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120 lines
4.0 KiB
120 lines
4.0 KiB
/* |
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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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* (3 - clause BSD License) |
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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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* * Redistributions 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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* * Redistributions 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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* * Neither the names of the copyright holders nor the names of the contributors |
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* may be used to endorse or promote products derived from this software |
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* 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 copyright holders 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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#include "test_precomp.hpp" |
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namespace cvtest |
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{ |
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using namespace std; |
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using namespace std::tr1; |
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using namespace testing; |
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using namespace perf; |
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using namespace cv; |
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using namespace cv::ximgproc; |
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CV_ENUM(SrcTypes, CV_8UC1, CV_8UC3, CV_16UC1, CV_16UC3); |
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typedef tuple<Size, SrcTypes> L0SmoothParams; |
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typedef TestWithParam<L0SmoothParams> L0SmoothTest; |
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TEST(L0SmoothTest, SplatSurfaceAccuracy) |
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{ |
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RNG rnd(0); |
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for (int i = 0; i < 3; i++) |
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{ |
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Size sz(rnd.uniform(512, 1024), rnd.uniform(512, 1024)); |
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Scalar surfaceValue; |
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int srcCn = 3; |
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rnd.fill(surfaceValue, RNG::UNIFORM, 0, 255); |
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Mat src(sz, CV_MAKE_TYPE(CV_8U, srcCn), surfaceValue); |
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double lambda = rnd.uniform(0.01, 0.05); |
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double kappa = rnd.uniform(1.5, 5.0); |
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Mat res; |
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l0Smooth(src, res, lambda, kappa); |
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// When filtering a constant image we should get the same image: |
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double normL1 = cvtest::norm(src, res, NORM_L1)/src.total()/src.channels(); |
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EXPECT_LE(normL1, 1.0/64); |
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} |
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} |
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TEST_P(L0SmoothTest, MultiThreadReproducibility) |
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{ |
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if (cv::getNumberOfCPUs() == 1) |
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return; |
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double MAX_DIF = 10.0; |
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double MAX_MEAN_DIF = 1.0 / 8.0; |
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int loopsCount = 2; |
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RNG rng(0); |
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L0SmoothParams params = GetParam(); |
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Size size = get<0>(params); |
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int srcType = get<1>(params); |
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Mat src(size,srcType); |
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if(src.depth()==CV_8U) |
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randu(src, 0, 255); |
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else if(src.depth()==CV_16U) |
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randu(src, 0, 65535); |
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else |
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randu(src, -100000.0f, 100000.0f); |
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for (int iter = 0; iter <= loopsCount; iter++) |
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{ |
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double lambda = rng.uniform(0.01, 0.05); |
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double kappa = rng.uniform(1.5, 5.0); |
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cv::setNumThreads(cv::getNumberOfCPUs()); |
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Mat resMultiThread; |
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l0Smooth(src, resMultiThread, lambda, kappa); |
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cv::setNumThreads(1); |
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Mat resSingleThread; |
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l0Smooth(src, resSingleThread, lambda, kappa); |
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EXPECT_LE(cv::norm(resSingleThread, resMultiThread, NORM_INF), MAX_DIF); |
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EXPECT_LE(cv::norm(resSingleThread, resMultiThread, NORM_L1), MAX_MEAN_DIF*src.total()*src.channels()); |
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} |
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} |
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INSTANTIATE_TEST_CASE_P(FullSet, L0SmoothTest,Combine(Values(szODD, szQVGA), SrcTypes::all())); |
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}
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