/*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 GpuMaterials 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 "precomp.hpp" using namespace std; using namespace cv; using namespace cv::gpu; #if !defined (HAVE_CUDA) 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(); } #else /* !defined (HAVE_CUDA) */ namespace cv { namespace gpu { namespace device { namespace pyrlk { void loadConstants(int cn, float minEigThreshold, int2 winSize, int iters); void calcSharrDeriv_gpu(DevMem2Db src, DevMem2D_ dx_buf, DevMem2D_ dy_buf, DevMem2D_ dIdx, DevMem2D_ dIdy, int cn, cudaStream_t stream = 0); void lkSparse_gpu(DevMem2Db I, DevMem2Db J, DevMem2D_ dIdx, DevMem2D_ dIdy, const float2* prevPts, float2* nextPts, uchar* status, float* err, int ptcount, int level, dim3 block, dim3 patch, cudaStream_t stream = 0); void lkDense_gpu(DevMem2Db I, DevMem2Db J, DevMem2D_ dIdx, DevMem2D_ dIdy, DevMem2Df u, DevMem2Df v, DevMem2Df* err, cudaStream_t stream = 0); } }}} void cv::gpu::PyrLKOpticalFlow::calcSharrDeriv(const GpuMat& src, GpuMat& dIdx, GpuMat& dIdy) { using namespace cv::gpu::device::pyrlk; CV_Assert(src.rows > 1 && src.cols > 1); CV_Assert(src.depth() == CV_8U); const int cn = src.channels(); ensureSizeIsEnough(src.size(), CV_MAKETYPE(CV_16S, cn), dx_calcBuf_); ensureSizeIsEnough(src.size(), CV_MAKETYPE(CV_16S, cn), dy_calcBuf_); calcSharrDeriv_gpu(src, dx_calcBuf_, dy_calcBuf_, dIdx, dIdy, cn); } void cv::gpu::PyrLKOpticalFlow::buildImagePyramid(const GpuMat& img0, vector& pyr, bool withBorder) { pyr.resize(maxLevel + 1); Size sz = img0.size(); for (int level = 0; level <= maxLevel; ++level) { GpuMat temp; if (withBorder) { temp.create(sz.height + winSize.height * 2, sz.width + winSize.width * 2, img0.type()); pyr[level] = temp(Rect(winSize.width, winSize.height, sz.width, sz.height)); } else { ensureSizeIsEnough(sz, img0.type(), pyr[level]); } if (level == 0) img0.copyTo(pyr[level]); else pyrDown(pyr[level - 1], pyr[level]); if (withBorder) copyMakeBorder(pyr[level], temp, winSize.height, winSize.height, winSize.width, winSize.width, BORDER_REFLECT_101); sz = Size((sz.width + 1) / 2, (sz.height + 1) / 2); if (sz.width <= winSize.width || sz.height <= winSize.height) { maxLevel = level; break; } } } void cv::gpu::PyrLKOpticalFlow::sparse(const GpuMat& prevImg, const GpuMat& nextImg, const GpuMat& prevPts, GpuMat& nextPts, GpuMat& status, GpuMat* err) { using namespace cv::gpu::device::pyrlk; if (prevPts.empty()) { nextPts.release(); status.release(); if (err) err->release(); return; } derivLambda = std::min(std::max(derivLambda, 0.0), 1.0); iters = std::min(std::max(iters, 0), 100); const int cn = prevImg.channels(); dim3 block; if (winSize.width * cn > 32) { block.x = 32; block.y = 8; } else { block.x = block.y = 16; } dim3 patch((winSize.width * cn + block.x - 1) / block.x, (winSize.height + block.y - 1) / block.y); CV_Assert(derivLambda >= 0); CV_Assert(maxLevel >= 0 && winSize.width > 2 && winSize.height > 2); CV_Assert(prevImg.size() == nextImg.size() && prevImg.type() == nextImg.type()); 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. // we pad each level with +/-winSize.{width|height} // pixels to simplify the further patch extraction. buildImagePyramid(prevImg, prevPyr_, true); buildImagePyramid(nextImg, nextPyr_, true); // dI/dx ~ Ix, dI/dy ~ Iy ensureSizeIsEnough(prevImg.rows + winSize.height * 2, prevImg.cols + winSize.width * 2, CV_MAKETYPE(CV_16S, cn), dx_buf_); ensureSizeIsEnough(prevImg.rows + winSize.height * 2, prevImg.cols + winSize.width * 2, CV_MAKETYPE(CV_16S, cn), dy_buf_); loadConstants(cn, minEigThreshold, make_int2(winSize.width, winSize.height), iters); for (int level = maxLevel; level >= 0; level--) { Size imgSize = prevPyr_[level].size(); GpuMat dxWhole(imgSize.height + winSize.height * 2, imgSize.width + winSize.width * 2, dx_buf_.type(), dx_buf_.data, dx_buf_.step); GpuMat dyWhole(imgSize.height + winSize.height * 2, imgSize.width + winSize.width * 2, dy_buf_.type(), dy_buf_.data, dy_buf_.step); dxWhole.setTo(Scalar::all(0)); dyWhole.setTo(Scalar::all(0)); GpuMat dIdx = dxWhole(Rect(winSize.width, winSize.height, imgSize.width, imgSize.height)); GpuMat dIdy = dyWhole(Rect(winSize.width, winSize.height, imgSize.width, imgSize.height)); calcSharrDeriv(prevPyr_[level], dIdx, dIdy); lkSparse_gpu(prevPyr_[level], nextPyr_[level], dIdx, dIdy, prevPts.ptr(), nextPts.ptr(), status.ptr(), level == 0 && err ? err->ptr() : 0, prevPts.cols, level, block, patch); } } void cv::gpu::PyrLKOpticalFlow::dense(const GpuMat& prevImg, const GpuMat& nextImg, GpuMat& u, GpuMat& v, GpuMat* err) { using namespace cv::gpu::device::pyrlk; derivLambda = std::min(std::max(derivLambda, 0.0), 1.0); iters = std::min(std::max(iters, 0), 100); CV_Assert(prevImg.type() == CV_8UC1); CV_Assert(prevImg.size() == nextImg.size() && prevImg.type() == nextImg.type()); CV_Assert(derivLambda >= 0); CV_Assert(maxLevel >= 0 && winSize.width > 2 && winSize.height > 2); if (useInitialFlow) { CV_Assert(u.size() == prevImg.size() && u.type() == CV_32FC1); CV_Assert(v.size() == prevImg.size() && v.type() == CV_32FC1); } else { u.create(prevImg.size(), CV_32FC1); v.create(prevImg.size(), CV_32FC1); u.setTo(Scalar::all(0)); v.setTo(Scalar::all(0)); } if (err) err->create(prevImg.size(), CV_32FC1); // build the image pyramids. // we pad each level with +/-winSize.{width|height} // pixels to simplify the further patch extraction. buildImagePyramid(prevImg, prevPyr_, true); buildImagePyramid(nextImg, nextPyr_, true); buildImagePyramid(u, uPyr_, false); buildImagePyramid(v, vPyr_, false); // dI/dx ~ Ix, dI/dy ~ Iy ensureSizeIsEnough(prevImg.rows + winSize.height * 2, prevImg.cols + winSize.width * 2, CV_16SC1, dx_buf_); ensureSizeIsEnough(prevImg.rows + winSize.height * 2, prevImg.cols + winSize.width * 2, CV_16SC1, dy_buf_); loadConstants(1, minEigThreshold, make_int2(winSize.width, winSize.height), iters); DevMem2Df derr = err ? *err : DevMem2Df(); for (int level = maxLevel; level >= 0; level--) { Size imgSize = prevPyr_[level].size(); GpuMat dxWhole(imgSize.height + winSize.height * 2, imgSize.width + winSize.width * 2, dx_buf_.type(), dx_buf_.data, dx_buf_.step); GpuMat dyWhole(imgSize.height + winSize.height * 2, imgSize.width + winSize.width * 2, dy_buf_.type(), dy_buf_.data, dy_buf_.step); dxWhole.setTo(Scalar::all(0)); dyWhole.setTo(Scalar::all(0)); GpuMat dIdx = dxWhole(Rect(winSize.width, winSize.height, imgSize.width, imgSize.height)); GpuMat dIdy = dyWhole(Rect(winSize.width, winSize.height, imgSize.width, imgSize.height)); calcSharrDeriv(prevPyr_[level], dIdx, dIdy); lkDense_gpu(prevPyr_[level], nextPyr_[level], dIdx, dIdy, uPyr_[level], vPyr_[level], level == 0 && err ? &derr : 0); if (level == 0) { uPyr_[0].copyTo(u); vPyr_[0].copyTo(v); } else { pyrUp(uPyr_[level], uPyr_[level - 1]); pyrUp(vPyr_[level], vPyr_[level - 1]); multiply(uPyr_[level - 1], Scalar::all(2), uPyr_[level - 1]); multiply(vPyr_[level - 1], Scalar::all(2), vPyr_[level - 1]); } } } #endif /* !defined (HAVE_CUDA) */