296 lines
11 KiB
C++
296 lines
11 KiB
C++
/*M///////////////////////////////////////////////////////////////////////////////////////
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//
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
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//
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// By downloading, copying, installing or using the software you agree to this license.
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// If you do not agree to this license, do not download, install,
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// copy or use the software.
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//
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//
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// License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
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// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
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// Third party copyrights are property of their respective owners.
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//
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// Redistribution and use in source and binary forms, with or without modification,
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// are permitted provided that the following conditions are met:
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//
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// * Redistribution's of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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//
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// * Redistribution's in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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//
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// * The name of the copyright holders may not be used to endorse or promote products
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// derived from this software without specific prior written permission.
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//
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// This software is provided by the copyright holders and contributors "as is" and
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// any express or implied warranties, including, but not limited to, the implied
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// warranties of merchantability and fitness for a particular purpose are disclaimed.
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// In no event shall the Intel Corporation or contributors be liable for any direct,
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// indirect, incidental, special, exemplary, or consequential damages
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// (including, but not limited to, procurement of substitute goods or services;
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// loss of use, data, or profits; or business interruption) however caused
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// and on any theory of liability, whether in contract, strict liability,
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// or tort (including negligence or otherwise) arising in any way out of
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// the use of this software, even if advised of the possibility of such damage.
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//
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//M*/
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#include "precomp.hpp"
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#if !defined (HAVE_CUDA)
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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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void cv::gpu::HoughCircles(const GpuMat&, GpuMat&, int, float, float, int, int, int, int, int) { throw_nogpu(); }
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void cv::gpu::HoughCircles(const GpuMat&, GpuMat&, HoughCirclesBuf&, int, float, float, int, int, int, int, int) { throw_nogpu(); }
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void cv::gpu::HoughCirclesDownload(const GpuMat&, 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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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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void circlesAccumCenters_gpu(const unsigned int* list, int count, PtrStepi dx, PtrStepi dy, PtrStepSzi accum, int minRadius, int maxRadius, float idp);
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int buildCentersList_gpu(PtrStepSzi accum, unsigned int* centers, int threshold);
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int circlesAccumRadius_gpu(const unsigned int* centers, int centersCount, const unsigned int* list, int count,
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float3* circles, int maxCircles, float dp, int minRadius, int maxRadius, int threshold, bool has20);
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}
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}}}
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//////////////////////////////////////////////////////////
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// HoughLines
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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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//////////////////////////////////////////////////////////
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// HoughCircles
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void cv::gpu::HoughCircles(const GpuMat& src, GpuMat& circles, int method, float dp, float minDist, int cannyThreshold, int votesThreshold, int minRadius, int maxRadius, int maxCircles)
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{
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HoughCirclesBuf buf;
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HoughCircles(src, circles, buf, method, dp, minDist, cannyThreshold, votesThreshold, minRadius, maxRadius, maxCircles);
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}
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void cv::gpu::HoughCircles(const GpuMat& src, GpuMat& circles, HoughCirclesBuf& buf, int method,
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float dp, float minDist, int cannyThreshold, int votesThreshold, int minRadius, int maxRadius, int maxCircles)
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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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CV_Assert(method == CV_HOUGH_GRADIENT);
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CV_Assert(dp > 0);
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CV_Assert(minRadius > 0 && maxRadius > minRadius);
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CV_Assert(cannyThreshold > 0);
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CV_Assert(votesThreshold > 0);
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CV_Assert(maxCircles > 0);
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const float idp = 1.0f / dp;
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cv::gpu::Canny(src, buf.cannyBuf, buf.edges, std::max(cannyThreshold / 2, 1), cannyThreshold);
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ensureSizeIsEnough(2, src.size().area(), CV_32SC1, buf.list);
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unsigned int* srcPoints = buf.list.ptr<unsigned int>(0);
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unsigned int* centers = buf.list.ptr<unsigned int>(1);
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const int pointsCount = buildPointList_gpu(buf.edges, srcPoints);
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if (pointsCount == 0)
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{
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circles.release();
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return;
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}
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ensureSizeIsEnough(cvCeil(src.rows * idp) + 2, cvCeil(src.cols * idp) + 2, CV_32SC1, buf.accum);
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buf.accum.setTo(Scalar::all(0));
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circlesAccumCenters_gpu(srcPoints, pointsCount, buf.cannyBuf.dx, buf.cannyBuf.dy, buf.accum, minRadius, maxRadius, idp);
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int centersCount = buildCentersList_gpu(buf.accum, centers, votesThreshold);
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if (centersCount == 0)
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{
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circles.release();
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return;
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}
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if (minDist > 1)
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{
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cv::AutoBuffer<ushort2> oldBuf_(centersCount);
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cv::AutoBuffer<ushort2> newBuf_(centersCount);
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int newCount = 0;
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ushort2* oldBuf = oldBuf_;
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ushort2* newBuf = newBuf_;
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cudaSafeCall( cudaMemcpy(oldBuf, centers, centersCount * sizeof(ushort2), cudaMemcpyDeviceToHost) );
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const int cellSize = cvRound(minDist);
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const int gridWidth = (src.cols + cellSize - 1) / cellSize;
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const int gridHeight = (src.rows + cellSize - 1) / cellSize;
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std::vector< std::vector<ushort2> > grid(gridWidth * gridHeight);
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minDist *= minDist;
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for (int i = 0; i < centersCount; ++i)
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{
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ushort2 p = oldBuf[i];
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bool good = true;
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int xCell = static_cast<int>(p.x / cellSize);
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int yCell = static_cast<int>(p.y / cellSize);
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int x1 = xCell - 1;
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int y1 = yCell - 1;
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int x2 = xCell + 1;
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int y2 = yCell + 1;
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// boundary check
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x1 = std::max(0, x1);
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y1 = std::max(0, y1);
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x2 = std::min(gridWidth - 1, x2);
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y2 = std::min(gridHeight - 1, y2);
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for (int yy = y1; yy <= y2; ++yy)
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{
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for (int xx = x1; xx <= x2; ++xx)
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{
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vector<ushort2>& m = grid[yy * gridWidth + xx];
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for(size_t j = 0; j < m.size(); ++j)
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{
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float dx = p.x - m[j].x;
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float dy = p.y - m[j].y;
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if (dx * dx + dy * dy < minDist)
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{
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good = false;
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goto break_out;
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}
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}
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}
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}
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break_out:
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if(good)
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{
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grid[yCell * gridWidth + xCell].push_back(p);
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newBuf[newCount++] = p;
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}
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}
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cudaSafeCall( cudaMemcpy(centers, newBuf, newCount * sizeof(unsigned int), cudaMemcpyHostToDevice) );
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centersCount = newCount;
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}
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ensureSizeIsEnough(1, maxCircles, CV_32FC3, circles);
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DeviceInfo devInfo;
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const int circlesCount = circlesAccumRadius_gpu(centers, centersCount, srcPoints, pointsCount, circles.ptr<float3>(), maxCircles,
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dp, minRadius, maxRadius, votesThreshold, devInfo.supports(FEATURE_SET_COMPUTE_20));
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if (circlesCount > 0)
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circles.cols = circlesCount;
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else
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circles.release();
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}
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void cv::gpu::HoughCirclesDownload(const GpuMat& d_circles, cv::OutputArray h_circles_)
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{
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if (d_circles.empty())
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{
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h_circles_.release();
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return;
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}
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CV_Assert(d_circles.rows == 1 && d_circles.type() == CV_32FC3);
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h_circles_.create(1, d_circles.cols, CV_32FC3);
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Mat h_circles = h_circles_.getMat();
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d_circles.download(h_circles);
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}
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#endif /* !defined (HAVE_CUDA) */
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