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.
544 lines
20 KiB
544 lines
20 KiB
14 years ago
|
/*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.
|
||
|
|
//
|
||
|
|
//
|
||
|
|
// Intel License Agreement
|
||
|
|
// For Open Source Computer Vision Library
|
||
|
|
//
|
||
|
|
// Copyright (C) 2000, Intel Corporation, all rights reserved.
|
||
|
|
// Third party copyrights are property of their respective owners.
|
||
|
|
//
|
||
|
|
// 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 materials provided with the distribution.
|
||
|
|
//
|
||
|
|
// * The name of Intel Corporation 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*/
|
||
|
14 years ago
|
|
||
|
14 years ago
|
#include "test_precomp.hpp"
|
||
|
|
#include "opencv2/highgui/highgui.hpp"
|
||
|
|
|
||
|
|
using namespace std;
|
||
|
|
using namespace cv;
|
||
|
|
|
||
|
|
const string FEATURES2D_DIR = "features2d";
|
||
|
|
const string IMAGE_FILENAME = "tsukuba.png";
|
||
|
|
|
||
|
|
/****************************************************************************************\
|
||
|
|
* Algorithmic tests for descriptor matchers *
|
||
|
|
\****************************************************************************************/
|
||
|
|
class CV_DescriptorMatcherTest : public cvtest::BaseTest
|
||
|
|
{
|
||
|
|
public:
|
||
|
14 years ago
|
CV_DescriptorMatcherTest( const string& _name, const Ptr<DescriptorMatcher>& _dmatcher, float _badPart ) :
|
||
|
14 years ago
|
badPart(_badPart), name(_name), dmatcher(_dmatcher)
|
||
|
14 years ago
|
{}
|
||
|
|
protected:
|
||
|
|
static const int dim = 500;
|
||
|
|
static const int queryDescCount = 300; // must be even number because we split train data in some cases in two
|
||
|
|
static const int countFactor = 4; // do not change it
|
||
|
|
const float badPart;
|
||
|
|
|
||
|
|
virtual void run( int );
|
||
|
|
void generateData( Mat& query, Mat& train );
|
||
|
|
|
||
|
|
void emptyDataTest();
|
||
|
|
void matchTest( const Mat& query, const Mat& train );
|
||
|
|
void knnMatchTest( const Mat& query, const Mat& train );
|
||
|
|
void radiusMatchTest( const Mat& query, const Mat& train );
|
||
|
|
|
||
|
14 years ago
|
string name;
|
||
|
14 years ago
|
Ptr<DescriptorMatcher> dmatcher;
|
||
|
14 years ago
|
|
||
|
14 years ago
|
private:
|
||
|
|
CV_DescriptorMatcherTest& operator=(const CV_DescriptorMatcherTest&) { return *this; }
|
||
|
|
};
|
||
|
|
|
||
|
|
void CV_DescriptorMatcherTest::emptyDataTest()
|
||
|
|
{
|
||
|
|
assert( !dmatcher.empty() );
|
||
|
|
Mat queryDescriptors, trainDescriptors, mask;
|
||
|
|
vector<Mat> trainDescriptorCollection, masks;
|
||
|
|
vector<DMatch> matches;
|
||
|
|
vector<vector<DMatch> > vmatches;
|
||
|
|
|
||
|
|
try
|
||
|
|
{
|
||
|
|
dmatcher->match( queryDescriptors, trainDescriptors, matches, mask );
|
||
|
|
}
|
||
|
|
catch(...)
|
||
|
|
{
|
||
|
|
ts->printf( cvtest::TS::LOG, "match() on empty descriptors must not generate exception (1).\n" );
|
||
|
|
ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_OUTPUT );
|
||
|
|
}
|
||
|
|
|
||
|
|
try
|
||
|
|
{
|
||
|
|
dmatcher->knnMatch( queryDescriptors, trainDescriptors, vmatches, 2, mask );
|
||
|
|
}
|
||
|
|
catch(...)
|
||
|
|
{
|
||
|
|
ts->printf( cvtest::TS::LOG, "knnMatch() on empty descriptors must not generate exception (1).\n" );
|
||
|
|
ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_OUTPUT );
|
||
|
|
}
|
||
|
|
|
||
|
|
try
|
||
|
|
{
|
||
|
|
dmatcher->radiusMatch( queryDescriptors, trainDescriptors, vmatches, 10.f, mask );
|
||
|
|
}
|
||
|
|
catch(...)
|
||
|
|
{
|
||
|
|
ts->printf( cvtest::TS::LOG, "radiusMatch() on empty descriptors must not generate exception (1).\n" );
|
||
|
|
ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_OUTPUT );
|
||
|
|
}
|
||
|
|
|
||
|
|
try
|
||
|
|
{
|
||
|
|
dmatcher->add( trainDescriptorCollection );
|
||
|
|
}
|
||
|
|
catch(...)
|
||
|
|
{
|
||
|
|
ts->printf( cvtest::TS::LOG, "add() on empty descriptors must not generate exception.\n" );
|
||
|
|
ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_OUTPUT );
|
||
|
|
}
|
||
|
|
|
||
|
|
try
|
||
|
|
{
|
||
|
|
dmatcher->match( queryDescriptors, matches, masks );
|
||
|
|
}
|
||
|
|
catch(...)
|
||
|
|
{
|
||
|
|
ts->printf( cvtest::TS::LOG, "match() on empty descriptors must not generate exception (2).\n" );
|
||
|
|
ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_OUTPUT );
|
||
|
|
}
|
||
|
|
|
||
|
|
try
|
||
|
|
{
|
||
|
|
dmatcher->knnMatch( queryDescriptors, vmatches, 2, masks );
|
||
|
|
}
|
||
|
|
catch(...)
|
||
|
|
{
|
||
|
|
ts->printf( cvtest::TS::LOG, "knnMatch() on empty descriptors must not generate exception (2).\n" );
|
||
|
|
ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_OUTPUT );
|
||
|
|
}
|
||
|
|
|
||
|
|
try
|
||
|
|
{
|
||
|
|
dmatcher->radiusMatch( queryDescriptors, vmatches, 10.f, masks );
|
||
|
|
}
|
||
|
|
catch(...)
|
||
|
|
{
|
||
|
|
ts->printf( cvtest::TS::LOG, "radiusMatch() on empty descriptors must not generate exception (2).\n" );
|
||
|
|
ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_OUTPUT );
|
||
|
|
}
|
||
|
|
|
||
|
|
}
|
||
|
|
|
||
|
|
void CV_DescriptorMatcherTest::generateData( Mat& query, Mat& train )
|
||
|
|
{
|
||
|
|
RNG& rng = theRNG();
|
||
|
|
|
||
|
|
// Generate query descriptors randomly.
|
||
|
|
// Descriptor vector elements are integer values.
|
||
|
|
Mat buf( queryDescCount, dim, CV_32SC1 );
|
||
|
|
rng.fill( buf, RNG::UNIFORM, Scalar::all(0), Scalar(3) );
|
||
|
|
buf.convertTo( query, CV_32FC1 );
|
||
|
|
|
||
|
|
// Generate train decriptors as follows:
|
||
|
|
// copy each query descriptor to train set countFactor times
|
||
|
|
// and perturb some one element of the copied descriptors in
|
||
|
|
// in ascending order. General boundaries of the perturbation
|
||
|
|
// are (0.f, 1.f).
|
||
|
|
train.create( query.rows*countFactor, query.cols, CV_32FC1 );
|
||
|
|
float step = 1.f / countFactor;
|
||
|
|
for( int qIdx = 0; qIdx < query.rows; qIdx++ )
|
||
|
|
{
|
||
|
|
Mat queryDescriptor = query.row(qIdx);
|
||
|
|
for( int c = 0; c < countFactor; c++ )
|
||
|
|
{
|
||
|
|
int tIdx = qIdx * countFactor + c;
|
||
|
|
Mat trainDescriptor = train.row(tIdx);
|
||
|
|
queryDescriptor.copyTo( trainDescriptor );
|
||
|
|
int elem = rng(dim);
|
||
|
|
float diff = rng.uniform( step*c, step*(c+1) );
|
||
|
|
trainDescriptor.at<float>(0, elem) += diff;
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
void CV_DescriptorMatcherTest::matchTest( const Mat& query, const Mat& train )
|
||
|
|
{
|
||
|
|
dmatcher->clear();
|
||
|
|
|
||
|
|
// test const version of match()
|
||
|
|
{
|
||
|
|
vector<DMatch> matches;
|
||
|
|
dmatcher->match( query, train, matches );
|
||
|
|
|
||
|
|
if( (int)matches.size() != queryDescCount )
|
||
|
|
{
|
||
|
|
ts->printf(cvtest::TS::LOG, "Incorrect matches count while test match() function (1).\n");
|
||
|
|
ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_OUTPUT );
|
||
|
|
}
|
||
|
|
else
|
||
|
|
{
|
||
|
|
int badCount = 0;
|
||
|
|
for( size_t i = 0; i < matches.size(); i++ )
|
||
|
|
{
|
||
|
13 years ago
|
DMatch& match = matches[i];
|
||
|
14 years ago
|
if( (match.queryIdx != (int)i) || (match.trainIdx != (int)i*countFactor) || (match.imgIdx != 0) )
|
||
|
|
badCount++;
|
||
|
|
}
|
||
|
|
if( (float)badCount > (float)queryDescCount*badPart )
|
||
|
|
{
|
||
|
|
ts->printf( cvtest::TS::LOG, "%f - too large bad matches part while test match() function (1).\n",
|
||
|
|
(float)badCount/(float)queryDescCount );
|
||
|
|
ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_OUTPUT );
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
13 years ago
|
// test const version of match() for the same query and test descriptors
|
||
|
|
{
|
||
|
|
vector<DMatch> matches;
|
||
|
|
dmatcher->match( query, query, matches );
|
||
|
|
|
||
|
|
if( (int)matches.size() != query.rows )
|
||
|
|
{
|
||
|
|
ts->printf(cvtest::TS::LOG, "Incorrect matches count while test match() function for the same query and test descriptors (1).\n");
|
||
|
|
ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_OUTPUT );
|
||
|
|
}
|
||
|
|
else
|
||
|
|
{
|
||
|
|
for( size_t i = 0; i < matches.size(); i++ )
|
||
|
|
{
|
||
|
|
DMatch& match = matches[i];
|
||
|
13 years ago
|
//std::cout << match.distance << std::endl;
|
||
|
13 years ago
|
|
||
|
|
if( match.queryIdx != (int)i || match.trainIdx != (int)i || std::abs(match.distance) > FLT_EPSILON )
|
||
|
|
{
|
||
|
|
ts->printf( cvtest::TS::LOG, "Bad match (i=%d, queryIdx=%d, trainIdx=%d, distance=%f) while test match() function for the same query and test descriptors (1).\n",
|
||
|
|
i, match.queryIdx, match.trainIdx, match.distance );
|
||
|
|
ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_OUTPUT );
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
14 years ago
|
// test version of match() with add()
|
||
|
|
{
|
||
|
|
vector<DMatch> matches;
|
||
|
|
// make add() twice to test such case
|
||
|
|
dmatcher->add( vector<Mat>(1,train.rowRange(0, train.rows/2)) );
|
||
|
|
dmatcher->add( vector<Mat>(1,train.rowRange(train.rows/2, train.rows)) );
|
||
|
|
// prepare masks (make first nearest match illegal)
|
||
|
|
vector<Mat> masks(2);
|
||
|
|
for(int mi = 0; mi < 2; mi++ )
|
||
|
|
{
|
||
|
|
masks[mi] = Mat(query.rows, train.rows/2, CV_8UC1, Scalar::all(1));
|
||
|
|
for( int di = 0; di < queryDescCount/2; di++ )
|
||
|
|
masks[mi].col(di*countFactor).setTo(Scalar::all(0));
|
||
|
|
}
|
||
|
|
|
||
|
|
dmatcher->match( query, matches, masks );
|
||
|
|
|
||
|
|
if( (int)matches.size() != queryDescCount )
|
||
|
|
{
|
||
|
|
ts->printf(cvtest::TS::LOG, "Incorrect matches count while test match() function (2).\n");
|
||
|
|
ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_OUTPUT );
|
||
|
|
}
|
||
|
|
else
|
||
|
|
{
|
||
|
|
int badCount = 0;
|
||
|
|
for( size_t i = 0; i < matches.size(); i++ )
|
||
|
|
{
|
||
|
13 years ago
|
DMatch& match = matches[i];
|
||
|
14 years ago
|
int shift = dmatcher->isMaskSupported() ? 1 : 0;
|
||
|
|
{
|
||
|
|
if( i < queryDescCount/2 )
|
||
|
|
{
|
||
|
|
if( (match.queryIdx != (int)i) || (match.trainIdx != (int)i*countFactor + shift) || (match.imgIdx != 0) )
|
||
|
|
badCount++;
|
||
|
|
}
|
||
|
|
else
|
||
|
|
{
|
||
|
|
if( (match.queryIdx != (int)i) || (match.trainIdx != ((int)i-queryDescCount/2)*countFactor + shift) || (match.imgIdx != 1) )
|
||
|
|
badCount++;
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
if( (float)badCount > (float)queryDescCount*badPart )
|
||
|
|
{
|
||
|
|
ts->printf( cvtest::TS::LOG, "%f - too large bad matches part while test match() function (2).\n",
|
||
|
|
(float)badCount/(float)queryDescCount );
|
||
|
|
ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
void CV_DescriptorMatcherTest::knnMatchTest( const Mat& query, const Mat& train )
|
||
|
|
{
|
||
|
|
dmatcher->clear();
|
||
|
|
|
||
|
|
// test const version of knnMatch()
|
||
|
|
{
|
||
|
|
const int knn = 3;
|
||
|
|
|
||
|
|
vector<vector<DMatch> > matches;
|
||
|
|
dmatcher->knnMatch( query, train, matches, knn );
|
||
|
|
|
||
|
|
if( (int)matches.size() != queryDescCount )
|
||
|
|
{
|
||
|
|
ts->printf(cvtest::TS::LOG, "Incorrect matches count while test knnMatch() function (1).\n");
|
||
|
|
ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_OUTPUT );
|
||
|
|
}
|
||
|
|
else
|
||
|
|
{
|
||
|
|
int badCount = 0;
|
||
|
|
for( size_t i = 0; i < matches.size(); i++ )
|
||
|
|
{
|
||
|
|
if( (int)matches[i].size() != knn )
|
||
|
|
badCount++;
|
||
|
|
else
|
||
|
|
{
|
||
|
|
int localBadCount = 0;
|
||
|
|
for( int k = 0; k < knn; k++ )
|
||
|
|
{
|
||
|
13 years ago
|
DMatch& match = matches[i][k];
|
||
|
14 years ago
|
if( (match.queryIdx != (int)i) || (match.trainIdx != (int)i*countFactor+k) || (match.imgIdx != 0) )
|
||
|
|
localBadCount++;
|
||
|
|
}
|
||
|
|
badCount += localBadCount > 0 ? 1 : 0;
|
||
|
|
}
|
||
|
|
}
|
||
|
|
if( (float)badCount > (float)queryDescCount*badPart )
|
||
|
|
{
|
||
|
|
ts->printf( cvtest::TS::LOG, "%f - too large bad matches part while test knnMatch() function (1).\n",
|
||
|
|
(float)badCount/(float)queryDescCount );
|
||
|
|
ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_OUTPUT );
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
// test version of knnMatch() with add()
|
||
|
|
{
|
||
|
|
const int knn = 2;
|
||
|
|
vector<vector<DMatch> > matches;
|
||
|
|
// make add() twice to test such case
|
||
|
|
dmatcher->add( vector<Mat>(1,train.rowRange(0, train.rows/2)) );
|
||
|
|
dmatcher->add( vector<Mat>(1,train.rowRange(train.rows/2, train.rows)) );
|
||
|
|
// prepare masks (make first nearest match illegal)
|
||
|
|
vector<Mat> masks(2);
|
||
|
|
for(int mi = 0; mi < 2; mi++ )
|
||
|
|
{
|
||
|
|
masks[mi] = Mat(query.rows, train.rows/2, CV_8UC1, Scalar::all(1));
|
||
|
|
for( int di = 0; di < queryDescCount/2; di++ )
|
||
|
|
masks[mi].col(di*countFactor).setTo(Scalar::all(0));
|
||
|
|
}
|
||
|
|
|
||
|
|
dmatcher->knnMatch( query, matches, knn, masks );
|
||
|
|
|
||
|
|
if( (int)matches.size() != queryDescCount )
|
||
|
|
{
|
||
|
|
ts->printf(cvtest::TS::LOG, "Incorrect matches count while test knnMatch() function (2).\n");
|
||
|
|
ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_OUTPUT );
|
||
|
|
}
|
||
|
|
else
|
||
|
|
{
|
||
|
|
int badCount = 0;
|
||
|
|
int shift = dmatcher->isMaskSupported() ? 1 : 0;
|
||
|
|
for( size_t i = 0; i < matches.size(); i++ )
|
||
|
|
{
|
||
|
|
if( (int)matches[i].size() != knn )
|
||
|
|
badCount++;
|
||
|
|
else
|
||
|
|
{
|
||
|
|
int localBadCount = 0;
|
||
|
|
for( int k = 0; k < knn; k++ )
|
||
|
|
{
|
||
|
13 years ago
|
DMatch& match = matches[i][k];
|
||
|
14 years ago
|
{
|
||
|
|
if( i < queryDescCount/2 )
|
||
|
|
{
|
||
|
|
if( (match.queryIdx != (int)i) || (match.trainIdx != (int)i*countFactor + k + shift) ||
|
||
|
|
(match.imgIdx != 0) )
|
||
|
|
localBadCount++;
|
||
|
|
}
|
||
|
|
else
|
||
|
|
{
|
||
|
|
if( (match.queryIdx != (int)i) || (match.trainIdx != ((int)i-queryDescCount/2)*countFactor + k + shift) ||
|
||
|
|
(match.imgIdx != 1) )
|
||
|
|
localBadCount++;
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
badCount += localBadCount > 0 ? 1 : 0;
|
||
|
|
}
|
||
|
|
}
|
||
|
|
if( (float)badCount > (float)queryDescCount*badPart )
|
||
|
|
{
|
||
|
|
ts->printf( cvtest::TS::LOG, "%f - too large bad matches part while test knnMatch() function (2).\n",
|
||
|
|
(float)badCount/(float)queryDescCount );
|
||
|
|
ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
void CV_DescriptorMatcherTest::radiusMatchTest( const Mat& query, const Mat& train )
|
||
|
|
{
|
||
|
|
dmatcher->clear();
|
||
|
|
// test const version of match()
|
||
|
|
{
|
||
|
|
const float radius = 1.f/countFactor;
|
||
|
|
vector<vector<DMatch> > matches;
|
||
|
|
dmatcher->radiusMatch( query, train, matches, radius );
|
||
|
|
|
||
|
|
if( (int)matches.size() != queryDescCount )
|
||
|
|
{
|
||
|
|
ts->printf(cvtest::TS::LOG, "Incorrect matches count while test radiusMatch() function (1).\n");
|
||
|
|
ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_OUTPUT );
|
||
|
|
}
|
||
|
|
else
|
||
|
|
{
|
||
|
|
int badCount = 0;
|
||
|
|
for( size_t i = 0; i < matches.size(); i++ )
|
||
|
|
{
|
||
|
|
if( (int)matches[i].size() != 1 )
|
||
|
|
badCount++;
|
||
|
|
else
|
||
|
|
{
|
||
|
13 years ago
|
DMatch& match = matches[i][0];
|
||
|
14 years ago
|
if( (match.queryIdx != (int)i) || (match.trainIdx != (int)i*countFactor) || (match.imgIdx != 0) )
|
||
|
|
badCount++;
|
||
|
|
}
|
||
|
|
}
|
||
|
|
if( (float)badCount > (float)queryDescCount*badPart )
|
||
|
|
{
|
||
|
|
ts->printf( cvtest::TS::LOG, "%f - too large bad matches part while test radiusMatch() function (1).\n",
|
||
|
|
(float)badCount/(float)queryDescCount );
|
||
|
|
ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_OUTPUT );
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
// test version of match() with add()
|
||
|
|
{
|
||
|
|
int n = 3;
|
||
|
|
const float radius = 1.f/countFactor * n;
|
||
|
|
vector<vector<DMatch> > matches;
|
||
|
|
// make add() twice to test such case
|
||
|
|
dmatcher->add( vector<Mat>(1,train.rowRange(0, train.rows/2)) );
|
||
|
|
dmatcher->add( vector<Mat>(1,train.rowRange(train.rows/2, train.rows)) );
|
||
|
|
// prepare masks (make first nearest match illegal)
|
||
|
|
vector<Mat> masks(2);
|
||
|
|
for(int mi = 0; mi < 2; mi++ )
|
||
|
|
{
|
||
|
|
masks[mi] = Mat(query.rows, train.rows/2, CV_8UC1, Scalar::all(1));
|
||
|
|
for( int di = 0; di < queryDescCount/2; di++ )
|
||
|
|
masks[mi].col(di*countFactor).setTo(Scalar::all(0));
|
||
|
|
}
|
||
|
|
|
||
|
|
dmatcher->radiusMatch( query, matches, radius, masks );
|
||
|
|
|
||
|
13 years ago
|
//int curRes = cvtest::TS::OK;
|
||
|
14 years ago
|
if( (int)matches.size() != queryDescCount )
|
||
|
|
{
|
||
|
|
ts->printf(cvtest::TS::LOG, "Incorrect matches count while test radiusMatch() function (1).\n");
|
||
|
|
ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_OUTPUT );
|
||
|
|
}
|
||
|
|
|
||
|
|
int badCount = 0;
|
||
|
|
int shift = dmatcher->isMaskSupported() ? 1 : 0;
|
||
|
|
int needMatchCount = dmatcher->isMaskSupported() ? n-1 : n;
|
||
|
|
for( size_t i = 0; i < matches.size(); i++ )
|
||
|
|
{
|
||
|
|
if( (int)matches[i].size() != needMatchCount )
|
||
|
|
badCount++;
|
||
|
|
else
|
||
|
|
{
|
||
|
|
int localBadCount = 0;
|
||
|
|
for( int k = 0; k < needMatchCount; k++ )
|
||
|
|
{
|
||
|
13 years ago
|
DMatch& match = matches[i][k];
|
||
|
14 years ago
|
{
|
||
|
|
if( i < queryDescCount/2 )
|
||
|
|
{
|
||
|
|
if( (match.queryIdx != (int)i) || (match.trainIdx != (int)i*countFactor + k + shift) ||
|
||
|
|
(match.imgIdx != 0) )
|
||
|
|
localBadCount++;
|
||
|
|
}
|
||
|
|
else
|
||
|
|
{
|
||
|
|
if( (match.queryIdx != (int)i) || (match.trainIdx != ((int)i-queryDescCount/2)*countFactor + k + shift) ||
|
||
|
|
(match.imgIdx != 1) )
|
||
|
|
localBadCount++;
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
badCount += localBadCount > 0 ? 1 : 0;
|
||
|
|
}
|
||
|
|
}
|
||
|
|
if( (float)badCount > (float)queryDescCount*badPart )
|
||
|
|
{
|
||
|
13 years ago
|
//curRes = cvtest::TS::FAIL_INVALID_OUTPUT;
|
||
|
14 years ago
|
ts->printf( cvtest::TS::LOG, "%f - too large bad matches part while test radiusMatch() function (2).\n",
|
||
|
|
(float)badCount/(float)queryDescCount );
|
||
|
|
ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
void CV_DescriptorMatcherTest::run( int )
|
||
|
|
{
|
||
|
|
Mat query, train;
|
||
|
|
generateData( query, train );
|
||
|
|
|
||
|
|
matchTest( query, train );
|
||
|
|
|
||
|
|
knnMatchTest( query, train );
|
||
|
|
|
||
|
|
radiusMatchTest( query, train );
|
||
|
|
}
|
||
|
|
|
||
|
|
/****************************************************************************************\
|
||
|
|
* Tests registrations *
|
||
|
14 years ago
|
\****************************************************************************************/
|
||
|
|
|
||
|
|
TEST( Features2d_DescriptorMatcher_BruteForce, regression )
|
||
|
14 years ago
|
{
|
||
|
13 years ago
|
CV_DescriptorMatcherTest test( "descriptor-matcher-brute-force", new BFMatcher(NORM_L2), 0.01f );
|
||
|
14 years ago
|
test.safe_run();
|
||
|
|
}
|
||
|
|
|
||
|
14 years ago
|
TEST( Features2d_DescriptorMatcher_FlannBased, regression )
|
||
|
14 years ago
|
{
|
||
|
14 years ago
|
CV_DescriptorMatcherTest test( "descriptor-matcher-flann-based", new FlannBasedMatcher, 0.04f );
|
||
|
14 years ago
|
test.safe_run();
|
||
|
|
}
|