Merge pull request #267 from pclove1:ocl_hough
This commit is contained in:
Andrey Kamaev
OpenCV Buildbot
commit
f3f55b30b0
@ -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`
|
||||
|
||||
|
||||
@ -41,8 +41,8 @@
|
||||
//
|
||||
//M*/
|
||||
|
||||
#ifndef __OPENCV_GPU_HPP__
|
||||
#define __OPENCV_GPU_HPP__
|
||||
#ifndef __OPENCV_OCL_HPP__
|
||||
#define __OPENCV_OCL_HPP__
|
||||
|
||||
#include <memory>
|
||||
#include <vector>
|
||||
@ -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__ */
|
||||
|
||||
98
modules/ocl/perf/perf_hough.cpp
Normal file
98
modules/ocl/perf/perf_hough.cpp
Normal file
@ -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<cv::Size, float, float> Size_Dp_MinDist_t;
|
||||
typedef perf::TestBaseWithParam<Size_Dp_MinDist_t> 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
|
||||
416
modules/ocl/src/hough.cpp
Normal file
416
modules/ocl/src/hough.cpp
Normal file
@ -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<pair<size_t , const void *> > 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<pair<size_t , const void *> > 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<pair<size_t , const void *> > 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<pair<size_t , const void *> > 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<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::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<unsigned int> oldBuf_(centersCount);
|
||||
cv::AutoBuffer<unsigned int> 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<unsigned int> > 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<int>(px / cellSize);
|
||||
int yCell = static_cast<int>(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<unsigned int>& 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) */
|
||||
280
modules/ocl/src/kernels/imgproc_hough.cl
Normal file
280
modules/ocl/src/kernels/imgproc_hough.cl
Normal file
@ -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);
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
112
modules/ocl/test/test_hough.cpp
Normal file
112
modules/ocl/test/test_hough.cpp
Normal file
@ -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<cv::Vec3f>& 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<cv::Vec3f> 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<cv::Vec3f>(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
|
||||
Loading…
x
Reference in New Issue
Block a user