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185 lines
5.3 KiB
C++
185 lines
5.3 KiB
C++
/*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) 2014, Biagio Montesano, 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 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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namespace opencv_test { namespace {
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#define QUERY_DES_COUNT 300
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#define DIM 32
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#define COUNT_FACTOR 4
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#define RADIUS 3
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void generateData( Mat& query, Mat& train );
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uchar invertSingleBits( uchar dividend_char, int numBits );
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/* invert numBits bits in input char */
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uchar invertSingleBits( uchar dividend_char, int numBits )
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{
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std::vector<int> bin_vector;
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long dividend;
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long bin_num;
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/* convert input char to a long */
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dividend = (long) dividend_char;
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/*if a 0 has been obtained, just generate a 8-bit long vector of zeros */
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if( dividend == 0 )
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bin_vector = std::vector<int>( 8, 0 );
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/* else, apply classic decimal to binary conversion */
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else
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{
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while ( dividend >= 1 )
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{
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bin_num = dividend % 2;
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dividend /= 2;
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bin_vector.push_back( bin_num );
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}
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}
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/* ensure that binary vector always has length 8 */
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if( bin_vector.size() < 8 )
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{
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std::vector<int> zeros( 8 - bin_vector.size(), 0 );
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bin_vector.insert( bin_vector.end(), zeros.begin(), zeros.end() );
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}
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/* invert numBits bits */
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for ( int index = 0; index < numBits; index++ )
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{
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if( bin_vector[index] == 0 )
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bin_vector[index] = 1;
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else
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bin_vector[index] = 0;
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}
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/* reconvert to decimal */
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uchar result = 0;
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for ( int i = (int) bin_vector.size() - 1; i >= 0; i-- )
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result += (uchar) ( bin_vector[i] * ( 1 << i ) );
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return result;
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}
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void generateData( Mat& query, Mat& train )
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{
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RNG& rng = theRNG();
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Mat buf( QUERY_DES_COUNT, DIM, CV_8UC1 );
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rng.fill( buf, RNG::UNIFORM, Scalar( 0 ), Scalar( 255 ) );
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buf.convertTo( query, CV_8UC1 );
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for ( int i = 0; i < query.rows; i++ )
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{
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for ( int j = 0; j < COUNT_FACTOR; j++ )
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{
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train.push_back( query.row( i ) );
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int randCol = rand() % 32;
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uchar u = query.at<uchar>( i, randCol );
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uchar modified_u = invertSingleBits( u, j + 1 );
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train.at<uchar>( i * COUNT_FACTOR + j, randCol ) = modified_u;
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}
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}
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}
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PERF_TEST(matching, single_match)
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{
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Mat query, train;
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std::vector<DMatch> dm;
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Ptr<BinaryDescriptorMatcher> bd = BinaryDescriptorMatcher::createBinaryDescriptorMatcher();
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generateData( query, train );
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TEST_CYCLE()
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bd->match( query, train, dm );
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SANITY_CHECK_NOTHING();
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}
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PERF_TEST(knn_matching, knn_match_distances_test)
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{
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Mat query, train, distances;
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std::vector<std::vector<DMatch> > dm;
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Ptr<BinaryDescriptorMatcher> bd = BinaryDescriptorMatcher::createBinaryDescriptorMatcher();
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generateData( query, train );
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TEST_CYCLE()
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{
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bd->knnMatch( query, train, dm, QUERY_DES_COUNT );
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for ( int i = 0; i < (int) dm.size(); i++ )
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{
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for ( int j = 0; j < (int) dm[i].size(); j++ )
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distances.push_back( dm[i][j].distance );
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}
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}
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SANITY_CHECK_NOTHING();
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}
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PERF_TEST(radius_match, radius_match_distances_test)
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{
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Mat query, train, distances;
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std::vector<std::vector<DMatch> > dm;
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Ptr<BinaryDescriptorMatcher> bd = BinaryDescriptorMatcher::createBinaryDescriptorMatcher();
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generateData( query, train );
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TEST_CYCLE()
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{
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bd->radiusMatch( query, train, dm, RADIUS );
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for ( int i = 0; i < (int) dm.size(); i++ )
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{
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for ( int j = 0; j < (int) dm[i].size(); j++ )
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distances.push_back( dm[i][j].distance );
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}
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}
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SANITY_CHECK_NOTHING();
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}
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}} // namespace
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