mirror of https://github.com/opencv/opencv.git
Open Source Computer Vision Library
https://opencv.org/
You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
167 lines
5.6 KiB
167 lines
5.6 KiB
/*M/////////////////////////////////////////////////////////////////////////////////////// |
|
// |
|
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. |
|
// |
|
// By downloading, copying, installing or using the software you agree to this license. |
|
// If you do not agree to this license, do not download, install, |
|
// copy or use the software. |
|
// |
|
// |
|
// License Agreement |
|
// For Open Source Computer Vision Library |
|
// |
|
// Copyright (C) 2010-2012, Multicoreware, Inc., all rights reserved. |
|
// Copyright (C) 2010-2012, Advanced Micro Devices, Inc., all rights reserved. |
|
// Third party copyrights are property of their respective owners. |
|
// |
|
// @Authors |
|
// Fangfang Bai, fangfang@multicorewareinc.com |
|
// Jin Ma, jin@multicorewareinc.com |
|
// |
|
// Redistribution and use in source and binary forms, with or without modification, |
|
// are permitted provided that the following conditions are met: |
|
// |
|
// * Redistribution's of source code must retain the above copyright notice, |
|
// this list of conditions and the following disclaimer. |
|
// |
|
// * Redistribution's in binary form must reproduce the above copyright notice, |
|
// this list of conditions and the following disclaimer in the documentation |
|
// and/or other oclMaterials provided with the distribution. |
|
// |
|
// * The name of the copyright holders may not be used to endorse or promote products |
|
// derived from this software without specific prior written permission. |
|
// |
|
// This software is provided by the copyright holders and contributors as is and |
|
// any express or implied warranties, including, but not limited to, the implied |
|
// warranties of merchantability and fitness for a particular purpose are disclaimed. |
|
// In no event shall the Intel Corporation or contributors be liable for any direct, |
|
// indirect, incidental, special, exemplary, or consequential damages |
|
// (including, but not limited to, procurement of substitute goods or services; |
|
// loss of use, data, or profits; or business interruption) however caused |
|
// and on any theory of liability, whether in contract, strict liability, |
|
// or tort (including negligence or otherwise) arising in any way out of |
|
// the use of this software, even if advised of the possibility of such damage. |
|
// |
|
//M*/ |
|
#include "precomp.hpp" |
|
|
|
//////////////////// BruteForceMatch ///////////////// |
|
PERFTEST(BruteForceMatcher) |
|
{ |
|
Mat trainIdx_cpu; |
|
Mat distance_cpu; |
|
Mat allDist_cpu; |
|
Mat nMatches_cpu; |
|
|
|
for (int size = Min_Size; size <= Max_Size; size *= Multiple) |
|
{ |
|
// Init CPU matcher |
|
int desc_len = 64; |
|
|
|
BFMatcher matcher(NORM_L2); |
|
|
|
Mat query; |
|
gen(query, size, desc_len, CV_32F, 0, 1); |
|
|
|
Mat train; |
|
gen(train, size, desc_len, CV_32F, 0, 1); |
|
// Output |
|
vector< vector<DMatch> > matches(2); |
|
vector< vector<DMatch> > d_matches(2); |
|
// Init GPU matcher |
|
ocl::BruteForceMatcher_OCL_base d_matcher(ocl::BruteForceMatcher_OCL_base::L2Dist); |
|
|
|
ocl::oclMat d_query(query); |
|
ocl::oclMat d_train(train); |
|
|
|
ocl::oclMat d_trainIdx, d_distance, d_allDist, d_nMatches; |
|
|
|
SUBTEST << size << "; match"; |
|
|
|
matcher.match(query, train, matches[0]); |
|
|
|
CPU_ON; |
|
matcher.match(query, train, matches[0]); |
|
CPU_OFF; |
|
|
|
WARMUP_ON; |
|
d_matcher.matchSingle(d_query, d_train, d_trainIdx, d_distance); |
|
WARMUP_OFF; |
|
|
|
GPU_ON; |
|
d_matcher.matchSingle(d_query, d_train, d_trainIdx, d_distance); |
|
GPU_OFF; |
|
|
|
GPU_FULL_ON; |
|
d_query.upload(query); |
|
d_train.upload(train); |
|
d_matcher.match(d_query, d_train, d_matches[0]); |
|
GPU_FULL_OFF; |
|
|
|
int diff = abs((int)d_matches[0].size() - (int)matches[0].size()); |
|
if(diff == 0) |
|
TestSystem::instance().setAccurate(1, 0); |
|
else |
|
TestSystem::instance().setAccurate(0, diff); |
|
|
|
SUBTEST << size << "; knnMatch"; |
|
|
|
matcher.knnMatch(query, train, matches, 2); |
|
|
|
CPU_ON; |
|
matcher.knnMatch(query, train, matches, 2); |
|
CPU_OFF; |
|
|
|
WARMUP_ON; |
|
d_matcher.knnMatchSingle(d_query, d_train, d_trainIdx, d_distance, d_allDist, 2); |
|
WARMUP_OFF; |
|
|
|
GPU_ON; |
|
d_matcher.knnMatchSingle(d_query, d_train, d_trainIdx, d_distance, d_allDist, 2); |
|
GPU_OFF; |
|
|
|
GPU_FULL_ON; |
|
d_query.upload(query); |
|
d_train.upload(train); |
|
d_matcher.knnMatch(d_query, d_train, d_matches, 2); |
|
GPU_FULL_OFF; |
|
|
|
diff = abs((int)d_matches[0].size() - (int)matches[0].size()); |
|
if(diff == 0) |
|
TestSystem::instance().setAccurate(1, 0); |
|
else |
|
TestSystem::instance().setAccurate(0, diff); |
|
|
|
SUBTEST << size << "; radiusMatch"; |
|
|
|
float max_distance = 2.0f; |
|
|
|
matcher.radiusMatch(query, train, matches, max_distance); |
|
|
|
CPU_ON; |
|
matcher.radiusMatch(query, train, matches, max_distance); |
|
CPU_OFF; |
|
|
|
d_trainIdx.release(); |
|
|
|
WARMUP_ON; |
|
d_matcher.radiusMatchSingle(d_query, d_train, d_trainIdx, d_distance, d_nMatches, max_distance); |
|
WARMUP_OFF; |
|
|
|
GPU_ON; |
|
d_matcher.radiusMatchSingle(d_query, d_train, d_trainIdx, d_distance, d_nMatches, max_distance); |
|
GPU_OFF; |
|
|
|
GPU_FULL_ON; |
|
d_query.upload(query); |
|
d_train.upload(train); |
|
d_matcher.radiusMatch(d_query, d_train, d_matches, max_distance); |
|
GPU_FULL_OFF; |
|
|
|
diff = abs((int)d_matches[0].size() - (int)matches[0].size()); |
|
if(diff == 0) |
|
TestSystem::instance().setAccurate(1, 0); |
|
else |
|
TestSystem::instance().setAccurate(0, diff); |
|
} |
|
} |