vendor: OpenCV 5.0.0 snapshot at 755e50675d97db9b7d449d8bd6b09888646f6c6e
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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) 2010-2012, Multicoreware, Inc., all rights reserved.
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// Copyright (C) 2010-2012, Advanced Micro Devices, 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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// @Authors
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// Fangfang Bai, fangfang@multicorewareinc.com
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// Jin Ma, jin@multicorewareinc.com
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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 implied warranties, including, but not limited to, the implied
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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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#include "../perf_precomp.hpp"
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#include "opencv2/ts/ocl_perf.hpp"
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#ifdef HAVE_OPENCL
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namespace opencv_test {
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namespace ocl {
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#undef VISUALIZE_FLOW
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//#define VISUALIZE_FLOW 1
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#ifdef VISUALIZE_FLOW
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// [TODO] move it to opencv_video/tracking.hpp
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// Standard visualization of the optical flow, according to Scharstein/Middlebury (ICCV 2007).
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// flow — input flow of CV_32FC2 type (field of motion vectors)
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// dst — output visual optical flow representation of CV_8UC3 type
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// maxFlow — max flow magnitude or (if <=0, it's computed automatically; use with care,
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// because it 'boosts' flow when there is almost no one).
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// pixels where the motion vector magnitude is equal or exceeds maxFlow will be
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// painted with maximum saturation.
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// eps — maxFlow threshold for 'no motion/still scene' cases
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// computedMaxFlow — the optional output value to hold the computed maxFlow, to let user
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// gradually calibrate maxFlow parameter.
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static void tsVisualizeFlow(InputArray flowarr, OutputArray dstarr,
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float maxFlow0 = -1.f, float eps = 1e-3f,
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float* computedMaxFlow=nullptr)
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{
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Mat flow = flowarr.getMat();
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CV_Assert(flow.type() == CV_32FC2);
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// --- color ring (55 colors, RGB) ---
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// sectors: RY=15, YG=6, GC=4, CB=11, BM=13, MR=6
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constexpr int RY=15, YG=6, GC=4, CB=11, BM=13, MR=6;
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constexpr int NCOLS = RY+YG+GC+CB+BM+MR; // 55
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std::array<Vec3b, NCOLS+1> cwheel_; // RGB
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int k = 0;
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for (int i=0;i<RY;i++,k++) cwheel_[k]=Vec3b(0, uint8_t(255*i/RY), 255);
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for (int i=0;i<YG;i++,k++) cwheel_[k]=Vec3b(0, 255, uint8_t(255-255*i/YG));
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for (int i=0;i<GC;i++,k++) cwheel_[k]=Vec3b(uint8_t(255*i/GC), 255, 0);
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for (int i=0;i<CB;i++,k++) cwheel_[k]=Vec3b(255, uint8_t(255-255*i/CB), 0);
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for (int i=0;i<BM;i++,k++) cwheel_[k]=Vec3b(255, 0, uint8_t(255*i/BM));
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for (int i=0;i<MR;i++,k++) cwheel_[k]=Vec3b(uint8_t(255-255*i/MR), 0, 255);
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cwheel_[NCOLS] = cwheel_[0];
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std::vector<float> maxvals(flow.rows);
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// --- compute max flow automatically ---
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if (maxFlow0 <= 0.0f) {
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parallel_for_(cv::Range(0, flow.rows), [&](const cv::Range& range) {
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for (int y = range.start; y < range.end; y++) {
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float maxval = 0.f;
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const cv::Vec2f* row = flow.ptr<cv::Vec2f>(y);
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for (int x = 0; x < flow.cols; x++) {
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float dx = row[x][0], dy = row[x][1];
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float mag = std::hypot(dx, dy);
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maxval = std::max(maxval, mag);
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}
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maxvals[y] = maxval;
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}
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});
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maxFlow0 = 0.f;
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for (int y = 0; y < flow.rows; y++)
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maxFlow0 = std::max(maxFlow0, maxvals[y]);
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}
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maxFlow0 = maxFlow0 > eps ? maxFlow0 : 1.f;
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dstarr.create(flow.size(), CV_8UC3);
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Mat dst = dstarr.getMat();
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// paint the optical flow map
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parallel_for_(cv::Range(0, flow.rows), [&](const cv::Range& range) {
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const Vec3b* cwheel = cwheel_.data();
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float maxval = 0.f, maxflow = maxFlow0;
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for (int y = range.start; y < range.end; y++) {
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const cv::Vec2f* src = flow.ptr<cv::Vec2f>(y);
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cv::Vec3b* out = dst.ptr<cv::Vec3b>(y);
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for (int x = 0; x < flow.cols; x++) {
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float dx = src[x][0];
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float dy = src[x][1];
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float mag = std::hypot(dx, dy);
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maxval = std::max(maxval, mag);
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mag = std::min(mag / maxflow, 1.f);
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// compute the color from angle
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float a = std::atan2(-dy, -dx) / static_cast<float>(M_PI);
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float f = (a + 1.0f) * 0.5f * (NCOLS - 1);
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int idx = (int)f;
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f -= idx;
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// 'white' means no motion,
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// the stronger the motion the more saturated the corresponding pixel is.
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Vec3b clr;
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for (int c = 0; c < 3; c++) {
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float chval = cwheel[idx][c] * (1.f - f) + cwheel[idx + 1][c] * f;
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chval = 255.f - mag * (255.f - chval);
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clr[c] = saturate_cast<uint8_t>(chval);
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}
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out[x] = clr;
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}
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maxvals[y] = maxval;
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}
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});
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if (computedMaxFlow) {
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maxFlow0 = 0.f;
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for (int y = 0; y < flow.rows; y++)
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maxFlow0 = std::max(maxFlow0, maxvals[y]);
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*computedMaxFlow = maxFlow0;
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}
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}
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#endif
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///////////// OpticalFlow Dual TVL1 ////////////////////////
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typedef tuple< tuple<int, double>, bool> OpticalFlowDualTVL1Params;
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typedef TestBaseWithParam<OpticalFlowDualTVL1Params> OpticalFlowDualTVL1Fixture;
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OCL_PERF_TEST_P(OpticalFlowDualTVL1Fixture, OpticalFlowDualTVL1,
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::testing::Combine(
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::testing::Values(make_tuple<int, double>(-1, 0.3),
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make_tuple<int, double>(3, 0.5)),
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::testing::Bool()
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)
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)
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{
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Mat frame0 = imread(getDataPath("cv/optflow/RubberWhale1.png"), IMREAD_GRAYSCALE);
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ASSERT_FALSE(frame0.empty()) << "can't load RubberWhale1.png";
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Mat frame1 = imread(getDataPath("cv/optflow/RubberWhale2.png"), IMREAD_GRAYSCALE);
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ASSERT_FALSE(frame1.empty()) << "can't load RubberWhale2.png";
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const Size srcSize = frame0.size();
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const OpticalFlowDualTVL1Params params = GetParam();
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const tuple<int, double> filteringScale = get<0>(params);
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const int medianFiltering = get<0>(filteringScale);
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const double scaleStep = get<1>(filteringScale);
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const bool useInitFlow = get<1>(params);
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//double eps = 0.9;
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UMat uFrame0; frame0.copyTo(uFrame0);
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UMat uFrame1; frame1.copyTo(uFrame1);
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UMat uFlow(srcSize, CV_32FC2);
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declare.in(uFrame0, uFrame1, WARMUP_READ).out(uFlow, WARMUP_READ);
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//create algorithm
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Ptr<DualTVL1OpticalFlow> alg = createOptFlow_DualTVL1();
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//set parameters
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alg->setScaleStep(scaleStep);
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alg->setMedianFiltering(medianFiltering);
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if (useInitFlow)
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{
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//calculate initial flow as result of optical flow
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alg->calc(uFrame0, uFrame1, uFlow);
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}
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//set flag to use initial flow
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alg->setUseInitialFlow(useInitFlow);
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OCL_TEST_CYCLE()
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alg->calc(uFrame0, uFrame1, uFlow);
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#ifdef VISUALIZE_FLOW
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imshow("frame0", uFrame0);
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UMat framediff;
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absdiff(uFrame0, uFrame1, framediff);
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imshow("framediff", framediff);
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Mat flow8u;
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tsVisualizeFlow(uFlow, flow8u);
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imshow("uFlow", flow8u);
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waitKey();
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#endif
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//SANITY_CHECK(uFlow, eps, ERROR_RELATIVE);
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SANITY_CHECK_NOTHING();
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}
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}
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} // namespace opencv_test::ocl
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#endif // HAVE_OPENCL
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