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93 lines
3.3 KiB
93 lines
3.3 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 "perf_precomp.hpp" |
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namespace cvtest |
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{ |
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using std::tr1::tuple; |
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using std::tr1::get; |
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using namespace perf; |
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using namespace testing; |
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using namespace cv; |
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using namespace cv::ximgproc; |
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typedef tuple<bool, Size, int, int, MatType> AMPerfTestParam; |
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typedef TestBaseWithParam<AMPerfTestParam> AdaptiveManifoldPerfTest; |
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PERF_TEST_P( AdaptiveManifoldPerfTest, perf, |
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Combine( |
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Values(true, false), //adjust_outliers flag |
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Values(sz1080p, sz720p), //size |
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Values(1, 3, 8), //joint channels num |
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Values(1, 3), //source channels num |
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Values(CV_8U, CV_32F) //source and joint depth |
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) |
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) |
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{ |
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AMPerfTestParam params = GetParam(); |
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bool adjustOutliers = get<0>(params); |
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Size sz = get<1>(params); |
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int jointCnNum = get<2>(params); |
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int srcCnNum = get<3>(params); |
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int depth = get<4>(params); |
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Mat joint(sz, CV_MAKE_TYPE(depth, jointCnNum)); |
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Mat src(sz, CV_MAKE_TYPE(depth, srcCnNum)); |
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Mat dst(sz, CV_MAKE_TYPE(depth, srcCnNum)); |
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cv::setNumThreads(cv::getNumberOfCPUs()); |
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declare.in(joint, src, WARMUP_RNG).out(dst).tbb_threads(cv::getNumberOfCPUs()); |
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double sigma_s = 16; |
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double sigma_r = 0.5; |
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TEST_CYCLE_N(3) |
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{ |
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Mat res; |
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amFilter(joint, src, res, sigma_s, sigma_r, adjustOutliers); |
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//at 5th cycle sigma_s will be five times more and tree depth will be 5 |
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sigma_s *= 1.38; |
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sigma_r /= 1.38; |
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} |
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SANITY_CHECK_NOTHING(); |
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} |
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}
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