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Open Source Computer Vision Library
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163 lines
5.7 KiB
163 lines
5.7 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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// License Agreement |
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// For Open Source Computer Vision Library |
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// |
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// Copyright (C) 2010-2012, Multicoreware, Inc., all rights reserved. |
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// Copyright (C) 2010-2012, Advanced Micro Devices, Inc., all rights reserved. |
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// Third party copyrights are property of their respective owners. |
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// |
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// @Authors |
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// Fangfang Bai, fangfang@multicorewareinc.com |
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// Jin Ma, jin@multicorewareinc.com |
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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 oclMaterials provided with the distribution. |
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// |
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// * The name of the copyright holders 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 "perf_precomp.hpp" |
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using namespace perf; |
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#define OCL_BFMATCHER_TYPICAL_MAT_SIZES ::testing::Values(cv::Size(128, 500), cv::Size(128, 1000), cv::Size(128, 2000)) |
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//////////////////// BruteForceMatch ///////////////// |
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typedef TestBaseWithParam<Size> BruteForceMatcherFixture; |
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PERF_TEST_P(BruteForceMatcherFixture, DISABLED_match, |
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OCL_BFMATCHER_TYPICAL_MAT_SIZES) // TODO too big difference between implementations |
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{ |
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const Size srcSize = GetParam(); |
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vector<DMatch> matches; |
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Mat query(srcSize, CV_32F), train(srcSize, CV_32F); |
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declare.in(query, train).time(srcSize.height == 2000 ? 8 : 4 ); |
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randu(query, 0.0f, 1.0f); |
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randu(train, 0.0f, 1.0f); |
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if (RUN_PLAIN_IMPL) |
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{ |
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BFMatcher matcher(NORM_L2); |
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TEST_CYCLE() matcher.match(query, train, matches); |
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SANITY_CHECK_MATCHES(matches); |
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} |
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else if (RUN_OCL_IMPL) |
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{ |
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ocl::BruteForceMatcher_OCL_base oclMatcher(ocl::BruteForceMatcher_OCL_base::L2Dist); |
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ocl::oclMat oclQuery(query), oclTrain(train); |
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TEST_CYCLE() oclMatcher.match(oclQuery, oclTrain, matches); |
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SANITY_CHECK_MATCHES(matches); |
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} |
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else |
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OCL_PERF_ELSE |
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} |
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PERF_TEST_P(BruteForceMatcherFixture, DISABLED_knnMatch, |
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OCL_BFMATCHER_TYPICAL_MAT_SIZES) // TODO too many outliers |
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{ |
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const Size srcSize = GetParam(); |
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vector<vector<DMatch> > matches(2); |
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Mat query(srcSize, CV_32F), train(srcSize, CV_32F); |
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randu(query, 0.0f, 1.0f); |
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randu(train, 0.0f, 1.0f); |
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declare.in(query, train); |
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if (srcSize.height == 2000) |
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declare.time(8); |
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if (RUN_PLAIN_IMPL) |
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{ |
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BFMatcher matcher (NORM_L2); |
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TEST_CYCLE() matcher.knnMatch(query, train, matches, 2); |
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std::vector<DMatch> & matches0 = matches[0], & matches1 = matches[1]; |
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SANITY_CHECK_MATCHES(matches0); |
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SANITY_CHECK_MATCHES(matches1); |
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} |
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else if (RUN_OCL_IMPL) |
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{ |
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ocl::BruteForceMatcher_OCL_base oclMatcher(ocl::BruteForceMatcher_OCL_base::L2Dist); |
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ocl::oclMat oclQuery(query), oclTrain(train); |
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TEST_CYCLE() oclMatcher.knnMatch(oclQuery, oclTrain, matches, 2); |
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std::vector<DMatch> & matches0 = matches[0], & matches1 = matches[1]; |
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SANITY_CHECK_MATCHES(matches0); |
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SANITY_CHECK_MATCHES(matches1); |
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} |
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else |
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OCL_PERF_ELSE |
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} |
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PERF_TEST_P(BruteForceMatcherFixture, DISABLED_radiusMatch, |
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OCL_BFMATCHER_TYPICAL_MAT_SIZES) // TODO too many outliers |
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{ |
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const Size srcSize = GetParam(); |
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const float max_distance = 2.0f; |
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vector<vector<DMatch> > matches(2); |
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Mat query(srcSize, CV_32F), train(srcSize, CV_32F); |
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declare.in(query, train); |
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Mat trainIdx, distance, allDist; |
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randu(query, 0.0f, 1.0f); |
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randu(train, 0.0f, 1.0f); |
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if (RUN_PLAIN_IMPL) |
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{ |
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BFMatcher matcher (NORM_L2); |
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TEST_CYCLE() matcher.radiusMatch(query, matches, max_distance); |
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std::vector<DMatch> & matches0 = matches[0], & matches1 = matches[1]; |
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SANITY_CHECK_MATCHES(matches0); |
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SANITY_CHECK_MATCHES(matches1); |
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} |
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else if (RUN_OCL_IMPL) |
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{ |
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ocl::oclMat oclQuery(query), oclTrain(train); |
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ocl::BruteForceMatcher_OCL_base oclMatcher(ocl::BruteForceMatcher_OCL_base::L2Dist); |
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TEST_CYCLE() oclMatcher.radiusMatch(oclQuery, oclTrain, matches, max_distance); |
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std::vector<DMatch> & matches0 = matches[0], & matches1 = matches[1]; |
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SANITY_CHECK_MATCHES(matches0); |
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SANITY_CHECK_MATCHES(matches1); |
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} |
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else |
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OCL_PERF_ELSE |
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} |
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#undef OCL_BFMATCHER_TYPICAL_MAT_SIZES
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