From ad86b80375b43d6dcc420a187966d48cd2e6ed1e Mon Sep 17 00:00:00 2001 From: Suenghoon Park Date: Thu, 13 Dec 2012 02:33:21 -0500 Subject: [PATCH] finished buildPointList --- modules/ocl/src/hough.cpp | 383 +++++++++++++++++++++++++++++++ modules/ocl/src/kernels/hough.cl | 307 +++++++++++++++++++++++++ 2 files changed, 690 insertions(+) create mode 100644 modules/ocl/src/hough.cpp create mode 100644 modules/ocl/src/kernels/hough.cl diff --git a/modules/ocl/src/hough.cpp b/modules/ocl/src/hough.cpp new file mode 100644 index 0000000000..dd4db84a47 --- /dev/null +++ b/modules/ocl/src/hough.cpp @@ -0,0 +1,383 @@ +/*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. +// +// Modified by Seunghoon Park(pclove1@gmail.com) +// +// 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::HoughLines(const oclMat&, oclMat&, float, float, int, bool, int) { throw_nogpu(); } +// void cv::ocl::HoughLines(const oclMat&, oclMat&, HoughLinesBuf&, float, float, int, bool, int) { throw_nogpu(); } +// void cv::ocl::HoughLinesDownload(const oclMat&, OutputArray, OutputArray) { throw_nogpu(); } + +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(); } + +// Ptr cv::ocl::GeneralizedHough_GPU::create(int) { throw_nogpu(); return Ptr(); } +// cv::ocl::GeneralizedHough_GPU::~GeneralizedHough_GPU() {} +// void cv::ocl::GeneralizedHough_GPU::setTemplate(const oclMat&, int, Point) { throw_nogpu(); } +// void cv::ocl::GeneralizedHough_GPU::setTemplate(const oclMat&, const oclMat&, const oclMat&, Point) { throw_nogpu(); } +// void cv::ocl::GeneralizedHough_GPU::detect(const oclMat&, oclMat&, int) { throw_nogpu(); } +// void cv::ocl::GeneralizedHough_GPU::detect(const oclMat&, const oclMat&, const oclMat&, oclMat&) { throw_nogpu(); } +// void cv::ocl::GeneralizedHough_GPU::download(const oclMat&, OutputArray, OutputArray) { throw_nogpu(); } +// void cv::ocl::GeneralizedHough_GPU::release() {} + +#else /* !defined (HAVE_OPENCL) */ + +namespace cv { namespace ocl +{ + int buildPointList_gpu(const oclMat& src, unsigned int* list); + + ///////////////////////////OpenCL kernel strings/////////////////////////// + extern const char *hough; +}} + + + +////////////////////////////////////////////////////////// +// common functions + +namespace cv { namespace ocl +{ + int buildPointList_gpu(const oclMat& src, unsigned int* list) + { + const int PIXELS_PER_THREAD = 16; + + // void* counterPtr; + // cudaSafeCall( cudaGetSymbolAddress(&counterPtr, g_counter) ); + // cudaSafeCall( cudaMemset(counterPtr, 0, sizeof(int)) ); + + int totalCount = 0; + int err = CL_SUCCESS; + cl_mem counter = clCreateBuffer(src.clCxt->impl->clContext, + CL_MEM_COPY_HOST_PTR, // CL_MEM_READ_WRITE, + sizeof(int), + &totalCount, // NULL, + &err); + openCLSafeCall(err); + // openCLSafeCall(clEnqueueWriteBuffer(src.clCxt->impl->clCmdQueue, counter, CL_TRUE, 0, sizeof(int), &totalCount, 0, 0, 0)); + + // const dim3 block(32, 4); + // const dim3 grid(divUp(src.cols, block.x * PIXELS_PER_THREAD), divUp(src.rows, block.y)); + + 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 : (src.cols / PIXELS_PER_BLOCK + 1) * PIXELS_PER_BLOCK; + const size_t glbSizeY = src.rows % blkSizeY == 0 ? src.rows : (src.rows / blkSizeY + 1) * blkSizeY; + size_t globalThreads[3] = { glbSizeX, glbSizeY, 1 }; + + // cudaSafeCall( cudaFuncSetCacheConfig(buildPointList, cudaFuncCachePreferShared) ); + + // buildPointList<<>>(src, list); + // cudaSafeCall( cudaGetLastError() ); + // cudaSafeCall( cudaDeviceSynchronize() ); + 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 )); + args.push_back( make_pair( sizeof(cl_mem) , (void *)&counter )); + + openCLExecuteKernel(src.clCxt, &hough, "buildPointList", globalThreads, localThreads, args, -1, -1); + // int totalCount; + // cudaSafeCall( cudaMemcpy(&totalCount, counterPtr, sizeof(int), cudaMemcpyDeviceToHost) ); + openCLSafeCall(clEnqueueReadBuffer(src.clCxt->impl->clCmdQueue, counter, CL_TRUE, 0, sizeof(int), &totalCount, 0, NULL, NULL)); + openCLSafeCall(clReleaseMemObject(counter)); + + return totalCount; + } +}} + +////////////////////////////////////////////////////////// +// HoughLines + +// namespace cv { namespace ocl { namespace device +// { +// namespace hough +// { +// void linesAccum_gpu(const unsigned int* list, int count, PtrStepSzi accum, float rho, float theta, size_t sharedMemPerBlock, bool has20); +// int linesGetResult_gpu(PtrStepSzi accum, float2* out, int* votes, int maxSize, float rho, float theta, int threshold, bool doSort); +// } +// }}} + +// void cv::ocl::HoughLines(const oclMat& src, oclMat& lines, float rho, float theta, int threshold, bool doSort, int maxLines) +// { +// HoughLinesBuf buf; +// HoughLines(src, lines, buf, rho, theta, threshold, doSort, maxLines); +// } + +// void cv::ocl::HoughLines(const oclMat& src, oclMat& lines, HoughLinesBuf& buf, float rho, float theta, int threshold, bool doSort, int maxLines) +// { +// using namespace cv::ocl::device::hough; + +// CV_Assert(src.type() == CV_8UC1); +// CV_Assert(src.cols < std::numeric_limits::max()); +// CV_Assert(src.rows < std::numeric_limits::max()); + +// ensureSizeIsEnough(1, src.size().area(), CV_32SC1, buf.list); +// unsigned int* srcPoints = buf.list.ptr(); + +// const int pointsCount = buildPointList_gpu(src, srcPoints); +// if (pointsCount == 0) +// { +// lines.release(); +// return; +// } + +// const int numangle = cvRound(CV_PI / theta); +// const int numrho = cvRound(((src.cols + src.rows) * 2 + 1) / rho); +// CV_Assert(numangle > 0 && numrho > 0); + +// ensureSizeIsEnough(numangle + 2, numrho + 2, CV_32SC1, buf.accum); +// buf.accum.setTo(Scalar::all(0)); + +// DeviceInfo devInfo; +// linesAccum_gpu(srcPoints, pointsCount, buf.accum, rho, theta, devInfo.sharedMemPerBlock(), devInfo.supports(FEATURE_SET_COMPUTE_20)); + +// ensureSizeIsEnough(2, maxLines, CV_32FC2, lines); + +// int linesCount = linesGetResult_gpu(buf.accum, lines.ptr(0), lines.ptr(1), maxLines, rho, theta, threshold, doSort); +// if (linesCount > 0) +// lines.cols = linesCount; +// else +// lines.release(); +// } + +// void cv::ocl::HoughLinesDownload(const oclMat& d_lines, OutputArray h_lines_, OutputArray h_votes_) +// { +// if (d_lines.empty()) +// { +// h_lines_.release(); +// if (h_votes_.needed()) +// h_votes_.release(); +// return; +// } + +// CV_Assert(d_lines.rows == 2 && d_lines.type() == CV_32FC2); + +// h_lines_.create(1, d_lines.cols, CV_32FC2); +// Mat h_lines = h_lines_.getMat(); +// d_lines.row(0).download(h_lines); + +// if (h_votes_.needed()) +// { +// h_votes_.create(1, d_lines.cols, CV_32SC1); +// Mat h_votes = h_votes_.getMat(); +// oclMat d_votes(1, d_lines.cols, CV_32SC1, const_cast(d_lines.ptr(1))); +// d_votes.download(h_votes); +// } +// } + +////////////////////////////////////////////////////////// +// HoughCircles + +// namespace cv { namespace ocl +// { +// 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::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(2, src.size().area(), CV_32SC1, buf.list); + // unsigned int* srcPoints = buf.list.ptr(0); + unsigned int* srcPoints = (unsigned int*)buf.list.data; + // unsigned int* centers = buf.list.ptr(1); + unsigned int* centers = (unsigned int*)buf.list.data + buf.list.step; + + const int pointsCount = buildPointList_gpu(buf.edges, srcPoints); + //std::cout << "pointsCount: " << pointsCount << std::endl; + 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 oldBuf_(centersCount); + // cv::AutoBuffer 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 > 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(p.x / cellSize); + // int yCell = static_cast(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& 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); + + // DeviceInfo devInfo; + // const int circlesCount = circlesAccumRadius_gpu(centers, centersCount, srcPoints, pointsCount, circles.ptr(), maxCircles, + // dp, minRadius, maxRadius, votesThreshold, devInfo.supports(FEATURE_SET_COMPUTE_20)); + + // if (circlesCount > 0) + // circles.cols = circlesCount; + // else + // circles.release(); +} + +void cv::ocl::HoughCirclesDownload(const oclMat& 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_OPENCL) */ diff --git a/modules/ocl/src/kernels/hough.cl b/modules/ocl/src/kernels/hough.cl new file mode 100644 index 0000000000..e4eabc62d8 --- /dev/null +++ b/modules/ocl/src/kernels/hough.cl @@ -0,0 +1,307 @@ +/*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 + +__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 + +// __global__ void circlesAccumCenters(const unsigned int* list, const int count, const PtrStepi dx, const PtrStepi dy, +// PtrStepi accum, const int width, const int height, const int minRadius, const int maxRadius, const float idp) +// { +// const int SHIFT = 10; +// const int ONE = 1 << SHIFT; + +// const int tid = blockIdx.x * blockDim.x + threadIdx.x; + +// if (tid >= count) +// return; + +// const unsigned int val = list[tid]; + +// const int x = (val & 0xFFFF); +// const int y = (val >> 16) & 0xFFFF; + +// const int vx = dx(y, x); +// const int vy = dy(y, x); + +// if (vx == 0 && vy == 0) +// return; + +// const float mag = ::sqrtf(vx * vx + vy * vy); + +// const int x0 = __float2int_rn((x * idp) * ONE); +// const int y0 = __float2int_rn((y * idp) * ONE); + +// int sx = __float2int_rn((vx * idp) * ONE / mag); +// int sy = __float2int_rn((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; + +// ::atomicAdd(accum.ptr(y2 + 1) + x2 + 1, 1); +// } + +// sx = -sx; +// sy = -sy; +// } +// } + +// void circlesAccumCenters_gpu(const unsigned int* list, int count, PtrStepi dx, PtrStepi dy, PtrStepSzi accum, int minRadius, int maxRadius, float idp) +// { +// const dim3 block(256); +// const dim3 grid(divUp(count, block.x)); + +// cudaSafeCall( cudaFuncSetCacheConfig(circlesAccumCenters, cudaFuncCachePreferL1) ); + +// circlesAccumCenters<<>>(list, count, dx, dy, accum, accum.cols - 2, accum.rows - 2, minRadius, maxRadius, idp); +// cudaSafeCall( cudaGetLastError() ); + +// cudaSafeCall( cudaDeviceSynchronize() ); +// } + +// //////////////////////////////////////////////////////////////////////// +// // buildCentersList + +// __global__ void buildCentersList(const PtrStepSzi accum, unsigned int* centers, const int threshold) +// { +// const int x = blockIdx.x * blockDim.x + threadIdx.x; +// const int y = blockIdx.y * blockDim.y + threadIdx.y; + +// if (x < accum.cols - 2 && y < accum.rows - 2) +// { +// const int top = accum(y, x + 1); + +// const int left = accum(y + 1, x); +// const int cur = accum(y + 1, x + 1); +// const int right = accum(y + 1, x + 2); + +// const int bottom = accum(y + 2, x + 1); + +// if (cur > threshold && cur > top && cur >= bottom && cur > left && cur >= right) +// { +// const unsigned int val = (y << 16) | x; +// const int idx = ::atomicAdd(&g_counter, 1); +// centers[idx] = val; +// } +// } +// } + +// int buildCentersList_gpu(PtrStepSzi accum, unsigned int* centers, int threshold) +// { +// void* counterPtr; +// cudaSafeCall( cudaGetSymbolAddress(&counterPtr, g_counter) ); + +// cudaSafeCall( cudaMemset(counterPtr, 0, sizeof(int)) ); + +// const dim3 block(32, 8); +// const dim3 grid(divUp(accum.cols - 2, block.x), divUp(accum.rows - 2, block.y)); + +// cudaSafeCall( cudaFuncSetCacheConfig(buildCentersList, cudaFuncCachePreferL1) ); + +// buildCentersList<<>>(accum, centers, threshold); +// cudaSafeCall( cudaGetLastError() ); + +// cudaSafeCall( cudaDeviceSynchronize() ); + +// int totalCount; +// cudaSafeCall( cudaMemcpy(&totalCount, counterPtr, sizeof(int), cudaMemcpyDeviceToHost) ); + +// return totalCount; +// } + +// //////////////////////////////////////////////////////////////////////// +// // circlesAccumRadius + +// __global__ void circlesAccumRadius(const unsigned int* centers, const unsigned int* list, const int count, +// float3* circles, const int maxCircles, const float dp, +// const int minRadius, const int maxRadius, const int histSize, const int threshold) +// { +// int* smem = DynamicSharedMem(); + +// for (int i = threadIdx.x; i < histSize + 2; i += blockDim.x) +// smem[i] = 0; +// __syncthreads(); + +// unsigned int val = centers[blockIdx.x]; + +// float cx = (val & 0xFFFF); +// float cy = (val >> 16) & 0xFFFF; + +// cx = (cx + 0.5f) * dp; +// cy = (cy + 0.5f) * dp; + +// for (int i = threadIdx.x; i < count; i += blockDim.x) +// { +// val = list[i]; + +// const int x = (val & 0xFFFF); +// const int y = (val >> 16) & 0xFFFF; + +// const float rad = ::sqrtf((cx - x) * (cx - x) + (cy - y) * (cy - y)); +// if (rad >= minRadius && rad <= maxRadius) +// { +// const int r = __float2int_rn(rad - minRadius); + +// Emulation::smem::atomicAdd(&smem[r + 1], 1); +// } +// } + +// __syncthreads(); + +// for (int i = threadIdx.x; i < histSize; i += blockDim.x) +// { +// const int curVotes = smem[i + 1]; + +// if (curVotes >= threshold && curVotes > smem[i] && curVotes >= smem[i + 2]) +// { +// const int ind = ::atomicAdd(&g_counter, 1); +// if (ind < maxCircles) +// circles[ind] = make_float3(cx, cy, i + minRadius); +// } +// } +// } + +// 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* counterPtr; +// cudaSafeCall( cudaGetSymbolAddress(&counterPtr, g_counter) ); + +// cudaSafeCall( cudaMemset(counterPtr, 0, sizeof(int)) ); + +// const dim3 block(has20 ? 1024 : 512); +// const dim3 grid(centersCount); + +// const int histSize = maxRadius - minRadius + 1; +// size_t smemSize = (histSize + 2) * sizeof(int); + +// circlesAccumRadius<<>>(centers, list, count, circles, maxCircles, dp, minRadius, maxRadius, histSize, threshold); +// cudaSafeCall( cudaGetLastError() ); + +// cudaSafeCall( cudaDeviceSynchronize() ); + +// int totalCount; +// cudaSafeCall( cudaMemcpy(&totalCount, counterPtr, sizeof(int), cudaMemcpyDeviceToHost) ); + +// totalCount = ::min(totalCount, maxCircles); + +// return totalCount; +// }