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Open Source Computer Vision Library
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167 lines
5.6 KiB
167 lines
5.6 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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//////////////////// BruteForceMatch ///////////////// |
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PERFTEST(BruteForceMatcher) |
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{ |
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Mat trainIdx_cpu; |
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Mat distance_cpu; |
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Mat allDist_cpu; |
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Mat nMatches_cpu; |
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for (int size = Min_Size; size <= Max_Size; size *= Multiple) |
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{ |
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// Init CPU matcher |
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int desc_len = 64; |
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BFMatcher matcher(NORM_L2); |
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Mat query; |
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gen(query, size, desc_len, CV_32F, 0, 1); |
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Mat train; |
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gen(train, size, desc_len, CV_32F, 0, 1); |
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// Output |
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vector< vector<DMatch> > matches(2); |
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vector< vector<DMatch> > d_matches(2); |
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// Init GPU matcher |
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ocl::BruteForceMatcher_OCL_base d_matcher(ocl::BruteForceMatcher_OCL_base::L2Dist); |
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ocl::oclMat d_query(query); |
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ocl::oclMat d_train(train); |
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ocl::oclMat d_trainIdx, d_distance, d_allDist, d_nMatches; |
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SUBTEST << size << "; match"; |
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matcher.match(query, train, matches[0]); |
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CPU_ON; |
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matcher.match(query, train, matches[0]); |
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CPU_OFF; |
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WARMUP_ON; |
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d_matcher.matchSingle(d_query, d_train, d_trainIdx, d_distance); |
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WARMUP_OFF; |
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GPU_ON; |
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d_matcher.matchSingle(d_query, d_train, d_trainIdx, d_distance); |
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GPU_OFF; |
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GPU_FULL_ON; |
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d_query.upload(query); |
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d_train.upload(train); |
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d_matcher.match(d_query, d_train, d_matches[0]); |
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GPU_FULL_OFF; |
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int diff = abs((int)d_matches[0].size() - (int)matches[0].size()); |
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if(diff == 0) |
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TestSystem::instance().setAccurate(1, 0); |
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else |
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TestSystem::instance().setAccurate(0, diff); |
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SUBTEST << size << "; knnMatch"; |
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matcher.knnMatch(query, train, matches, 2); |
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CPU_ON; |
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matcher.knnMatch(query, train, matches, 2); |
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CPU_OFF; |
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WARMUP_ON; |
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d_matcher.knnMatchSingle(d_query, d_train, d_trainIdx, d_distance, d_allDist, 2); |
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WARMUP_OFF; |
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GPU_ON; |
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d_matcher.knnMatchSingle(d_query, d_train, d_trainIdx, d_distance, d_allDist, 2); |
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GPU_OFF; |
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GPU_FULL_ON; |
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d_query.upload(query); |
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d_train.upload(train); |
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d_matcher.knnMatch(d_query, d_train, d_matches, 2); |
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GPU_FULL_OFF; |
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diff = abs((int)d_matches[0].size() - (int)matches[0].size()); |
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if(diff == 0) |
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TestSystem::instance().setAccurate(1, 0); |
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else |
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TestSystem::instance().setAccurate(0, diff); |
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SUBTEST << size << "; radiusMatch"; |
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float max_distance = 2.0f; |
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matcher.radiusMatch(query, train, matches, max_distance); |
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CPU_ON; |
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matcher.radiusMatch(query, train, matches, max_distance); |
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CPU_OFF; |
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d_trainIdx.release(); |
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WARMUP_ON; |
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d_matcher.radiusMatchSingle(d_query, d_train, d_trainIdx, d_distance, d_nMatches, max_distance); |
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WARMUP_OFF; |
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GPU_ON; |
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d_matcher.radiusMatchSingle(d_query, d_train, d_trainIdx, d_distance, d_nMatches, max_distance); |
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GPU_OFF; |
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GPU_FULL_ON; |
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d_query.upload(query); |
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d_train.upload(train); |
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d_matcher.radiusMatch(d_query, d_train, d_matches, max_distance); |
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GPU_FULL_OFF; |
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diff = abs((int)d_matches[0].size() - (int)matches[0].size()); |
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if(diff == 0) |
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TestSystem::instance().setAccurate(1, 0); |
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else |
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TestSystem::instance().setAccurate(0, diff); |
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} |
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} |