mirrors/opencv_contrib
1
0
Fork 0
Code Pull Requests Packages Releases Activity
Files
main
opencv_contrib/modules/optflow/perf/opencl/perf_optflow_dualTVL1.cpp
T

231 lines
9.1 KiB
C++
Raw Permalink Blame History

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