_loc_caller<unsigned char>, min_max_loc_caller<char>,
|
||||
min_max_loc_caller<unsigned short>, min_max_loc_caller<short>,
|
||||
min_max_loc_caller<int>, min_max_loc_caller<float>, min_max_loc_caller<double> } };
|
||||
|
||||
static const MaskedCaller masked_callers[2][7] =
|
||||
{ { min_max_loc_mask_multipass_caller<unsigned char>, min_max_loc_mask_multipass_caller<char>,
|
||||
min_max_loc_mask_multipass_caller<unsigned short>, min_max_loc_mask_multipass_caller<short>,
|
||||
min_max_loc_mask_multipass_caller<int>, min_max_loc_mask_multipass_caller<float>, 0 },
|
||||
{ min_max_loc_mask_caller<unsigned char>, min_max_loc_mask_caller<char>,
|
||||
min_max_loc_mask_caller<unsigned short>, min_max_loc_mask_caller<short>,
|
||||
min_max_loc_mask_caller<int>, min_max_loc_mask_caller<float>, min_max_loc_mask_caller<double> } };
|
||||
|
||||
CV_Assert(src.channels() == 1);
|
||||
CV_Assert(mask.empty() || (mask.type() == CV_8U && src.size() == mask.size()));
|
||||
CV_Assert(src.type() != CV_64F || hasNativeDoubleSupport(getDevice()));
|
||||
|
||||
double minVal_; if (!minVal) minVal = &minVal_;
|
||||
double maxVal_; if (!maxVal) maxVal = &maxVal_;
|
||||
int minLoc_[2];
|
||||
int maxLoc_[2];
|
||||
|
||||
Size valbuf_size, locbuf_size;
|
||||
get_buf_size_required(src.cols, src.rows, src.elemSize(), valbuf_size.width,
|
||||
valbuf_size.height, locbuf_size.width, locbuf_size.height);
|
||||
valbuf.create(valbuf_size, CV_8U);
|
||||
locbuf.create(locbuf_size, CV_8U);
|
||||
|
||||
if (mask.empty())
|
||||
{
|
||||
Caller caller = callers[hasAtomicsSupport(getDevice())][src.type()];
|
||||
if (!caller) CV_Error(CV_StsBadArg, "minMaxLoc: unsupported type");
|
||||
caller(src, minVal, maxVal, minLoc_, maxLoc_, valbuf, locbuf);
|
||||
}
|
||||
else
|
||||
{
|
||||
MaskedCaller caller = masked_callers[hasAtomicsSupport(getDevice())][src.type()];
|
||||
if (!caller) CV_Error(CV_StsBadArg, "minMaxLoc: unsupported type");
|
||||
caller(src, mask, minVal, maxVal, minLoc_, maxLoc_, valbuf, locbuf);
|
||||
}
|
||||
|
||||
if (minLoc) { minLoc->x = minLoc_[0]; minLoc->y = minLoc_[1]; }
|
||||
if (maxLoc) { maxLoc->x = maxLoc_[0]; maxLoc->y = maxLoc_[1]; }
|
||||
}
|
||||
|
||||
////////////////////////////////////////////////////////////////////////
|
||||
// Count non zero
|
||||
|
||||
namespace cv { namespace gpu { namespace mathfunc { namespace countnonzero {
|
||||
|
||||
void get_buf_size_required(int cols, int rows, int& bufcols, int& bufrows);
|
||||
|
||||
template <typename T>
|
||||
int count_non_zero_caller(const DevMem2D src, PtrStep buf);
|
||||
|
||||
template <typename T>
|
||||
int count_non_zero_multipass_caller(const DevMem2D src, PtrStep buf);
|
||||
|
||||
}}}}
|
||||
|
||||
int cv::gpu::countNonZero(const GpuMat& src)
|
||||
{
|
||||
GpuMat buf;
|
||||
return countNonZero(src, buf);
|
||||
}
|
||||
|
||||
int cv::gpu::countNonZero(const GpuMat& src, GpuMat& buf)
|
||||
{
|
||||
using namespace mathfunc::countnonzero;
|
||||
|
||||
typedef int (*Caller)(const DevMem2D src, PtrStep buf);
|
||||
|
||||
static const Caller callers[2][7] =
|
||||
{ { count_non_zero_multipass_caller<unsigned char>, count_non_zero_multipass_caller<char>,
|
||||
count_non_zero_multipass_caller<unsigned short>, count_non_zero_multipass_caller<short>,
|
||||
count_non_zero_multipass_caller<int>, count_non_zero_multipass_caller<float>, 0},
|
||||
{ count_non_zero_caller<unsigned char>, count_non_zero_caller<char>,
|
||||
count_non_zero_caller<unsigned short>, count_non_zero_caller<short>,
|
||||
count_non_zero_caller<int>, count_non_zero_caller<float>, count_non_zero_caller<double> } };
|
||||
|
||||
CV_Assert(src.channels() == 1);
|
||||
CV_Assert(src.type() != CV_64F || hasNativeDoubleSupport(getDevice()));
|
||||
|
||||
Size buf_size;
|
||||
get_buf_size_required(src.cols, src.rows, buf_size.width, buf_size.height);
|
||||
buf.create(buf_size, CV_8U);
|
||||
|
||||
Caller caller = callers[hasAtomicsSupport(getDevice())][src.type()];
|
||||
if (!caller) CV_Error(CV_StsBadArg, "countNonZero: unsupported type");
|
||||
return caller(src, buf);
|
||||
}
|
||||
|
||||
////////////////////////////////////////////////////////////////////////
|
||||
// LUT
|
||||
|
||||
@ -711,144 +343,4 @@ void cv::gpu::polarToCart(const GpuMat& magnitude, const GpuMat& angle, GpuMat&
|
||||
}
|
||||
|
||||
|
||||
//////////////////////////////////////////////////////////////////////////////
|
||||
// min/max
|
||||
|
||||
namespace cv { namespace gpu { namespace mathfunc
|
||||
{
|
||||
template <typename T>
|
||||
void min_gpu(const DevMem2D_<T>& src1, const DevMem2D_<T>& src2, const DevMem2D_<T>& dst, cudaStream_t stream);
|
||||
|
||||
template <typename T>
|
||||
void max_gpu(const DevMem2D_<T>& src1, const DevMem2D_<T>& src2, const DevMem2D_<T>& dst, cudaStream_t stream);
|
||||
|
||||
template <typename T>
|
||||
void min_gpu(const DevMem2D_<T>& src1, double src2, const DevMem2D_<T>& dst, cudaStream_t stream);
|
||||
|
||||
template <typename T>
|
||||
void max_gpu(const DevMem2D_<T>& src1, double src2, const DevMem2D_<T>& dst, cudaStream_t stream);
|
||||
}}}
|
||||
|
||||
namespace
|
||||
{
|
||||
template <typename T>
|
||||
void min_caller(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, cudaStream_t stream)
|
||||
{
|
||||
CV_Assert(src1.size() == src2.size() && src1.type() == src2.type());
|
||||
dst.create(src1.size(), src1.type());
|
||||
mathfunc::min_gpu<T>(src1.reshape(1), src2.reshape(1), dst.reshape(1), stream);
|
||||
}
|
||||
|
||||
template <typename T>
|
||||
void min_caller(const GpuMat& src1, double src2, GpuMat& dst, cudaStream_t stream)
|
||||
{
|
||||
dst.create(src1.size(), src1.type());
|
||||
mathfunc::min_gpu<T>(src1.reshape(1), src2, dst.reshape(1), stream);
|
||||
}
|
||||
|
||||
template <typename T>
|
||||
void max_caller(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, cudaStream_t stream)
|
||||
{
|
||||
CV_Assert(src1.size() == src2.size() && src1.type() == src2.type());
|
||||
dst.create(src1.size(), src1.type());
|
||||
mathfunc::max_gpu<T>(src1.reshape(1), src2.reshape(1), dst.reshape(1), stream);
|
||||
}
|
||||
|
||||
template <typename T>
|
||||
void max_caller(const GpuMat& src1, double src2, GpuMat& dst, cudaStream_t stream)
|
||||
{
|
||||
dst.create(src1.size(), src1.type());
|
||||
mathfunc::max_gpu<T>(src1.reshape(1), src2, dst.reshape(1), stream);
|
||||
}
|
||||
}
|
||||
|
||||
void cv::gpu::min(const GpuMat& src1, const GpuMat& src2, GpuMat& dst)
|
||||
{
|
||||
typedef void (*func_t)(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, cudaStream_t stream);
|
||||
static const func_t funcs[] =
|
||||
{
|
||||
min_caller<uchar>, min_caller<char>, min_caller<ushort>, min_caller<short>, min_caller<int>,
|
||||
min_caller<float>, min_caller<double>
|
||||
};
|
||||
funcs[src1.depth()](src1, src2, dst, 0);
|
||||
}
|
||||
|
||||
void cv::gpu::min(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const Stream& stream)
|
||||
{
|
||||
typedef void (*func_t)(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, cudaStream_t stream);
|
||||
static const func_t funcs[] =
|
||||
{
|
||||
min_caller<uchar>, min_caller<char>, min_caller<ushort>, min_caller<short>, min_caller<int>,
|
||||
min_caller<float>, min_caller<double>
|
||||
};
|
||||
funcs[src1.depth()](src1, src2, dst, StreamAccessor::getStream(stream));
|
||||
}
|
||||
|
||||
void cv::gpu::min(const GpuMat& src1, double src2, GpuMat& dst)
|
||||
{
|
||||
typedef void (*func_t)(const GpuMat& src1, double src2, GpuMat& dst, cudaStream_t stream);
|
||||
static const func_t funcs[] =
|
||||
{
|
||||
min_caller<uchar>, min_caller<char>, min_caller<ushort>, min_caller<short>, min_caller<int>,
|
||||
min_caller<float>, min_caller<double>
|
||||
};
|
||||
funcs[src1.depth()](src1, src2, dst, 0);
|
||||
}
|
||||
|
||||
void cv::gpu::min(const GpuMat& src1, double src2, GpuMat& dst, const Stream& stream)
|
||||
{
|
||||
typedef void (*func_t)(const GpuMat& src1, double src2, GpuMat& dst, cudaStream_t stream);
|
||||
static const func_t funcs[] =
|
||||
{
|
||||
min_caller<uchar>, min_caller<char>, min_caller<ushort>, min_caller<short>, min_caller<int>,
|
||||
min_caller<float>, min_caller<double>
|
||||
};
|
||||
funcs[src1.depth()](src1, src2, dst, StreamAccessor::getStream(stream));
|
||||
}
|
||||
|
||||
void cv::gpu::max(const GpuMat& src1, const GpuMat& src2, GpuMat& dst)
|
||||
{
|
||||
typedef void (*func_t)(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, cudaStream_t stream);
|
||||
static const func_t funcs[] =
|
||||
{
|
||||
max_caller<uchar>, max_caller<char>, max_caller<ushort>, max_caller<short>, max_caller<int>,
|
||||
max_caller<float>, max_caller<double>
|
||||
};
|
||||
funcs[src1.depth()](src1, src2, dst, 0);
|
||||
}
|
||||
|
||||
void cv::gpu::max(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const Stream& stream)
|
||||
{
|
||||
typedef void (*func_t)(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, cudaStream_t stream);
|
||||
static const func_t funcs[] =
|
||||
{
|
||||
max_caller<uchar>, max_caller<char>, max_caller<ushort>, max_caller<short>, max_caller<int>,
|
||||
max_caller<float>, max_caller<double>
|
||||
};
|
||||
funcs[src1.depth()](src1, src2, dst, StreamAccessor::getStream(stream));
|
||||
}
|
||||
|
||||
void cv::gpu::max(const GpuMat& src1, double src2, GpuMat& dst)
|
||||
{
|
||||
typedef void (*func_t)(const GpuMat& src1, double src2, GpuMat& dst, cudaStream_t stream);
|
||||
static const func_t funcs[] =
|
||||
{
|
||||
max_caller<uchar>, max_caller<char>, max_caller<ushort>, max_caller<short>, max_caller<int>,
|
||||
max_caller<float>, max_caller<double>
|
||||
};
|
||||
funcs[src1.depth()](src1, src2, dst, 0);
|
||||
}
|
||||
|
||||
void cv::gpu::max(const GpuMat& src1, double src2, GpuMat& dst, const Stream& stream)
|
||||
{
|
||||
typedef void (*func_t)(const GpuMat& src1, double src2, GpuMat& dst, cudaStream_t stream);
|
||||
static const func_t funcs[] =
|
||||
{
|
||||
max_caller<uchar>, max_caller<char>, max_caller<ushort>, max_caller<short>, max_caller<int>,
|
||||
max_caller<float>, max_caller<double>
|
||||
};
|
||||
funcs[src1.depth()](src1, src2, dst, StreamAccessor::getStream(stream));
|
||||
}
|
||||
|
||||
|
||||
#endif /* !defined (HAVE_CUDA) */
|
||||
|
||||
@ -345,4 +345,127 @@ namespace cv { namespace gpu { namespace mathfunc
|
||||
template void bitwiseMaskXorCaller<ushort>(int, int, int, const PtrStep, const PtrStep, const PtrStep, PtrStep, cudaStream_t);
|
||||
template void bitwiseMaskXorCaller<uint>(int, int, int, const PtrStep, const PtrStep, const PtrStep, PtrStep, cudaStream_t);
|
||||
|
||||
|
||||
//////////////////////////////////////////////////////////////////////////
|
||||
// min/max
|
||||
|
||||
struct MinOp
|
||||
{
|
||||
template <typename T>
|
||||
__device__ T operator()(T a, T b)
|
||||
{
|
||||
return min(a, b);
|
||||
}
|
||||
__device__ float operator()(float a, float b)
|
||||
{
|
||||
return fmin(a, b);
|
||||
}
|
||||
__device__ double operator()(double a, double b)
|
||||
{
|
||||
return fmin(a, b);
|
||||
}
|
||||
};
|
||||
|
||||
struct MaxOp
|
||||
{
|
||||
template <typename T>
|
||||
__device__ T operator()(T a, T b)
|
||||
{
|
||||
return max(a, b);
|
||||
}
|
||||
__device__ float operator()(float a, float b)
|
||||
{
|
||||
return fmax(a, b);
|
||||
}
|
||||
__device__ double operator()(double a, double b)
|
||||
{
|
||||
return fmax(a, b);
|
||||
}
|
||||
};
|
||||
|
||||
struct ScalarMinOp
|
||||
{
|
||||
double s;
|
||||
|
||||
explicit ScalarMinOp(double s_) : s(s_) {}
|
||||
|
||||
template <typename T>
|
||||
__device__ T operator()(T a)
|
||||
{
|
||||
return saturate_cast<T>(fmin((double)a, s));
|
||||
}
|
||||
};
|
||||
|
||||
struct ScalarMaxOp
|
||||
{
|
||||
double s;
|
||||
|
||||
explicit ScalarMaxOp(double s_) : s(s_) {}
|
||||
|
||||
template <typename T>
|
||||
__device__ T operator()(T a)
|
||||
{
|
||||
return saturate_cast<T>(fmax((double)a, s));
|
||||
}
|
||||
};
|
||||
|
||||
template <typename T>
|
||||
void min_gpu(const DevMem2D_<T>& src1, const DevMem2D_<T>& src2, const DevMem2D_<T>& dst, cudaStream_t stream)
|
||||
{
|
||||
MinOp op;
|
||||
transform(src1, src2, dst, op, stream);
|
||||
}
|
||||
|
||||
template void min_gpu<uchar >(const DevMem2D& src1, const DevMem2D& src2, const DevMem2D& dst, cudaStream_t stream);
|
||||
template void min_gpu<char >(const DevMem2D_<char>& src1, const DevMem2D_<char>& src2, const DevMem2D_<char>& dst, cudaStream_t stream);
|
||||
template void min_gpu<ushort>(const DevMem2D_<ushort>& src1, const DevMem2D_<ushort>& src2, const DevMem2D_<ushort>& dst, cudaStream_t stream);
|
||||
template void min_gpu<short >(const DevMem2D_<short>& src1, const DevMem2D_<short>& src2, const DevMem2D_<short>& dst, cudaStream_t stream);
|
||||
template void min_gpu<int >(const DevMem2D_<int>& src1, const DevMem2D_<int>& src2, const DevMem2D_<int>& dst, cudaStream_t stream);
|
||||
template void min_gpu<float >(const DevMem2D_<float>& src1, const DevMem2D_<float>& src2, const DevMem2D_<float>& dst, cudaStream_t stream);
|
||||
template void min_gpu<double>(const DevMem2D_<double>& src1, const DevMem2D_<double>& src2, const DevMem2D_<double>& dst, cudaStream_t stream);
|
||||
|
||||
template <typename T>
|
||||
void max_gpu(const DevMem2D_<T>& src1, const DevMem2D_<T>& src2, const DevMem2D_<T>& dst, cudaStream_t stream)
|
||||
{
|
||||
MaxOp op;
|
||||
transform(src1, src2, dst, op, stream);
|
||||
}
|
||||
|
||||
template void max_gpu<uchar >(const DevMem2D& src1, const DevMem2D& src2, const DevMem2D& dst, cudaStream_t stream);
|
||||
template void max_gpu<char >(const DevMem2D_<char>& src1, const DevMem2D_<char>& src2, const DevMem2D_<char>& dst, cudaStream_t stream);
|
||||
template void max_gpu<ushort>(const DevMem2D_<ushort>& src1, const DevMem2D_<ushort>& src2, const DevMem2D_<ushort>& dst, cudaStream_t stream);
|
||||
template void max_gpu<short >(const DevMem2D_<short>& src1, const DevMem2D_<short>& src2, const DevMem2D_<short>& dst, cudaStream_t stream);
|
||||
template void max_gpu<int >(const DevMem2D_<int>& src1, const DevMem2D_<int>& src2, const DevMem2D_<int>& dst, cudaStream_t stream);
|
||||
template void max_gpu<float >(const DevMem2D_<float>& src1, const DevMem2D_<float>& src2, const DevMem2D_<float>& dst, cudaStream_t stream);
|
||||
template void max_gpu<double>(const DevMem2D_<double>& src1, const DevMem2D_<double>& src2, const DevMem2D_<double>& dst, cudaStream_t stream);
|
||||
|
||||
template <typename T>
|
||||
void min_gpu(const DevMem2D_<T>& src1, double src2, const DevMem2D_<T>& dst, cudaStream_t stream)
|
||||
{
|
||||
ScalarMinOp op(src2);
|
||||
transform(src1, dst, op, stream);
|
||||
}
|
||||
|
||||
template void min_gpu<uchar >(const DevMem2D& src1, double src2, const DevMem2D& dst, cudaStream_t stream);
|
||||
template void min_gpu<char >(const DevMem2D_<char>& src1, double src2, const DevMem2D_<char>& dst, cudaStream_t stream);
|
||||
template void min_gpu<ushort>(const DevMem2D_<ushort>& src1, double src2, const DevMem2D_<ushort>& dst, cudaStream_t stream);
|
||||
template void min_gpu<short >(const DevMem2D_<short>& src1, double src2, const DevMem2D_<short>& dst, cudaStream_t stream);
|
||||
template void min_gpu<int >(const DevMem2D_<int>& src1, double src2, const DevMem2D_<int>& dst, cudaStream_t stream);
|
||||
template void min_gpu<float >(const DevMem2D_<float>& src1, double src2, const DevMem2D_<float>& dst, cudaStream_t stream);
|
||||
template void min_gpu<double>(const DevMem2D_<double>& src1, double src2, const DevMem2D_<double>& dst, cudaStream_t stream);
|
||||
|
||||
template <typename T>
|
||||
void max_gpu(const DevMem2D_<T>& src1, double src2, const DevMem2D_<T>& dst, cudaStream_t stream)
|
||||
{
|
||||
ScalarMaxOp op(src2);
|
||||
transform(src1, dst, op, stream);
|
||||
}
|
||||
|
||||
template void max_gpu<uchar >(const DevMem2D& src1, double src2, const DevMem2D& dst, cudaStream_t stream);
|
||||
template void max_gpu<char >(const DevMem2D_<char>& src1, double src2, const DevMem2D_<char>& dst, cudaStream_t stream);
|
||||
template void max_gpu<ushort>(const DevMem2D_<ushort>& src1, double src2, const DevMem2D_<ushort>& dst, cudaStream_t stream);
|
||||
template void max_gpu<short >(const DevMem2D_<short>& src1, double src2, const DevMem2D_<short>& dst, cudaStream_t stream);
|
||||
template void max_gpu<int >(const DevMem2D_<int>& src1, double src2, const DevMem2D_<int>& dst, cudaStream_t stream);
|
||||
template void max_gpu<float >(const DevMem2D_<float>& src1, double src2, const DevMem2D_<float>& dst, cudaStream_t stream);
|
||||
template void max_gpu<double>(const DevMem2D_<double>& src1, double src2, const DevMem2D_<double>& dst, cudaStream_t stream);
|
||||
}}}
|
||||
|
||||
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
@ -66,10 +66,14 @@ void cv::gpu::bitwise_and(const GpuMat&, const GpuMat&, GpuMat&, const GpuMat&)
|
||||
void cv::gpu::bitwise_and(const GpuMat&, const GpuMat&, GpuMat&, const GpuMat&, const Stream&) { throw_nogpu(); }
|
||||
void cv::gpu::bitwise_xor(const GpuMat&, const GpuMat&, GpuMat&, const GpuMat&) { throw_nogpu(); }
|
||||
void cv::gpu::bitwise_xor(const GpuMat&, const GpuMat&, GpuMat&, const GpuMat&, const Stream&) { throw_nogpu(); }
|
||||
cv::gpu::GpuMat cv::gpu::operator ~ (const GpuMat&) { throw_nogpu(); return GpuMat(); }
|
||||
cv::gpu::GpuMat cv::gpu::operator | (const GpuMat&, const GpuMat&) { throw_nogpu(); return GpuMat(); }
|
||||
cv::gpu::GpuMat cv::gpu::operator & (const GpuMat&, const GpuMat&) { throw_nogpu(); return GpuMat(); }
|
||||
cv::gpu::GpuMat cv::gpu::operator ^ (const GpuMat&, const GpuMat&) { throw_nogpu(); return GpuMat(); }
|
||||
void cv::gpu::min(const GpuMat&, const GpuMat&, GpuMat&) { throw_nogpu(); }
|
||||
void cv::gpu::min(const GpuMat&, const GpuMat&, GpuMat&, const Stream&) { throw_nogpu(); }
|
||||
void cv::gpu::min(const GpuMat&, double, GpuMat&) { throw_nogpu(); }
|
||||
void cv::gpu::min(const GpuMat&, double, GpuMat&, const Stream&) { throw_nogpu(); }
|
||||
void cv::gpu::max(const GpuMat&, const GpuMat&, GpuMat&) { throw_nogpu(); }
|
||||
void cv::gpu::max(const GpuMat&, const GpuMat&, GpuMat&, const Stream&) { throw_nogpu(); }
|
||||
void cv::gpu::max(const GpuMat&, double, GpuMat&) { throw_nogpu(); }
|
||||
void cv::gpu::max(const GpuMat&, double, GpuMat&, const Stream&) { throw_nogpu(); }
|
||||
|
||||
#else
|
||||
|
||||
@ -574,4 +578,144 @@ void cv::gpu::bitwise_xor(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, c
|
||||
::bitwiseXorCaller(src1, src2, dst, mask, StreamAccessor::getStream(stream));
|
||||
}
|
||||
|
||||
|
||||
//////////////////////////////////////////////////////////////////////////////
|
||||
// Minimum and maximum operations
|
||||
|
||||
namespace cv { namespace gpu { namespace mathfunc
|
||||
{
|
||||
template <typename T>
|
||||
void min_gpu(const DevMem2D_<T>& src1, const DevMem2D_<T>& src2, const DevMem2D_<T>& dst, cudaStream_t stream);
|
||||
|
||||
template <typename T>
|
||||
void max_gpu(const DevMem2D_<T>& src1, const DevMem2D_<T>& src2, const DevMem2D_<T>& dst, cudaStream_t stream);
|
||||
|
||||
template <typename T>
|
||||
void min_gpu(const DevMem2D_<T>& src1, double src2, const DevMem2D_<T>& dst, cudaStream_t stream);
|
||||
|
||||
template <typename T>
|
||||
void max_gpu(const DevMem2D_<T>& src1, double src2, const DevMem2D_<T>& dst, cudaStream_t stream);
|
||||
}}}
|
||||
|
||||
namespace
|
||||
{
|
||||
template <typename T>
|
||||
void min_caller(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, cudaStream_t stream)
|
||||
{
|
||||
CV_Assert(src1.size() == src2.size() && src1.type() == src2.type());
|
||||
dst.create(src1.size(), src1.type());
|
||||
mathfunc::min_gpu<T>(src1.reshape(1), src2.reshape(1), dst.reshape(1), stream);
|
||||
}
|
||||
|
||||
template <typename T>
|
||||
void min_caller(const GpuMat& src1, double src2, GpuMat& dst, cudaStream_t stream)
|
||||
{
|
||||
dst.create(src1.size(), src1.type());
|
||||
mathfunc::min_gpu<T>(src1.reshape(1), src2, dst.reshape(1), stream);
|
||||
}
|
||||
|
||||
template <typename T>
|
||||
void max_caller(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, cudaStream_t stream)
|
||||
{
|
||||
CV_Assert(src1.size() == src2.size() && src1.type() == src2.type());
|
||||
dst.create(src1.size(), src1.type());
|
||||
mathfunc::max_gpu<T>(src1.reshape(1), src2.reshape(1), dst.reshape(1), stream);
|
||||
}
|
||||
|
||||
template <typename T>
|
||||
void max_caller(const GpuMat& src1, double src2, GpuMat& dst, cudaStream_t stream)
|
||||
{
|
||||
dst.create(src1.size(), src1.type());
|
||||
mathfunc::max_gpu<T>(src1.reshape(1), src2, dst.reshape(1), stream);
|
||||
}
|
||||
}
|
||||
|
||||
void cv::gpu::min(const GpuMat& src1, const GpuMat& src2, GpuMat& dst)
|
||||
{
|
||||
typedef void (*func_t)(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, cudaStream_t stream);
|
||||
static const func_t funcs[] =
|
||||
{
|
||||
min_caller<uchar>, min_caller<char>, min_caller<ushort>, min_caller<short>, min_caller<int>,
|
||||
min_caller<float>, min_caller<double>
|
||||
};
|
||||
funcs[src1.depth()](src1, src2, dst, 0);
|
||||
}
|
||||
|
||||
void cv::gpu::min(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const Stream& stream)
|
||||
{
|
||||
typedef void (*func_t)(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, cudaStream_t stream);
|
||||
static const func_t funcs[] =
|
||||
{
|
||||
min_caller<uchar>, min_caller<char>, min_caller<ushort>, min_caller<short>, min_caller<int>,
|
||||
min_caller<float>, min_caller<double>
|
||||
};
|
||||
funcs[src1.depth()](src1, src2, dst, StreamAccessor::getStream(stream));
|
||||
}
|
||||
|
||||
void cv::gpu::min(const GpuMat& src1, double src2, GpuMat& dst)
|
||||
{
|
||||
typedef void (*func_t)(const GpuMat& src1, double src2, GpuMat& dst, cudaStream_t stream);
|
||||
static const func_t funcs[] =
|
||||
{
|
||||
min_caller<uchar>, min_caller<char>, min_caller<ushort>, min_caller<short>, min_caller<int>,
|
||||
min_caller<float>, min_caller<double>
|
||||
};
|
||||
funcs[src1.depth()](src1, src2, dst, 0);
|
||||
}
|
||||
|
||||
void cv::gpu::min(const GpuMat& src1, double src2, GpuMat& dst, const Stream& stream)
|
||||
{
|
||||
typedef void (*func_t)(const GpuMat& src1, double src2, GpuMat& dst, cudaStream_t stream);
|
||||
static const func_t funcs[] =
|
||||
{
|
||||
min_caller<uchar>, min_caller<char>, min_caller<ushort>, min_caller<short>, min_caller<int>,
|
||||
min_caller<float>, min_caller<double>
|
||||
};
|
||||
funcs[src1.depth()](src1, src2, dst, StreamAccessor::getStream(stream));
|
||||
}
|
||||
|
||||
void cv::gpu::max(const GpuMat& src1, const GpuMat& src2, GpuMat& dst)
|
||||
{
|
||||
typedef void (*func_t)(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, cudaStream_t stream);
|
||||
static const func_t funcs[] =
|
||||
{
|
||||
max_caller<uchar>, max_caller<char>, max_caller<ushort>, max_caller<short>, max_caller<int>,
|
||||
max_caller<float>, max_caller<double>
|
||||
};
|
||||
funcs[src1.depth()](src1, src2, dst, 0);
|
||||
}
|
||||
|
||||
void cv::gpu::max(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, const Stream& stream)
|
||||
{
|
||||
typedef void (*func_t)(const GpuMat& src1, const GpuMat& src2, GpuMat& dst, cudaStream_t stream);
|
||||
static const func_t funcs[] =
|
||||
{
|
||||
max_caller<uchar>, max_caller<char>, max_caller<ushort>, max_caller<short>, max_caller<int>,
|
||||
max_caller<float>, max_caller<double>
|
||||
};
|
||||
funcs[src1.depth()](src1, src2, dst, StreamAccessor::getStream(stream));
|
||||
}
|
||||
|
||||
void cv::gpu::max(const GpuMat& src1, double src2, GpuMat& dst)
|
||||
{
|
||||
typedef void (*func_t)(const GpuMat& src1, double src2, GpuMat& dst, cudaStream_t stream);
|
||||
static const func_t funcs[] =
|
||||
{
|
||||
max_caller<uchar>, max_caller<char>, max_caller<ushort>, max_caller<short>, max_caller<int>,
|
||||
max_caller<float>, max_caller<double>
|
||||
};
|
||||
funcs[src1.depth()](src1, src2, dst, 0);
|
||||
}
|
||||
|
||||
void cv::gpu::max(const GpuMat& src1, double src2, GpuMat& dst, const Stream& stream)
|
||||
{
|
||||
typedef void (*func_t)(const GpuMat& src1, double src2, GpuMat& dst, cudaStream_t stream);
|
||||
static const func_t funcs[] =
|
||||
{
|
||||
max_caller<uchar>, max_caller<char>, max_caller<ushort>, max_caller<short>, max_caller<int>,
|
||||
max_caller<float>, max_caller<double>
|
||||
};
|
||||
funcs[src1.depth()](src1, src2, dst, StreamAccessor::getStream(stream));
|
||||
}
|
||||
|
||||
#endif
|
||||
@ -0,0 +1,423 @@
|
||||
/*M///////////////////////////////////////////////////////////////////////////////////////
|
||||
//
|
||||
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
|
||||
//
|
||||
// By downloading, copying, installing or using the software you agree to this license.
|
||||
// If you do not agree to this license, do not download, install,
|
||||
// copy or use the software.
|
||||
//
|
||||
//
|
||||
// License Agreement
|
||||
// For Open Source Computer Vision Library
|
||||
//
|
||||
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
|
||||
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
|
||||
// Third party copyrights are property of their respective owners.
|
||||
//
|
||||
// Redistribution and use in source and binary forms, with or without modification,
|
||||
// are permitted provided that the following conditions are met:
|
||||
//
|
||||
// * Redistribution's of source code must retain the above copyright notice,
|
||||
// this list of conditions and the following disclaimer.
|
||||
//
|
||||
// * Redistribution's in binary form must reproduce the above copyright notice,
|
||||
// this list of conditions and the following disclaimer in the documentation
|
||||
// and/or other GpuMaterials provided with the distribution.
|
||||
//
|
||||
// * The name of the copyright holders may not be used to endorse or promote products
|
||||
// derived from this software without specific prior written permission.
|
||||
//
|
||||
// This software is provided by the copyright holders and contributors "as is" and
|
||||
// any express or bpied warranties, including, but not limited to, the bpied
|
||||
// warranties of merchantability and fitness for a particular purpose are disclaimed.
|
||||
// In no event shall the Intel Corporation or contributors be liable for any direct,
|
||||
// indirect, incidental, special, exemplary, or consequential damages
|
||||
// (including, but not limited to, procurement of substitute goods or services;
|
||||
// loss of use, data, or profits; or business interruption) however caused
|
||||
// and on any theory of liability, whether in contract, strict liability,
|
||||
// or tort (including negligence or otherwise) arising in any way out of
|
||||
// the use of this software, even if advised of the possibility of such damage.
|
||||
//
|
||||
//M*/
|
||||
|
||||
#include "precomp.hpp"
|
||||
|
||||
using namespace cv;
|
||||
using namespace cv::gpu;
|
||||
|
||||
#if !defined (HAVE_CUDA)
|
||||
|
||||
void cv::gpu::meanStdDev(const GpuMat&, Scalar&, Scalar&) { throw_nogpu(); }
|
||||
double cv::gpu::norm(const GpuMat&, int) { throw_nogpu(); return 0.0; }
|
||||
double cv::gpu::norm(const GpuMat&, const GpuMat&, int) { throw_nogpu(); return 0.0; }
|
||||
Scalar cv::gpu::sum(const GpuMat&) { throw_nogpu(); return Scalar(); }
|
||||
Scalar cv::gpu::sum(const GpuMat&, GpuMat&) { throw_nogpu(); return Scalar(); }
|
||||
Scalar cv::gpu::sqrSum(const GpuMat&) { throw_nogpu(); return Scalar(); }
|
||||
Scalar cv::gpu::sqrSum(const GpuMat&, GpuMat&) { throw_nogpu(); return Scalar(); }
|
||||
void cv::gpu::minMax(const GpuMat&, double*, double*, const GpuMat&) { throw_nogpu(); }
|
||||
void cv::gpu::minMax(const GpuMat&, double*, double*, const GpuMat&, GpuMat&) { throw_nogpu(); }
|
||||
void cv::gpu::minMaxLoc(const GpuMat&, double*, double*, Point*, Point*, const GpuMat&) { throw_nogpu(); }
|
||||
void cv::gpu::minMaxLoc(const GpuMat&, double*, double*, Point*, Point*, const GpuMat&, GpuMat&, GpuMat&) { throw_nogpu(); }
|
||||
int cv::gpu::countNonZero(const GpuMat&) { throw_nogpu(); return 0; }
|
||||
int cv::gpu::countNonZero(const GpuMat&, GpuMat&) { throw_nogpu(); return 0; }
|
||||
|
||||
#else
|
||||
|
||||
|
||||
////////////////////////////////////////////////////////////////////////
|
||||
// meanStdDev
|
||||
|
||||
void cv::gpu::meanStdDev(const GpuMat& src, Scalar& mean, Scalar& stddev)
|
||||
{
|
||||
CV_Assert(src.type() == CV_8UC1);
|
||||
|
||||
NppiSize sz;
|
||||
sz.width = src.cols;
|
||||
sz.height = src.rows;
|
||||
|
||||
nppSafeCall( nppiMean_StdDev_8u_C1R(src.ptr<Npp8u>(), src.step, sz, mean.val, stddev.val) );
|
||||
}
|
||||
|
||||
|
||||
////////////////////////////////////////////////////////////////////////
|
||||
// norm
|
||||
|
||||
double cv::gpu::norm(const GpuMat& src1, int normType)
|
||||
{
|
||||
return norm(src1, GpuMat(src1.size(), src1.type(), Scalar::all(0.0)), normType);
|
||||
}
|
||||
|
||||
double cv::gpu::norm(const GpuMat& src1, const GpuMat& src2, int normType)
|
||||
{
|
||||
CV_DbgAssert(src1.size() == src2.size() && src1.type() == src2.type());
|
||||
|
||||
CV_Assert(src1.type() == CV_8UC1);
|
||||
CV_Assert(normType == NORM_INF || normType == NORM_L1 || normType == NORM_L2);
|
||||
|
||||
typedef NppStatus (*npp_norm_diff_func_t)(const Npp8u* pSrc1, int nSrcStep1, const Npp8u* pSrc2, int nSrcStep2,
|
||||
NppiSize oSizeROI, Npp64f* pRetVal);
|
||||
|
||||
static const npp_norm_diff_func_t npp_norm_diff_func[] = {nppiNormDiff_Inf_8u_C1R, nppiNormDiff_L1_8u_C1R, nppiNormDiff_L2_8u_C1R};
|
||||
|
||||
NppiSize sz;
|
||||
sz.width = src1.cols;
|
||||
sz.height = src1.rows;
|
||||
|
||||
int funcIdx = normType >> 1;
|
||||
double retVal;
|
||||
|
||||
nppSafeCall( npp_norm_diff_func[funcIdx](src1.ptr<Npp8u>(), src1.step,
|
||||
src2.ptr<Npp8u>(), src2.step,
|
||||
sz, &retVal) );
|
||||
|
||||
return retVal;
|
||||
}
|
||||
|
||||
////////////////////////////////////////////////////////////////////////
|
||||
// Sum
|
||||
|
||||
namespace cv { namespace gpu { namespace mathfunc
|
||||
{
|
||||
template <typename T>
|
||||
void sum_caller(const DevMem2D src, PtrStep buf, double* sum, int cn);
|
||||
|
||||
template <typename T>
|
||||
void sum_multipass_caller(const DevMem2D src, PtrStep buf, double* sum, int cn);
|
||||
|
||||
template <typename T>
|
||||
void sqsum_caller(const DevMem2D src, PtrStep buf, double* sum, int cn);
|
||||
|
||||
template <typename T>
|
||||
void sqsum_multipass_caller(const DevMem2D src, PtrStep buf, double* sum, int cn);
|
||||
|
||||
namespace sum
|
||||
{
|
||||
void get_buf_size_required(int cols, int rows, int cn, int& bufcols, int& bufrows);
|
||||
}
|
||||
}}}
|
||||
|
||||
|
||||
Scalar cv::gpu::sum(const GpuMat& src)
|
||||
{
|
||||
GpuMat buf;
|
||||
return sum(src, buf);
|
||||
}
|
||||
|
||||
|
||||
Scalar cv::gpu::sum(const GpuMat& src, GpuMat& buf)
|
||||
{
|
||||
using namespace mathfunc;
|
||||
|
||||
typedef void (*Caller)(const DevMem2D, PtrStep, double*, int);
|
||||
static const Caller callers[2][7] =
|
||||
{ { sum_multipass_caller<unsigned char>, sum_multipass_caller<char>,
|
||||
sum_multipass_caller<unsigned short>, sum_multipass_caller<short>,
|
||||
sum_multipass_caller<int>, sum_multipass_caller<float>, 0 },
|
||||
{ sum_caller<unsigned char>, sum_caller<char>,
|
||||
sum_caller<unsigned short>, sum_caller<short>,
|
||||
sum_caller<int>, sum_caller<float>, 0 } };
|
||||
|
||||
Size bufSize;
|
||||
sum::get_buf_size_required(src.cols, src.rows, src.channels(), bufSize.width, bufSize.height);
|
||||
buf.create(bufSize, CV_8U);
|
||||
|
||||
Caller caller = callers[hasAtomicsSupport(getDevice())][src.depth()];
|
||||
if (!caller) CV_Error(CV_StsBadArg, "sum: unsupported type");
|
||||
|
||||
double result[4];
|
||||
caller(src, buf, result, src.channels());
|
||||
return Scalar(result[0], result[1], result[2], result[3]);
|
||||
}
|
||||
|
||||
|
||||
Scalar cv::gpu::sqrSum(const GpuMat& src)
|
||||
{
|
||||
GpuMat buf;
|
||||
return sqrSum(src, buf);
|
||||
}
|
||||
|
||||
|
||||
Scalar cv::gpu::sqrSum(const GpuMat& src, GpuMat& buf)
|
||||
{
|
||||
using namespace mathfunc;
|
||||
|
||||
typedef void (*Caller)(const DevMem2D, PtrStep, double*, int);
|
||||
static const Caller callers[2][7] =
|
||||
{ { sqsum_multipass_caller<unsigned char>, sqsum_multipass_caller<char>,
|
||||
sqsum_multipass_caller<unsigned short>, sqsum_multipass_caller<short>,
|
||||
sqsum_multipass_caller<int>, sqsum_multipass_caller<float>, 0 },
|
||||
{ sqsum_caller<unsigned char>, sqsum_caller<char>,
|
||||
sqsum_caller<unsigned short>, sqsum_caller<short>,
|
||||
sqsum_caller<int>, sqsum_caller<float>, 0 } };
|
||||
|
||||
Size bufSize;
|
||||
sum::get_buf_size_required(src.cols, src.rows, src.channels(), bufSize.width, bufSize.height);
|
||||
buf.create(bufSize, CV_8U);
|
||||
|
||||
Caller caller = callers[hasAtomicsSupport(getDevice())][src.depth()];
|
||||
if (!caller) CV_Error(CV_StsBadArg, "sqrSum: unsupported type");
|
||||
|
||||
double result[4];
|
||||
caller(src, buf, result, src.channels());
|
||||
return Scalar(result[0], result[1], result[2], result[3]);
|
||||
}
|
||||
|
||||
////////////////////////////////////////////////////////////////////////
|
||||
// Find min or max
|
||||
|
||||
namespace cv { namespace gpu { namespace mathfunc { namespace minmax {
|
||||
|
||||
void get_buf_size_required(int cols, int rows, int elem_size, int& bufcols, int& bufrows);
|
||||
|
||||
template <typename T>
|
||||
void min_max_caller(const DevMem2D src, double* minval, double* maxval, PtrStep buf);
|
||||
|
||||
template <typename T>
|
||||
void min_max_mask_caller(const DevMem2D src, const PtrStep mask, double* minval, double* maxval, PtrStep buf);
|
||||
|
||||
template <typename T>
|
||||
void min_max_multipass_caller(const DevMem2D src, double* minval, double* maxval, PtrStep buf);
|
||||
|
||||
template <typename T>
|
||||
void min_max_mask_multipass_caller(const DevMem2D src, const PtrStep mask, double* minval, double* maxval, PtrStep buf);
|
||||
|
||||
}}}}
|
||||
|
||||
|
||||
void cv::gpu::minMax(const GpuMat& src, double* minVal, double* maxVal, const GpuMat& mask)
|
||||
{
|
||||
GpuMat buf;
|
||||
minMax(src, minVal, maxVal, mask, buf);
|
||||
}
|
||||
|
||||
|
||||
void cv::gpu::minMax(const GpuMat& src, double* minVal, double* maxVal, const GpuMat& mask, GpuMat& buf)
|
||||
{
|
||||
using namespace mathfunc::minmax;
|
||||
|
||||
typedef void (*Caller)(const DevMem2D, double*, double*, PtrStep);
|
||||
typedef void (*MaskedCaller)(const DevMem2D, const PtrStep, double*, double*, PtrStep);
|
||||
|
||||
static const Caller callers[2][7] =
|
||||
{ { min_max_multipass_caller<unsigned char>, min_max_multipass_caller<char>,
|
||||
min_max_multipass_caller<unsigned short>, min_max_multipass_caller<short>,
|
||||
min_max_multipass_caller<int>, min_max_multipass_caller<float>, 0 },
|
||||
{ min_max_caller<unsigned char>, min_max_caller<char>,
|
||||
min_max_caller<unsigned short>, min_max_caller<short>,
|
||||
min_max_caller<int>, min_max_caller<float>, min_max_caller<double> } };
|
||||
|
||||
static const MaskedCaller masked_callers[2][7] =
|
||||
{ { min_max_mask_multipass_caller<unsigned char>, min_max_mask_multipass_caller<char>,
|
||||
min_max_mask_multipass_caller<unsigned short>, min_max_mask_multipass_caller<short>,
|
||||
min_max_mask_multipass_caller<int>, min_max_mask_multipass_caller<float>, 0 },
|
||||
{ min_max_mask_caller<unsigned char>, min_max_mask_caller<char>,
|
||||
min_max_mask_caller<unsigned short>, min_max_mask_caller<short>,
|
||||
min_max_mask_caller<int>, min_max_mask_caller<float>,
|
||||
min_max_mask_caller<double> } };
|
||||
|
||||
|
||||
CV_Assert(src.channels() == 1);
|
||||
CV_Assert(mask.empty() || (mask.type() == CV_8U && src.size() == mask.size()));
|
||||
CV_Assert(src.type() != CV_64F || hasNativeDoubleSupport(getDevice()));
|
||||
|
||||
double minVal_; if (!minVal) minVal = &minVal_;
|
||||
double maxVal_; if (!maxVal) maxVal = &maxVal_;
|
||||
|
||||
Size bufSize;
|
||||
get_buf_size_required(src.cols, src.rows, src.elemSize(), bufSize.width, bufSize.height);
|
||||
buf.create(bufSize, CV_8U);
|
||||
|
||||
if (mask.empty())
|
||||
{
|
||||
Caller caller = callers[hasAtomicsSupport(getDevice())][src.type()];
|
||||
if (!caller) CV_Error(CV_StsBadArg, "minMax: unsupported type");
|
||||
caller(src, minVal, maxVal, buf);
|
||||
}
|
||||
else
|
||||
{
|
||||
MaskedCaller caller = masked_callers[hasAtomicsSupport(getDevice())][src.type()];
|
||||
if (!caller) CV_Error(CV_StsBadArg, "minMax: unsupported type");
|
||||
caller(src, mask, minVal, maxVal, buf);
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
////////////////////////////////////////////////////////////////////////
|
||||
// Locate min and max
|
||||
|
||||
namespace cv { namespace gpu { namespace mathfunc { namespace minmaxloc {
|
||||
|
||||
void get_buf_size_required(int cols, int rows, int elem_size, int& b1cols,
|
||||
int& b1rows, int& b2cols, int& b2rows);
|
||||
|
||||
template <typename T>
|
||||
void min_max_loc_caller(const DevMem2D src, double* minval, double* maxval,
|
||||
int minloc[2], int maxloc[2], PtrStep valbuf, PtrStep locbuf);
|
||||
|
||||
template <typename T>
|
||||
void min_max_loc_mask_caller(const DevMem2D src, const PtrStep mask, double* minval, double* maxval,
|
||||
int minloc[2], int maxloc[2], PtrStep valbuf, PtrStep locbuf);
|
||||
|
||||
template <typename T>
|
||||
void min_max_loc_multipass_caller(const DevMem2D src, double* minval, double* maxval,
|
||||
int minloc[2], int maxloc[2], PtrStep valbuf, PtrStep locbuf);
|
||||
|
||||
template <typename T>
|
||||
void min_max_loc_mask_multipass_caller(const DevMem2D src, const PtrStep mask, double* minval, double* maxval,
|
||||
int minloc[2], int maxloc[2], PtrStep valbuf, PtrStep locbuf);
|
||||
}}}}
|
||||
|
||||
|
||||
void cv::gpu::minMaxLoc(const GpuMat& src, double* minVal, double* maxVal, Point* minLoc, Point* maxLoc, const GpuMat& mask)
|
||||
{
|
||||
GpuMat valbuf, locbuf;
|
||||
minMaxLoc(src, minVal, maxVal, minLoc, maxLoc, mask, valbuf, locbuf);
|
||||
}
|
||||
|
||||
|
||||
void cv::gpu::minMaxLoc(const GpuMat& src, double* minVal, double* maxVal, Point* minLoc, Point* maxLoc,
|
||||
const GpuMat& mask, GpuMat& valbuf, GpuMat& locbuf)
|
||||
{
|
||||
using namespace mathfunc::minmaxloc;
|
||||
|
||||
typedef void (*Caller)(const DevMem2D, double*, double*, int[2], int[2], PtrStep, PtrStep);
|
||||
typedef void (*MaskedCaller)(const DevMem2D, const PtrStep, double*, double*, int[2], int[2], PtrStep, PtrStep);
|
||||
|
||||
static const Caller callers[2][7] =
|
||||
{ { min_max_loc_multipass_caller<unsigned char>, min_max_loc_multipass_caller<char>,
|
||||
min_max_loc_multipass_caller<unsigned short>, min_max_loc_multipass_caller<short>,
|
||||
min_max_loc_multipass_caller<int>, min_max_loc_multipass_caller<float>, 0 },
|
||||
{ min_max_loc_caller<unsigned char>, min_max_loc_caller<char>,
|
||||
min_max_loc_caller<unsigned short>, min_max_loc_caller<short>,
|
||||
min_max_loc_caller<int>, min_max_loc_caller<float>, min_max_loc_caller<double> } };
|
||||
|
||||
static const MaskedCaller masked_callers[2][7] =
|
||||
{ { min_max_loc_mask_multipass_caller<unsigned char>, min_max_loc_mask_multipass_caller<char>,
|
||||
min_max_loc_mask_multipass_caller<unsigned short>, min_max_loc_mask_multipass_caller<short>,
|
||||
min_max_loc_mask_multipass_caller<int>, min_max_loc_mask_multipass_caller<float>, 0 },
|
||||
{ min_max_loc_mask_caller<unsigned char>, min_max_loc_mask_caller<char>,
|
||||
min_max_loc_mask_caller<unsigned short>, min_max_loc_mask_caller<short>,
|
||||
min_max_loc_mask_caller<int>, min_max_loc_mask_caller<float>, min_max_loc_mask_caller<double> } };
|
||||
|
||||
CV_Assert(src.channels() == 1);
|
||||
CV_Assert(mask.empty() || (mask.type() == CV_8U && src.size() == mask.size()));
|
||||
CV_Assert(src.type() != CV_64F || hasNativeDoubleSupport(getDevice()));
|
||||
|
||||
double minVal_; if (!minVal) minVal = &minVal_;
|
||||
double maxVal_; if (!maxVal) maxVal = &maxVal_;
|
||||
int minLoc_[2];
|
||||
int maxLoc_[2];
|
||||
|
||||
Size valbuf_size, locbuf_size;
|
||||
get_buf_size_required(src.cols, src.rows, src.elemSize(), valbuf_size.width,
|
||||
valbuf_size.height, locbuf_size.width, locbuf_size.height);
|
||||
valbuf.create(valbuf_size, CV_8U);
|
||||
locbuf.create(locbuf_size, CV_8U);
|
||||
|
||||
if (mask.empty())
|
||||
{
|
||||
Caller caller = callers[hasAtomicsSupport(getDevice())][src.type()];
|
||||
if (!caller) CV_Error(CV_StsBadArg, "minMaxLoc: unsupported type");
|
||||
caller(src, minVal, maxVal, minLoc_, maxLoc_, valbuf, locbuf);
|
||||
}
|
||||
else
|
||||
{
|
||||
MaskedCaller caller = masked_callers[hasAtomicsSupport(getDevice())][src.type()];
|
||||
if (!caller) CV_Error(CV_StsBadArg, "minMaxLoc: unsupported type");
|
||||
caller(src, mask, minVal, maxVal, minLoc_, maxLoc_, valbuf, locbuf);
|
||||
}
|
||||
|
||||
if (minLoc) { minLoc->x = minLoc_[0]; minLoc->y = minLoc_[1]; }
|
||||
if (maxLoc) { maxLoc->x = maxLoc_[0]; maxLoc->y = maxLoc_[1]; }
|
||||
}
|
||||
|
||||
//////////////////////////////////////////////////////////////////////////////
|
||||
// Count non-zero elements
|
||||
|
||||
namespace cv { namespace gpu { namespace mathfunc { namespace countnonzero {
|
||||
|
||||
void get_buf_size_required(int cols, int rows, int& bufcols, int& bufrows);
|
||||
|
||||
template <typename T>
|
||||
int count_non_zero_caller(const DevMem2D src, PtrStep buf);
|
||||
|
||||
template <typename T>
|
||||
int count_non_zero_multipass_caller(const DevMem2D src, PtrStep buf);
|
||||
|
||||
}}}}
|
||||
|
||||
|
||||
int cv::gpu::countNonZero(const GpuMat& src)
|
||||
{
|
||||
GpuMat buf;
|
||||
return countNonZero(src, buf);
|
||||
}
|
||||
|
||||
|
||||
int cv::gpu::countNonZero(const GpuMat& src, GpuMat& buf)
|
||||
{
|
||||
using namespace mathfunc::countnonzero;
|
||||
|
||||
typedef int (*Caller)(const DevMem2D src, PtrStep buf);
|
||||
|
||||
static const Caller callers[2][7] =
|
||||
{ { count_non_zero_multipass_caller<unsigned char>, count_non_zero_multipass_caller<char>,
|
||||
count_non_zero_multipass_caller<unsigned short>, count_non_zero_multipass_caller<short>,
|
||||
count_non_zero_multipass_caller<int>, count_non_zero_multipass_caller<float>, 0},
|
||||
{ count_non_zero_caller<unsigned char>, count_non_zero_caller<char>,
|
||||
count_non_zero_caller<unsigned short>, count_non_zero_caller<short>,
|
||||
count_non_zero_caller<int>, count_non_zero_caller<float>, count_non_zero_caller<double> } };
|
||||
|
||||
CV_Assert(src.channels() == 1);
|
||||
CV_Assert(src.type() != CV_64F || hasNativeDoubleSupport(getDevice()));
|
||||
|
||||
Size buf_size;
|
||||
get_buf_size_required(src.cols, src.rows, buf_size.width, buf_size.height);
|
||||
buf.create(buf_size, CV_8U);
|
||||
|
||||
Caller caller = callers[hasAtomicsSupport(getDevice())][src.type()];
|
||||
if (!caller) CV_Error(CV_StsBadArg, "countNonZero: unsupported type");
|
||||
return caller(src, buf);
|
||||
}
|
||||
|
||||
#endif
|
||||
Loading…
Reference in New Issue
Block a user