/*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 materials 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 implied warranties, including, but not limited to, the implied // 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 std; using namespace cv; using namespace cv::gpu; #if !defined (HAVE_CUDA) || defined (CUDA_DISABLER) void cv::gpu::HoughCircles(const GpuMat&, GpuMat&, int, float, float, int, int, int, int, int) { throw_nogpu(); } void cv::gpu::HoughCircles(const GpuMat&, GpuMat&, HoughCirclesBuf&, int, float, float, int, int, int, int, int) { throw_nogpu(); } void cv::gpu::HoughCirclesDownload(const GpuMat&, OutputArray) { throw_nogpu(); } #else /* !defined (HAVE_CUDA) */ namespace cv { namespace gpu { namespace device { namespace hough { int buildPointList_gpu(PtrStepSzb src, unsigned int* list); } }}} namespace cv { namespace gpu { namespace device { namespace hough { void circlesAccumCenters_gpu(const unsigned int* list, int count, PtrStepi dx, PtrStepi dy, PtrStepSzi accum, int minRadius, int maxRadius, float idp); int buildCentersList_gpu(PtrStepSzi accum, unsigned int* centers, int threshold); int circlesAccumRadius_gpu(const unsigned int* centers, int centersCount, const unsigned int* list, int count, float3* circles, int maxCircles, float dp, int minRadius, int maxRadius, int threshold, bool has20); } }}} 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) { HoughCirclesBuf buf; HoughCircles(src, circles, buf, method, dp, minDist, cannyThreshold, votesThreshold, minRadius, maxRadius, maxCircles); } void cv::gpu::HoughCircles(const GpuMat& src, GpuMat& circles, HoughCirclesBuf& buf, int method, float dp, float minDist, int cannyThreshold, int votesThreshold, int minRadius, int maxRadius, int maxCircles) { using namespace cv::gpu::device::hough; CV_Assert(src.type() == CV_8UC1); CV_Assert(src.cols < std::numeric_limits<unsigned short>::max()); CV_Assert(src.rows < std::numeric_limits<unsigned short>::max()); CV_Assert(method == CV_HOUGH_GRADIENT); CV_Assert(dp > 0); CV_Assert(minRadius > 0 && maxRadius > minRadius); CV_Assert(cannyThreshold > 0); CV_Assert(votesThreshold > 0); CV_Assert(maxCircles > 0); const float idp = 1.0f / dp; cv::gpu::Canny(src, buf.cannyBuf, buf.edges, std::max(cannyThreshold / 2, 1), cannyThreshold); ensureSizeIsEnough(2, src.size().area(), CV_32SC1, buf.list); unsigned int* srcPoints = buf.list.ptr<unsigned int>(0); unsigned int* centers = buf.list.ptr<unsigned int>(1); const int pointsCount = buildPointList_gpu(buf.edges, srcPoints); if (pointsCount == 0) { circles.release(); return; } ensureSizeIsEnough(cvCeil(src.rows * idp) + 2, cvCeil(src.cols * idp) + 2, CV_32SC1, buf.accum); buf.accum.setTo(Scalar::all(0)); circlesAccumCenters_gpu(srcPoints, pointsCount, buf.cannyBuf.dx, buf.cannyBuf.dy, buf.accum, minRadius, maxRadius, idp); int centersCount = buildCentersList_gpu(buf.accum, centers, votesThreshold); if (centersCount == 0) { circles.release(); return; } if (minDist > 1) { cv::AutoBuffer<ushort2> oldBuf_(centersCount); cv::AutoBuffer<ushort2> newBuf_(centersCount); int newCount = 0; ushort2* oldBuf = oldBuf_; ushort2* newBuf = newBuf_; cudaSafeCall( cudaMemcpy(oldBuf, centers, centersCount * sizeof(ushort2), cudaMemcpyDeviceToHost) ); const int cellSize = cvRound(minDist); const int gridWidth = (src.cols + cellSize - 1) / cellSize; const int gridHeight = (src.rows + cellSize - 1) / cellSize; std::vector< std::vector<ushort2> > grid(gridWidth * gridHeight); const float minDist2 = minDist * minDist; for (int i = 0; i < centersCount; ++i) { ushort2 p = oldBuf[i]; bool good = true; int xCell = static_cast<int>(p.x / cellSize); int yCell = static_cast<int>(p.y / cellSize); int x1 = xCell - 1; int y1 = yCell - 1; int x2 = xCell + 1; int y2 = yCell + 1; // boundary check x1 = std::max(0, x1); y1 = std::max(0, y1); x2 = std::min(gridWidth - 1, x2); y2 = std::min(gridHeight - 1, y2); for (int yy = y1; yy <= y2; ++yy) { for (int xx = x1; xx <= x2; ++xx) { vector<ushort2>& m = grid[yy * gridWidth + xx]; for(size_t j = 0; j < m.size(); ++j) { float dx = (float)(p.x - m[j].x); float dy = (float)(p.y - m[j].y); if (dx * dx + dy * dy < minDist2) { good = false; goto break_out; } } } } break_out: if(good) { grid[yCell * gridWidth + xCell].push_back(p); newBuf[newCount++] = p; } } cudaSafeCall( cudaMemcpy(centers, newBuf, newCount * sizeof(unsigned int), cudaMemcpyHostToDevice) ); centersCount = newCount; } ensureSizeIsEnough(1, maxCircles, CV_32FC3, circles); const int circlesCount = circlesAccumRadius_gpu(centers, centersCount, srcPoints, pointsCount, circles.ptr<float3>(), maxCircles, dp, minRadius, maxRadius, votesThreshold, deviceSupports(FEATURE_SET_COMPUTE_20)); if (circlesCount > 0) circles.cols = circlesCount; else circles.release(); } void cv::gpu::HoughCirclesDownload(const GpuMat& d_circles, cv::OutputArray h_circles_) { if (d_circles.empty()) { h_circles_.release(); return; } CV_Assert(d_circles.rows == 1 && d_circles.type() == CV_32FC3); h_circles_.create(1, d_circles.cols, CV_32FC3); Mat h_circles = h_circles_.getMat(); d_circles.download(h_circles); } #endif /* !defined (HAVE_CUDA) */