1077 lines
44 KiB
Plaintext
1077 lines
44 KiB
Plaintext
/*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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#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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{
|
|
const float2 d = saturate_cast<float2>(r_row[j]);
|
|
|
|
const float2 dr = make_float2(d.x * cosA - d.y * sinA, d.x * sinA + d.y * cosA);
|
|
|
|
float2 c = make_float2(p.x - dr.x, p.y - dr.y);
|
|
c.x *= idp;
|
|
c.y *= idp;
|
|
|
|
if (c.x >= 0 && c.x < cols && c.y >= 0 && c.y < rows)
|
|
::atomicAdd(hist.ptr((a + 1) * (rows + 2) + __float2int_rn(c.y + 1)) + __float2int_rn(c.x + 1), 1);
|
|
}
|
|
}
|
|
}
|
|
|
|
void GHT_Ballard_PosRotation_calcHist_gpu(const unsigned int* coordList, const float* thetaList, int pointsCount,
|
|
PtrStepSz<short2> r_table, const int* r_sizes,
|
|
PtrStepi hist, int rows, int cols,
|
|
float minAngle, float angleStep, int angleRange,
|
|
float dp, int levels)
|
|
{
|
|
const dim3 block(256);
|
|
const dim3 grid(pointsCount);
|
|
|
|
const float idp = 1.0f / dp;
|
|
const float thetaScale = levels / (2.0f * CV_PI_F);
|
|
|
|
GHT_Ballard_PosRotation_calcHist<<<grid, block>>>(coordList, thetaList,
|
|
r_table, r_sizes,
|
|
hist, rows, cols,
|
|
minAngle, angleStep, angleRange,
|
|
idp, thetaScale);
|
|
cudaSafeCall( cudaGetLastError() );
|
|
|
|
cudaSafeCall( cudaDeviceSynchronize() );
|
|
}
|
|
|
|
__global__ void GHT_Ballard_PosRotation_findPosInHist(const PtrStepi hist, const int rows, const int cols, const int angleRange,
|
|
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,
|
|
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 GHT_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(GHT_Guil_Full_findPosInHist, cudaFuncCachePreferL1) );
|
|
|
|
GHT_Guil_Full_findPosInHist<<<grid, block>>>(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 /* CUDA_DISABLER */
|