Open Source Computer Vision Library
https://opencv.org/
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180 lines
6.8 KiB
180 lines
6.8 KiB
/*M/////////////////////////////////////////////////////////////////////////////////////// |
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// |
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. |
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// |
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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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// Intel License Agreement |
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// For Open Source Computer Vision Library |
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// |
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// Copyright (C) 2000, Intel Corporation, all rights reserved. |
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// Third party copyrights are property of their respective owners. |
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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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// * Redistribution's 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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// * Redistribution's 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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// * The name of Intel Corporation may not be used to endorse or promote products |
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// derived from this software 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 the Intel Corporation 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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//M*/ |
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#include "gputest.hpp" |
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#include <algorithm> |
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#include <iterator> |
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using namespace cv; |
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using namespace cv::gpu; |
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using namespace std; |
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class CV_GpuBruteForceMatcherTest : public CvTest |
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{ |
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public: |
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CV_GpuBruteForceMatcherTest() : CvTest( "GPU-BruteForceMatcher", "BruteForceMatcher" ) {} |
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protected: |
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void run(int) |
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{ |
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try |
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{ |
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BruteForceMatcher< L2<float> > matcherCPU; |
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BruteForceMatcher_GPU< L2<float> > matcherGPU; |
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vector<DMatch> matchesCPU, matchesGPU; |
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vector< vector<DMatch> > knnMatchesCPU, knnMatchesGPU; |
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vector< vector<DMatch> > radiusMatchesCPU, radiusMatchesGPU; |
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RNG rng(*ts->get_rng()); |
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const int desc_len = rng.uniform(40, 300); |
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Mat queryCPU(rng.uniform(100, 300), desc_len, CV_32F); |
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rng.fill(queryCPU, cv::RNG::UNIFORM, cv::Scalar::all(0.0), cv::Scalar::all(10.0)); |
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GpuMat queryGPU(queryCPU); |
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const int nTrains = rng.uniform(1, 5); |
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vector<Mat> trainsCPU(nTrains); |
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vector<GpuMat> trainsGPU(nTrains); |
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vector<Mat> masksCPU(nTrains); |
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vector<GpuMat> masksGPU(nTrains); |
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for (int i = 0; i < nTrains; ++i) |
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{ |
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Mat train(rng.uniform(100, 300), desc_len, CV_32F); |
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rng.fill(train, cv::RNG::UNIFORM, cv::Scalar::all(0.0), cv::Scalar::all(10.0)); |
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trainsCPU[i] = train; |
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trainsGPU[i].upload(train); |
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bool with_mask = rng.uniform(0, 10) < 5; |
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if (with_mask) |
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{ |
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Mat mask(queryCPU.rows, train.rows, CV_8U); |
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rng.fill(mask, cv::RNG::UNIFORM, cv::Scalar::all(0), cv::Scalar::all(200)); |
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masksCPU[i] = mask; |
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masksGPU[i].upload(mask); |
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} |
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} |
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matcherCPU.add(trainsCPU); |
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matcherGPU.add(trainsGPU); |
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matcherCPU.match(queryCPU, matchesCPU, masksCPU); |
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matcherGPU.match(queryGPU, matchesGPU, masksGPU); |
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if (!compareMatches(matchesCPU, matchesGPU)) |
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{ |
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ts->printf(CvTS::LOG, "Match FAIL\n"); |
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ts->set_failed_test_info(CvTS::FAIL_MISMATCH); |
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return; |
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} |
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const int knn = rng.uniform(3, 10); |
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matcherCPU.knnMatch(queryCPU, knnMatchesCPU, knn, masksCPU, true); |
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matcherGPU.knnMatch(queryGPU, knnMatchesGPU, knn, masksGPU, true); |
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if (!compareMatches(knnMatchesCPU, knnMatchesGPU)) |
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{ |
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ts->printf(CvTS::LOG, "KNN Match FAIL\n"); |
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ts->set_failed_test_info(CvTS::FAIL_MISMATCH); |
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return; |
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} |
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const float maxDistance = rng.uniform(25.0f, 65.0f); |
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matcherCPU.radiusMatch(queryCPU, radiusMatchesCPU, maxDistance, masksCPU, true); |
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matcherGPU.radiusMatch(queryGPU, radiusMatchesGPU, maxDistance, masksGPU, true); |
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if (!compareMatches(radiusMatchesCPU, radiusMatchesGPU)) |
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{ |
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ts->printf(CvTS::LOG, "Radius Match FAIL\n"); |
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ts->set_failed_test_info(CvTS::FAIL_MISMATCH); |
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return; |
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} |
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} |
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catch (const cv::Exception& e) |
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{ |
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if (!check_and_treat_gpu_exception(e, ts)) |
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throw; |
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return; |
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} |
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ts->set_failed_test_info(CvTS::OK); |
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} |
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private: |
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static void convertMatches(const vector< vector<DMatch> >& knnMatches, vector<DMatch>& matches) |
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{ |
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matches.clear(); |
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for (size_t i = 0; i < knnMatches.size(); ++i) |
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copy(knnMatches[i].begin(), knnMatches[i].end(), back_inserter(matches)); |
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} |
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struct DMatchEqual : public binary_function<DMatch, DMatch, bool> |
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{ |
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bool operator()(const DMatch& m1, const DMatch& m2) const |
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{ |
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return m1.imgIdx == m2.imgIdx && m1.queryIdx == m2.queryIdx && m1.trainIdx == m2.trainIdx; |
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} |
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}; |
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static bool compareMatches(const vector<DMatch>& matches1, const vector<DMatch>& matches2) |
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{ |
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if (matches1.size() != matches2.size()) |
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return false; |
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return equal(matches1.begin(), matches1.end(), matches2.begin(), DMatchEqual()); |
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} |
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static bool compareMatches(const vector< vector<DMatch> >& matches1, const vector< vector<DMatch> >& matches2) |
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{ |
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vector<DMatch> m1, m2; |
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convertMatches(matches1, m1); |
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convertMatches(matches2, m2); |
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return compareMatches(m1, m2); |
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} |
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} brute_force_matcher_test; |