/*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*/ #if !defined CUDA_DISABLER #include #include #include "opencv2/core/cuda/common.hpp" #include "opencv2/core/cuda/emulation.hpp" #include "opencv2/core/cuda/vec_math.hpp" #include "opencv2/core/cuda/functional.hpp" #include "opencv2/opencv_modules.hpp" #ifdef HAVE_OPENCV_CUDAARITHM namespace cv { namespace cuda { namespace device { namespace ght { __device__ int g_counter; template __global__ void buildEdgePointList(const PtrStepSzb edges, const PtrStep dx, const PtrStep dy, unsigned int* coordList, float* thetaList) { __shared__ unsigned int s_coordLists[4][32 * PIXELS_PER_THREAD]; __shared__ float s_thetaLists[4][32 * PIXELS_PER_THREAD]; __shared__ int s_sizes[4]; __shared__ int s_globStart[4]; const int x = blockIdx.x * blockDim.x * PIXELS_PER_THREAD + threadIdx.x; const int y = blockIdx.y * blockDim.y + threadIdx.y; if (threadIdx.x == 0) s_sizes[threadIdx.y] = 0; __syncthreads(); if (y < edges.rows) { // fill the queue const uchar* edgesRow = edges.ptr(y); const T* dxRow = dx.ptr(y); const T* dyRow = dy.ptr(y); for (int i = 0, xx = x; i < PIXELS_PER_THREAD && xx < edges.cols; ++i, xx += blockDim.x) { const T dxVal = dxRow[xx]; const T dyVal = dyRow[xx]; if (edgesRow[xx] && (dxVal != 0 || dyVal != 0)) { const unsigned int coord = (y << 16) | xx; float theta = ::atan2f(dyVal, dxVal); if (theta < 0) theta += 2.0f * CV_PI_F; const int qidx = Emulation::smem::atomicAdd(&s_sizes[threadIdx.y], 1); s_coordLists[threadIdx.y][qidx] = coord; s_thetaLists[threadIdx.y][qidx] = theta; } } } __syncthreads(); // let one thread reserve the space required in the global list if (threadIdx.x == 0 && threadIdx.y == 0) { // find how many items are stored in each list int totalSize = 0; for (int i = 0; i < blockDim.y; ++i) { s_globStart[i] = totalSize; totalSize += s_sizes[i]; } // calculate the offset in the global list const int globalOffset = atomicAdd(&g_counter, totalSize); for (int i = 0; i < blockDim.y; ++i) s_globStart[i] += globalOffset; } __syncthreads(); // copy local queues to global queue const int qsize = s_sizes[threadIdx.y]; int gidx = s_globStart[threadIdx.y] + threadIdx.x; for(int i = threadIdx.x; i < qsize; i += blockDim.x, gidx += blockDim.x) { coordList[gidx] = s_coordLists[threadIdx.y][i]; thetaList[gidx] = s_thetaLists[threadIdx.y][i]; } } template int buildEdgePointList_gpu(PtrStepSzb edges, PtrStepSzb dx, PtrStepSzb dy, unsigned int* coordList, float* thetaList) { const int PIXELS_PER_THREAD = 8; void* counterPtr; cudaSafeCall( cudaGetSymbolAddress(&counterPtr, g_counter) ); cudaSafeCall( cudaMemset(counterPtr, 0, sizeof(int)) ); const dim3 block(32, 4); const dim3 grid(divUp(edges.cols, block.x * PIXELS_PER_THREAD), divUp(edges.rows, block.y)); cudaSafeCall( cudaFuncSetCacheConfig(buildEdgePointList, cudaFuncCachePreferShared) ); buildEdgePointList<<>>(edges, (PtrStepSz) dx, (PtrStepSz) dy, coordList, thetaList); cudaSafeCall( cudaGetLastError() ); cudaSafeCall( cudaDeviceSynchronize() ); int totalCount; cudaSafeCall( cudaMemcpy(&totalCount, counterPtr, sizeof(int), cudaMemcpyDeviceToHost) ); return totalCount; } template int buildEdgePointList_gpu(PtrStepSzb edges, PtrStepSzb dx, PtrStepSzb dy, unsigned int* coordList, float* thetaList); template int buildEdgePointList_gpu(PtrStepSzb edges, PtrStepSzb dx, PtrStepSzb dy, unsigned int* coordList, float* thetaList); template int buildEdgePointList_gpu(PtrStepSzb edges, PtrStepSzb dx, PtrStepSzb dy, unsigned int* coordList, float* thetaList); __global__ void buildRTable(const unsigned int* coordList, const float* thetaList, const int pointsCount, PtrStep r_table, int* r_sizes, int maxSize, const short2 templCenter, const float thetaScale) { const int tid = blockIdx.x * blockDim.x + threadIdx.x; if (tid >= pointsCount) return; const unsigned int coord = coordList[tid]; short2 p; p.x = (coord & 0xFFFF); p.y = (coord >> 16) & 0xFFFF; const float theta = thetaList[tid]; const int n = __float2int_rn(theta * thetaScale); const int ind = ::atomicAdd(r_sizes + n, 1); if (ind < maxSize) r_table(n, ind) = saturate_cast(p - templCenter); } void buildRTable_gpu(const unsigned int* coordList, const float* thetaList, int pointsCount, PtrStepSz r_table, int* r_sizes, short2 templCenter, int levels) { const dim3 block(256); const dim3 grid(divUp(pointsCount, block.x)); const float thetaScale = levels / (2.0f * CV_PI_F); buildRTable<<>>(coordList, thetaList, pointsCount, r_table, r_sizes, r_table.cols, templCenter, thetaScale); cudaSafeCall( cudaGetLastError() ); cudaSafeCall( cudaDeviceSynchronize() ); } //////////////////////////////////////////////////////////////////////// // Ballard_Pos __global__ void Ballard_Pos_calcHist(const unsigned int* coordList, const float* thetaList, const int pointsCount, const PtrStep r_table, const int* r_sizes, PtrStepSzi hist, const float idp, const float thetaScale) { const int tid = blockIdx.x * blockDim.x + threadIdx.x; if (tid >= pointsCount) return; const unsigned int coord = coordList[tid]; short2 p; p.x = (coord & 0xFFFF); p.y = (coord >> 16) & 0xFFFF; const float theta = thetaList[tid]; const int n = __float2int_rn(theta * thetaScale); const short2* r_row = r_table.ptr(n); const int r_row_size = r_sizes[n]; for (int j = 0; j < r_row_size; ++j) { short2 c = saturate_cast(p - r_row[j]); c.x = __float2int_rn(c.x * idp); c.y = __float2int_rn(c.y * idp); if (c.x >= 0 && c.x < hist.cols - 2 && c.y >= 0 && c.y < hist.rows - 2) ::atomicAdd(hist.ptr(c.y + 1) + c.x + 1, 1); } } void Ballard_Pos_calcHist_gpu(const unsigned int* coordList, const float* thetaList, int pointsCount, PtrStepSz r_table, const int* r_sizes, PtrStepSzi hist, float dp, int levels) { const dim3 block(256); const dim3 grid(divUp(pointsCount, block.x)); const float idp = 1.0f / dp; const float thetaScale = levels / (2.0f * CV_PI_F); Ballard_Pos_calcHist<<>>(coordList, thetaList, pointsCount, r_table, r_sizes, hist, idp, thetaScale); cudaSafeCall( cudaGetLastError() ); cudaSafeCall( cudaDeviceSynchronize() ); } __global__ void Ballard_Pos_findPosInHist(const PtrStepSzi hist, float4* out, int3* votes, const int maxSize, const float dp, const int threshold) { const int x = blockIdx.x * blockDim.x + threadIdx.x; const int y = blockIdx.y * blockDim.y + threadIdx.y; if (x >= hist.cols - 2 || y >= hist.rows - 2) return; const int curVotes = hist(y + 1, x + 1); if (curVotes > threshold && curVotes > hist(y + 1, x) && curVotes >= hist(y + 1, x + 2) && curVotes > hist(y, x + 1) && curVotes >= hist(y + 2, x + 1)) { const int ind = ::atomicAdd(&g_counter, 1); if (ind < maxSize) { out[ind] = make_float4(x * dp, y * dp, 1.0f, 0.0f); votes[ind] = make_int3(curVotes, 0, 0); } } } int Ballard_Pos_findPosInHist_gpu(PtrStepSzi hist, float4* out, int3* votes, int maxSize, float dp, int threshold) { void* counterPtr; cudaSafeCall( cudaGetSymbolAddress(&counterPtr, g_counter) ); cudaSafeCall( cudaMemset(counterPtr, 0, sizeof(int)) ); const dim3 block(32, 8); const dim3 grid(divUp(hist.cols - 2, block.x), divUp(hist.rows - 2, block.y)); cudaSafeCall( cudaFuncSetCacheConfig(Ballard_Pos_findPosInHist, cudaFuncCachePreferL1) ); Ballard_Pos_findPosInHist<<>>(hist, out, votes, maxSize, dp, threshold); cudaSafeCall( cudaGetLastError() ); cudaSafeCall( cudaDeviceSynchronize() ); int totalCount; cudaSafeCall( cudaMemcpy(&totalCount, counterPtr, sizeof(int), cudaMemcpyDeviceToHost) ); totalCount = ::min(totalCount, maxSize); return totalCount; } //////////////////////////////////////////////////////////////////////// // Guil_Full struct FeatureTable { uchar* p1_pos_data; size_t p1_pos_step; uchar* p1_theta_data; size_t p1_theta_step; uchar* p2_pos_data; size_t p2_pos_step; uchar* d12_data; size_t d12_step; uchar* r1_data; size_t r1_step; uchar* r2_data; size_t r2_step; }; __constant__ FeatureTable c_templFeatures; __constant__ FeatureTable c_imageFeatures; void Guil_Full_setTemplFeatures(PtrStepb p1_pos, PtrStepb p1_theta, PtrStepb p2_pos, PtrStepb d12, PtrStepb r1, PtrStepb r2) { FeatureTable tbl; tbl.p1_pos_data = p1_pos.data; tbl.p1_pos_step = p1_pos.step; tbl.p1_theta_data = p1_theta.data; tbl.p1_theta_step = p1_theta.step; tbl.p2_pos_data = p2_pos.data; tbl.p2_pos_step = p2_pos.step; tbl.d12_data = d12.data; tbl.d12_step = d12.step; tbl.r1_data = r1.data; tbl.r1_step = r1.step; tbl.r2_data = r2.data; tbl.r2_step = r2.step; cudaSafeCall( cudaMemcpyToSymbol(c_templFeatures, &tbl, sizeof(FeatureTable)) ); } void Guil_Full_setImageFeatures(PtrStepb p1_pos, PtrStepb p1_theta, PtrStepb p2_pos, PtrStepb d12, PtrStepb r1, PtrStepb r2) { FeatureTable tbl; tbl.p1_pos_data = p1_pos.data; tbl.p1_pos_step = p1_pos.step; tbl.p1_theta_data = p1_theta.data; tbl.p1_theta_step = p1_theta.step; tbl.p2_pos_data = p2_pos.data; tbl.p2_pos_step = p2_pos.step; tbl.d12_data = d12.data; tbl.d12_step = d12.step; tbl.r1_data = r1.data; tbl.r1_step = r1.step; tbl.r2_data = r2.data; tbl.r2_step = r2.step; cudaSafeCall( cudaMemcpyToSymbol(c_imageFeatures, &tbl, sizeof(FeatureTable)) ); } struct TemplFeatureTable { static __device__ float2* p1_pos(int n) { return (float2*)(c_templFeatures.p1_pos_data + n * c_templFeatures.p1_pos_step); } static __device__ float* p1_theta(int n) { return (float*)(c_templFeatures.p1_theta_data + n * c_templFeatures.p1_theta_step); } static __device__ float2* p2_pos(int n) { return (float2*)(c_templFeatures.p2_pos_data + n * c_templFeatures.p2_pos_step); } static __device__ float* d12(int n) { return (float*)(c_templFeatures.d12_data + n * c_templFeatures.d12_step); } static __device__ float2* r1(int n) { return (float2*)(c_templFeatures.r1_data + n * c_templFeatures.r1_step); } static __device__ float2* r2(int n) { return (float2*)(c_templFeatures.r2_data + n * c_templFeatures.r2_step); } }; struct ImageFeatureTable { static __device__ float2* p1_pos(int n) { return (float2*)(c_imageFeatures.p1_pos_data + n * c_imageFeatures.p1_pos_step); } static __device__ float* p1_theta(int n) { return (float*)(c_imageFeatures.p1_theta_data + n * c_imageFeatures.p1_theta_step); } static __device__ float2* p2_pos(int n) { return (float2*)(c_imageFeatures.p2_pos_data + n * c_imageFeatures.p2_pos_step); } static __device__ float* d12(int n) { return (float*)(c_imageFeatures.d12_data + n * c_imageFeatures.d12_step); } static __device__ float2* r1(int n) { return (float2*)(c_imageFeatures.r1_data + n * c_imageFeatures.r1_step); } static __device__ float2* r2(int n) { return (float2*)(c_imageFeatures.r2_data + n * c_imageFeatures.r2_step); } }; __device__ float clampAngle(float a) { float res = a; while (res > 2.0f * CV_PI_F) res -= 2.0f * CV_PI_F; while (res < 0.0f) res += 2.0f * CV_PI_F; return res; } __device__ bool angleEq(float a, float b, float eps) { return (::fabs(clampAngle(a - b)) <= eps); } template __global__ void Guil_Full_buildFeatureList(const unsigned int* coordList, const float* thetaList, const int pointsCount, int* sizes, const int maxSize, const float xi, const float angleEpsilon, const float alphaScale, const float2 center, const float maxDist) { const float p1_theta = thetaList[blockIdx.x]; const unsigned int coord1 = coordList[blockIdx.x]; float2 p1_pos; p1_pos.x = (coord1 & 0xFFFF); p1_pos.y = (coord1 >> 16) & 0xFFFF; for (int i = threadIdx.x; i < pointsCount; i += blockDim.x) { const float p2_theta = thetaList[i]; const unsigned int coord2 = coordList[i]; float2 p2_pos; p2_pos.x = (coord2 & 0xFFFF); p2_pos.y = (coord2 >> 16) & 0xFFFF; if (angleEq(p1_theta - p2_theta, xi, angleEpsilon)) { const float2 d = p1_pos - p2_pos; float alpha12 = clampAngle(::atan2(d.y, d.x) - p1_theta); float d12 = ::sqrtf(d.x * d.x + d.y * d.y); if (d12 > maxDist) continue; float2 r1 = p1_pos - center; float2 r2 = p2_pos - center; const int n = __float2int_rn(alpha12 * alphaScale); const int ind = ::atomicAdd(sizes + n, 1); if (ind < maxSize) { if (!isTempl) { FT::p1_pos(n)[ind] = p1_pos; FT::p2_pos(n)[ind] = p2_pos; } FT::p1_theta(n)[ind] = p1_theta; FT::d12(n)[ind] = d12; if (isTempl) { FT::r1(n)[ind] = r1; FT::r2(n)[ind] = r2; } } } } } template void Guil_Full_buildFeatureList_caller(const unsigned int* coordList, const float* thetaList, int pointsCount, int* sizes, int maxSize, float xi, float angleEpsilon, int levels, float2 center, float maxDist) { const dim3 block(256); const dim3 grid(pointsCount); const float alphaScale = levels / (2.0f * CV_PI_F); Guil_Full_buildFeatureList<<>>(coordList, thetaList, pointsCount, sizes, maxSize, xi * (CV_PI_F / 180.0f), angleEpsilon * (CV_PI_F / 180.0f), alphaScale, center, maxDist); cudaSafeCall( cudaGetLastError() ); cudaSafeCall( cudaDeviceSynchronize() ); thrust::device_ptr sizesPtr(sizes); thrust::transform(sizesPtr, sizesPtr + levels + 1, sizesPtr, device::bind2nd(device::minimum(), maxSize)); } void Guil_Full_buildTemplFeatureList_gpu(const unsigned int* coordList, const float* thetaList, int pointsCount, int* sizes, int maxSize, float xi, float angleEpsilon, int levels, float2 center, float maxDist) { Guil_Full_buildFeatureList_caller(coordList, thetaList, pointsCount, sizes, maxSize, xi, angleEpsilon, levels, center, maxDist); } void Guil_Full_buildImageFeatureList_gpu(const unsigned int* coordList, const float* thetaList, int pointsCount, int* sizes, int maxSize, float xi, float angleEpsilon, int levels, float2 center, float maxDist) { Guil_Full_buildFeatureList_caller(coordList, thetaList, pointsCount, sizes, maxSize, xi, angleEpsilon, levels, center, maxDist); } __global__ void Guil_Full_calcOHist(const int* templSizes, const int* imageSizes, int* OHist, const float minAngle, const float maxAngle, const float iAngleStep, const int angleRange) { extern __shared__ int s_OHist[]; for (int i = threadIdx.x; i <= angleRange; i += blockDim.x) s_OHist[i] = 0; __syncthreads(); const int tIdx = blockIdx.x; const int level = blockIdx.y; const int tSize = templSizes[level]; if (tIdx < tSize) { const int imSize = imageSizes[level]; const float t_p1_theta = TemplFeatureTable::p1_theta(level)[tIdx]; for (int i = threadIdx.x; i < imSize; i += blockDim.x) { const float im_p1_theta = ImageFeatureTable::p1_theta(level)[i]; const float angle = clampAngle(im_p1_theta - t_p1_theta); if (angle >= minAngle && angle <= maxAngle) { const int n = __float2int_rn((angle - minAngle) * iAngleStep); Emulation::smem::atomicAdd(&s_OHist[n], 1); } } } __syncthreads(); for (int i = threadIdx.x; i <= angleRange; i += blockDim.x) ::atomicAdd(OHist + i, s_OHist[i]); } void Guil_Full_calcOHist_gpu(const int* templSizes, const int* imageSizes, int* OHist, float minAngle, float maxAngle, float angleStep, int angleRange, int levels, int tMaxSize) { const dim3 block(256); const dim3 grid(tMaxSize, levels + 1); minAngle *= (CV_PI_F / 180.0f); maxAngle *= (CV_PI_F / 180.0f); angleStep *= (CV_PI_F / 180.0f); const size_t smemSize = (angleRange + 1) * sizeof(float); Guil_Full_calcOHist<<>>(templSizes, imageSizes, OHist, minAngle, maxAngle, 1.0f / angleStep, angleRange); cudaSafeCall( cudaGetLastError() ); cudaSafeCall( cudaDeviceSynchronize() ); } __global__ void Guil_Full_calcSHist(const int* templSizes, const int* imageSizes, int* SHist, const float angle, const float angleEpsilon, const float minScale, const float maxScale, const float iScaleStep, const int scaleRange) { extern __shared__ int s_SHist[]; for (int i = threadIdx.x; i <= scaleRange; i += blockDim.x) s_SHist[i] = 0; __syncthreads(); const int tIdx = blockIdx.x; const int level = blockIdx.y; const int tSize = templSizes[level]; if (tIdx < tSize) { const int imSize = imageSizes[level]; const float t_p1_theta = TemplFeatureTable::p1_theta(level)[tIdx] + angle; const float t_d12 = TemplFeatureTable::d12(level)[tIdx] + angle; for (int i = threadIdx.x; i < imSize; i += blockDim.x) { const float im_p1_theta = ImageFeatureTable::p1_theta(level)[i]; const float im_d12 = ImageFeatureTable::d12(level)[i]; if (angleEq(im_p1_theta, t_p1_theta, angleEpsilon)) { const float scale = im_d12 / t_d12; if (scale >= minScale && scale <= maxScale) { const int s = __float2int_rn((scale - minScale) * iScaleStep); Emulation::smem::atomicAdd(&s_SHist[s], 1); } } } } __syncthreads(); for (int i = threadIdx.x; i <= scaleRange; i += blockDim.x) ::atomicAdd(SHist + i, s_SHist[i]); } void Guil_Full_calcSHist_gpu(const int* templSizes, const int* imageSizes, int* SHist, float angle, float angleEpsilon, float minScale, float maxScale, float iScaleStep, int scaleRange, int levels, int tMaxSize) { const dim3 block(256); const dim3 grid(tMaxSize, levels + 1); angle *= (CV_PI_F / 180.0f); angleEpsilon *= (CV_PI_F / 180.0f); const size_t smemSize = (scaleRange + 1) * sizeof(float); Guil_Full_calcSHist<<>>(templSizes, imageSizes, SHist, angle, angleEpsilon, minScale, maxScale, iScaleStep, scaleRange); cudaSafeCall( cudaGetLastError() ); cudaSafeCall( cudaDeviceSynchronize() ); } __global__ void Guil_Full_calcPHist(const int* templSizes, const int* imageSizes, PtrStepSzi PHist, const float angle, const float sinVal, const float cosVal, const float angleEpsilon, const float scale, const float idp) { const int tIdx = blockIdx.x; const int level = blockIdx.y; const int tSize = templSizes[level]; if (tIdx < tSize) { const int imSize = imageSizes[level]; const float t_p1_theta = TemplFeatureTable::p1_theta(level)[tIdx] + angle; float2 r1 = TemplFeatureTable::r1(level)[tIdx]; float2 r2 = TemplFeatureTable::r2(level)[tIdx]; r1 = r1 * scale; r2 = r2 * scale; r1 = make_float2(cosVal * r1.x - sinVal * r1.y, sinVal * r1.x + cosVal * r1.y); r2 = make_float2(cosVal * r2.x - sinVal * r2.y, sinVal * r2.x + cosVal * r2.y); for (int i = threadIdx.x; i < imSize; i += blockDim.x) { const float im_p1_theta = ImageFeatureTable::p1_theta(level)[i]; const float2 im_p1_pos = ImageFeatureTable::p1_pos(level)[i]; const float2 im_p2_pos = ImageFeatureTable::p2_pos(level)[i]; if (angleEq(im_p1_theta, t_p1_theta, angleEpsilon)) { float2 c1, c2; c1 = im_p1_pos - r1; c1 = c1 * idp; c2 = im_p2_pos - r2; c2 = c2 * idp; if (::fabs(c1.x - c2.x) > 1 || ::fabs(c1.y - c2.y) > 1) continue; if (c1.y >= 0 && c1.y < PHist.rows - 2 && c1.x >= 0 && c1.x < PHist.cols - 2) ::atomicAdd(PHist.ptr(__float2int_rn(c1.y) + 1) + __float2int_rn(c1.x) + 1, 1); } } } } void Guil_Full_calcPHist_gpu(const int* templSizes, const int* imageSizes, PtrStepSzi PHist, float angle, float angleEpsilon, float scale, float dp, int levels, int tMaxSize) { const dim3 block(256); const dim3 grid(tMaxSize, levels + 1); angle *= (CV_PI_F / 180.0f); angleEpsilon *= (CV_PI_F / 180.0f); const float sinVal = ::sinf(angle); const float cosVal = ::cosf(angle); cudaSafeCall( cudaFuncSetCacheConfig(Guil_Full_calcPHist, cudaFuncCachePreferL1) ); Guil_Full_calcPHist<<>>(templSizes, imageSizes, PHist, angle, sinVal, cosVal, angleEpsilon, scale, 1.0f / dp); cudaSafeCall( cudaGetLastError() ); cudaSafeCall( cudaDeviceSynchronize() ); } __global__ void Guil_Full_findPosInHist(const PtrStepSzi hist, float4* out, int3* votes, const int maxSize, const float angle, const int angleVotes, const float scale, const int scaleVotes, const float dp, const int threshold) { const int x = blockIdx.x * blockDim.x + threadIdx.x; const int y = blockIdx.y * blockDim.y + threadIdx.y; if (x >= hist.cols - 2 || y >= hist.rows - 2) return; const int curVotes = hist(y + 1, x + 1); if (curVotes > threshold && curVotes > hist(y + 1, x) && curVotes >= hist(y + 1, x + 2) && curVotes > hist(y, x + 1) && curVotes >= hist(y + 2, x + 1)) { const int ind = ::atomicAdd(&g_counter, 1); if (ind < maxSize) { out[ind] = make_float4(x * dp, y * dp, scale, angle); votes[ind] = make_int3(curVotes, scaleVotes, angleVotes); } } } int Guil_Full_findPosInHist_gpu(PtrStepSzi hist, float4* out, int3* votes, int curSize, int maxSize, float angle, int angleVotes, float scale, int scaleVotes, float dp, int threshold) { void* counterPtr; cudaSafeCall( cudaGetSymbolAddress(&counterPtr, g_counter) ); cudaSafeCall( cudaMemcpy(counterPtr, &curSize, sizeof(int), cudaMemcpyHostToDevice) ); const dim3 block(32, 8); const dim3 grid(divUp(hist.cols - 2, block.x), divUp(hist.rows - 2, block.y)); cudaSafeCall( cudaFuncSetCacheConfig(Guil_Full_findPosInHist, cudaFuncCachePreferL1) ); Guil_Full_findPosInHist<<>>(hist, out, votes, maxSize, angle, angleVotes, scale, scaleVotes, dp, threshold); cudaSafeCall( cudaGetLastError() ); cudaSafeCall( cudaDeviceSynchronize() ); int totalCount; cudaSafeCall( cudaMemcpy(&totalCount, counterPtr, sizeof(int), cudaMemcpyDeviceToHost) ); totalCount = ::min(totalCount, maxSize); return totalCount; } } }}} #endif // HAVE_OPENCV_CUDAARITHM #endif /* CUDA_DISABLER */