opencv/modules/gpu/src/pyrlk.cpp
Andrey Kamaev 2a6fb2867e Remove all using directives for STL namespace and members
Made all STL usages explicit to be able automatically find all usages of
particular class or function.
2013-02-25 15:04:17 +04:00

249 lines
8.3 KiB
C++

/*M///////////////////////////////////////////////////////////////////////////////////////
//
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//
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// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
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#include "precomp.hpp"
using namespace cv;
using namespace cv::gpu;
#if !defined (HAVE_CUDA) || defined (CUDA_DISABLER)
cv::gpu::PyrLKOpticalFlow::PyrLKOpticalFlow() { throw_nogpu(); }
void cv::gpu::PyrLKOpticalFlow::sparse(const GpuMat&, const GpuMat&, const GpuMat&, GpuMat&, GpuMat&, GpuMat*) { throw_nogpu(); }
void cv::gpu::PyrLKOpticalFlow::dense(const GpuMat&, const GpuMat&, GpuMat&, GpuMat&, GpuMat*) { throw_nogpu(); }
void cv::gpu::PyrLKOpticalFlow::releaseMemory() {}
#else /* !defined (HAVE_CUDA) */
namespace pyrlk
{
void loadConstants(int2 winSize, int iters);
void sparse1(PtrStepSzf I, PtrStepSzf J, const float2* prevPts, float2* nextPts, uchar* status, float* err, int ptcount,
int level, dim3 block, dim3 patch, cudaStream_t stream = 0);
void sparse4(PtrStepSz<float4> I, PtrStepSz<float4> J, const float2* prevPts, float2* nextPts, uchar* status, float* err, int ptcount,
int level, dim3 block, dim3 patch, cudaStream_t stream = 0);
void dense(PtrStepSzb I, PtrStepSzf J, PtrStepSzf u, PtrStepSzf v, PtrStepSzf prevU, PtrStepSzf prevV,
PtrStepSzf err, int2 winSize, cudaStream_t stream = 0);
}
cv::gpu::PyrLKOpticalFlow::PyrLKOpticalFlow()
{
winSize = Size(21, 21);
maxLevel = 3;
iters = 30;
useInitialFlow = false;
}
namespace
{
void calcPatchSize(cv::Size winSize, dim3& block, dim3& patch)
{
if (winSize.width > 32 && winSize.width > 2 * winSize.height)
{
block.x = deviceSupports(FEATURE_SET_COMPUTE_12) ? 32 : 16;
block.y = 8;
}
else
{
block.x = 16;
block.y = deviceSupports(FEATURE_SET_COMPUTE_12) ? 16 : 8;
}
patch.x = (winSize.width + block.x - 1) / block.x;
patch.y = (winSize.height + block.y - 1) / block.y;
block.z = patch.z = 1;
}
}
void cv::gpu::PyrLKOpticalFlow::sparse(const GpuMat& prevImg, const GpuMat& nextImg, const GpuMat& prevPts, GpuMat& nextPts, GpuMat& status, GpuMat* err)
{
if (prevPts.empty())
{
nextPts.release();
status.release();
if (err) err->release();
return;
}
dim3 block, patch;
calcPatchSize(winSize, block, patch);
CV_Assert(prevImg.channels() == 1 || prevImg.channels() == 3 || prevImg.channels() == 4);
CV_Assert(prevImg.size() == nextImg.size() && prevImg.type() == nextImg.type());
CV_Assert(maxLevel >= 0);
CV_Assert(winSize.width > 2 && winSize.height > 2);
CV_Assert(patch.x > 0 && patch.x < 6 && patch.y > 0 && patch.y < 6);
CV_Assert(prevPts.rows == 1 && prevPts.type() == CV_32FC2);
if (useInitialFlow)
CV_Assert(nextPts.size() == prevPts.size() && nextPts.type() == CV_32FC2);
else
ensureSizeIsEnough(1, prevPts.cols, prevPts.type(), nextPts);
GpuMat temp1 = (useInitialFlow ? nextPts : prevPts).reshape(1);
GpuMat temp2 = nextPts.reshape(1);
multiply(temp1, Scalar::all(1.0 / (1 << maxLevel) / 2.0), temp2);
ensureSizeIsEnough(1, prevPts.cols, CV_8UC1, status);
status.setTo(Scalar::all(1));
if (err)
ensureSizeIsEnough(1, prevPts.cols, CV_32FC1, *err);
// build the image pyramids.
prevPyr_.resize(maxLevel + 1);
nextPyr_.resize(maxLevel + 1);
int cn = prevImg.channels();
if (cn == 1 || cn == 4)
{
prevImg.convertTo(prevPyr_[0], CV_32F);
nextImg.convertTo(nextPyr_[0], CV_32F);
}
else
{
cvtColor(prevImg, buf_, COLOR_BGR2BGRA);
buf_.convertTo(prevPyr_[0], CV_32F);
cvtColor(nextImg, buf_, COLOR_BGR2BGRA);
buf_.convertTo(nextPyr_[0], CV_32F);
}
for (int level = 1; level <= maxLevel; ++level)
{
pyrDown(prevPyr_[level - 1], prevPyr_[level]);
pyrDown(nextPyr_[level - 1], nextPyr_[level]);
}
pyrlk::loadConstants(make_int2(winSize.width, winSize.height), iters);
for (int level = maxLevel; level >= 0; level--)
{
if (cn == 1)
{
pyrlk::sparse1(prevPyr_[level], nextPyr_[level],
prevPts.ptr<float2>(), nextPts.ptr<float2>(), status.ptr(), level == 0 && err ? err->ptr<float>() : 0, prevPts.cols,
level, block, patch);
}
else
{
pyrlk::sparse4(prevPyr_[level], nextPyr_[level],
prevPts.ptr<float2>(), nextPts.ptr<float2>(), status.ptr(), level == 0 && err ? err->ptr<float>() : 0, prevPts.cols,
level, block, patch);
}
}
}
void cv::gpu::PyrLKOpticalFlow::dense(const GpuMat& prevImg, const GpuMat& nextImg, GpuMat& u, GpuMat& v, GpuMat* err)
{
CV_Assert(prevImg.type() == CV_8UC1);
CV_Assert(prevImg.size() == nextImg.size() && prevImg.type() == nextImg.type());
CV_Assert(maxLevel >= 0);
CV_Assert(winSize.width > 2 && winSize.height > 2);
if (err)
err->create(prevImg.size(), CV_32FC1);
// build the image pyramids.
prevPyr_.resize(maxLevel + 1);
nextPyr_.resize(maxLevel + 1);
prevPyr_[0] = prevImg;
nextImg.convertTo(nextPyr_[0], CV_32F);
for (int level = 1; level <= maxLevel; ++level)
{
pyrDown(prevPyr_[level - 1], prevPyr_[level]);
pyrDown(nextPyr_[level - 1], nextPyr_[level]);
}
ensureSizeIsEnough(prevImg.size(), CV_32FC1, uPyr_[0]);
ensureSizeIsEnough(prevImg.size(), CV_32FC1, vPyr_[0]);
ensureSizeIsEnough(prevImg.size(), CV_32FC1, uPyr_[1]);
ensureSizeIsEnough(prevImg.size(), CV_32FC1, vPyr_[1]);
uPyr_[1].setTo(Scalar::all(0));
vPyr_[1].setTo(Scalar::all(0));
int2 winSize2i = make_int2(winSize.width, winSize.height);
pyrlk::loadConstants(winSize2i, iters);
PtrStepSzf derr = err ? *err : PtrStepSzf();
int idx = 0;
for (int level = maxLevel; level >= 0; level--)
{
int idx2 = (idx + 1) & 1;
pyrlk::dense(prevPyr_[level], nextPyr_[level], uPyr_[idx], vPyr_[idx], uPyr_[idx2], vPyr_[idx2],
level == 0 ? derr : PtrStepSzf(), winSize2i);
if (level > 0)
idx = idx2;
}
uPyr_[idx].copyTo(u);
vPyr_[idx].copyTo(v);
}
void cv::gpu::PyrLKOpticalFlow::releaseMemory()
{
prevPyr_.clear();
nextPyr_.clear();
buf_.release();
uPyr_[0].release();
vPyr_[0].release();
uPyr_[1].release();
vPyr_[1].release();
}
#endif /* !defined (HAVE_CUDA) */