Open Source Computer Vision Library https://opencv.org/
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/*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:
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// this list of conditions and the following disclaimer.
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//M*/
#include "perf_precomp.hpp"
#include "opencv2/ts/ocl_perf.hpp"
using std::tr1::make_tuple;
#ifdef HAVE_OPENCL
namespace cvtest {
namespace ocl {
///////////// 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"), cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(frame0.empty()) << "can't load RubberWhale1.png";
Mat frame1 = imread(getDataPath("cv/optflow/RubberWhale2.png"), cv::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
cv::Ptr<cv::DenseOpticalFlow> alg = cv::createOptFlow_DualTVL1();
//set parameters
alg->set("scaleStep", scaleStep);
alg->setInt("medianFiltering", medianFiltering);
if (useInitFlow)
{
//calculate initial flow as result of optical flow
alg->calc(uFrame0, uFrame1, uFlow);
}
//set flag to use initial flow
alg->setBool("useInitialFlow", useInitFlow);
OCL_TEST_CYCLE()
alg->calc(uFrame0, uFrame1, uFlow);
SANITY_CHECK(uFlow, eps, ERROR_RELATIVE);
}
}
} // namespace cvtest::ocl
#endif // HAVE_OPENCL