diff --git a/modules/ocl/doc/image_processing.rst b/modules/ocl/doc/image_processing.rst index 94712e091d..3f97301749 100644 --- a/modules/ocl/doc/image_processing.rst +++ b/modules/ocl/doc/image_processing.rst @@ -329,3 +329,38 @@ Interpolate frames (images) using provided optical flow (displacement field). :param newFrame: Output image. :param buf: Temporary buffer, will have width x 6*height size, CV_32FC1 type and contain 6 oclMat: occlusion masks for first frame, occlusion masks for second, interpolated forward horizontal flow, interpolated forward vertical flow, interpolated backward horizontal flow, interpolated backward vertical flow. + + +ocl::HoughCircles +----------------- +Finds circles in a grayscale image using the Hough transform. + +.. ocv:function:: void ocl::HoughCircles(const oclMat& src, oclMat& circles, int method, float dp, float minDist, int cannyThreshold, int votesThreshold, int minRadius, int maxRadius, int maxCircles = 4096) + +.. ocv:function:: void ocl::HoughCircles(const oclMat& src, oclMat& circles, HoughCirclesBuf& buf, int method, float dp, float minDist, int cannyThreshold, int votesThreshold, int minRadius, int maxRadius, int maxCircles = 4096) + + :param src: 8-bit, single-channel grayscale input image. + + :param circles: Output vector of found circles. Each vector is encoded as a 3-element floating-point vector :math:`(x, y, radius)` . + + :param method: Detection method to use. Currently, the only implemented method is ``CV_HOUGH_GRADIENT`` , which is basically *21HT* , described in [Yuen90]_. + + :param dp: Inverse ratio of the accumulator resolution to the image resolution. For example, if ``dp=1`` , the accumulator has the same resolution as the input image. If ``dp=2`` , the accumulator has half as big width and height. + + :param minDist: Minimum distance between the centers of the detected circles. If the parameter is too small, multiple neighbor circles may be falsely detected in addition to a true one. If it is too large, some circles may be missed. + + :param cannyThreshold: The higher threshold of the two passed to the :ocv:func:`ocl::Canny` edge detector (the lower one is twice smaller). + + :param votesThreshold: The accumulator threshold for the circle centers at the detection stage. The smaller it is, the more false circles may be detected. + + :param minRadius: Minimum circle radius. + + :param maxRadius: Maximum circle radius. + + :param maxCircles: Maximum number of output circles. + + :param buf: Optional buffer to avoid extra memory allocations (for many calls with the same sizes). + +.. note:: Currently only non-ROI oclMat is supported for src. +.. seealso:: :ocv:func:`HoughCircles` + diff --git a/modules/ocl/include/opencv2/ocl/ocl.hpp b/modules/ocl/include/opencv2/ocl/ocl.hpp index 4a56cff204..c32f9482e7 100644 --- a/modules/ocl/include/opencv2/ocl/ocl.hpp +++ b/modules/ocl/include/opencv2/ocl/ocl.hpp @@ -41,8 +41,8 @@ // //M*/ -#ifndef __OPENCV_GPU_HPP__ -#define __OPENCV_GPU_HPP__ +#ifndef __OPENCV_OCL_HPP__ +#define __OPENCV_OCL_HPP__ #include #include @@ -827,6 +827,22 @@ namespace cv }; + ///////////////////////////////////////// Hough Transform ///////////////////////////////////////// + //! HoughCircles + struct HoughCirclesBuf + { + oclMat edges; + oclMat accum; + oclMat srcPoints; + oclMat centers; + CannyBuf cannyBuf; + }; + + CV_EXPORTS void HoughCircles(const oclMat& src, oclMat& circles, int method, float dp, float minDist, int cannyThreshold, int votesThreshold, int minRadius, int maxRadius, int maxCircles = 4096); + CV_EXPORTS void HoughCircles(const oclMat& src, oclMat& circles, HoughCirclesBuf& buf, int method, float dp, float minDist, int cannyThreshold, int votesThreshold, int minRadius, int maxRadius, int maxCircles = 4096); + CV_EXPORTS void HoughCirclesDownload(const oclMat& d_circles, OutputArray h_circles); + + ///////////////////////////////////////// clAmdFft related ///////////////////////////////////////// //! Performs a forward or inverse discrete Fourier transform (1D or 2D) of floating point matrix. //! Param dft_size is the size of DFT transform. @@ -1746,4 +1762,4 @@ namespace cv #if _MSC_VER >= 1200 #pragma warning( pop) #endif -#endif /* __OPENCV_GPU_HPP__ */ +#endif /* __OPENCV_OCL_HPP__ */ diff --git a/modules/ocl/perf/perf_hough.cpp b/modules/ocl/perf/perf_hough.cpp new file mode 100644 index 0000000000..d0d130e922 --- /dev/null +++ b/modules/ocl/perf/perf_hough.cpp @@ -0,0 +1,98 @@ +/*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) 2010-2012, Multicoreware, Inc., all rights reserved. +// Copyright (C) 2010-2012, Advanced Micro Devices, 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 oclMaterials 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" + +#ifdef HAVE_OPENCL + +using namespace cv; +using namespace perf; + +////////////////////////////////////////////////////////////////////// +// HoughCircles + +typedef std::tr1::tuple Size_Dp_MinDist_t; +typedef perf::TestBaseWithParam Size_Dp_MinDist; + +PERF_TEST_P(Size_Dp_MinDist, OCL_HoughCircles, + testing::Combine( + testing::Values(perf::sz720p, perf::szSXGA, perf::sz1080p), + testing::Values(1.0f, 2.0f, 4.0f), + testing::Values(1.0f, 10.0f))) +{ + const cv::Size size = std::tr1::get<0>(GetParam()); + const float dp = std::tr1::get<1>(GetParam()); + const float minDist = std::tr1::get<2>(GetParam()); + + const int minRadius = 10; + const int maxRadius = 30; + const int cannyThreshold = 100; + const int votesThreshold = 15; + + cv::RNG rng(123456789); + + cv::Mat src(size, CV_8UC1, cv::Scalar::all(0)); + + const int numCircles = rng.uniform(50, 100); + for (int i = 0; i < numCircles; ++i) + { + cv::Point center(rng.uniform(0, src.cols), rng.uniform(0, src.rows)); + const int radius = rng.uniform(minRadius, maxRadius + 1); + + cv::circle(src, center, radius, cv::Scalar::all(255), -1); + } + + cv::ocl::oclMat ocl_src(src); + cv::ocl::oclMat ocl_circles; + + declare.time(10.0).iterations(25); + + TEST_CYCLE() + { + cv::ocl::HoughCircles(ocl_src, ocl_circles, CV_HOUGH_GRADIENT, dp, minDist, cannyThreshold, votesThreshold, minRadius, maxRadius); + } + + cv::Mat circles(ocl_circles); + SANITY_CHECK(circles); +} + +#endif // HAVE_OPENCL diff --git a/modules/ocl/src/hough.cpp b/modules/ocl/src/hough.cpp new file mode 100644 index 0000000000..0d2e9b81fa --- /dev/null +++ b/modules/ocl/src/hough.cpp @@ -0,0 +1,416 @@ +/*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::ocl; + +#if !defined (HAVE_OPENCL) + +void cv::ocl::HoughCircles(const oclMat&, oclMat&, int, float, float, int, int, int, int, int) { throw_nogpu(); } +void cv::ocl::HoughCircles(const oclMat&, oclMat&, HoughCirclesBuf&, int, float, float, int, int, int, int, int) { throw_nogpu(); } +void cv::ocl::HoughCirclesDownload(const oclMat&, OutputArray) { throw_nogpu(); } + +#else /* !defined (HAVE_OPENCL) */ + +#define MUL_UP(a, b) ((a)/(b)+1)*(b) + +namespace cv { namespace ocl { + ///////////////////////////OpenCL kernel strings/////////////////////////// + extern const char *imgproc_hough; + + namespace hough + { + int buildPointList_gpu(const oclMat& src, oclMat& list); + void circlesAccumCenters_gpu(const unsigned int* list, int count, const oclMat& dx, const oclMat& dy, oclMat& accum, int minRadius, int maxRadius, float idp); + int buildCentersList_gpu(const oclMat& accum, oclMat& centers, int threshold); + + int circlesAccumRadius_gpu(const oclMat& centers, int centersCount, + const oclMat& list, int count, + oclMat& circles, int maxCircles, + float dp, int minRadius, int maxRadius, int threshold); + } +}} + + + +////////////////////////////////////////////////////////// +// common functions + +namespace cv { namespace ocl { namespace hough +{ + int buildPointList_gpu(const oclMat& src, oclMat& list) + { + const int PIXELS_PER_THREAD = 16; + + int totalCount = 0; + int err = CL_SUCCESS; + cl_mem counter = clCreateBuffer(src.clCxt->impl->clContext, + CL_MEM_COPY_HOST_PTR, + sizeof(int), + &totalCount, + &err); + openCLSafeCall(err); + + const size_t blkSizeX = 32; + const size_t blkSizeY = 4; + size_t localThreads[3] = { blkSizeX, blkSizeY, 1 }; + + const int PIXELS_PER_BLOCK = blkSizeX * PIXELS_PER_THREAD; + const size_t glbSizeX = src.cols % (PIXELS_PER_BLOCK) == 0 ? src.cols : MUL_UP(src.cols, PIXELS_PER_BLOCK); + const size_t glbSizeY = src.rows % blkSizeY == 0 ? src.rows : MUL_UP(src.rows, blkSizeY); + size_t globalThreads[3] = { glbSizeX, glbSizeY, 1 }; + + vector > args; + args.push_back( make_pair( sizeof(cl_mem) , (void *)&src.data )); + args.push_back( make_pair( sizeof(cl_int) , (void *)&src.cols )); + args.push_back( make_pair( sizeof(cl_int) , (void *)&src.rows )); + args.push_back( make_pair( sizeof(cl_int) , (void *)&src.step )); + args.push_back( make_pair( sizeof(cl_mem) , (void *)&list.data )); + args.push_back( make_pair( sizeof(cl_mem) , (void *)&counter )); + + openCLExecuteKernel(src.clCxt, &imgproc_hough, "buildPointList", globalThreads, localThreads, args, -1, -1); + openCLSafeCall(clEnqueueReadBuffer(src.clCxt->impl->clCmdQueue, counter, CL_TRUE, 0, sizeof(int), &totalCount, 0, NULL, NULL)); + openCLSafeCall(clReleaseMemObject(counter)); + + return totalCount; + } +}}} + +////////////////////////////////////////////////////////// +// HoughCircles + +namespace cv { namespace ocl { namespace hough +{ + void circlesAccumCenters_gpu(const oclMat& list, int count, const oclMat& dx, const oclMat& dy, oclMat& accum, int minRadius, int maxRadius, float idp) + { + const size_t blkSizeX = 256; + size_t localThreads[3] = { 256, 1, 1 }; + + const size_t glbSizeX = count % blkSizeX == 0 ? count : MUL_UP(count, blkSizeX); + size_t globalThreads[3] = { glbSizeX, 1, 1 }; + + const int width = accum.cols - 2; + const int height = accum.rows - 2; + + vector > args; + args.push_back( make_pair( sizeof(cl_mem) , (void *)&list.data )); + args.push_back( make_pair( sizeof(cl_int) , (void *)&count )); + args.push_back( make_pair( sizeof(cl_mem) , (void *)&dx.data )); + args.push_back( make_pair( sizeof(cl_int) , (void *)&dx.step )); + args.push_back( make_pair( sizeof(cl_mem) , (void *)&dy.data )); + args.push_back( make_pair( sizeof(cl_int) , (void *)&dy.step )); + args.push_back( make_pair( sizeof(cl_mem) , (void *)&accum.data )); + args.push_back( make_pair( sizeof(cl_int) , (void *)&accum.step )); + args.push_back( make_pair( sizeof(cl_int) , (void *)&width )); + args.push_back( make_pair( sizeof(cl_int) , (void *)&height )); + args.push_back( make_pair( sizeof(cl_int) , (void *)&minRadius)); + args.push_back( make_pair( sizeof(cl_int) , (void *)&maxRadius)); + args.push_back( make_pair( sizeof(cl_float), (void *)&idp)); + + openCLExecuteKernel(accum.clCxt, &imgproc_hough, "circlesAccumCenters", globalThreads, localThreads, args, -1, -1); + } + + int buildCentersList_gpu(const oclMat& accum, oclMat& centers, int threshold) + { + int totalCount = 0; + int err = CL_SUCCESS; + cl_mem counter = clCreateBuffer(accum.clCxt->impl->clContext, + CL_MEM_COPY_HOST_PTR, + sizeof(int), + &totalCount, + &err); + openCLSafeCall(err); + + const size_t blkSizeX = 32; + const size_t blkSizeY = 8; + size_t localThreads[3] = { blkSizeX, blkSizeY, 1 }; + + const size_t glbSizeX = (accum.cols - 2) % blkSizeX == 0 ? accum.cols - 2 : MUL_UP(accum.cols - 2, blkSizeX); + const size_t glbSizeY = (accum.rows - 2) % blkSizeY == 0 ? accum.rows - 2 : MUL_UP(accum.rows - 2, blkSizeY); + size_t globalThreads[3] = { glbSizeX, glbSizeY, 1 }; + + vector > args; + args.push_back( make_pair( sizeof(cl_mem) , (void *)&accum.data )); + args.push_back( make_pair( sizeof(cl_int) , (void *)&accum.cols )); + args.push_back( make_pair( sizeof(cl_int) , (void *)&accum.rows )); + args.push_back( make_pair( sizeof(cl_int) , (void *)&accum.step )); + args.push_back( make_pair( sizeof(cl_mem) , (void *)¢ers.data )); + args.push_back( make_pair( sizeof(cl_int) , (void *)&threshold )); + args.push_back( make_pair( sizeof(cl_mem) , (void *)&counter )); + + openCLExecuteKernel(accum.clCxt, &imgproc_hough, "buildCentersList", globalThreads, localThreads, args, -1, -1); + + openCLSafeCall(clEnqueueReadBuffer(accum.clCxt->impl->clCmdQueue, counter, CL_TRUE, 0, sizeof(int), &totalCount, 0, NULL, NULL)); + openCLSafeCall(clReleaseMemObject(counter)); + + return totalCount; + } + + int circlesAccumRadius_gpu(const oclMat& centers, int centersCount, + const oclMat& list, int count, + oclMat& circles, int maxCircles, + float dp, int minRadius, int maxRadius, int threshold) + { + int totalCount = 0; + int err = CL_SUCCESS; + cl_mem counter = clCreateBuffer(circles.clCxt->impl->clContext, + CL_MEM_COPY_HOST_PTR, + sizeof(int), + &totalCount, + &err); + openCLSafeCall(err); + + const size_t blkSizeX = circles.clCxt->impl->maxWorkGroupSize; + size_t localThreads[3] = { blkSizeX, 1, 1 }; + + const size_t glbSizeX = centersCount * blkSizeX; + size_t globalThreads[3] = { glbSizeX, 1, 1 }; + + const int histSize = maxRadius - minRadius + 1; + size_t smemSize = (histSize + 2) * sizeof(int); + + vector > args; + args.push_back( make_pair( sizeof(cl_mem) , (void *)¢ers.data )); + args.push_back( make_pair( sizeof(cl_mem) , (void *)&list.data )); + args.push_back( make_pair( sizeof(cl_int) , (void *)&count )); + args.push_back( make_pair( sizeof(cl_mem) , (void *)&circles.data )); + args.push_back( make_pair( sizeof(cl_int) , (void *)&maxCircles )); + args.push_back( make_pair( sizeof(cl_float), (void *)&dp )); + args.push_back( make_pair( sizeof(cl_int) , (void *)&minRadius )); + args.push_back( make_pair( sizeof(cl_int) , (void *)&maxRadius )); + args.push_back( make_pair( sizeof(cl_int) , (void *)&histSize )); + args.push_back( make_pair( sizeof(cl_int) , (void *)&threshold )); + args.push_back( make_pair( smemSize , (void *)NULL )); + args.push_back( make_pair( sizeof(cl_mem) , (void *)&counter )); + + CV_Assert(circles.offset == 0); + + openCLExecuteKernel(circles.clCxt, &imgproc_hough, "circlesAccumRadius", globalThreads, localThreads, args, -1, -1); + + openCLSafeCall(clEnqueueReadBuffer(circles.clCxt->impl->clCmdQueue, counter, CL_TRUE, 0, sizeof(int), &totalCount, 0, NULL, NULL)); + + openCLSafeCall(clReleaseMemObject(counter)); + + totalCount = ::min(totalCount, maxCircles); + + return totalCount; + } + + +}}} // namespace cv { namespace ocl { namespace hough + + + +void cv::ocl::HoughCircles(const oclMat& src, oclMat& 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::ocl::HoughCircles(const oclMat& src, oclMat& circles, HoughCirclesBuf& buf, int method, + float dp, float minDist, int cannyThreshold, int votesThreshold, int minRadius, int maxRadius, int maxCircles) +{ + CV_Assert(src.type() == CV_8UC1); + CV_Assert(src.cols < std::numeric_limits::max()); + CV_Assert(src.rows < std::numeric_limits::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::ocl::Canny(src, buf.cannyBuf, buf.edges, std::max(cannyThreshold / 2, 1), cannyThreshold); + + ensureSizeIsEnough(1, src.size().area(), CV_32SC1, buf.srcPoints); + const int pointsCount = hough::buildPointList_gpu(buf.edges, buf.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)); + + hough::circlesAccumCenters_gpu(buf.srcPoints, pointsCount, buf.cannyBuf.dx, buf.cannyBuf.dy, buf.accum, minRadius, maxRadius, idp); + + ensureSizeIsEnough(1, src.size().area(), CV_32SC1, buf.centers); + int centersCount = hough::buildCentersList_gpu(buf.accum, buf.centers, votesThreshold); + if (centersCount == 0) + { + circles.release(); + return; + } + + if (minDist > 1) + { + cv::AutoBuffer oldBuf_(centersCount); + cv::AutoBuffer newBuf_(centersCount); + int newCount = 0; + + unsigned int* oldBuf = oldBuf_; + unsigned int* newBuf = newBuf_; + + openCLSafeCall(clEnqueueReadBuffer(buf.centers.clCxt->impl->clCmdQueue, + (cl_mem)buf.centers.data, + CL_TRUE, + 0, + centersCount * sizeof(unsigned int), + oldBuf, + 0, + NULL, + NULL)); + + + 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 > grid(gridWidth * gridHeight); + + const float minDist2 = minDist * minDist; + + for (int i = 0; i < centersCount; ++i) + { + unsigned int p = oldBuf[i]; + const int px = p & 0xFFFF; + const int py = (p >> 16) & 0xFFFF; + + bool good = true; + + int xCell = static_cast(px / cellSize); + int yCell = static_cast(py / 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& m = grid[yy * gridWidth + xx]; + + for(size_t j = 0; j < m.size(); ++j) + { + const int val = m[j]; + const int jx = val & 0xFFFF; + const int jy = (val >> 16) & 0xFFFF; + + float dx = (float)(px - jx); + float dy = (float)(py - jy); + + 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; + } + } + + openCLSafeCall(clEnqueueWriteBuffer(buf.centers.clCxt->impl->clCmdQueue, + (cl_mem)buf.centers.data, + CL_TRUE, + 0, + newCount * sizeof(unsigned int), + newBuf, + 0, + 0, + 0)); + centersCount = newCount; + } + + ensureSizeIsEnough(1, maxCircles, CV_32FC3, circles); + + const int circlesCount = hough::circlesAccumRadius_gpu(buf.centers, centersCount, + buf.srcPoints, pointsCount, + circles, maxCircles, + dp, minRadius, maxRadius, votesThreshold); + + if (circlesCount > 0) + circles.cols = circlesCount; + else + circles.release(); +} + +void cv::ocl::HoughCirclesDownload(const oclMat& d_circles, cv::OutputArray h_circles_) +{ + // FIX ME: garbage values are copied! + CV_Error(CV_StsNotImplemented, "HoughCirclesDownload is not implemented"); + + 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_OPENCL) */ diff --git a/modules/ocl/src/kernels/imgproc_hough.cl b/modules/ocl/src/kernels/imgproc_hough.cl new file mode 100644 index 0000000000..06655dea31 --- /dev/null +++ b/modules/ocl/src/kernels/imgproc_hough.cl @@ -0,0 +1,280 @@ +/*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 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*/ + +#pragma OPENCL EXTENSION cl_khr_global_int32_base_atomics : enable +#pragma OPENCL EXTENSION cl_khr_local_int32_base_atomics : enable + +//////////////////////////////////////////////////////////////////////// +// buildPointList + +#define PIXELS_PER_THREAD 16 + +// TODO: add offset to support ROI +__kernel void buildPointList(__global const uchar* src, + int cols, + int rows, + int step, + __global unsigned int* list, + __global int* counter) +{ + __local unsigned int s_queues[4][32 * PIXELS_PER_THREAD]; + __local int s_qsize[4]; + __local int s_globStart[4]; + + const int x = get_group_id(0) * get_local_size(0) * PIXELS_PER_THREAD + get_local_id(0); + const int y = get_global_id(1); + + if (get_local_id(0) == 0) + s_qsize[get_local_id(1)] = 0; + barrier(CLK_LOCAL_MEM_FENCE); + + if (y < rows) + { + // fill the queue + __global const uchar* srcRow = &src[y * step]; + for (int i = 0, xx = x; i < PIXELS_PER_THREAD && xx < cols; ++i, xx += get_local_size(0)) + { + if (srcRow[xx]) + { + const unsigned int val = (y << 16) | xx; + const int qidx = atomic_add(&s_qsize[get_local_id(1)], 1); + s_queues[get_local_id(1)][qidx] = val; + } + } + } + + barrier(CLK_LOCAL_MEM_FENCE); + + // let one work-item reserve the space required in the global list + if (get_local_id(0) == 0 && get_local_id(1) == 0) + { + // find how many items are stored in each list + int totalSize = 0; + for (int i = 0; i < get_local_size(1); ++i) + { + s_globStart[i] = totalSize; + totalSize += s_qsize[i]; + } + + // calculate the offset in the global list + const int globalOffset = atomic_add(counter, totalSize); + for (int i = 0; i < get_local_size(1); ++i) + s_globStart[i] += globalOffset; + } + + barrier(CLK_GLOBAL_MEM_FENCE); + + // copy local queues to global queue + const int qsize = s_qsize[get_local_id(1)]; + int gidx = s_globStart[get_local_id(1)] + get_local_id(0); + for(int i = get_local_id(0); i < qsize; i += get_local_size(0), gidx += get_local_size(0)) + list[gidx] = s_queues[get_local_id(1)][i]; +} + +//////////////////////////////////////////////////////////////////////// +// circlesAccumCenters + +// TODO: add offset to support ROI +__kernel void circlesAccumCenters(__global const unsigned int* list, + const int count, + __global const int* dx, + const int dxStep, + __global const int* dy, + const int dyStep, + __global int* accum, + const int accumStep, + const int width, + const int height, + const int minRadius, + const int maxRadius, + const float idp) +{ + const int dxStepInPixel = dxStep / sizeof(int); + const int dyStepInPixel = dyStep / sizeof(int); + const int accumStepInPixel = accumStep / sizeof(int); + + const int SHIFT = 10; + const int ONE = 1 << SHIFT; + + // const int tid = blockIdx.x * blockDim.x + threadIdx.x; + const int wid = get_global_id(0); + + if (wid >= count) + return; + + const unsigned int val = list[wid]; + + const int x = (val & 0xFFFF); + const int y = (val >> 16) & 0xFFFF; + + const int vx = dx[mad24(y, dxStepInPixel, x)]; + const int vy = dy[mad24(y, dyStepInPixel, x)]; + + if (vx == 0 && vy == 0) + return; + + const float mag = sqrt(convert_float(vx * vx + vy * vy)); + + const int x0 = convert_int_rte((x * idp) * ONE); + const int y0 = convert_int_rte((y * idp) * ONE); + + int sx = convert_int_rte((vx * idp) * ONE / mag); + int sy = convert_int_rte((vy * idp) * ONE / mag); + + // Step from minRadius to maxRadius in both directions of the gradient + for (int k1 = 0; k1 < 2; ++k1) + { + int x1 = x0 + minRadius * sx; + int y1 = y0 + minRadius * sy; + + for (int r = minRadius; r <= maxRadius; x1 += sx, y1 += sy, ++r) + { + const int x2 = x1 >> SHIFT; + const int y2 = y1 >> SHIFT; + + if (x2 < 0 || x2 >= width || y2 < 0 || y2 >= height) + break; + + atomic_add(&accum[mad24(y2+1, accumStepInPixel, x2+1)], 1); + } + + sx = -sx; + sy = -sy; + } +} + +// //////////////////////////////////////////////////////////////////////// +// // buildCentersList + +// TODO: add offset to support ROI +__kernel void buildCentersList(__global const int* accum, + const int accumCols, + const int accumRows, + const int accumStep, + __global unsigned int* centers, + const int threshold, + __global int* counter) +{ + const int accumStepInPixel = accumStep/sizeof(int); + + const int x = get_global_id(0); + const int y = get_global_id(1); + + if (x < accumCols - 2 && y < accumRows - 2) + { + const int top = accum[mad24(y, accumStepInPixel, x + 1)]; + + const int left = accum[mad24(y + 1, accumStepInPixel, x)]; + const int cur = accum[mad24(y + 1, accumStepInPixel, x + 1)]; + const int right = accum[mad24(y + 1, accumStepInPixel, x + 2)]; + + const int bottom = accum[mad24(y + 2, accumStepInPixel, x + 1)];; + + if (cur > threshold && cur > top && cur >= bottom && cur > left && cur >= right) + { + const unsigned int val = (y << 16) | x; + const int idx = atomic_add(counter, 1); + centers[idx] = val; + } + } +} + + +// //////////////////////////////////////////////////////////////////////// +// // circlesAccumRadius + +// TODO: add offset to support ROI +__kernel void circlesAccumRadius(__global const unsigned int* centers, + __global const unsigned int* list, const int count, + __global float4* circles, const int maxCircles, + const float dp, + const int minRadius, const int maxRadius, + const int histSize, + const int threshold, + __local int* smem, + __global int* counter) +{ + for (int i = get_local_id(0); i < histSize + 2; i += get_local_size(0)) + smem[i] = 0; + barrier(CLK_LOCAL_MEM_FENCE); + + unsigned int val = centers[get_group_id(0)]; + + float cx = convert_float(val & 0xFFFF); + float cy = convert_float((val >> 16) & 0xFFFF); + + cx = (cx + 0.5f) * dp; + cy = (cy + 0.5f) * dp; + + for (int i = get_local_id(0); i < count; i += get_local_size(0)) + { + val = list[i]; + + const int x = (val & 0xFFFF); + const int y = (val >> 16) & 0xFFFF; + + const float rad = sqrt((cx - x) * (cx - x) + (cy - y) * (cy - y)); + if (rad >= minRadius && rad <= maxRadius) + { + const int r = convert_int_rte(rad - minRadius); + + atomic_add(&smem[r + 1], 1); + } + } + + barrier(CLK_LOCAL_MEM_FENCE); + + for (int i = get_local_id(0); i < histSize; i += get_local_size(0)) + { + const int curVotes = smem[i + 1]; + + if (curVotes >= threshold && curVotes > smem[i] && curVotes >= smem[i + 2]) + + { + const int ind = atomic_add(counter, 1); + if (ind < maxCircles) + { + circles[ind] = (float4)(cx, cy, convert_float(i + minRadius), 0.0f); + } + } + } +} diff --git a/modules/ocl/test/test_hough.cpp b/modules/ocl/test/test_hough.cpp new file mode 100644 index 0000000000..3a5cec5f95 --- /dev/null +++ b/modules/ocl/test/test_hough.cpp @@ -0,0 +1,112 @@ +/*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) 2008-2011, 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 Intel Corporation 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" + +#ifdef HAVE_OPENCL + +/////////////////////////////////////////////////////////////////////////////////////////////////////// +// HoughCircles + +PARAM_TEST_CASE(HoughCircles, cv::Size) +{ + static void drawCircles(cv::Mat& dst, const std::vector& circles, bool fill) + { + dst.setTo(cv::Scalar::all(0)); + + for (size_t i = 0; i < circles.size(); ++i) + cv::circle(dst, cv::Point2f(circles[i][0], circles[i][1]), (int)circles[i][2], cv::Scalar::all(255), fill ? -1 : 1); + } +}; + +TEST_P(HoughCircles, Accuracy) +{ + const cv::Size size = GET_PARAM(0); + + const float dp = 2.0f; + const float minDist = 10.0f; + const int minRadius = 10; + const int maxRadius = 20; + const int cannyThreshold = 100; + const int votesThreshold = 15; + + std::vector circles_gold(4); + circles_gold[0] = cv::Vec3i(20, 20, minRadius); + circles_gold[1] = cv::Vec3i(90, 87, minRadius + 3); + circles_gold[2] = cv::Vec3i(30, 70, minRadius + 8); + circles_gold[3] = cv::Vec3i(80, 10, maxRadius); + + cv::Mat src(size, CV_8UC1); + drawCircles(src, circles_gold, true); + cv::ocl::oclMat d_src(src); + + cv::ocl::oclMat d_circles; + cv::ocl::HoughCircles(d_src, d_circles, CV_HOUGH_GRADIENT, dp, minDist, cannyThreshold, votesThreshold, minRadius, maxRadius); + ASSERT_TRUE(d_circles.rows > 0); + + cv::Mat circles; + d_circles.download(circles); + + for (int i = 0; i < circles.cols; ++i) + { + cv::Vec3f cur = circles.at(i); + + bool found = false; + + for (size_t j = 0; j < circles_gold.size(); ++j) + { + cv::Vec3f gold = circles_gold[j]; + + if (std::fabs(cur[0] - gold[0]) < minDist && std::fabs(cur[1] - gold[1]) < minDist && std::fabs(cur[2] - gold[2]) < minDist) + { + found = true; + break; + } + } + + ASSERT_TRUE(found); + } +} + +INSTANTIATE_TEST_CASE_P(Hough, HoughCircles, DIFFERENT_SIZES); + +#endif // HAVE_OPENCL