Open Source Computer Vision Library
https://opencv.org/
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1078 lines
44 KiB
1078 lines
44 KiB
/*M/////////////////////////////////////////////////////////////////////////////////////// |
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// |
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. |
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// |
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// By downloading, copying, installing or using the software you agree to this license. |
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// If you do not agree to this license, do not download, install, |
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// copy or use the software. |
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// |
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// |
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// License Agreement |
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// For Open Source Computer Vision Library |
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// |
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// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. |
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// Copyright (C) 2009, Willow Garage Inc., all rights reserved. |
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// Third party copyrights are property of their respective owners. |
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// |
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// Redistribution and use in source and binary forms, with or without modification, |
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// are permitted provided that the following conditions are met: |
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// |
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// * Redistribution's of source code must retain the above copyright notice, |
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// this list of conditions and the following disclaimer. |
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// |
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// * Redistribution's in binary form must reproduce the above copyright notice, |
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// this list of conditions and the following disclaimer in the documentation |
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// and/or other materials provided with the distribution. |
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// |
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// * The name of the copyright holders may not be used to endorse or promote products |
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// derived from this software without specific prior written permission. |
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// |
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// This software is provided by the copyright holders and contributors "as is" and |
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// any express or implied warranties, including, but not limited to, the implied |
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// warranties of merchantability and fitness for a particular purpose are disclaimed. |
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// In no event shall the Intel Corporation or contributors be liable for any direct, |
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// indirect, incidental, special, exemplary, or consequential damages |
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// (including, but not limited to, procurement of substitute goods or services; |
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// loss of use, data, or profits; or business interruption) however caused |
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// and on any theory of liability, whether in contract, strict liability, |
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// or tort (including negligence or otherwise) arising in any way out of |
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// the use of this software, even if advised of the possibility of such damage. |
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// |
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//M*/ |
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#define CUDA_DISABLER |
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#if !defined CUDA_DISABLER |
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#include <thrust/device_ptr.h> |
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#include <thrust/transform.h> |
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#include "opencv2/gpu/device/common.hpp" |
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#include "opencv2/gpu/device/emulation.hpp" |
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#include "opencv2/gpu/device/vec_math.hpp" |
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#include "opencv2/gpu/device/functional.hpp" |
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namespace cv { namespace gpu { namespace device |
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{ |
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namespace hough |
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{ |
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__device__ static int g_counter; |
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template <typename T, int PIXELS_PER_THREAD> |
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__global__ void buildEdgePointList(const PtrStepSzb edges, const PtrStep<T> dx, const PtrStep<T> dy, unsigned int* coordList, float* thetaList) |
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{ |
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__shared__ unsigned int s_coordLists[4][32 * PIXELS_PER_THREAD]; |
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__shared__ float s_thetaLists[4][32 * PIXELS_PER_THREAD]; |
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__shared__ int s_sizes[4]; |
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__shared__ int s_globStart[4]; |
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const int x = blockIdx.x * blockDim.x * PIXELS_PER_THREAD + threadIdx.x; |
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const int y = blockIdx.y * blockDim.y + threadIdx.y; |
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if (threadIdx.x == 0) |
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s_sizes[threadIdx.y] = 0; |
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__syncthreads(); |
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if (y < edges.rows) |
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{ |
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// fill the queue |
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const uchar* edgesRow = edges.ptr(y); |
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const T* dxRow = dx.ptr(y); |
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const T* dyRow = dy.ptr(y); |
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for (int i = 0, xx = x; i < PIXELS_PER_THREAD && xx < edges.cols; ++i, xx += blockDim.x) |
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{ |
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const T dxVal = dxRow[xx]; |
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const T dyVal = dyRow[xx]; |
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if (edgesRow[xx] && (dxVal != 0 || dyVal != 0)) |
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{ |
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const unsigned int coord = (y << 16) | xx; |
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float theta = ::atan2f(dyVal, dxVal); |
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if (theta < 0) |
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theta += 2.0f * CV_PI_F; |
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const int qidx = Emulation::smem::atomicAdd(&s_sizes[threadIdx.y], 1); |
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s_coordLists[threadIdx.y][qidx] = coord; |
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s_thetaLists[threadIdx.y][qidx] = theta; |
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} |
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} |
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} |
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__syncthreads(); |
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// let one thread reserve the space required in the global list |
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if (threadIdx.x == 0 && threadIdx.y == 0) |
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{ |
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// find how many items are stored in each list |
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int totalSize = 0; |
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for (int i = 0; i < blockDim.y; ++i) |
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{ |
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s_globStart[i] = totalSize; |
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totalSize += s_sizes[i]; |
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} |
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// calculate the offset in the global list |
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const int globalOffset = atomicAdd(&g_counter, totalSize); |
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for (int i = 0; i < blockDim.y; ++i) |
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s_globStart[i] += globalOffset; |
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} |
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__syncthreads(); |
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// copy local queues to global queue |
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const int qsize = s_sizes[threadIdx.y]; |
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int gidx = s_globStart[threadIdx.y] + threadIdx.x; |
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for(int i = threadIdx.x; i < qsize; i += blockDim.x, gidx += blockDim.x) |
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{ |
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coordList[gidx] = s_coordLists[threadIdx.y][i]; |
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thetaList[gidx] = s_thetaLists[threadIdx.y][i]; |
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} |
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} |
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template <typename T> |
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int buildEdgePointList_gpu(PtrStepSzb edges, PtrStepSzb dx, PtrStepSzb dy, unsigned int* coordList, float* thetaList) |
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{ |
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const int PIXELS_PER_THREAD = 8; |
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void* counterPtr; |
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cudaSafeCall( cudaGetSymbolAddress(&counterPtr, g_counter) ); |
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cudaSafeCall( cudaMemset(counterPtr, 0, sizeof(int)) ); |
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const dim3 block(32, 4); |
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const dim3 grid(divUp(edges.cols, block.x * PIXELS_PER_THREAD), divUp(edges.rows, block.y)); |
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cudaSafeCall( cudaFuncSetCacheConfig(buildEdgePointList<T, PIXELS_PER_THREAD>, cudaFuncCachePreferShared) ); |
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buildEdgePointList<T, PIXELS_PER_THREAD><<<grid, block>>>(edges, (PtrStepSz<T>) dx, (PtrStepSz<T>) dy, coordList, thetaList); |
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cudaSafeCall( cudaGetLastError() ); |
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cudaSafeCall( cudaDeviceSynchronize() ); |
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int totalCount; |
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cudaSafeCall( cudaMemcpy(&totalCount, counterPtr, sizeof(int), cudaMemcpyDeviceToHost) ); |
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return totalCount; |
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} |
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template int buildEdgePointList_gpu<short>(PtrStepSzb edges, PtrStepSzb dx, PtrStepSzb dy, unsigned int* coordList, float* thetaList); |
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template int buildEdgePointList_gpu<int>(PtrStepSzb edges, PtrStepSzb dx, PtrStepSzb dy, unsigned int* coordList, float* thetaList); |
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template int buildEdgePointList_gpu<float>(PtrStepSzb edges, PtrStepSzb dx, PtrStepSzb dy, unsigned int* coordList, float* thetaList); |
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__global__ void buildRTable(const unsigned int* coordList, const float* thetaList, const int pointsCount, |
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PtrStep<short2> r_table, int* r_sizes, int maxSize, |
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const short2 templCenter, const float thetaScale) |
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{ |
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const int tid = blockIdx.x * blockDim.x + threadIdx.x; |
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if (tid >= pointsCount) |
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return; |
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const unsigned int coord = coordList[tid]; |
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short2 p; |
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p.x = (coord & 0xFFFF); |
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p.y = (coord >> 16) & 0xFFFF; |
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const float theta = thetaList[tid]; |
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const int n = __float2int_rn(theta * thetaScale); |
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const int ind = ::atomicAdd(r_sizes + n, 1); |
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if (ind < maxSize) |
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r_table(n, ind) = saturate_cast<short2>(p - templCenter); |
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} |
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void buildRTable_gpu(const unsigned int* coordList, const float* thetaList, int pointsCount, |
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PtrStepSz<short2> r_table, int* r_sizes, |
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short2 templCenter, int levels) |
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{ |
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const dim3 block(256); |
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const dim3 grid(divUp(pointsCount, block.x)); |
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const float thetaScale = levels / (2.0f * CV_PI_F); |
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buildRTable<<<grid, block>>>(coordList, thetaList, pointsCount, r_table, r_sizes, r_table.cols, templCenter, thetaScale); |
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cudaSafeCall( cudaGetLastError() ); |
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cudaSafeCall( cudaDeviceSynchronize() ); |
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} |
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//////////////////////////////////////////////////////////////////////// |
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// GHT_Ballard_Pos |
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__global__ void GHT_Ballard_Pos_calcHist(const unsigned int* coordList, const float* thetaList, const int pointsCount, |
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const PtrStep<short2> r_table, const int* r_sizes, |
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PtrStepSzi hist, |
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const float idp, const float thetaScale) |
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{ |
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const int tid = blockIdx.x * blockDim.x + threadIdx.x; |
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if (tid >= pointsCount) |
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return; |
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const unsigned int coord = coordList[tid]; |
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short2 p; |
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p.x = (coord & 0xFFFF); |
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p.y = (coord >> 16) & 0xFFFF; |
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const float theta = thetaList[tid]; |
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const int n = __float2int_rn(theta * thetaScale); |
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const short2* r_row = r_table.ptr(n); |
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const int r_row_size = r_sizes[n]; |
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for (int j = 0; j < r_row_size; ++j) |
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{ |
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int2 c = p - r_row[j]; |
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c.x = __float2int_rn(c.x * idp); |
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c.y = __float2int_rn(c.y * idp); |
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if (c.x >= 0 && c.x < hist.cols - 2 && c.y >= 0 && c.y < hist.rows - 2) |
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::atomicAdd(hist.ptr(c.y + 1) + c.x + 1, 1); |
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} |
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} |
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void GHT_Ballard_Pos_calcHist_gpu(const unsigned int* coordList, const float* thetaList, int pointsCount, |
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PtrStepSz<short2> r_table, const int* r_sizes, |
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PtrStepSzi hist, |
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float dp, int levels) |
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{ |
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const dim3 block(256); |
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const dim3 grid(divUp(pointsCount, block.x)); |
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const float idp = 1.0f / dp; |
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const float thetaScale = levels / (2.0f * CV_PI_F); |
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GHT_Ballard_Pos_calcHist<<<grid, block>>>(coordList, thetaList, pointsCount, r_table, r_sizes, hist, idp, thetaScale); |
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cudaSafeCall( cudaGetLastError() ); |
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cudaSafeCall( cudaDeviceSynchronize() ); |
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} |
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__global__ void GHT_Ballard_Pos_findPosInHist(const PtrStepSzi hist, float4* out, int3* votes, const int maxSize, const float dp, const int threshold) |
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{ |
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const int x = blockIdx.x * blockDim.x + threadIdx.x; |
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const int y = blockIdx.y * blockDim.y + threadIdx.y; |
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if (x >= hist.cols - 2 || y >= hist.rows - 2) |
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return; |
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const int curVotes = hist(y + 1, x + 1); |
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if (curVotes > threshold && |
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curVotes > hist(y + 1, x) && |
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curVotes >= hist(y + 1, x + 2) && |
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curVotes > hist(y, x + 1) && |
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curVotes >= hist(y + 2, x + 1)) |
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{ |
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const int ind = ::atomicAdd(&g_counter, 1); |
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if (ind < maxSize) |
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{ |
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out[ind] = make_float4(x * dp, y * dp, 1.0f, 0.0f); |
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votes[ind] = make_int3(curVotes, 0, 0); |
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} |
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} |
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} |
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int GHT_Ballard_Pos_findPosInHist_gpu(PtrStepSzi hist, float4* out, int3* votes, int maxSize, float dp, int threshold) |
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{ |
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void* counterPtr; |
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cudaSafeCall( cudaGetSymbolAddress(&counterPtr, g_counter) ); |
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cudaSafeCall( cudaMemset(counterPtr, 0, sizeof(int)) ); |
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const dim3 block(32, 8); |
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const dim3 grid(divUp(hist.cols - 2, block.x), divUp(hist.rows - 2, block.y)); |
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cudaSafeCall( cudaFuncSetCacheConfig(GHT_Ballard_Pos_findPosInHist, cudaFuncCachePreferL1) ); |
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GHT_Ballard_Pos_findPosInHist<<<grid, block>>>(hist, out, votes, maxSize, dp, threshold); |
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cudaSafeCall( cudaGetLastError() ); |
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cudaSafeCall( cudaDeviceSynchronize() ); |
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int totalCount; |
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cudaSafeCall( cudaMemcpy(&totalCount, counterPtr, sizeof(int), cudaMemcpyDeviceToHost) ); |
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totalCount = ::min(totalCount, maxSize); |
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return totalCount; |
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} |
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//////////////////////////////////////////////////////////////////////// |
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// GHT_Ballard_PosScale |
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__global__ void GHT_Ballard_PosScale_calcHist(const unsigned int* coordList, const float* thetaList, |
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PtrStep<short2> r_table, const int* r_sizes, |
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PtrStepi hist, const int rows, const int cols, |
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const float minScale, const float scaleStep, const int scaleRange, |
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const float idp, const float thetaScale) |
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{ |
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const unsigned int coord = coordList[blockIdx.x]; |
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float2 p; |
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p.x = (coord & 0xFFFF); |
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p.y = (coord >> 16) & 0xFFFF; |
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const float theta = thetaList[blockIdx.x]; |
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const int n = __float2int_rn(theta * thetaScale); |
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const short2* r_row = r_table.ptr(n); |
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const int r_row_size = r_sizes[n]; |
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for (int j = 0; j < r_row_size; ++j) |
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{ |
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const float2 d = saturate_cast<float2>(r_row[j]); |
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for (int s = threadIdx.x; s < scaleRange; s += blockDim.x) |
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{ |
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const float scale = minScale + s * scaleStep; |
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float2 c = p - scale * d; |
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c.x *= idp; |
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c.y *= idp; |
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if (c.x >= 0 && c.x < cols && c.y >= 0 && c.y < rows) |
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::atomicAdd(hist.ptr((s + 1) * (rows + 2) + __float2int_rn(c.y + 1)) + __float2int_rn(c.x + 1), 1); |
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} |
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} |
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} |
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void GHT_Ballard_PosScale_calcHist_gpu(const unsigned int* coordList, const float* thetaList, int pointsCount, |
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PtrStepSz<short2> r_table, const int* r_sizes, |
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PtrStepi hist, int rows, int cols, |
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float minScale, float scaleStep, int scaleRange, |
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float dp, int levels) |
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{ |
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const dim3 block(256); |
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const dim3 grid(pointsCount); |
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const float idp = 1.0f / dp; |
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const float thetaScale = levels / (2.0f * CV_PI_F); |
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GHT_Ballard_PosScale_calcHist<<<grid, block>>>(coordList, thetaList, |
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r_table, r_sizes, |
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hist, rows, cols, |
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minScale, scaleStep, scaleRange, |
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idp, thetaScale); |
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cudaSafeCall( cudaGetLastError() ); |
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cudaSafeCall( cudaDeviceSynchronize() ); |
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} |
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__global__ void GHT_Ballard_PosScale_findPosInHist(const PtrStepi hist, const int rows, const int cols, const int scaleRange, |
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float4* out, int3* votes, const int maxSize, |
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const float minScale, const float scaleStep, const float dp, const int threshold) |
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{ |
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const int x = blockIdx.x * blockDim.x + threadIdx.x; |
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const int y = blockIdx.y * blockDim.y + threadIdx.y; |
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if (x >= cols || y >= rows) |
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return; |
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for (int s = 0; s < scaleRange; ++s) |
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{ |
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const float scale = minScale + s * scaleStep; |
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const int prevScaleIdx = (s) * (rows + 2); |
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const int curScaleIdx = (s + 1) * (rows + 2); |
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const int nextScaleIdx = (s + 2) * (rows + 2); |
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const int curVotes = hist(curScaleIdx + y + 1, x + 1); |
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if (curVotes > threshold && |
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curVotes > hist(curScaleIdx + y + 1, x) && |
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curVotes >= hist(curScaleIdx + y + 1, x + 2) && |
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curVotes > hist(curScaleIdx + y, x + 1) && |
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curVotes >= hist(curScaleIdx + y + 2, x + 1) && |
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curVotes > hist(prevScaleIdx + y + 1, x + 1) && |
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curVotes >= hist(nextScaleIdx + y + 1, x + 1)) |
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{ |
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const int ind = ::atomicAdd(&g_counter, 1); |
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if (ind < maxSize) |
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{ |
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out[ind] = make_float4(x * dp, y * dp, scale, 0.0f); |
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votes[ind] = make_int3(curVotes, curVotes, 0); |
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} |
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} |
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} |
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} |
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int GHT_Ballard_PosScale_findPosInHist_gpu(PtrStepi hist, int rows, int cols, int scaleRange, float4* out, int3* votes, int maxSize, |
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float minScale, float scaleStep, float dp, int threshold) |
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{ |
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void* counterPtr; |
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cudaSafeCall( cudaGetSymbolAddress(&counterPtr, g_counter) ); |
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cudaSafeCall( cudaMemset(counterPtr, 0, sizeof(int)) ); |
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const dim3 block(32, 8); |
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const dim3 grid(divUp(cols, block.x), divUp(rows, block.y)); |
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cudaSafeCall( cudaFuncSetCacheConfig(GHT_Ballard_PosScale_findPosInHist, cudaFuncCachePreferL1) ); |
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GHT_Ballard_PosScale_findPosInHist<<<grid, block>>>(hist, rows, cols, scaleRange, out, votes, maxSize, minScale, scaleStep, dp, threshold); |
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cudaSafeCall( cudaGetLastError() ); |
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cudaSafeCall( cudaDeviceSynchronize() ); |
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int totalCount; |
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cudaSafeCall( cudaMemcpy(&totalCount, counterPtr, sizeof(int), cudaMemcpyDeviceToHost) ); |
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totalCount = ::min(totalCount, maxSize); |
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return totalCount; |
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} |
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//////////////////////////////////////////////////////////////////////// |
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// GHT_Ballard_PosRotation |
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__global__ void GHT_Ballard_PosRotation_calcHist(const unsigned int* coordList, const float* thetaList, |
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PtrStep<short2> r_table, const int* r_sizes, |
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PtrStepi hist, const int rows, const int cols, |
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const float minAngle, const float angleStep, const int angleRange, |
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const float idp, const float thetaScale) |
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{ |
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const unsigned int coord = coordList[blockIdx.x]; |
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float2 p; |
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p.x = (coord & 0xFFFF); |
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p.y = (coord >> 16) & 0xFFFF; |
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const float thetaVal = thetaList[blockIdx.x]; |
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for (int a = threadIdx.x; a < angleRange; a += blockDim.x) |
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{ |
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const float angle = (minAngle + a * angleStep) * (CV_PI_F / 180.0f); |
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float sinA, cosA; |
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sincosf(angle, &sinA, &cosA); |
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float theta = thetaVal - angle; |
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if (theta < 0) |
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theta += 2.0f * CV_PI_F; |
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const int n = __float2int_rn(theta * thetaScale); |
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const short2* r_row = r_table.ptr(n); |
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const int r_row_size = r_sizes[n]; |
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for (int j = 0; j < r_row_size; ++j) |
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{ |
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const float2 d = saturate_cast<float2>(r_row[j]); |
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const float2 dr = make_float2(d.x * cosA - d.y * sinA, d.x * sinA + d.y * cosA); |
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float2 c = make_float2(p.x - dr.x, p.y - dr.y); |
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c.x *= idp; |
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c.y *= idp; |
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if (c.x >= 0 && c.x < cols && c.y >= 0 && c.y < rows) |
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::atomicAdd(hist.ptr((a + 1) * (rows + 2) + __float2int_rn(c.y + 1)) + __float2int_rn(c.x + 1), 1); |
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} |
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} |
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} |
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void GHT_Ballard_PosRotation_calcHist_gpu(const unsigned int* coordList, const float* thetaList, int pointsCount, |
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PtrStepSz<short2> r_table, const int* r_sizes, |
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PtrStepi hist, int rows, int cols, |
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float minAngle, float angleStep, int angleRange, |
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float dp, int levels) |
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{ |
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const dim3 block(256); |
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const dim3 grid(pointsCount); |
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const float idp = 1.0f / dp; |
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const float thetaScale = levels / (2.0f * CV_PI_F); |
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GHT_Ballard_PosRotation_calcHist<<<grid, block>>>(coordList, thetaList, |
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r_table, r_sizes, |
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hist, rows, cols, |
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minAngle, angleStep, angleRange, |
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idp, thetaScale); |
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cudaSafeCall( cudaGetLastError() ); |
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cudaSafeCall( cudaDeviceSynchronize() ); |
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} |
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__global__ void GHT_Ballard_PosRotation_findPosInHist(const PtrStepi hist, const int rows, const int cols, const int angleRange, |
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float4* out, int3* votes, const int maxSize, |
|
const float minAngle, const float angleStep, 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 >= cols || y >= rows) |
|
return; |
|
|
|
for (int a = 0; a < angleRange; ++a) |
|
{ |
|
const float angle = minAngle + a * angleStep; |
|
|
|
const int prevAngleIdx = (a) * (rows + 2); |
|
const int curAngleIdx = (a + 1) * (rows + 2); |
|
const int nextAngleIdx = (a + 2) * (rows + 2); |
|
|
|
const int curVotes = hist(curAngleIdx + y + 1, x + 1); |
|
|
|
if (curVotes > threshold && |
|
curVotes > hist(curAngleIdx + y + 1, x) && |
|
curVotes >= hist(curAngleIdx + y + 1, x + 2) && |
|
curVotes > hist(curAngleIdx + y, x + 1) && |
|
curVotes >= hist(curAngleIdx + y + 2, x + 1) && |
|
curVotes > hist(prevAngleIdx + y + 1, x + 1) && |
|
curVotes >= hist(nextAngleIdx + y + 1, x + 1)) |
|
{ |
|
const int ind = ::atomicAdd(&g_counter, 1); |
|
|
|
if (ind < maxSize) |
|
{ |
|
out[ind] = make_float4(x * dp, y * dp, 1.0f, angle); |
|
votes[ind] = make_int3(curVotes, 0, curVotes); |
|
} |
|
} |
|
} |
|
} |
|
|
|
int GHT_Ballard_PosRotation_findPosInHist_gpu(PtrStepi hist, int rows, int cols, int angleRange, float4* out, int3* votes, int maxSize, |
|
float minAngle, float angleStep, 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(cols, block.x), divUp(rows, block.y)); |
|
|
|
cudaSafeCall( cudaFuncSetCacheConfig(GHT_Ballard_PosRotation_findPosInHist, cudaFuncCachePreferL1) ); |
|
|
|
GHT_Ballard_PosRotation_findPosInHist<<<grid, block>>>(hist, rows, cols, angleRange, out, votes, maxSize, minAngle, angleStep, dp, threshold); |
|
cudaSafeCall( cudaGetLastError() ); |
|
|
|
cudaSafeCall( cudaDeviceSynchronize() ); |
|
|
|
int totalCount; |
|
cudaSafeCall( cudaMemcpy(&totalCount, counterPtr, sizeof(int), cudaMemcpyDeviceToHost) ); |
|
|
|
totalCount = ::min(totalCount, maxSize); |
|
|
|
return totalCount; |
|
} |
|
|
|
//////////////////////////////////////////////////////////////////////// |
|
// GHT_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 GHT_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 GHT_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 <class FT, bool isTempl> |
|
__global__ void GHT_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 <class FT, bool isTempl> |
|
void GHT_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); |
|
|
|
GHT_Guil_Full_buildFeatureList<FT, isTempl><<<grid, block>>>(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<int> sizesPtr(sizes); |
|
thrust::transform(sizesPtr, sizesPtr + levels + 1, sizesPtr, device::bind2nd(device::minimum<int>(), maxSize)); |
|
} |
|
|
|
void GHT_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) |
|
{ |
|
GHT_Guil_Full_buildFeatureList_caller<TemplFeatureTable, true>(coordList, thetaList, pointsCount, |
|
sizes, maxSize, |
|
xi, angleEpsilon, levels, |
|
center, maxDist); |
|
} |
|
void GHT_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) |
|
{ |
|
GHT_Guil_Full_buildFeatureList_caller<ImageFeatureTable, false>(coordList, thetaList, pointsCount, |
|
sizes, maxSize, |
|
xi, angleEpsilon, levels, |
|
center, maxDist); |
|
} |
|
|
|
__global__ void GHT_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 GHT_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); |
|
|
|
GHT_Guil_Full_calcOHist<<<grid, block, smemSize>>>(templSizes, imageSizes, OHist, |
|
minAngle, maxAngle, 1.0f / angleStep, angleRange); |
|
cudaSafeCall( cudaGetLastError() ); |
|
|
|
cudaSafeCall( cudaDeviceSynchronize() ); |
|
} |
|
|
|
__global__ void GHT_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 GHT_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); |
|
|
|
GHT_Guil_Full_calcSHist<<<grid, block, smemSize>>>(templSizes, imageSizes, SHist, |
|
angle, angleEpsilon, |
|
minScale, maxScale, iScaleStep, scaleRange); |
|
cudaSafeCall( cudaGetLastError() ); |
|
|
|
cudaSafeCall( cudaDeviceSynchronize() ); |
|
} |
|
|
|
__global__ void GHT_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 GHT_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(GHT_Guil_Full_calcPHist, cudaFuncCachePreferL1) ); |
|
|
|
GHT_Guil_Full_calcPHist<<<grid, block>>>(templSizes, imageSizes, PHist, |
|
angle, sinVal, cosVal, angleEpsilon, scale, |
|
1.0f / dp); |
|
cudaSafeCall( cudaGetLastError() ); |
|
|
|
cudaSafeCall( cudaDeviceSynchronize() ); |
|
} |
|
|
|
__global__ void GHT_Guil_Full_findPosInHist(const PtrStepSzi hist, float4* out, int3* votes, const int maxSize, |
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const float angle, const int angleVotes, const float scale, const int scaleVotes, |
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const float dp, const int threshold) |
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{ |
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const int x = blockIdx.x * blockDim.x + threadIdx.x; |
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const int y = blockIdx.y * blockDim.y + threadIdx.y; |
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if (x >= hist.cols - 2 || y >= hist.rows - 2) |
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return; |
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const int curVotes = hist(y + 1, x + 1); |
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if (curVotes > threshold && |
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curVotes > hist(y + 1, x) && |
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curVotes >= hist(y + 1, x + 2) && |
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curVotes > hist(y, x + 1) && |
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curVotes >= hist(y + 2, x + 1)) |
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{ |
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const int ind = ::atomicAdd(&g_counter, 1); |
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if (ind < maxSize) |
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{ |
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out[ind] = make_float4(x * dp, y * dp, scale, angle); |
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votes[ind] = make_int3(curVotes, scaleVotes, angleVotes); |
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} |
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} |
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} |
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int GHT_Guil_Full_findPosInHist_gpu(PtrStepSzi hist, float4* out, int3* votes, int curSize, int maxSize, |
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float angle, int angleVotes, float scale, int scaleVotes, |
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float dp, int threshold) |
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{ |
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void* counterPtr; |
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cudaSafeCall( cudaGetSymbolAddress(&counterPtr, g_counter) ); |
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cudaSafeCall( cudaMemcpy(counterPtr, &curSize, sizeof(int), cudaMemcpyHostToDevice) ); |
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const dim3 block(32, 8); |
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const dim3 grid(divUp(hist.cols - 2, block.x), divUp(hist.rows - 2, block.y)); |
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cudaSafeCall( cudaFuncSetCacheConfig(GHT_Guil_Full_findPosInHist, cudaFuncCachePreferL1) ); |
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GHT_Guil_Full_findPosInHist<<<grid, block>>>(hist, out, votes, maxSize, |
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angle, angleVotes, scale, scaleVotes, |
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dp, threshold); |
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cudaSafeCall( cudaGetLastError() ); |
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cudaSafeCall( cudaDeviceSynchronize() ); |
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int totalCount; |
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cudaSafeCall( cudaMemcpy(&totalCount, counterPtr, sizeof(int), cudaMemcpyDeviceToHost) ); |
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totalCount = ::min(totalCount, maxSize); |
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return totalCount; |
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} |
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} |
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}}} |
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#endif /* CUDA_DISABLER */
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