gpu::calcOpticalFlowBM
This commit is contained in:
Vladislav Vinogradov
170
modules/gpu/src/cuda/optflowbm.cu
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170
modules/gpu/src/cuda/optflowbm.cu
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/*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 "opencv2/gpu/device/common.hpp"
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#include "opencv2/gpu/device/limits.hpp"
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using namespace cv::gpu;
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using namespace cv::gpu::device;
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namespace
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{
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texture<uchar, cudaTextureType2D, cudaReadModeElementType> tex_prev(false, cudaFilterModePoint, cudaAddressModeClamp);
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texture<uchar, cudaTextureType2D, cudaReadModeElementType> tex_curr(false, cudaFilterModePoint, cudaAddressModeClamp);
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__device__ int cmpBlocks(int X1, int Y1, int X2, int Y2, int2 blockSize)
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{
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int s = 0;
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for (int y = 0; y < blockSize.y; ++y)
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{
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for (int x = 0; x < blockSize.x; ++x)
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s += ::abs(tex2D(tex_prev, X1 + x, Y1 + y) - tex2D(tex_curr, X2 + x, Y2 + y));
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}
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return s;
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}
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__global__ void calcOptFlowBM(PtrStepSzf velx, PtrStepf vely, const int2 blockSize, const int2 shiftSize, const bool usePrevious,
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const int maxX, const int maxY, const int acceptLevel, const int escapeLevel,
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const short2* ss, const int ssCount)
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{
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const int j = blockIdx.x * blockDim.x + threadIdx.x;
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const int i = blockIdx.y * blockDim.y + threadIdx.y;
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if (i >= velx.rows || j >= velx.cols)
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return;
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const int X1 = j * shiftSize.x;
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const int Y1 = i * shiftSize.y;
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const int offX = usePrevious ? __float2int_rn(velx(i, j)) : 0;
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const int offY = usePrevious ? __float2int_rn(vely(i, j)) : 0;
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int X2 = X1 + offX;
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int Y2 = Y1 + offY;
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int dist = numeric_limits<int>::max();
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if (0 <= X2 && X2 <= maxX && 0 <= Y2 && Y2 <= maxY)
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dist = cmpBlocks(X1, Y1, X2, Y2, blockSize);
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int countMin = 1;
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int sumx = offX;
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int sumy = offY;
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if (dist > acceptLevel)
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{
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// do brute-force search
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for (int k = 0; k < ssCount; ++k)
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{
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const short2 ssVal = ss[k];
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const int dx = offX + ssVal.x;
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const int dy = offY + ssVal.y;
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X2 = X1 + dx;
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Y2 = Y1 + dy;
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if (0 <= X2 && X2 <= maxX && 0 <= Y2 && Y2 <= maxY)
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{
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const int tmpDist = cmpBlocks(X1, Y1, X2, Y2, blockSize);
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if (tmpDist < acceptLevel)
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{
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sumx = dx;
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sumy = dy;
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countMin = 1;
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break;
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}
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if (tmpDist < dist)
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{
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dist = tmpDist;
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sumx = dx;
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sumy = dy;
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countMin = 1;
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}
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else if (tmpDist == dist)
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{
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sumx += dx;
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sumy += dy;
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countMin++;
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}
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}
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}
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if (dist > escapeLevel)
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{
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sumx = offX;
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sumy = offY;
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countMin = 1;
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}
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}
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velx(i, j) = static_cast<float>(sumx) / countMin;
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vely(i, j) = static_cast<float>(sumy) / countMin;
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}
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}
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namespace optflowbm
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{
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void calc(PtrStepSzb prev, PtrStepSzb curr, PtrStepSzf velx, PtrStepSzf vely, int2 blockSize, int2 shiftSize, bool usePrevious,
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int maxX, int maxY, int acceptLevel, int escapeLevel, const short2* ss, int ssCount, cudaStream_t stream)
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{
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bindTexture(&tex_prev, prev);
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bindTexture(&tex_curr, curr);
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const dim3 block(32, 8);
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const dim3 grid(divUp(velx.cols, block.x), divUp(vely.rows, block.y));
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calcOptFlowBM<<<grid, block, 0, stream>>>(velx, vely, blockSize, shiftSize, usePrevious,
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maxX, maxY, acceptLevel, escapeLevel, ss, ssCount);
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cudaSafeCall( cudaGetLastError() );
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if (stream == 0)
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cudaSafeCall( cudaDeviceSynchronize() );
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}
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}
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#endif // !defined CUDA_DISABLER
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205
modules/gpu/src/optflowbm.cpp
Normal file
205
modules/gpu/src/optflowbm.cpp
Normal file
@@ -0,0 +1,205 @@
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/*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.
|
||||
//
|
||||
//
|
||||
// License Agreement
|
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// For Open Source Computer Vision Library
|
||||
//
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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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// * Redistribution's of source code must retain the above copyright notice,
|
||||
// this list of conditions and the following disclaimer.
|
||||
//
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||||
// * Redistribution's in binary form must reproduce the above copyright notice,
|
||||
// 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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// * 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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// This software is provided by the copyright holders and contributors "as is" and
|
||||
// any express or implied warranties, including, but not limited to, the implied
|
||||
// warranties of merchantability and fitness for a particular purpose are disclaimed.
|
||||
// In no event shall the Intel Corporation or contributors be liable for any direct,
|
||||
// indirect, incidental, special, exemplary, or consequential damages
|
||||
// (including, but not limited to, procurement of substitute goods or services;
|
||||
// loss of use, data, or profits; or business interruption) however caused
|
||||
// and on any theory of liability, whether in contract, strict liability,
|
||||
// or tort (including negligence or otherwise) arising in any way out of
|
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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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#include "precomp.hpp"
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using namespace std;
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using namespace cv;
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using namespace cv::gpu;
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#if !defined HAVE_CUDA || defined(CUDA_DISABLER)
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void cv::gpu::calcOpticalFlowBM(const GpuMat&, const GpuMat&, Size, Size, Size, bool, GpuMat&, GpuMat&, GpuMat&, Stream&) { throw_nogpu(); }
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#else // HAVE_CUDA
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namespace optflowbm
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{
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void calc(PtrStepSzb prev, PtrStepSzb curr, PtrStepSzf velx, PtrStepSzf vely, int2 blockSize, int2 shiftSize, bool usePrevious,
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int maxX, int maxY, int acceptLevel, int escapeLevel, const short2* ss, int ssCount, cudaStream_t stream);
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}
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void cv::gpu::calcOpticalFlowBM(const GpuMat& prev, const GpuMat& curr, Size blockSize, Size shiftSize, Size maxRange, bool usePrevious, GpuMat& velx, GpuMat& vely, GpuMat& buf, Stream& st)
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{
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CV_Assert( prev.type() == CV_8UC1 );
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CV_Assert( curr.size() == prev.size() && curr.type() == prev.type() );
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const Size velSize((prev.cols - blockSize.width + shiftSize.width) / shiftSize.width,
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(prev.rows - blockSize.height + shiftSize.height) / shiftSize.height);
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velx.create(velSize, CV_32FC1);
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vely.create(velSize, CV_32FC1);
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// scanning scheme coordinates
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vector<short2> ss((2 * maxRange.width + 1) * (2 * maxRange.height + 1));
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int ssCount = 0;
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// Calculate scanning scheme
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const int minCount = std::min(maxRange.width, maxRange.height);
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// use spiral search pattern
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//
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// 9 10 11 12
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// 8 1 2 13
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// 7 * 3 14
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// 6 5 4 15
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//... 20 19 18 17
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//
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for (int i = 0; i < minCount; ++i)
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{
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// four cycles along sides
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int x = -i - 1, y = x;
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// upper side
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for (int j = -i; j <= i + 1; ++j, ++ssCount)
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{
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ss[ssCount].x = ++x;
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ss[ssCount].y = y;
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}
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// right side
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for (int j = -i; j <= i + 1; ++j, ++ssCount)
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{
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ss[ssCount].x = x;
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ss[ssCount].y = ++y;
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}
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// bottom side
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for (int j = -i; j <= i + 1; ++j, ++ssCount)
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{
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ss[ssCount].x = --x;
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ss[ssCount].y = y;
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}
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// left side
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for (int j = -i; j <= i + 1; ++j, ++ssCount)
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{
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ss[ssCount].x = x;
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ss[ssCount].y = --y;
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}
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}
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// the rest part
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if (maxRange.width < maxRange.height)
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{
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const int xleft = -minCount;
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// cycle by neighbor rings
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for (int i = minCount; i < maxRange.height; ++i)
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{
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// two cycles by x
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int y = -(i + 1);
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int x = xleft;
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// upper side
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for (int j = -maxRange.width; j <= maxRange.width; ++j, ++ssCount, ++x)
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{
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ss[ssCount].x = x;
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ss[ssCount].y = y;
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}
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x = xleft;
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y = -y;
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// bottom side
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for (int j = -maxRange.width; j <= maxRange.width; ++j, ++ssCount, ++x)
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{
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ss[ssCount].x = x;
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ss[ssCount].y = y;
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}
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}
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}
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else if (maxRange.width > maxRange.height)
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{
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const int yupper = -minCount;
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// cycle by neighbor rings
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for (int i = minCount; i < maxRange.width; ++i)
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{
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// two cycles by y
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int x = -(i + 1);
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int y = yupper;
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// left side
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for (int j = -maxRange.height; j <= maxRange.height; ++j, ++ssCount, ++y)
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{
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ss[ssCount].x = x;
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ss[ssCount].y = y;
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}
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y = yupper;
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x = -x;
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// right side
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for (int j = -maxRange.height; j <= maxRange.height; ++j, ++ssCount, ++y)
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{
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ss[ssCount].x = x;
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ss[ssCount].y = y;
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}
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}
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}
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const cudaStream_t stream = StreamAccessor::getStream(st);
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ensureSizeIsEnough(1, ssCount, CV_16SC2, buf);
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if (stream == 0)
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cudaSafeCall( cudaMemcpy(buf.data, &ss[0], ssCount * sizeof(short2), cudaMemcpyHostToDevice) );
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else
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cudaSafeCall( cudaMemcpyAsync(buf.data, &ss[0], ssCount * sizeof(short2), cudaMemcpyHostToDevice, stream) );
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const int maxX = prev.cols - blockSize.width;
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const int maxY = prev.rows - blockSize.height;
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const int SMALL_DIFF = 2;
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const int BIG_DIFF = 128;
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const int blSize = blockSize.area();
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const int acceptLevel = blSize * SMALL_DIFF;
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const int escapeLevel = blSize * BIG_DIFF;
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optflowbm::calc(prev, curr, velx, vely,
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make_int2(blockSize.width, blockSize.height), make_int2(shiftSize.width, shiftSize.height), usePrevious,
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maxX, maxY, acceptLevel, escapeLevel, buf.ptr<short2>(), ssCount, stream);
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}
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#endif // HAVE_CUDA
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