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1710 lines
67 KiB
Plaintext
1710 lines
67 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 bpied warranties, including, but not limited to, the bpied
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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/sort.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/limits.hpp"
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#include "opencv2/gpu/device/dynamic_smem.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__ int g_counter;
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////////////////////////////////////////////////////////////////////////
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// buildPointList
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template <int PIXELS_PER_THREAD>
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__global__ void buildPointList(const PtrStepSzb src, unsigned int* list)
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{
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__shared__ unsigned int s_queues[4][32 * PIXELS_PER_THREAD];
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__shared__ int s_qsize[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_qsize[threadIdx.y] = 0;
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__syncthreads();
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if (y < src.rows)
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{
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// fill the queue
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const uchar* srcRow = src.ptr(y);
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for (int i = 0, xx = x; i < PIXELS_PER_THREAD && xx < src.cols; ++i, xx += blockDim.x)
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{
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if (srcRow[xx])
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{
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const unsigned int val = (y << 16) | xx;
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const int qidx = Emulation::smem::atomicAdd(&s_qsize[threadIdx.y], 1);
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s_queues[threadIdx.y][qidx] = val;
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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_qsize[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_qsize[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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list[gidx] = s_queues[threadIdx.y][i];
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}
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int buildPointList_gpu(PtrStepSzb src, unsigned int* list)
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{
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const int PIXELS_PER_THREAD = 16;
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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(src.cols, block.x * PIXELS_PER_THREAD), divUp(src.rows, block.y));
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cudaSafeCall( cudaFuncSetCacheConfig(buildPointList<PIXELS_PER_THREAD>, cudaFuncCachePreferShared) );
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buildPointList<PIXELS_PER_THREAD><<<grid, block>>>(src, list);
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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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////////////////////////////////////////////////////////////////////////
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// linesAccum
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__global__ void linesAccumGlobal(const unsigned int* list, const int count, PtrStepi accum, const float irho, const float theta, const int numrho)
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{
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const int n = blockIdx.x;
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const float ang = n * theta;
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float sinVal;
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float cosVal;
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sincosf(ang, &sinVal, &cosVal);
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sinVal *= irho;
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cosVal *= irho;
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const int shift = (numrho - 1) / 2;
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int* accumRow = accum.ptr(n + 1);
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for (int i = threadIdx.x; i < count; i += blockDim.x)
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{
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const unsigned int val = list[i];
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const int x = (val & 0xFFFF);
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const int y = (val >> 16) & 0xFFFF;
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int r = __float2int_rn(x * cosVal + y * sinVal);
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r += shift;
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::atomicAdd(accumRow + r + 1, 1);
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}
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}
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__global__ void linesAccumShared(const unsigned int* list, const int count, PtrStepi accum, const float irho, const float theta, const int numrho)
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{
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int* smem = DynamicSharedMem<int>();
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for (int i = threadIdx.x; i < numrho + 1; i += blockDim.x)
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smem[i] = 0;
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__syncthreads();
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const int n = blockIdx.x;
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const float ang = n * theta;
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float sinVal;
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float cosVal;
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sincosf(ang, &sinVal, &cosVal);
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sinVal *= irho;
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cosVal *= irho;
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const int shift = (numrho - 1) / 2;
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for (int i = threadIdx.x; i < count; i += blockDim.x)
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{
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const unsigned int val = list[i];
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const int x = (val & 0xFFFF);
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const int y = (val >> 16) & 0xFFFF;
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int r = __float2int_rn(x * cosVal + y * sinVal);
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r += shift;
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Emulation::smem::atomicAdd(&smem[r + 1], 1);
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}
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__syncthreads();
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int* accumRow = accum.ptr(n + 1);
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for (int i = threadIdx.x; i < numrho + 1; i += blockDim.x)
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accumRow[i] = smem[i];
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}
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void linesAccum_gpu(const unsigned int* list, int count, PtrStepSzi accum, float rho, float theta, size_t sharedMemPerBlock, bool has20)
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{
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const dim3 block(has20 ? 1024 : 512);
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const dim3 grid(accum.rows - 2);
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size_t smemSize = (accum.cols - 1) * sizeof(int);
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if (smemSize < sharedMemPerBlock - 1000)
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linesAccumShared<<<grid, block, smemSize>>>(list, count, accum, 1.0f / rho, theta, accum.cols - 2);
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else
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linesAccumGlobal<<<grid, block>>>(list, count, accum, 1.0f / rho, theta, accum.cols - 2);
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cudaSafeCall( cudaGetLastError() );
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cudaSafeCall( cudaDeviceSynchronize() );
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}
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////////////////////////////////////////////////////////////////////////
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// linesGetResult
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__global__ void linesGetResult(const PtrStepSzi accum, float2* out, int* votes, const int maxSize, const float rho, const float theta, const int threshold, const int numrho)
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{
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const int r = blockIdx.x * blockDim.x + threadIdx.x;
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const int n = blockIdx.y * blockDim.y + threadIdx.y;
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if (r >= accum.cols - 2 || n >= accum.rows - 2)
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return;
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const int curVotes = accum(n + 1, r + 1);
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if (curVotes > threshold &&
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curVotes > accum(n + 1, r) &&
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curVotes >= accum(n + 1, r + 2) &&
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curVotes > accum(n, r + 1) &&
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curVotes >= accum(n + 2, r + 1))
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{
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const float radius = (r - (numrho - 1) * 0.5f) * rho;
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const float angle = n * theta;
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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_float2(radius, angle);
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votes[ind] = curVotes;
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}
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}
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}
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int linesGetResult_gpu(PtrStepSzi accum, float2* out, int* votes, int maxSize, float rho, float theta, int threshold, bool doSort)
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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(accum.cols - 2, block.x), divUp(accum.rows - 2, block.y));
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cudaSafeCall( cudaFuncSetCacheConfig(linesGetResult, cudaFuncCachePreferL1) );
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linesGetResult<<<grid, block>>>(accum, out, votes, maxSize, rho, theta, threshold, accum.cols - 2);
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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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if (doSort && totalCount > 0)
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{
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thrust::device_ptr<float2> outPtr(out);
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thrust::device_ptr<int> votesPtr(votes);
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thrust::sort_by_key(votesPtr, votesPtr + totalCount, outPtr, thrust::greater<int>());
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}
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return totalCount;
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}
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////////////////////////////////////////////////////////////////////////
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// houghLinesProbabilistic
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texture<uchar, cudaTextureType2D, cudaReadModeElementType> tex_mask(false, cudaFilterModePoint, cudaAddressModeClamp);
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__global__ void houghLinesProbabilistic(const PtrStepSzi accum,
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int4* out, const int maxSize,
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const float rho, const float theta,
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const int lineGap, const int lineLength,
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const int rows, const int cols)
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{
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const int r = blockIdx.x * blockDim.x + threadIdx.x;
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const int n = blockIdx.y * blockDim.y + threadIdx.y;
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if (r >= accum.cols - 2 || n >= accum.rows - 2)
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return;
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const int curVotes = accum(n + 1, r + 1);
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if (curVotes >= lineLength &&
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curVotes > accum(n, r) &&
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curVotes > accum(n, r + 1) &&
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curVotes > accum(n, r + 2) &&
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curVotes > accum(n + 1, r) &&
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curVotes > accum(n + 1, r + 2) &&
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curVotes > accum(n + 2, r) &&
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curVotes > accum(n + 2, r + 1) &&
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curVotes > accum(n + 2, r + 2))
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{
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const float radius = (r - (accum.cols - 2 - 1) * 0.5f) * rho;
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const float angle = n * theta;
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float cosa;
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float sina;
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sincosf(angle, &sina, &cosa);
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float2 p0 = make_float2(cosa * radius, sina * radius);
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float2 dir = make_float2(-sina, cosa);
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float2 pb[4] = {make_float2(-1, -1), make_float2(-1, -1), make_float2(-1, -1), make_float2(-1, -1)};
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float a;
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if (dir.x != 0)
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{
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a = -p0.x / dir.x;
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pb[0].x = 0;
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pb[0].y = p0.y + a * dir.y;
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a = (cols - 1 - p0.x) / dir.x;
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pb[1].x = cols - 1;
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pb[1].y = p0.y + a * dir.y;
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}
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if (dir.y != 0)
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{
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a = -p0.y / dir.y;
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pb[2].x = p0.x + a * dir.x;
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pb[2].y = 0;
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a = (rows - 1 - p0.y) / dir.y;
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pb[3].x = p0.x + a * dir.x;
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pb[3].y = rows - 1;
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}
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if (pb[0].x == 0 && (pb[0].y >= 0 && pb[0].y < rows))
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{
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p0 = pb[0];
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if (dir.x < 0)
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dir = -dir;
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}
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else if (pb[1].x == cols - 1 && (pb[0].y >= 0 && pb[0].y < rows))
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{
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p0 = pb[1];
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if (dir.x > 0)
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dir = -dir;
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}
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else if (pb[2].y == 0 && (pb[2].x >= 0 && pb[2].x < cols))
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{
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p0 = pb[2];
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if (dir.y < 0)
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dir = -dir;
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}
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else if (pb[3].y == rows - 1 && (pb[3].x >= 0 && pb[3].x < cols))
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{
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p0 = pb[3];
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if (dir.y > 0)
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dir = -dir;
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}
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float2 d;
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if (::fabsf(dir.x) > ::fabsf(dir.y))
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{
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d.x = dir.x > 0 ? 1 : -1;
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d.y = dir.y / ::fabsf(dir.x);
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}
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else
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{
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d.x = dir.x / ::fabsf(dir.y);
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d.y = dir.y > 0 ? 1 : -1;
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}
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float2 line_end[2];
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int gap;
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bool inLine = false;
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float2 p1 = p0;
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if (p1.x < 0 || p1.x >= cols || p1.y < 0 || p1.y >= rows)
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return;
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for (;;)
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{
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if (tex2D(tex_mask, p1.x, p1.y))
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{
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gap = 0;
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if (!inLine)
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{
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line_end[0] = p1;
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line_end[1] = p1;
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inLine = true;
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}
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else
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{
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line_end[1] = p1;
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}
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}
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else if (inLine)
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{
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if (++gap > lineGap)
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{
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bool good_line = ::abs(line_end[1].x - line_end[0].x) >= lineLength ||
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::abs(line_end[1].y - line_end[0].y) >= lineLength;
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if (good_line)
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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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out[ind] = make_int4(line_end[0].x, line_end[0].y, line_end[1].x, line_end[1].y);
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}
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gap = 0;
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inLine = false;
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}
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}
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p1 = p1 + d;
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if (p1.x < 0 || p1.x >= cols || p1.y < 0 || p1.y >= rows)
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{
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if (inLine)
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{
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bool good_line = ::abs(line_end[1].x - line_end[0].x) >= lineLength ||
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::abs(line_end[1].y - line_end[0].y) >= lineLength;
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if (good_line)
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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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out[ind] = make_int4(line_end[0].x, line_end[0].y, line_end[1].x, line_end[1].y);
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}
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}
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break;
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}
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}
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}
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}
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int houghLinesProbabilistic_gpu(PtrStepSzb mask, PtrStepSzi accum, int4* out, int maxSize, float rho, float theta, int lineGap, int lineLength)
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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(accum.cols - 2, block.x), divUp(accum.rows - 2, block.y));
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bindTexture(&tex_mask, mask);
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houghLinesProbabilistic<<<grid, block>>>(accum,
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out, maxSize,
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rho, theta,
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lineGap, lineLength,
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mask.rows, mask.cols);
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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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// circlesAccumCenters
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__global__ void circlesAccumCenters(const unsigned int* list, const int count, const PtrStepi dx, const PtrStepi dy,
|
|
PtrStepi accum, const int width, const int height, const int minRadius, const int maxRadius, const float idp)
|
|
{
|
|
const int SHIFT = 10;
|
|
const int ONE = 1 << SHIFT;
|
|
|
|
const int tid = blockIdx.x * blockDim.x + threadIdx.x;
|
|
|
|
if (tid >= count)
|
|
return;
|
|
|
|
const unsigned int val = list[tid];
|
|
|
|
const int x = (val & 0xFFFF);
|
|
const int y = (val >> 16) & 0xFFFF;
|
|
|
|
const int vx = dx(y, x);
|
|
const int vy = dy(y, x);
|
|
|
|
if (vx == 0 && vy == 0)
|
|
return;
|
|
|
|
const float mag = ::sqrtf(vx * vx + vy * vy);
|
|
|
|
const int x0 = __float2int_rn((x * idp) * ONE);
|
|
const int y0 = __float2int_rn((y * idp) * ONE);
|
|
|
|
int sx = __float2int_rn((vx * idp) * ONE / mag);
|
|
int sy = __float2int_rn((vy * idp) * ONE / mag);
|
|
|
|
// Step from minRadius to maxRadius in both directions of the gradient
|
|
for (int k1 = 0; k1 < 2; ++k1)
|
|
{
|
|
int x1 = x0 + minRadius * sx;
|
|
int y1 = y0 + minRadius * sy;
|
|
|
|
for (int r = minRadius; r <= maxRadius; x1 += sx, y1 += sy, ++r)
|
|
{
|
|
const int x2 = x1 >> SHIFT;
|
|
const int y2 = y1 >> SHIFT;
|
|
|
|
if (x2 < 0 || x2 >= width || y2 < 0 || y2 >= height)
|
|
break;
|
|
|
|
::atomicAdd(accum.ptr(y2 + 1) + x2 + 1, 1);
|
|
}
|
|
|
|
sx = -sx;
|
|
sy = -sy;
|
|
}
|
|
}
|
|
|
|
void circlesAccumCenters_gpu(const unsigned int* list, int count, PtrStepi dx, PtrStepi dy, PtrStepSzi accum, int minRadius, int maxRadius, float idp)
|
|
{
|
|
const dim3 block(256);
|
|
const dim3 grid(divUp(count, block.x));
|
|
|
|
cudaSafeCall( cudaFuncSetCacheConfig(circlesAccumCenters, cudaFuncCachePreferL1) );
|
|
|
|
circlesAccumCenters<<<grid, block>>>(list, count, dx, dy, accum, accum.cols - 2, accum.rows - 2, minRadius, maxRadius, idp);
|
|
cudaSafeCall( cudaGetLastError() );
|
|
|
|
cudaSafeCall( cudaDeviceSynchronize() );
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////////
|
|
// buildCentersList
|
|
|
|
__global__ void buildCentersList(const PtrStepSzi accum, unsigned int* centers, const int threshold)
|
|
{
|
|
const int x = blockIdx.x * blockDim.x + threadIdx.x;
|
|
const int y = blockIdx.y * blockDim.y + threadIdx.y;
|
|
|
|
if (x < accum.cols - 2 && y < accum.rows - 2)
|
|
{
|
|
const int top = accum(y, x + 1);
|
|
|
|
const int left = accum(y + 1, x);
|
|
const int cur = accum(y + 1, x + 1);
|
|
const int right = accum(y + 1, x + 2);
|
|
|
|
const int bottom = accum(y + 2, x + 1);
|
|
|
|
if (cur > threshold && cur > top && cur >= bottom && cur > left && cur >= right)
|
|
{
|
|
const unsigned int val = (y << 16) | x;
|
|
const int idx = ::atomicAdd(&g_counter, 1);
|
|
centers[idx] = val;
|
|
}
|
|
}
|
|
}
|
|
|
|
int buildCentersList_gpu(PtrStepSzi accum, unsigned int* centers, int threshold)
|
|
{
|
|
void* counterPtr;
|
|
cudaSafeCall( cudaGetSymbolAddress(&counterPtr, g_counter) );
|
|
|
|
cudaSafeCall( cudaMemset(counterPtr, 0, sizeof(int)) );
|
|
|
|
const dim3 block(32, 8);
|
|
const dim3 grid(divUp(accum.cols - 2, block.x), divUp(accum.rows - 2, block.y));
|
|
|
|
cudaSafeCall( cudaFuncSetCacheConfig(buildCentersList, cudaFuncCachePreferL1) );
|
|
|
|
buildCentersList<<<grid, block>>>(accum, centers, threshold);
|
|
cudaSafeCall( cudaGetLastError() );
|
|
|
|
cudaSafeCall( cudaDeviceSynchronize() );
|
|
|
|
int totalCount;
|
|
cudaSafeCall( cudaMemcpy(&totalCount, counterPtr, sizeof(int), cudaMemcpyDeviceToHost) );
|
|
|
|
return totalCount;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////////
|
|
// circlesAccumRadius
|
|
|
|
__global__ void circlesAccumRadius(const unsigned int* centers, const unsigned int* list, const int count,
|
|
float3* circles, const int maxCircles, const float dp,
|
|
const int minRadius, const int maxRadius, const int histSize, const int threshold)
|
|
{
|
|
int* smem = DynamicSharedMem<int>();
|
|
|
|
for (int i = threadIdx.x; i < histSize + 2; i += blockDim.x)
|
|
smem[i] = 0;
|
|
__syncthreads();
|
|
|
|
unsigned int val = centers[blockIdx.x];
|
|
|
|
float cx = (val & 0xFFFF);
|
|
float cy = (val >> 16) & 0xFFFF;
|
|
|
|
cx = (cx + 0.5f) * dp;
|
|
cy = (cy + 0.5f) * dp;
|
|
|
|
for (int i = threadIdx.x; i < count; i += blockDim.x)
|
|
{
|
|
val = list[i];
|
|
|
|
const int x = (val & 0xFFFF);
|
|
const int y = (val >> 16) & 0xFFFF;
|
|
|
|
const float rad = ::sqrtf((cx - x) * (cx - x) + (cy - y) * (cy - y));
|
|
if (rad >= minRadius && rad <= maxRadius)
|
|
{
|
|
const int r = __float2int_rn(rad - minRadius);
|
|
|
|
Emulation::smem::atomicAdd(&smem[r + 1], 1);
|
|
}
|
|
}
|
|
|
|
__syncthreads();
|
|
|
|
for (int i = threadIdx.x; i < histSize; i += blockDim.x)
|
|
{
|
|
const int curVotes = smem[i + 1];
|
|
|
|
if (curVotes >= threshold && curVotes > smem[i] && curVotes >= smem[i + 2])
|
|
{
|
|
const int ind = ::atomicAdd(&g_counter, 1);
|
|
if (ind < maxCircles)
|
|
circles[ind] = make_float3(cx, cy, i + minRadius);
|
|
}
|
|
}
|
|
}
|
|
|
|
int circlesAccumRadius_gpu(const unsigned int* centers, int centersCount, const unsigned int* list, int count,
|
|
float3* circles, int maxCircles, float dp, int minRadius, int maxRadius, int threshold, bool has20)
|
|
{
|
|
void* counterPtr;
|
|
cudaSafeCall( cudaGetSymbolAddress(&counterPtr, g_counter) );
|
|
|
|
cudaSafeCall( cudaMemset(counterPtr, 0, sizeof(int)) );
|
|
|
|
const dim3 block(has20 ? 1024 : 512);
|
|
const dim3 grid(centersCount);
|
|
|
|
const int histSize = maxRadius - minRadius + 1;
|
|
size_t smemSize = (histSize + 2) * sizeof(int);
|
|
|
|
circlesAccumRadius<<<grid, block, smemSize>>>(centers, list, count, circles, maxCircles, dp, minRadius, maxRadius, histSize, threshold);
|
|
cudaSafeCall( cudaGetLastError() );
|
|
|
|
cudaSafeCall( cudaDeviceSynchronize() );
|
|
|
|
int totalCount;
|
|
cudaSafeCall( cudaMemcpy(&totalCount, counterPtr, sizeof(int), cudaMemcpyDeviceToHost) );
|
|
|
|
totalCount = ::min(totalCount, maxCircles);
|
|
|
|
return totalCount;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////////
|
|
// Generalized Hough
|
|
|
|
template <typename T, int PIXELS_PER_THREAD>
|
|
__global__ void buildEdgePointList(const PtrStepSzb edges, const PtrStep<T> dx, const PtrStep<T> dy, unsigned int* coordList, float* thetaList)
|
|
{
|
|
__shared__ unsigned int s_coordLists[4][32 * PIXELS_PER_THREAD];
|
|
__shared__ float s_thetaLists[4][32 * PIXELS_PER_THREAD];
|
|
__shared__ int s_sizes[4];
|
|
__shared__ int s_globStart[4];
|
|
|
|
const int x = blockIdx.x * blockDim.x * PIXELS_PER_THREAD + threadIdx.x;
|
|
const int y = blockIdx.y * blockDim.y + threadIdx.y;
|
|
|
|
if (threadIdx.x == 0)
|
|
s_sizes[threadIdx.y] = 0;
|
|
__syncthreads();
|
|
|
|
if (y < edges.rows)
|
|
{
|
|
// fill the queue
|
|
const uchar* edgesRow = edges.ptr(y);
|
|
const T* dxRow = dx.ptr(y);
|
|
const T* dyRow = dy.ptr(y);
|
|
|
|
for (int i = 0, xx = x; i < PIXELS_PER_THREAD && xx < edges.cols; ++i, xx += blockDim.x)
|
|
{
|
|
const T dxVal = dxRow[xx];
|
|
const T dyVal = dyRow[xx];
|
|
|
|
if (edgesRow[xx] && (dxVal != 0 || dyVal != 0))
|
|
{
|
|
const unsigned int coord = (y << 16) | xx;
|
|
|
|
float theta = ::atan2f(dyVal, dxVal);
|
|
if (theta < 0)
|
|
theta += 2.0f * CV_PI_F;
|
|
|
|
const int qidx = Emulation::smem::atomicAdd(&s_sizes[threadIdx.y], 1);
|
|
|
|
s_coordLists[threadIdx.y][qidx] = coord;
|
|
s_thetaLists[threadIdx.y][qidx] = theta;
|
|
}
|
|
}
|
|
}
|
|
|
|
__syncthreads();
|
|
|
|
// let one thread reserve the space required in the global list
|
|
if (threadIdx.x == 0 && threadIdx.y == 0)
|
|
{
|
|
// find how many items are stored in each list
|
|
int totalSize = 0;
|
|
for (int i = 0; i < blockDim.y; ++i)
|
|
{
|
|
s_globStart[i] = totalSize;
|
|
totalSize += s_sizes[i];
|
|
}
|
|
|
|
// calculate the offset in the global list
|
|
const int globalOffset = atomicAdd(&g_counter, totalSize);
|
|
for (int i = 0; i < blockDim.y; ++i)
|
|
s_globStart[i] += globalOffset;
|
|
}
|
|
|
|
__syncthreads();
|
|
|
|
// copy local queues to global queue
|
|
const int qsize = s_sizes[threadIdx.y];
|
|
int gidx = s_globStart[threadIdx.y] + threadIdx.x;
|
|
for(int i = threadIdx.x; i < qsize; i += blockDim.x, gidx += blockDim.x)
|
|
{
|
|
coordList[gidx] = s_coordLists[threadIdx.y][i];
|
|
thetaList[gidx] = s_thetaLists[threadIdx.y][i];
|
|
}
|
|
}
|
|
|
|
template <typename T>
|
|
int buildEdgePointList_gpu(PtrStepSzb edges, PtrStepSzb dx, PtrStepSzb dy, unsigned int* coordList, float* thetaList)
|
|
{
|
|
const int PIXELS_PER_THREAD = 8;
|
|
|
|
void* counterPtr;
|
|
cudaSafeCall( cudaGetSymbolAddress(&counterPtr, g_counter) );
|
|
|
|
cudaSafeCall( cudaMemset(counterPtr, 0, sizeof(int)) );
|
|
|
|
const dim3 block(32, 4);
|
|
const dim3 grid(divUp(edges.cols, block.x * PIXELS_PER_THREAD), divUp(edges.rows, block.y));
|
|
|
|
cudaSafeCall( cudaFuncSetCacheConfig(buildEdgePointList<T, PIXELS_PER_THREAD>, cudaFuncCachePreferShared) );
|
|
|
|
buildEdgePointList<T, PIXELS_PER_THREAD><<<grid, block>>>(edges, (PtrStepSz<T>) dx, (PtrStepSz<T>) dy, coordList, thetaList);
|
|
cudaSafeCall( cudaGetLastError() );
|
|
|
|
cudaSafeCall( cudaDeviceSynchronize() );
|
|
|
|
int totalCount;
|
|
cudaSafeCall( cudaMemcpy(&totalCount, counterPtr, sizeof(int), cudaMemcpyDeviceToHost) );
|
|
|
|
return totalCount;
|
|
}
|
|
|
|
template int buildEdgePointList_gpu<short>(PtrStepSzb edges, PtrStepSzb dx, PtrStepSzb dy, unsigned int* coordList, float* thetaList);
|
|
template int buildEdgePointList_gpu<int>(PtrStepSzb edges, PtrStepSzb dx, PtrStepSzb dy, unsigned int* coordList, float* thetaList);
|
|
template int buildEdgePointList_gpu<float>(PtrStepSzb edges, PtrStepSzb dx, PtrStepSzb dy, unsigned int* coordList, float* thetaList);
|
|
|
|
__global__ void buildRTable(const unsigned int* coordList, const float* thetaList, const int pointsCount,
|
|
PtrStep<short2> r_table, int* r_sizes, int maxSize,
|
|
const short2 templCenter, const float thetaScale)
|
|
{
|
|
const int tid = blockIdx.x * blockDim.x + threadIdx.x;
|
|
|
|
if (tid >= pointsCount)
|
|
return;
|
|
|
|
const unsigned int coord = coordList[tid];
|
|
short2 p;
|
|
p.x = (coord & 0xFFFF);
|
|
p.y = (coord >> 16) & 0xFFFF;
|
|
|
|
const float theta = thetaList[tid];
|
|
const int n = __float2int_rn(theta * thetaScale);
|
|
|
|
const int ind = ::atomicAdd(r_sizes + n, 1);
|
|
if (ind < maxSize)
|
|
r_table(n, ind) = p - templCenter;
|
|
}
|
|
|
|
void buildRTable_gpu(const unsigned int* coordList, const float* thetaList, int pointsCount,
|
|
PtrStepSz<short2> r_table, int* r_sizes,
|
|
short2 templCenter, int levels)
|
|
{
|
|
const dim3 block(256);
|
|
const dim3 grid(divUp(pointsCount, block.x));
|
|
|
|
const float thetaScale = levels / (2.0f * CV_PI_F);
|
|
|
|
buildRTable<<<grid, block>>>(coordList, thetaList, pointsCount, r_table, r_sizes, r_table.cols, templCenter, thetaScale);
|
|
cudaSafeCall( cudaGetLastError() );
|
|
|
|
cudaSafeCall( cudaDeviceSynchronize() );
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////////
|
|
// GHT_Ballard_Pos
|
|
|
|
__global__ void GHT_Ballard_Pos_calcHist(const unsigned int* coordList, const float* thetaList, const int pointsCount,
|
|
const PtrStep<short2> r_table, const int* r_sizes,
|
|
PtrStepSzi hist,
|
|
const float idp, const float thetaScale)
|
|
{
|
|
const int tid = blockIdx.x * blockDim.x + threadIdx.x;
|
|
|
|
if (tid >= pointsCount)
|
|
return;
|
|
|
|
const unsigned int coord = coordList[tid];
|
|
short2 p;
|
|
p.x = (coord & 0xFFFF);
|
|
p.y = (coord >> 16) & 0xFFFF;
|
|
|
|
const float theta = thetaList[tid];
|
|
const int n = __float2int_rn(theta * thetaScale);
|
|
|
|
const short2* r_row = r_table.ptr(n);
|
|
const int r_row_size = r_sizes[n];
|
|
|
|
for (int j = 0; j < r_row_size; ++j)
|
|
{
|
|
short2 c = p - r_row[j];
|
|
|
|
c.x = __float2int_rn(c.x * idp);
|
|
c.y = __float2int_rn(c.y * idp);
|
|
|
|
if (c.x >= 0 && c.x < hist.cols - 2 && c.y >= 0 && c.y < hist.rows - 2)
|
|
::atomicAdd(hist.ptr(c.y + 1) + c.x + 1, 1);
|
|
}
|
|
}
|
|
|
|
void GHT_Ballard_Pos_calcHist_gpu(const unsigned int* coordList, const float* thetaList, int pointsCount,
|
|
PtrStepSz<short2> r_table, const int* r_sizes,
|
|
PtrStepSzi hist,
|
|
float dp, int levels)
|
|
{
|
|
const dim3 block(256);
|
|
const dim3 grid(divUp(pointsCount, block.x));
|
|
|
|
const float idp = 1.0f / dp;
|
|
const float thetaScale = levels / (2.0f * CV_PI_F);
|
|
|
|
GHT_Ballard_Pos_calcHist<<<grid, block>>>(coordList, thetaList, pointsCount, r_table, r_sizes, hist, idp, thetaScale);
|
|
cudaSafeCall( cudaGetLastError() );
|
|
|
|
cudaSafeCall( cudaDeviceSynchronize() );
|
|
}
|
|
|
|
__global__ void GHT_Ballard_Pos_findPosInHist(const PtrStepSzi hist, float4* out, int3* votes, const int maxSize, const float dp, const int threshold)
|
|
{
|
|
const int x = blockIdx.x * blockDim.x + threadIdx.x;
|
|
const int y = blockIdx.y * blockDim.y + threadIdx.y;
|
|
|
|
if (x >= hist.cols - 2 || y >= hist.rows - 2)
|
|
return;
|
|
|
|
const int curVotes = hist(y + 1, x + 1);
|
|
|
|
if (curVotes > threshold &&
|
|
curVotes > hist(y + 1, x) &&
|
|
curVotes >= hist(y + 1, x + 2) &&
|
|
curVotes > hist(y, x + 1) &&
|
|
curVotes >= hist(y + 2, x + 1))
|
|
{
|
|
const int ind = ::atomicAdd(&g_counter, 1);
|
|
|
|
if (ind < maxSize)
|
|
{
|
|
out[ind] = make_float4(x * dp, y * dp, 1.0f, 0.0f);
|
|
votes[ind] = make_int3(curVotes, 0, 0);
|
|
}
|
|
}
|
|
}
|
|
|
|
int GHT_Ballard_Pos_findPosInHist_gpu(PtrStepSzi hist, float4* out, int3* votes, int maxSize, float dp, int threshold)
|
|
{
|
|
void* counterPtr;
|
|
cudaSafeCall( cudaGetSymbolAddress(&counterPtr, g_counter) );
|
|
|
|
cudaSafeCall( cudaMemset(counterPtr, 0, sizeof(int)) );
|
|
|
|
const dim3 block(32, 8);
|
|
const dim3 grid(divUp(hist.cols - 2, block.x), divUp(hist.rows - 2, block.y));
|
|
|
|
cudaSafeCall( cudaFuncSetCacheConfig(GHT_Ballard_Pos_findPosInHist, cudaFuncCachePreferL1) );
|
|
|
|
GHT_Ballard_Pos_findPosInHist<<<grid, block>>>(hist, out, votes, maxSize, dp, threshold);
|
|
cudaSafeCall( cudaGetLastError() );
|
|
|
|
cudaSafeCall( cudaDeviceSynchronize() );
|
|
|
|
int totalCount;
|
|
cudaSafeCall( cudaMemcpy(&totalCount, counterPtr, sizeof(int), cudaMemcpyDeviceToHost) );
|
|
|
|
totalCount = ::min(totalCount, maxSize);
|
|
|
|
return totalCount;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////////
|
|
// GHT_Ballard_PosScale
|
|
|
|
__global__ void GHT_Ballard_PosScale_calcHist(const unsigned int* coordList, const float* thetaList,
|
|
PtrStep<short2> r_table, const int* r_sizes,
|
|
PtrStepi hist, const int rows, const int cols,
|
|
const float minScale, const float scaleStep, const int scaleRange,
|
|
const float idp, const float thetaScale)
|
|
{
|
|
const unsigned int coord = coordList[blockIdx.x];
|
|
float2 p;
|
|
p.x = (coord & 0xFFFF);
|
|
p.y = (coord >> 16) & 0xFFFF;
|
|
|
|
const float theta = thetaList[blockIdx.x];
|
|
const int n = __float2int_rn(theta * thetaScale);
|
|
|
|
const short2* r_row = r_table.ptr(n);
|
|
const int r_row_size = r_sizes[n];
|
|
|
|
for (int j = 0; j < r_row_size; ++j)
|
|
{
|
|
const float2 d = saturate_cast<float2>(r_row[j]);
|
|
|
|
for (int s = threadIdx.x; s < scaleRange; s += blockDim.x)
|
|
{
|
|
const float scale = minScale + s * scaleStep;
|
|
|
|
float2 c = p - scale * d;
|
|
|
|
c.x *= idp;
|
|
c.y *= idp;
|
|
|
|
if (c.x >= 0 && c.x < cols && c.y >= 0 && c.y < rows)
|
|
::atomicAdd(hist.ptr((s + 1) * (rows + 2) + __float2int_rn(c.y + 1)) + __float2int_rn(c.x + 1), 1);
|
|
}
|
|
}
|
|
}
|
|
|
|
void GHT_Ballard_PosScale_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 minScale, float scaleStep, int scaleRange,
|
|
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_PosScale_calcHist<<<grid, block>>>(coordList, thetaList,
|
|
r_table, r_sizes,
|
|
hist, rows, cols,
|
|
minScale, scaleStep, scaleRange,
|
|
idp, thetaScale);
|
|
cudaSafeCall( cudaGetLastError() );
|
|
|
|
cudaSafeCall( cudaDeviceSynchronize() );
|
|
}
|
|
|
|
__global__ void GHT_Ballard_PosScale_findPosInHist(const PtrStepi hist, const int rows, const int cols, const int scaleRange,
|
|
float4* out, int3* votes, const int maxSize,
|
|
const float minScale, const float scaleStep, 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 s = 0; s < scaleRange; ++s)
|
|
{
|
|
const float scale = minScale + s * scaleStep;
|
|
|
|
const int prevScaleIdx = (s) * (rows + 2);
|
|
const int curScaleIdx = (s + 1) * (rows + 2);
|
|
const int nextScaleIdx = (s + 2) * (rows + 2);
|
|
|
|
const int curVotes = hist(curScaleIdx + y + 1, x + 1);
|
|
|
|
if (curVotes > threshold &&
|
|
curVotes > hist(curScaleIdx + y + 1, x) &&
|
|
curVotes >= hist(curScaleIdx + y + 1, x + 2) &&
|
|
curVotes > hist(curScaleIdx + y, x + 1) &&
|
|
curVotes >= hist(curScaleIdx + y + 2, x + 1) &&
|
|
curVotes > hist(prevScaleIdx + y + 1, x + 1) &&
|
|
curVotes >= hist(nextScaleIdx + y + 1, x + 1))
|
|
{
|
|
const int ind = ::atomicAdd(&g_counter, 1);
|
|
|
|
if (ind < maxSize)
|
|
{
|
|
out[ind] = make_float4(x * dp, y * dp, scale, 0.0f);
|
|
votes[ind] = make_int3(curVotes, curVotes, 0);
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
int GHT_Ballard_PosScale_findPosInHist_gpu(PtrStepi hist, int rows, int cols, int scaleRange, float4* out, int3* votes, int maxSize,
|
|
float minScale, float scaleStep, 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_PosScale_findPosInHist, cudaFuncCachePreferL1) );
|
|
|
|
GHT_Ballard_PosScale_findPosInHist<<<grid, block>>>(hist, rows, cols, scaleRange, out, votes, maxSize, minScale, scaleStep, dp, threshold);
|
|
cudaSafeCall( cudaGetLastError() );
|
|
|
|
cudaSafeCall( cudaDeviceSynchronize() );
|
|
|
|
int totalCount;
|
|
cudaSafeCall( cudaMemcpy(&totalCount, counterPtr, sizeof(int), cudaMemcpyDeviceToHost) );
|
|
|
|
totalCount = ::min(totalCount, maxSize);
|
|
|
|
return totalCount;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////////
|
|
// GHT_Ballard_PosRotation
|
|
|
|
__global__ void GHT_Ballard_PosRotation_calcHist(const unsigned int* coordList, const float* thetaList,
|
|
PtrStep<short2> r_table, const int* r_sizes,
|
|
PtrStepi hist, const int rows, const int cols,
|
|
const float minAngle, const float angleStep, const int angleRange,
|
|
const float idp, const float thetaScale)
|
|
{
|
|
const unsigned int coord = coordList[blockIdx.x];
|
|
float2 p;
|
|
p.x = (coord & 0xFFFF);
|
|
p.y = (coord >> 16) & 0xFFFF;
|
|
|
|
const float thetaVal = thetaList[blockIdx.x];
|
|
|
|
for (int a = threadIdx.x; a < angleRange; a += blockDim.x)
|
|
{
|
|
const float angle = (minAngle + a * angleStep) * (CV_PI_F / 180.0f);
|
|
float sinA, cosA;
|
|
sincosf(angle, &sinA, &cosA);
|
|
|
|
float theta = thetaVal - angle;
|
|
if (theta < 0)
|
|
theta += 2.0f * CV_PI_F;
|
|
|
|
const int n = __float2int_rn(theta * thetaScale);
|
|
|
|
const short2* r_row = r_table.ptr(n);
|
|
const int r_row_size = r_sizes[n];
|
|
|
|
for (int j = 0; j < r_row_size; ++j)
|
|
{
|
|
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 */
|