/*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 cv; using namespace cv::gpu; using namespace std; #if !defined (HAVE_CUDA) || defined (CUDA_DISABLER) void cv::gpu::BroxOpticalFlow::operator ()(const GpuMat&, const GpuMat&, GpuMat&, GpuMat&, Stream&) { throw_nogpu(); } void cv::gpu::interpolateFrames(const GpuMat&, const GpuMat&, const GpuMat&, const GpuMat&, const GpuMat&, const GpuMat&, float, GpuMat&, GpuMat&, Stream&) { throw_nogpu(); } void cv::gpu::createOpticalFlowNeedleMap(const GpuMat&, const GpuMat&, GpuMat&, GpuMat&) { throw_nogpu(); } #else namespace { size_t getBufSize(const NCVBroxOpticalFlowDescriptor& desc, const NCVMatrix& frame0, const NCVMatrix& frame1, NCVMatrix& u, NCVMatrix& v, const cudaDeviceProp& devProp) { NCVMemStackAllocator gpuCounter(static_cast(devProp.textureAlignment)); ncvSafeCall( NCVBroxOpticalFlow(desc, gpuCounter, frame0, frame1, u, v, 0) ); return gpuCounter.maxSize(); } } namespace { static void outputHandler(const std::string &msg) { CV_Error(CV_GpuApiCallError, msg.c_str()); } } void cv::gpu::BroxOpticalFlow::operator ()(const GpuMat& frame0, const GpuMat& frame1, GpuMat& u, GpuMat& v, Stream& s) { ncvSetDebugOutputHandler(outputHandler); CV_Assert(frame0.type() == CV_32FC1); CV_Assert(frame1.size() == frame0.size() && frame1.type() == frame0.type()); u.create(frame0.size(), CV_32FC1); v.create(frame0.size(), CV_32FC1); cudaDeviceProp devProp; cudaSafeCall( cudaGetDeviceProperties(&devProp, getDevice()) ); NCVBroxOpticalFlowDescriptor desc; desc.alpha = alpha; desc.gamma = gamma; desc.scale_factor = scale_factor; desc.number_of_inner_iterations = inner_iterations; desc.number_of_outer_iterations = outer_iterations; desc.number_of_solver_iterations = solver_iterations; NCVMemSegment frame0MemSeg; frame0MemSeg.begin.memtype = NCVMemoryTypeDevice; frame0MemSeg.begin.ptr = const_cast(frame0.data); frame0MemSeg.size = frame0.step * frame0.rows; NCVMemSegment frame1MemSeg; frame1MemSeg.begin.memtype = NCVMemoryTypeDevice; frame1MemSeg.begin.ptr = const_cast(frame1.data); frame1MemSeg.size = frame1.step * frame1.rows; NCVMemSegment uMemSeg; uMemSeg.begin.memtype = NCVMemoryTypeDevice; uMemSeg.begin.ptr = u.ptr(); uMemSeg.size = u.step * u.rows; NCVMemSegment vMemSeg; vMemSeg.begin.memtype = NCVMemoryTypeDevice; vMemSeg.begin.ptr = v.ptr(); vMemSeg.size = v.step * v.rows; NCVMatrixReuse frame0Mat(frame0MemSeg, static_cast(devProp.textureAlignment), frame0.cols, frame0.rows, static_cast(frame0.step)); NCVMatrixReuse frame1Mat(frame1MemSeg, static_cast(devProp.textureAlignment), frame1.cols, frame1.rows, static_cast(frame1.step)); NCVMatrixReuse uMat(uMemSeg, static_cast(devProp.textureAlignment), u.cols, u.rows, static_cast(u.step)); NCVMatrixReuse vMat(vMemSeg, static_cast(devProp.textureAlignment), v.cols, v.rows, static_cast(v.step)); cudaStream_t stream = StreamAccessor::getStream(s); size_t bufSize = getBufSize(desc, frame0Mat, frame1Mat, uMat, vMat, devProp); ensureSizeIsEnough(1, static_cast(bufSize), CV_8UC1, buf); NCVMemStackAllocator gpuAllocator(NCVMemoryTypeDevice, bufSize, static_cast(devProp.textureAlignment), buf.ptr()); ncvSafeCall( NCVBroxOpticalFlow(desc, gpuAllocator, frame0Mat, frame1Mat, uMat, vMat, stream) ); } void cv::gpu::interpolateFrames(const GpuMat& frame0, const GpuMat& frame1, const GpuMat& fu, const GpuMat& fv, const GpuMat& bu, const GpuMat& bv, float pos, GpuMat& newFrame, GpuMat& buf, Stream& s) { CV_Assert(frame0.type() == CV_32FC1); CV_Assert(frame1.size() == frame0.size() && frame1.type() == frame0.type()); CV_Assert(fu.size() == frame0.size() && fu.type() == frame0.type()); CV_Assert(fv.size() == frame0.size() && fv.type() == frame0.type()); CV_Assert(bu.size() == frame0.size() && bu.type() == frame0.type()); CV_Assert(bv.size() == frame0.size() && bv.type() == frame0.type()); newFrame.create(frame0.size(), frame0.type()); buf.create(6 * frame0.rows, frame0.cols, CV_32FC1); buf.setTo(Scalar::all(0)); // occlusion masks GpuMat occ0 = buf.rowRange(0 * frame0.rows, 1 * frame0.rows); GpuMat occ1 = buf.rowRange(1 * frame0.rows, 2 * frame0.rows); // interpolated forward flow GpuMat fui = buf.rowRange(2 * frame0.rows, 3 * frame0.rows); GpuMat fvi = buf.rowRange(3 * frame0.rows, 4 * frame0.rows); // interpolated backward flow GpuMat bui = buf.rowRange(4 * frame0.rows, 5 * frame0.rows); GpuMat bvi = buf.rowRange(5 * frame0.rows, 6 * frame0.rows); size_t step = frame0.step; CV_Assert(frame1.step == step && fu.step == step && fv.step == step && bu.step == step && bv.step == step && newFrame.step == step && buf.step == step); cudaStream_t stream = StreamAccessor::getStream(s); NppStStreamHandler h(stream); NppStInterpolationState state; state.size = NcvSize32u(frame0.cols, frame0.rows); state.nStep = static_cast(step); state.pSrcFrame0 = const_cast(frame0.ptr()); state.pSrcFrame1 = const_cast(frame1.ptr()); state.pFU = const_cast(fu.ptr()); state.pFV = const_cast(fv.ptr()); state.pBU = const_cast(bu.ptr()); state.pBV = const_cast(bv.ptr()); state.pos = pos; state.pNewFrame = newFrame.ptr(); state.ppBuffers[0] = occ0.ptr(); state.ppBuffers[1] = occ1.ptr(); state.ppBuffers[2] = fui.ptr(); state.ppBuffers[3] = fvi.ptr(); state.ppBuffers[4] = bui.ptr(); state.ppBuffers[5] = bvi.ptr(); ncvSafeCall( nppiStInterpolateFrames(&state) ); if (stream == 0) cudaSafeCall( cudaDeviceSynchronize() ); } namespace cv { namespace gpu { namespace device { namespace optical_flow { void NeedleMapAverage_gpu(PtrStepSzf u, PtrStepSzf v, PtrStepSzf u_avg, PtrStepSzf v_avg); void CreateOpticalFlowNeedleMap_gpu(PtrStepSzf u_avg, PtrStepSzf v_avg, float* vertex_buffer, float* color_data, float max_flow, float xscale, float yscale); } }}} void cv::gpu::createOpticalFlowNeedleMap(const GpuMat& u, const GpuMat& v, GpuMat& vertex, GpuMat& colors) { using namespace cv::gpu::device::optical_flow; CV_Assert(u.type() == CV_32FC1); CV_Assert(v.type() == u.type() && v.size() == u.size()); const int NEEDLE_MAP_SCALE = 16; const int x_needles = u.cols / NEEDLE_MAP_SCALE; const int y_needles = u.rows / NEEDLE_MAP_SCALE; GpuMat u_avg(y_needles, x_needles, CV_32FC1); GpuMat v_avg(y_needles, x_needles, CV_32FC1); NeedleMapAverage_gpu(u, v, u_avg, v_avg); const int NUM_VERTS_PER_ARROW = 6; const int num_arrows = x_needles * y_needles * NUM_VERTS_PER_ARROW; vertex.create(1, num_arrows, CV_32FC3); colors.create(1, num_arrows, CV_32FC3); colors.setTo(Scalar::all(1.0)); double uMax, vMax; minMax(u_avg, 0, &uMax); minMax(v_avg, 0, &vMax); float max_flow = static_cast(std::sqrt(uMax * uMax + vMax * vMax)); CreateOpticalFlowNeedleMap_gpu(u_avg, v_avg, vertex.ptr(), colors.ptr(), max_flow, 1.0f / u.cols, 1.0f / u.rows); cvtColor(colors, colors, COLOR_HSV2RGB); } #endif /* HAVE_CUDA */