opencv/modules/gpu/src/cuda/hough.cu

299 lines
11 KiB
Plaintext
Raw Normal View History

2012-08-13 21:44:23 +08:00
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or bpied warranties, including, but not limited to, the bpied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#include <thrust/sort.h>
#include "opencv2/gpu/device/common.hpp"
2012-08-14 21:00:57 +08:00
#include "opencv2/gpu/device/emulation.hpp"
2012-08-13 21:44:23 +08:00
namespace cv { namespace gpu { namespace device
{
namespace hough
{
2012-08-15 17:18:35 +08:00
__device__ int g_counter;
////////////////////////////////////////////////////////////////////////
// buildPointList
2012-08-14 21:00:57 +08:00
const int PIXELS_PER_THREAD = 16;
__global__ void buildPointList(const DevMem2Db src, unsigned int* list)
2012-08-13 21:44:23 +08:00
{
2012-08-15 17:18:35 +08:00
__shared__ int s_queues[4][32 * PIXELS_PER_THREAD];
__shared__ int s_qsize[4];
__shared__ int s_globStart[4];
2012-08-14 21:42:15 +08:00
const int x = blockIdx.x * blockDim.x * PIXELS_PER_THREAD + threadIdx.x;
const int y = blockIdx.y * blockDim.y + threadIdx.y;
2012-08-13 21:44:23 +08:00
2012-08-14 21:00:57 +08:00
if (y >= src.rows)
2012-08-13 21:44:23 +08:00
return;
2012-08-14 21:42:15 +08:00
if (threadIdx.x == 0)
s_qsize[threadIdx.y] = 0;
2012-08-14 21:00:57 +08:00
2012-08-14 21:42:15 +08:00
__syncthreads();
2012-08-14 21:00:57 +08:00
// fill the queue
const uchar* srcRow = src.ptr(y);
2012-08-14 21:42:15 +08:00
for (int i = 0, xx = x; i < PIXELS_PER_THREAD && xx < src.cols; ++i, xx += blockDim.x)
2012-08-13 21:44:23 +08:00
{
if (srcRow[xx])
2012-08-13 21:44:23 +08:00
{
2012-08-14 21:42:15 +08:00
const unsigned int val = (y << 16) | xx;
2012-08-15 17:18:35 +08:00
const int qidx = Emulation::smem::atomicAdd(&s_qsize[threadIdx.y], 1);
2012-08-14 21:42:15 +08:00
s_queues[threadIdx.y][qidx] = val;
2012-08-14 21:00:57 +08:00
}
}
2012-08-13 21:44:23 +08:00
2012-08-14 21:00:57 +08:00
__syncthreads();
2012-08-13 21:44:23 +08:00
2012-08-14 21:00:57 +08:00
// 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;
2012-08-14 21:42:15 +08:00
for (int i = 0; i < blockDim.y; ++i)
2012-08-14 21:00:57 +08:00
{
s_globStart[i] = totalSize;
totalSize += s_qsize[i];
2012-08-13 21:44:23 +08:00
}
2012-08-14 21:00:57 +08:00
2012-08-15 17:18:35 +08:00
// calculate the offset in the global list
const int globalOffset = atomicAdd(&g_counter, totalSize);
2012-08-14 21:42:15 +08:00
for (int i = 0; i < blockDim.y; ++i)
s_globStart[i] += globalOffset;
2012-08-14 21:00:57 +08:00
}
__syncthreads();
// copy local queues to global queue
2012-08-15 17:18:35 +08:00
const int qsize = s_qsize[threadIdx.y];
int gidx = s_globStart[threadIdx.y] + threadIdx.x;
for(int i = threadIdx.x; i < qsize; i += blockDim.x, gidx += blockDim.x)
list[gidx] = s_queues[threadIdx.y][i];
2012-08-13 21:44:23 +08:00
}
2012-08-15 17:18:35 +08:00
int buildPointList_gpu(DevMem2Db src, unsigned int* list)
2012-08-13 21:44:23 +08:00
{
void* counterPtr;
cudaSafeCall( cudaGetSymbolAddress(&counterPtr, g_counter) );
2012-08-14 21:00:57 +08:00
cudaSafeCall( cudaMemset(counterPtr, 0, sizeof(int)) );
2012-08-14 21:00:57 +08:00
const dim3 block(32, 4);
const dim3 grid(divUp(src.cols, block.x * PIXELS_PER_THREAD), divUp(src.rows, block.y));
cudaSafeCall( cudaFuncSetCacheConfig(buildPointList, cudaFuncCachePreferShared) );
2012-08-13 21:44:23 +08:00
2012-08-14 21:00:57 +08:00
buildPointList<<<grid, block>>>(src, list);
2012-08-13 21:44:23 +08:00
cudaSafeCall( cudaGetLastError() );
cudaSafeCall( cudaDeviceSynchronize() );
2012-08-14 21:00:57 +08:00
int totalCount;
cudaSafeCall( cudaMemcpy(&totalCount, counterPtr, sizeof(int), cudaMemcpyDeviceToHost) );
2012-08-14 21:00:57 +08:00
return totalCount;
2012-08-13 21:44:23 +08:00
}
2012-08-15 17:18:35 +08:00
////////////////////////////////////////////////////////////////////////
// linesAccum
__global__ void linesAccumGlobal(const unsigned int* list, const int count, PtrStepi accum, const float irho, const float theta, const int numrho)
2012-08-14 21:00:57 +08:00
{
2012-08-15 17:18:35 +08:00
const int n = blockIdx.x;
const float ang = n * theta;
2012-08-14 21:00:57 +08:00
float sinVal;
float cosVal;
sincosf(ang, &sinVal, &cosVal);
sinVal *= irho;
cosVal *= irho;
2012-08-15 17:18:35 +08:00
const int shift = (numrho - 1) / 2;
2012-08-15 17:18:35 +08:00
int* accumRow = accum.ptr(n + 1);
2012-08-15 17:18:35 +08:00
for (int i = threadIdx.x; i < count; i += blockDim.x)
{
const unsigned int val = list[i];
2012-08-15 17:18:35 +08:00
const int x = (val & 0xFFFF);
const int y = (val >> 16) & 0xFFFF;
2012-08-15 17:18:35 +08:00
int r = __float2int_rn(x * cosVal + y * sinVal);
r += shift;
2012-08-15 17:18:35 +08:00
::atomicAdd(accumRow + r + 1, 1);
2012-08-15 17:18:35 +08:00
}
}
__global__ void linesAccumShared(const unsigned int* list, const int count, PtrStepi accum, const float irho, const float theta, const int numrho)
{
extern __shared__ int smem[];
for (int i = threadIdx.x; i < numrho + 1; i += blockDim.x)
2012-08-14 21:00:57 +08:00
smem[i] = 0;
2012-08-15 17:18:35 +08:00
2012-08-14 21:00:57 +08:00
__syncthreads();
const int n = blockIdx.x;
const float ang = n * theta;
float sinVal;
float cosVal;
sincosf(ang, &sinVal, &cosVal);
sinVal *= irho;
cosVal *= irho;
2012-08-14 21:00:57 +08:00
const int shift = (numrho - 1) / 2;
2012-08-14 21:00:57 +08:00
for (int i = threadIdx.x; i < count; i += blockDim.x)
{
const unsigned int val = list[i];
2012-08-15 17:18:35 +08:00
const int x = (val & 0xFFFF);
const int y = (val >> 16) & 0xFFFF;
2012-08-14 21:00:57 +08:00
int r = __float2int_rn(x * cosVal + y * sinVal);
r += shift;
2012-08-14 21:00:57 +08:00
2012-08-15 17:18:35 +08:00
Emulation::smem::atomicAdd(&smem[r + 1], 1);
2012-08-14 21:00:57 +08:00
}
2012-08-15 17:18:35 +08:00
2012-08-14 21:00:57 +08:00
__syncthreads();
int* accumRow = accum.ptr(n + 1);
for (int i = threadIdx.x; i < numrho + 1; i += blockDim.x)
accumRow[i] = smem[i];
2012-08-14 21:00:57 +08:00
}
2012-08-15 21:16:02 +08:00
void linesAccum_gpu(const unsigned int* list, int count, DevMem2Di accum, float rho, float theta, size_t sharedMemPerBlock, bool has20)
2012-08-14 21:00:57 +08:00
{
2012-08-15 21:16:02 +08:00
const dim3 block(has20 ? 1024 : 512);
2012-08-14 21:00:57 +08:00
const dim3 grid(accum.rows - 2);
2012-08-15 17:18:35 +08:00
cudaSafeCall( cudaFuncSetCacheConfig(linesAccumShared, cudaFuncCachePreferShared) );
size_t smemSize = (accum.cols - 1) * sizeof(int);
2012-08-14 21:00:57 +08:00
2012-08-15 17:18:35 +08:00
if (smemSize < sharedMemPerBlock - 1000)
linesAccumShared<<<grid, block, smemSize>>>(list, count, accum, 1.0f / rho, theta, accum.cols - 2);
else
linesAccumGlobal<<<grid, block>>>(list, count, accum, 1.0f / rho, theta, accum.cols - 2);
2012-08-14 21:00:57 +08:00
cudaSafeCall( cudaGetLastError() );
cudaSafeCall( cudaDeviceSynchronize() );
}
2012-08-13 21:44:23 +08:00
2012-08-15 17:18:35 +08:00
////////////////////////////////////////////////////////////////////////
// linesGetResult
__global__ void linesGetResult(const DevMem2Di accum, float2* out, int* votes, const int maxSize, const float rho, const float theta, const float threshold, const int numrho)
2012-08-13 21:44:23 +08:00
{
2012-08-15 17:18:35 +08:00
__shared__ int smem[8][32];
2012-08-13 21:44:23 +08:00
const int x = blockIdx.x * (blockDim.x - 2) + threadIdx.x;
const int y = blockIdx.y * (blockDim.y - 2) + threadIdx.y;
2012-08-13 21:44:23 +08:00
if (x >= accum.cols || y >= accum.rows)
2012-08-13 21:44:23 +08:00
return;
smem[threadIdx.y][threadIdx.x] = accum(y, x);
2012-08-13 21:44:23 +08:00
__syncthreads();
const int r = x - 1;
const int n = y - 1;
2012-08-13 21:44:23 +08:00
if (threadIdx.x == 0 || threadIdx.x == blockDim.x - 1 || threadIdx.y == 0 || threadIdx.y == blockDim.y - 1 || r >= accum.cols - 2 || n >= accum.rows - 2)
return;
if (smem[threadIdx.y][threadIdx.x] > threshold &&
smem[threadIdx.y][threadIdx.x] > smem[threadIdx.y - 1][threadIdx.x] &&
smem[threadIdx.y][threadIdx.x] >= smem[threadIdx.y + 1][threadIdx.x] &&
smem[threadIdx.y][threadIdx.x] > smem[threadIdx.y][threadIdx.x - 1] &&
smem[threadIdx.y][threadIdx.x] >= smem[threadIdx.y][threadIdx.x + 1])
{
2012-08-15 17:18:35 +08:00
const float radius = (r - (numrho - 1) * 0.5f) * rho;
const float angle = n * theta;
2012-08-13 21:44:23 +08:00
2012-08-15 17:18:35 +08:00
const int ind = ::atomicAdd(&g_counter, 1);
2012-08-13 21:44:23 +08:00
if (ind < maxSize)
{
out[ind] = make_float2(radius, angle);
2012-08-15 19:05:18 +08:00
votes[ind] = smem[threadIdx.y][threadIdx.x];
2012-08-13 21:44:23 +08:00
}
}
}
2012-08-15 19:05:18 +08:00
int linesGetResult_gpu(DevMem2Di accum, float2* out, int* votes, int maxSize, float rho, float theta, float threshold, bool doSort)
2012-08-13 21:44:23 +08:00
{
void* counterPtr;
cudaSafeCall( cudaGetSymbolAddress(&counterPtr, g_counter) );
2012-08-13 21:44:23 +08:00
cudaSafeCall( cudaMemset(counterPtr, 0, sizeof(int)) );
2012-08-13 21:44:23 +08:00
const dim3 block(32, 8);
const dim3 grid(divUp(accum.cols, block.x - 2), divUp(accum.rows, block.y - 2));
linesGetResult<<<grid, block>>>(accum, out, votes, maxSize, rho, theta, threshold, accum.cols - 2);
2012-08-13 21:44:23 +08:00
cudaSafeCall( cudaGetLastError() );
cudaSafeCall( cudaDeviceSynchronize() );
int totalCount;
cudaSafeCall( cudaMemcpy(&totalCount, counterPtr, sizeof(int), cudaMemcpyDeviceToHost) );
2012-08-13 21:44:23 +08:00
totalCount = ::min(totalCount, maxSize);
if (doSort && totalCount > 0)
2012-08-13 21:44:23 +08:00
{
thrust::device_ptr<float2> outPtr(out);
thrust::device_ptr<int> votesPtr(votes);
thrust::sort_by_key(votesPtr, votesPtr + totalCount, outPtr, thrust::greater<int>());
2012-08-13 21:44:23 +08:00
}
return totalCount;
2012-08-13 21:44:23 +08:00
}
}
}}}