split CUDA Hough sources
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modules/gpu/src/hough_lines.cpp
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142
modules/gpu/src/hough_lines.cpp
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/*M///////////////////////////////////////////////////////////////////////////////////////
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// For Open Source Computer Vision Library
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//M*/
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#include "precomp.hpp"
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using namespace std;
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using namespace cv;
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using namespace cv::gpu;
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#if !defined (HAVE_CUDA) || defined (CUDA_DISABLER)
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void cv::gpu::HoughLines(const GpuMat&, GpuMat&, float, float, int, bool, int) { throw_nogpu(); }
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void cv::gpu::HoughLines(const GpuMat&, GpuMat&, HoughLinesBuf&, float, float, int, bool, int) { throw_nogpu(); }
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void cv::gpu::HoughLinesDownload(const GpuMat&, OutputArray, OutputArray) { throw_nogpu(); }
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#else /* !defined (HAVE_CUDA) */
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namespace cv { namespace gpu { namespace device
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{
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namespace hough
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{
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int buildPointList_gpu(PtrStepSzb src, unsigned int* list);
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}
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}}}
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namespace cv { namespace gpu { namespace device
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{
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namespace hough
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{
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void linesAccum_gpu(const unsigned int* list, int count, PtrStepSzi accum, float rho, float theta, size_t sharedMemPerBlock, bool has20);
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int linesGetResult_gpu(PtrStepSzi accum, float2* out, int* votes, int maxSize, float rho, float theta, int threshold, bool doSort);
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}
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}}}
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void cv::gpu::HoughLines(const GpuMat& src, GpuMat& lines, float rho, float theta, int threshold, bool doSort, int maxLines)
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{
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HoughLinesBuf buf;
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HoughLines(src, lines, buf, rho, theta, threshold, doSort, maxLines);
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}
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void cv::gpu::HoughLines(const GpuMat& src, GpuMat& lines, HoughLinesBuf& buf, float rho, float theta, int threshold, bool doSort, int maxLines)
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{
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using namespace cv::gpu::device::hough;
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CV_Assert(src.type() == CV_8UC1);
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CV_Assert(src.cols < std::numeric_limits<unsigned short>::max());
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CV_Assert(src.rows < std::numeric_limits<unsigned short>::max());
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ensureSizeIsEnough(1, src.size().area(), CV_32SC1, buf.list);
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unsigned int* srcPoints = buf.list.ptr<unsigned int>();
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const int pointsCount = buildPointList_gpu(src, srcPoints);
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if (pointsCount == 0)
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{
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lines.release();
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return;
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}
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const int numangle = cvRound(CV_PI / theta);
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const int numrho = cvRound(((src.cols + src.rows) * 2 + 1) / rho);
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CV_Assert(numangle > 0 && numrho > 0);
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ensureSizeIsEnough(numangle + 2, numrho + 2, CV_32SC1, buf.accum);
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buf.accum.setTo(Scalar::all(0));
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DeviceInfo devInfo;
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linesAccum_gpu(srcPoints, pointsCount, buf.accum, rho, theta, devInfo.sharedMemPerBlock(), devInfo.supports(FEATURE_SET_COMPUTE_20));
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ensureSizeIsEnough(2, maxLines, CV_32FC2, lines);
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int linesCount = linesGetResult_gpu(buf.accum, lines.ptr<float2>(0), lines.ptr<int>(1), maxLines, rho, theta, threshold, doSort);
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if (linesCount > 0)
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lines.cols = linesCount;
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else
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lines.release();
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}
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void cv::gpu::HoughLinesDownload(const GpuMat& d_lines, OutputArray h_lines_, OutputArray h_votes_)
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{
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if (d_lines.empty())
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{
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h_lines_.release();
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if (h_votes_.needed())
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h_votes_.release();
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return;
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}
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CV_Assert(d_lines.rows == 2 && d_lines.type() == CV_32FC2);
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h_lines_.create(1, d_lines.cols, CV_32FC2);
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Mat h_lines = h_lines_.getMat();
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d_lines.row(0).download(h_lines);
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if (h_votes_.needed())
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{
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h_votes_.create(1, d_lines.cols, CV_32SC1);
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Mat h_votes = h_votes_.getMat();
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GpuMat d_votes(1, d_lines.cols, CV_32SC1, const_cast<int*>(d_lines.ptr<int>(1)));
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d_votes.download(h_votes);
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}
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}
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#endif /* !defined (HAVE_CUDA) */
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