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/*
* 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
* (3 - clause BSD License)
*
* Redistribution and use in source and binary forms, with or without modification,
* are permitted provided that the following conditions are met :
*
* * Redistributions of source code must retain the above copyright notice,
* this list of conditions and the following disclaimer.
*
* * Redistributions 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.
*
* * Neither the names of the copyright holders nor the names of the contributors
* may 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 copyright holders 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.
*/
#include "perf_precomp.hpp"
using std::tr1::tuple;
using std::tr1::get;
using namespace perf;
using namespace testing;
using namespace cv;
using namespace cv::optflow;
void MakeArtificialExample(Mat &dst_frame1, Mat &dst_frame2);
typedef tuple<String, Size> DISParams;
typedef TestBaseWithParam<DISParams> DenseOpticalFlow_DIS;
PERF_TEST_P(DenseOpticalFlow_DIS, perf,
Combine(Values("PRESET_ULTRAFAST", "PRESET_FAST", "PRESET_MEDIUM"), Values(szVGA, sz720p, sz1080p)))
{
DISParams params = GetParam();
// use strings to print preset names in the perf test results:
String preset_string = get<0>(params);
int preset = DISOpticalFlow::PRESET_FAST;
if (preset_string == "PRESET_ULTRAFAST")
preset = DISOpticalFlow::PRESET_ULTRAFAST;
else if (preset_string == "PRESET_FAST")
preset = DISOpticalFlow::PRESET_FAST;
else if (preset_string == "PRESET_MEDIUM")
preset = DISOpticalFlow::PRESET_MEDIUM;
Size sz = get<1>(params);
Mat frame1(sz, CV_8U);
Mat frame2(sz, CV_8U);
Mat flow;
MakeArtificialExample(frame1, frame2);
cv::setNumThreads(cv::getNumberOfCPUs());
TEST_CYCLE_N(10)
{
Ptr<DenseOpticalFlow> algo = createOptFlow_DIS(preset);
algo->calc(frame1, frame2, flow);
}
SANITY_CHECK_NOTHING();
}
void MakeArtificialExample(Mat &dst_frame1, Mat &dst_frame2)
{
int src_scale = 2;
int OF_scale = 6;
double sigma = dst_frame1.cols / 300;
Mat tmp(Size(dst_frame1.cols / (int)pow(2, src_scale), dst_frame1.rows / (int)pow(2, src_scale)), CV_8U);
randu(tmp, 0, 255);
resize(tmp, dst_frame1, dst_frame1.size(), 0.0, 0.0, INTER_LINEAR);
resize(tmp, dst_frame2, dst_frame2.size(), 0.0, 0.0, INTER_LINEAR);
Mat displacement_field(Size(dst_frame1.cols / (int)pow(2, OF_scale), dst_frame1.rows / (int)pow(2, OF_scale)),
CV_32FC2);
randn(displacement_field, 0.0, sigma);
resize(displacement_field, displacement_field, dst_frame2.size(), 0.0, 0.0, INTER_CUBIC);
for (int i = 0; i < displacement_field.rows; i++)
for (int j = 0; j < displacement_field.cols; j++)
displacement_field.at<Vec2f>(i, j) += Vec2f((float)j, (float)i);
remap(dst_frame2, dst_frame2, displacement_field, Mat(), INTER_LINEAR, BORDER_REPLICATE);
}
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