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opencv/samples/cpp/detector_descriptor_evaluation.cpp
Andrey Kamaev c5aba337e9 Fixed number of warnings. Fixed mingw64 build.
2012-06-12 14:46:12 +00:00

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
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//
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// 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.
//
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#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/features2d/features2d.hpp"
#include "opencv2/legacy/legacy.hpp"
#include <limits>
#include <cstdio>
#include <iostream>
#include <fstream>
using namespace std;
using namespace cv;
string data_path;
/****************************************************************************************\
* Functions to evaluate affine covariant detectors and descriptors. *
\****************************************************************************************/
static inline Point2f applyHomography( const Mat_<double>& H, const Point2f& pt )
{
double z = H(2,0)*pt.x + H(2,1)*pt.y + H(2,2);
if( z )
{
double w = 1./z;
return Point2f( (float)((H(0,0)*pt.x + H(0,1)*pt.y + H(0,2))*w),
(float)((H(1,0)*pt.x + H(1,1)*pt.y + H(1,2))*w) );
}
return Point2f( numeric_limits<float>::max(), numeric_limits<float>::max() );
}
static inline void linearizeHomographyAt( const Mat_<double>& H, const Point2f& pt, Mat_<double>& A )
{
A.create(2,2);
double p1 = H(0,0)*pt.x + H(0,1)*pt.y + H(0,2),
p2 = H(1,0)*pt.x + H(1,1)*pt.y + H(1,2),
p3 = H(2,0)*pt.x + H(2,1)*pt.y + H(2,2),
p3_2 = p3*p3;
if( p3 )
{
A(0,0) = H(0,0)/p3 - p1*H(2,0)/p3_2; // fxdx
A(0,1) = H(0,1)/p3 - p1*H(2,1)/p3_2; // fxdy
A(1,0) = H(1,0)/p3 - p2*H(2,0)/p3_2; // fydx
A(1,1) = H(1,1)/p3 - p2*H(2,1)/p3_2; // fydx
}
else
A.setTo(Scalar::all(numeric_limits<double>::max()));
}
static void calcKeyPointProjections( const vector<KeyPoint>& src, const Mat_<double>& H, vector<KeyPoint>& dst )
{
if( !src.empty() )
{
assert( !H.empty() && H.cols == 3 && H.rows == 3);
dst.resize(src.size());
vector<KeyPoint>::const_iterator srcIt = src.begin();
vector<KeyPoint>::iterator dstIt = dst.begin();
for( ; srcIt != src.end(); ++srcIt, ++dstIt )
{
Point2f dstPt = applyHomography(H, srcIt->pt);
float srcSize2 = srcIt->size * srcIt->size;
Mat_<double> M(2, 2);
M(0,0) = M(1,1) = 1./srcSize2;
M(1,0) = M(0,1) = 0;
Mat_<double> invM; invert(M, invM);
Mat_<double> Aff; linearizeHomographyAt(H, srcIt->pt, Aff);
Mat_<double> dstM; invert(Aff*invM*Aff.t(), dstM);
Mat_<double> eval; eigen( dstM, eval );
assert( eval(0,0) && eval(1,0) );
float dstSize = (float)pow(1./(eval(0,0)*eval(1,0)), 0.25);
// TODO: check angle projection
float srcAngleRad = (float)(srcIt->angle*CV_PI/180);
Point2f vec1(cos(srcAngleRad), sin(srcAngleRad)), vec2;
vec2.x = (float)(Aff(0,0)*vec1.x + Aff(0,1)*vec1.y);
vec2.y = (float)(Aff(1,0)*vec1.x + Aff(0,1)*vec1.y);
float dstAngleGrad = fastAtan2(vec2.y, vec2.x);
*dstIt = KeyPoint( dstPt, dstSize, dstAngleGrad, srcIt->response, srcIt->octave, srcIt->class_id );
}
}
}
static void filterKeyPointsByImageSize( vector<KeyPoint>& keypoints, const Size& imgSize )
{
if( !keypoints.empty() )
{
vector<KeyPoint> filtered;
filtered.reserve(keypoints.size());
Rect r(0, 0, imgSize.width, imgSize.height);
vector<KeyPoint>::const_iterator it = keypoints.begin();
for( int i = 0; it != keypoints.end(); ++it, i++ )
if( r.contains(it->pt) )
filtered.push_back(*it);
keypoints.assign(filtered.begin(), filtered.end());
}
}
/****************************************************************************************\
* Detectors evaluation *
\****************************************************************************************/
const int DATASETS_COUNT = 8;
const int TEST_CASE_COUNT = 5;
const string IMAGE_DATASETS_DIR = "detectors_descriptors_evaluation/images_datasets/";
const string DETECTORS_DIR = "detectors_descriptors_evaluation/detectors/";
const string DESCRIPTORS_DIR = "detectors_descriptors_evaluation/descriptors/";
const string KEYPOINTS_DIR = "detectors_descriptors_evaluation/keypoints_datasets/";
const string PARAMS_POSTFIX = "_params.xml";
const string RES_POSTFIX = "_res.xml";
const string REPEAT = "repeatability";
const string CORRESP_COUNT = "correspondence_count";
string DATASET_NAMES[DATASETS_COUNT] = { "bark", "bikes", "boat", "graf", "leuven", "trees", "ubc", "wall"};
string DEFAULT_PARAMS = "default";
string IS_ACTIVE_PARAMS = "isActiveParams";
string IS_SAVE_KEYPOINTS = "isSaveKeypoints";
class BaseQualityEvaluator
{
public:
BaseQualityEvaluator( const char* _algName, const char* _testName ) : algName(_algName), testName(_testName)
{
//TODO: change this
isWriteGraphicsData = true;
}
void run();
virtual ~BaseQualityEvaluator(){}
protected:
virtual string getRunParamsFilename() const = 0;
virtual string getResultsFilename() const = 0;
virtual string getPlotPath() const = 0;
virtual void calcQualityClear( int datasetIdx ) = 0;
virtual bool isCalcQualityEmpty( int datasetIdx ) const = 0;
void readAllDatasetsRunParams();
virtual void readDatasetRunParams( FileNode& fn, int datasetIdx ) = 0;
void writeAllDatasetsRunParams() const;
virtual void writeDatasetRunParams( FileStorage& fs, int datasetIdx ) const = 0;
void setDefaultAllDatasetsRunParams();
virtual void setDefaultDatasetRunParams( int datasetIdx ) = 0;
virtual void readDefaultRunParams( FileNode& /*fn*/ ) {}
virtual void writeDefaultRunParams( FileStorage& /*fs*/ ) const {}
bool readDataset( const string& datasetName, vector<Mat>& Hs, vector<Mat>& imgs );
virtual void readAlgorithm() {}
virtual void processRunParamsFile() {}
virtual void runDatasetTest( const vector<Mat>& /*imgs*/, const vector<Mat>& /*Hs*/, int /*di*/, int& /*progress*/ ) {}
virtual void processResults( int datasetIdx );
virtual void processResults();
virtual void writePlotData( int /*datasetIdx*/ ) const {}
string algName, testName;
bool isWriteParams, isWriteGraphicsData;
};
void BaseQualityEvaluator::readAllDatasetsRunParams()
{
string filename = getRunParamsFilename();
FileStorage fs( filename, FileStorage::READ );
if( !fs.isOpened() )
{
isWriteParams = true;
setDefaultAllDatasetsRunParams();
printf("All runParams are default.\n");
}
else
{
isWriteParams = false;
FileNode topfn = fs.getFirstTopLevelNode();
FileNode pfn = topfn[DEFAULT_PARAMS];
readDefaultRunParams(pfn);
for( int i = 0; i < DATASETS_COUNT; i++ )
{
FileNode fn = topfn[DATASET_NAMES[i]];
if( fn.empty() )
{
printf( "%d-runParams is default.\n", i);
setDefaultDatasetRunParams(i);
}
else
readDatasetRunParams(fn, i);
}
}
}
void BaseQualityEvaluator::writeAllDatasetsRunParams() const
{
string filename = getRunParamsFilename();
FileStorage fs( filename, FileStorage::WRITE );
if( fs.isOpened() )
{
fs << "run_params" << "{"; // top file node
fs << DEFAULT_PARAMS << "{";
writeDefaultRunParams(fs);
fs << "}";
for( int i = 0; i < DATASETS_COUNT; i++ )
{
fs << DATASET_NAMES[i] << "{";
writeDatasetRunParams(fs, i);
fs << "}";
}
fs << "}";
}
else
printf( "File %s for writing run params can not be opened.\n", filename.c_str() );
}
void BaseQualityEvaluator::setDefaultAllDatasetsRunParams()
{
for( int i = 0; i < DATASETS_COUNT; i++ )
setDefaultDatasetRunParams(i);
}
bool BaseQualityEvaluator::readDataset( const string& datasetName, vector<Mat>& Hs, vector<Mat>& imgs )
{
Hs.resize( TEST_CASE_COUNT );
imgs.resize( TEST_CASE_COUNT+1 );
string dirname = data_path + IMAGE_DATASETS_DIR + datasetName + "/";
for( int i = 0; i < (int)Hs.size(); i++ )
{
stringstream filename; filename << "H1to" << i+2 << "p.xml";
FileStorage fs( dirname + filename.str(), FileStorage::READ );
if( !fs.isOpened() )
{
cout << "filename " << dirname + filename.str() << endl;
FileStorage fs2( dirname + filename.str(), FileStorage::READ );
return false;
}
fs.getFirstTopLevelNode() >> Hs[i];
}
for( int i = 0; i < (int)imgs.size(); i++ )
{
stringstream filename; filename << "img" << i+1 << ".png";
imgs[i] = imread( dirname + filename.str(), 0 );
if( imgs[i].empty() )
{
cout << "filename " << filename.str() << endl;
return false;
}
}
return true;
}
void BaseQualityEvaluator::processResults( int datasetIdx )
{
if( isWriteGraphicsData )
writePlotData( datasetIdx );
}
void BaseQualityEvaluator::processResults()
{
if( isWriteParams )
writeAllDatasetsRunParams();
}
void BaseQualityEvaluator::run()
{
readAlgorithm ();
processRunParamsFile ();
int notReadDatasets = 0;
int progress = 0;
FileStorage runParamsFS( getRunParamsFilename(), FileStorage::READ );
isWriteParams = (! runParamsFS.isOpened());
FileNode topfn = runParamsFS.getFirstTopLevelNode();
FileNode defaultParams = topfn[DEFAULT_PARAMS];
readDefaultRunParams (defaultParams);
cout << testName << endl;
for(int di = 0; di < DATASETS_COUNT; di++ )
{
cout << "Dataset " << di << " [" << DATASET_NAMES[di] << "] " << flush;
vector<Mat> imgs, Hs;
if( !readDataset( DATASET_NAMES[di], Hs, imgs ) )
{
calcQualityClear (di);
printf( "Images or homography matrices of dataset named %s can not be read\n",
DATASET_NAMES[di].c_str());
notReadDatasets++;
continue;
}
FileNode fn = topfn[DATASET_NAMES[di]];
readDatasetRunParams(fn, di);
runDatasetTest (imgs, Hs, di, progress);
processResults( di );
cout << endl;
}
if( notReadDatasets == DATASETS_COUNT )
{
printf( "All datasets were not be read\n");
exit(-1);
}
else
processResults();
runParamsFS.release();
}
class DetectorQualityEvaluator : public BaseQualityEvaluator
{
public:
DetectorQualityEvaluator( const char* _detectorName, const char* _testName ) : BaseQualityEvaluator( _detectorName, _testName )
{
calcQuality.resize(DATASETS_COUNT);
isSaveKeypoints.resize(DATASETS_COUNT);
isActiveParams.resize(DATASETS_COUNT);
isSaveKeypointsDefault = false;
isActiveParamsDefault = false;
}
protected:
virtual string getRunParamsFilename() const;
virtual string getResultsFilename() const;
virtual string getPlotPath() const;
virtual void calcQualityClear( int datasetIdx );
virtual bool isCalcQualityEmpty( int datasetIdx ) const;
virtual void readDatasetRunParams( FileNode& fn, int datasetIdx );
virtual void writeDatasetRunParams( FileStorage& fs, int datasetIdx ) const;
virtual void setDefaultDatasetRunParams( int datasetIdx );
virtual void readDefaultRunParams( FileNode &fn );
virtual void writeDefaultRunParams( FileStorage &fs ) const;
virtual void writePlotData( int di ) const;
void openToWriteKeypointsFile( FileStorage& fs, int datasetIdx );
virtual void readAlgorithm();
virtual void processRunParamsFile() {}
virtual void runDatasetTest( const vector<Mat> &imgs, const vector<Mat> &Hs, int di, int &progress );
Ptr<FeatureDetector> specificDetector;
Ptr<FeatureDetector> defaultDetector;
struct Quality
{
float repeatability;
int correspondenceCount;
};
vector<vector<Quality> > calcQuality;
vector<bool> isSaveKeypoints;
vector<bool> isActiveParams;
bool isSaveKeypointsDefault;
bool isActiveParamsDefault;
};
string DetectorQualityEvaluator::getRunParamsFilename() const
{
return data_path + DETECTORS_DIR + algName + PARAMS_POSTFIX;
}
string DetectorQualityEvaluator::getResultsFilename() const
{
return data_path + DETECTORS_DIR + algName + RES_POSTFIX;
}
string DetectorQualityEvaluator::getPlotPath() const
{
return data_path + DETECTORS_DIR + "plots/";
}
void DetectorQualityEvaluator::calcQualityClear( int datasetIdx )
{
calcQuality[datasetIdx].clear();
}
bool DetectorQualityEvaluator::isCalcQualityEmpty( int datasetIdx ) const
{
return calcQuality[datasetIdx].empty();
}
void DetectorQualityEvaluator::readDefaultRunParams (FileNode &fn)
{
if (! fn.empty() )
{
isSaveKeypointsDefault = (int)fn[IS_SAVE_KEYPOINTS] != 0;
defaultDetector->read (fn);
}
}
void DetectorQualityEvaluator::writeDefaultRunParams (FileStorage &fs) const
{
fs << IS_SAVE_KEYPOINTS << isSaveKeypointsDefault;
defaultDetector->write (fs);
}
void DetectorQualityEvaluator::readDatasetRunParams( FileNode& fn, int datasetIdx )
{
isActiveParams[datasetIdx] = (int)fn[IS_ACTIVE_PARAMS] != 0;
if (isActiveParams[datasetIdx])
{
isSaveKeypoints[datasetIdx] = (int)fn[IS_SAVE_KEYPOINTS] != 0;
specificDetector->read (fn);
}
else
{
setDefaultDatasetRunParams(datasetIdx);
}
}
void DetectorQualityEvaluator::writeDatasetRunParams( FileStorage& fs, int datasetIdx ) const
{
fs << IS_ACTIVE_PARAMS << isActiveParams[datasetIdx];
fs << IS_SAVE_KEYPOINTS << isSaveKeypoints[datasetIdx];
defaultDetector->write (fs);
}
void DetectorQualityEvaluator::setDefaultDatasetRunParams( int datasetIdx )
{
isSaveKeypoints[datasetIdx] = isSaveKeypointsDefault;
isActiveParams[datasetIdx] = isActiveParamsDefault;
}
void DetectorQualityEvaluator::writePlotData(int di ) const
{
int imgXVals[] = { 2, 3, 4, 5, 6 }; // if scale, blur or light changes
int viewpointXVals[] = { 20, 30, 40, 50, 60 }; // if viewpoint changes
int jpegXVals[] = { 60, 80, 90, 95, 98 }; // if jpeg compression
int* xVals = 0;
if( !DATASET_NAMES[di].compare("ubc") )
{
xVals = jpegXVals;
}
else if( !DATASET_NAMES[di].compare("graf") || !DATASET_NAMES[di].compare("wall") )
{
xVals = viewpointXVals;
}
else
xVals = imgXVals;
stringstream rFilename, cFilename;
rFilename << getPlotPath() << algName << "_" << DATASET_NAMES[di] << "_repeatability.csv";
cFilename << getPlotPath() << algName << "_" << DATASET_NAMES[di] << "_correspondenceCount.csv";
ofstream rfile(rFilename.str().c_str()), cfile(cFilename.str().c_str());
for( int ci = 0; ci < TEST_CASE_COUNT; ci++ )
{
rfile << xVals[ci] << ", " << calcQuality[di][ci].repeatability << endl;
cfile << xVals[ci] << ", " << calcQuality[di][ci].correspondenceCount << endl;
}
}
void DetectorQualityEvaluator::openToWriteKeypointsFile( FileStorage& fs, int datasetIdx )
{
string filename = data_path + KEYPOINTS_DIR + algName + "_"+ DATASET_NAMES[datasetIdx] + ".xml.gz" ;
fs.open(filename, FileStorage::WRITE);
if( !fs.isOpened() )
printf( "keypoints can not be written in file %s because this file can not be opened\n", filename.c_str() );
}
inline void writeKeypoints( FileStorage& fs, const vector<KeyPoint>& keypoints, int imgIdx )
{
if( fs.isOpened() )
{
stringstream imgName; imgName << "img" << imgIdx;
write( fs, imgName.str(), keypoints );
}
}
inline void readKeypoints( FileStorage& fs, vector<KeyPoint>& keypoints, int imgIdx )
{
assert( fs.isOpened() );
stringstream imgName; imgName << "img" << imgIdx;
read( fs[imgName.str()], keypoints);
}
void DetectorQualityEvaluator::readAlgorithm ()
{
defaultDetector = FeatureDetector::create( algName );
specificDetector = FeatureDetector::create( algName );
if( defaultDetector == 0 )
{
printf( "Algorithm can not be read\n" );
exit(-1);
}
}
static int update_progress( const string& /*name*/, int progress, int test_case_idx, int count, double dt )
{
int width = 60 /*- (int)name.length()*/;
if( count > 0 )
{
int t = cvRound( ((double)test_case_idx * width)/count );
if( t > progress )
{
cout << "." << flush;
progress = t;
}
}
else if( cvRound(dt) > progress )
{
cout << "." << flush;
progress = cvRound(dt);
}
return progress;
}
void DetectorQualityEvaluator::runDatasetTest (const vector<Mat> &imgs, const vector<Mat> &Hs, int di, int &progress)
{
Ptr<FeatureDetector> detector = isActiveParams[di] ? specificDetector : defaultDetector;
FileStorage keypontsFS;
if( isSaveKeypoints[di] )
openToWriteKeypointsFile( keypontsFS, di );
calcQuality[di].resize(TEST_CASE_COUNT);
vector<KeyPoint> keypoints1;
detector->detect( imgs[0], keypoints1 );
writeKeypoints( keypontsFS, keypoints1, 0);
int progressCount = DATASETS_COUNT*TEST_CASE_COUNT;
for( int ci = 0; ci < TEST_CASE_COUNT; ci++ )
{
progress = update_progress( testName, progress, di*TEST_CASE_COUNT + ci + 1, progressCount, 0 );
vector<KeyPoint> keypoints2;
float rep;
evaluateFeatureDetector( imgs[0], imgs[ci+1], Hs[ci], &keypoints1, &keypoints2,
rep, calcQuality[di][ci].correspondenceCount,
detector );
calcQuality[di][ci].repeatability = rep == -1 ? rep : 100.f*rep;
writeKeypoints( keypontsFS, keypoints2, ci+1);
}
}
// static void testLog( bool isBadAccuracy )
// {
// if( isBadAccuracy )
// printf(" bad accuracy\n");
// else
// printf("\n");
// }
/****************************************************************************************\
* Descriptors evaluation *
\****************************************************************************************/
const string RECALL = "recall";
const string PRECISION = "precision";
const string KEYPOINTS_FILENAME = "keypointsFilename";
const string PROJECT_KEYPOINTS_FROM_1IMAGE = "projectKeypointsFrom1Image";
const string MATCH_FILTER = "matchFilter";
const string RUN_PARAMS_IS_IDENTICAL = "runParamsIsIdentical";
const string ONE_WAY_TRAIN_DIR = "detectors_descriptors_evaluation/one_way_train_images/";
const string ONE_WAY_IMAGES_LIST = "one_way_train_images.txt";
class DescriptorQualityEvaluator : public BaseQualityEvaluator
{
public:
enum{ NO_MATCH_FILTER = 0 };
DescriptorQualityEvaluator( const char* _descriptorName, const char* _testName, const char* _matcherName = 0 ) :
BaseQualityEvaluator( _descriptorName, _testName )
{
calcQuality.resize(DATASETS_COUNT);
calcDatasetQuality.resize(DATASETS_COUNT);
commRunParams.resize(DATASETS_COUNT);
commRunParamsDefault.projectKeypointsFrom1Image = true;
commRunParamsDefault.matchFilter = NO_MATCH_FILTER;
commRunParamsDefault.isActiveParams = false;
if( _matcherName )
matcherName = _matcherName;
}
protected:
virtual string getRunParamsFilename() const;
virtual string getResultsFilename() const;
virtual string getPlotPath() const;
virtual void calcQualityClear( int datasetIdx );
virtual bool isCalcQualityEmpty( int datasetIdx ) const;
virtual void readDatasetRunParams( FileNode& fn, int datasetIdx ); //
virtual void writeDatasetRunParams( FileStorage& fs, int datasetIdx ) const;
virtual void setDefaultDatasetRunParams( int datasetIdx );
virtual void readDefaultRunParams( FileNode &fn );
virtual void writeDefaultRunParams( FileStorage &fs ) const;
virtual void readAlgorithm();
virtual void processRunParamsFile() {}
virtual void runDatasetTest( const vector<Mat> &imgs, const vector<Mat> &Hs, int di, int &progress );
virtual void writePlotData( int di ) const;
void calculatePlotData( vector<vector<DMatch> > &allMatches, vector<vector<uchar> > &allCorrectMatchesMask, int di );
struct Quality
{
float recall;
float precision;
};
vector<vector<Quality> > calcQuality;
vector<vector<Quality> > calcDatasetQuality;
struct CommonRunParams
{
string keypontsFilename;
bool projectKeypointsFrom1Image;
int matchFilter; // not used now
bool isActiveParams;
};
vector<CommonRunParams> commRunParams;
Ptr<GenericDescriptorMatch> specificDescMatcher;
Ptr<GenericDescriptorMatch> defaultDescMatcher;
CommonRunParams commRunParamsDefault;
string matcherName;
};
string DescriptorQualityEvaluator::getRunParamsFilename() const
{
return data_path + DESCRIPTORS_DIR + algName + PARAMS_POSTFIX;
}
string DescriptorQualityEvaluator::getResultsFilename() const
{
return data_path + DESCRIPTORS_DIR + algName + RES_POSTFIX;
}
string DescriptorQualityEvaluator::getPlotPath() const
{
return data_path + DESCRIPTORS_DIR + "plots/";
}
void DescriptorQualityEvaluator::calcQualityClear( int datasetIdx )
{
calcQuality[datasetIdx].clear();
}
bool DescriptorQualityEvaluator::isCalcQualityEmpty( int datasetIdx ) const
{
return calcQuality[datasetIdx].empty();
}
void DescriptorQualityEvaluator::readDefaultRunParams (FileNode &fn)
{
if (! fn.empty() )
{
commRunParamsDefault.projectKeypointsFrom1Image = (int)fn[PROJECT_KEYPOINTS_FROM_1IMAGE] != 0;
commRunParamsDefault.matchFilter = (int)fn[MATCH_FILTER];
defaultDescMatcher->read (fn);
}
}
void DescriptorQualityEvaluator::writeDefaultRunParams (FileStorage &fs) const
{
fs << PROJECT_KEYPOINTS_FROM_1IMAGE << commRunParamsDefault.projectKeypointsFrom1Image;
fs << MATCH_FILTER << commRunParamsDefault.matchFilter;
defaultDescMatcher->write (fs);
}
void DescriptorQualityEvaluator::readDatasetRunParams( FileNode& fn, int datasetIdx )
{
commRunParams[datasetIdx].isActiveParams = (int)fn[IS_ACTIVE_PARAMS] != 0;
if (commRunParams[datasetIdx].isActiveParams)
{
commRunParams[datasetIdx].keypontsFilename = (string)fn[KEYPOINTS_FILENAME];
commRunParams[datasetIdx].projectKeypointsFrom1Image = (int)fn[PROJECT_KEYPOINTS_FROM_1IMAGE] != 0;
commRunParams[datasetIdx].matchFilter = (int)fn[MATCH_FILTER];
specificDescMatcher->read (fn);
}
else
{
setDefaultDatasetRunParams(datasetIdx);
}
}
void DescriptorQualityEvaluator::writeDatasetRunParams( FileStorage& fs, int datasetIdx ) const
{
fs << IS_ACTIVE_PARAMS << commRunParams[datasetIdx].isActiveParams;
fs << KEYPOINTS_FILENAME << commRunParams[datasetIdx].keypontsFilename;
fs << PROJECT_KEYPOINTS_FROM_1IMAGE << commRunParams[datasetIdx].projectKeypointsFrom1Image;
fs << MATCH_FILTER << commRunParams[datasetIdx].matchFilter;
defaultDescMatcher->write (fs);
}
void DescriptorQualityEvaluator::setDefaultDatasetRunParams( int datasetIdx )
{
commRunParams[datasetIdx] = commRunParamsDefault;
commRunParams[datasetIdx].keypontsFilename = "SURF_" + DATASET_NAMES[datasetIdx] + ".xml.gz";
}
void DescriptorQualityEvaluator::writePlotData( int di ) const
{
stringstream filename;
filename << getPlotPath() << algName << "_" << DATASET_NAMES[di] << ".csv";
FILE *file = fopen (filename.str().c_str(), "w");
size_t size = calcDatasetQuality[di].size();
for (size_t i=0;i<size;i++)
{
fprintf( file, "%f, %f\n", 1 - calcDatasetQuality[di][i].precision, calcDatasetQuality[di][i].recall);
}
fclose( file );
}
void DescriptorQualityEvaluator::readAlgorithm( )
{
defaultDescMatcher = GenericDescriptorMatcher::create( algName );
specificDescMatcher = GenericDescriptorMatcher::create( algName );
if( defaultDescMatcher == 0 )
{
Ptr<DescriptorExtractor> extractor = DescriptorExtractor::create( algName );
Ptr<DescriptorMatcher> matcher = DescriptorMatcher::create( matcherName );
defaultDescMatcher = new VectorDescriptorMatch( extractor, matcher );
specificDescMatcher = new VectorDescriptorMatch( extractor, matcher );
if( extractor == 0 || matcher == 0 )
{
printf("Algorithm can not be read\n");
exit(-1);
}
}
}
void DescriptorQualityEvaluator::calculatePlotData( vector<vector<DMatch> > &allMatches, vector<vector<uchar> > &allCorrectMatchesMask, int di )
{
vector<Point2f> recallPrecisionCurve;
computeRecallPrecisionCurve( allMatches, allCorrectMatchesMask, recallPrecisionCurve );
calcDatasetQuality[di].clear();
const float resultPrecision = 0.5;
bool isResultCalculated = false;
const double eps = 1e-2;
Quality initQuality;
initQuality.recall = 0;
initQuality.precision = 0;
calcDatasetQuality[di].push_back( initQuality );
for( size_t i=0;i<recallPrecisionCurve.size();i++ )
{
Quality quality;
quality.recall = recallPrecisionCurve[i].y;
quality.precision = 1 - recallPrecisionCurve[i].x;
Quality back = calcDatasetQuality[di].back();
if( fabs( quality.recall - back.recall ) < eps && fabs( quality.precision - back.precision ) < eps )
continue;
calcDatasetQuality[di].push_back( quality );
if( !isResultCalculated && quality.precision < resultPrecision )
{
for(int ci=0;ci<TEST_CASE_COUNT;ci++)
{
calcQuality[di][ci].recall = quality.recall;
calcQuality[di][ci].precision = quality.precision;
}
isResultCalculated = true;
}
}
}
void DescriptorQualityEvaluator::runDatasetTest (const vector<Mat> &imgs, const vector<Mat> &Hs, int di, int &progress)
{
FileStorage keypontsFS( data_path + KEYPOINTS_DIR + commRunParams[di].keypontsFilename, FileStorage::READ );
if( !keypontsFS.isOpened())
{
calcQuality[di].clear();
printf( "keypoints from file %s can not be read\n", commRunParams[di].keypontsFilename.c_str() );
return;
}
Ptr<GenericDescriptorMatcher> descMatch = commRunParams[di].isActiveParams ? specificDescMatcher : defaultDescMatcher;
calcQuality[di].resize(TEST_CASE_COUNT);
vector<KeyPoint> keypoints1;
readKeypoints( keypontsFS, keypoints1, 0);
int progressCount = DATASETS_COUNT*TEST_CASE_COUNT;
vector<vector<DMatch> > allMatches1to2;
vector<vector<uchar> > allCorrectMatchesMask;
for( int ci = 0; ci < TEST_CASE_COUNT; ci++ )
{
progress = update_progress( testName, progress, di*TEST_CASE_COUNT + ci + 1, progressCount, 0 );
vector<KeyPoint> keypoints2;
if( commRunParams[di].projectKeypointsFrom1Image )
{
// TODO need to test function calcKeyPointProjections
calcKeyPointProjections( keypoints1, Hs[ci], keypoints2 );
filterKeyPointsByImageSize( keypoints2, imgs[ci+1].size() );
}
else
readKeypoints( keypontsFS, keypoints2, ci+1 );
// TODO if( commRunParams[di].matchFilter )
vector<vector<DMatch> > matches1to2;
vector<vector<uchar> > correctMatchesMask;
vector<Point2f> recallPrecisionCurve; // not used because we need recallPrecisionCurve for
// all images in dataset
evaluateGenericDescriptorMatcher( imgs[0], imgs[ci+1], Hs[ci], keypoints1, keypoints2,
&matches1to2, &correctMatchesMask, recallPrecisionCurve,
descMatch );
allMatches1to2.insert( allMatches1to2.end(), matches1to2.begin(), matches1to2.end() );
allCorrectMatchesMask.insert( allCorrectMatchesMask.end(), correctMatchesMask.begin(), correctMatchesMask.end() );
}
calculatePlotData( allMatches1to2, allCorrectMatchesMask, di );
}
//--------------------------------- Calonder descriptor test --------------------------------------------
class CalonderDescriptorQualityEvaluator : public DescriptorQualityEvaluator
{
public:
CalonderDescriptorQualityEvaluator() :
DescriptorQualityEvaluator( "Calonder", "quality-descriptor-calonder") {}
virtual void readAlgorithm( )
{
string classifierFile = data_path + "/features2d/calonder_classifier.rtc";
defaultDescMatcher = new VectorDescriptorMatch( new CalonderDescriptorExtractor<float>( classifierFile ),
new BFMatcher(NORM_L2) );
specificDescMatcher = defaultDescMatcher;
}
};
//--------------------------------- One Way descriptor test --------------------------------------------
class OneWayDescriptorQualityTest : public DescriptorQualityEvaluator
{
public:
OneWayDescriptorQualityTest() :
DescriptorQualityEvaluator("ONEWAY", "quality-descriptor-one-way")
{
}
protected:
virtual void processRunParamsFile ();
virtual void writeDatasetRunParams( FileStorage& fs, int datasetIdx ) const;
};
void OneWayDescriptorQualityTest::processRunParamsFile ()
{
string filename = getRunParamsFilename();
FileStorage fs = FileStorage (filename, FileStorage::READ);
FileNode fn = fs.getFirstTopLevelNode();
fn = fn[DEFAULT_PARAMS];
string pcaFilename = data_path + (string)fn["pcaFilename"];
string trainPath = data_path + (string)fn["trainPath"];
string trainImagesList = (string)fn["trainImagesList"];
int patch_width = fn["patchWidth"];
int patch_height = fn["patchHeight"];
Size patchSize = cvSize (patch_width, patch_height);
int poseCount = fn["poseCount"];
if (trainImagesList.length () == 0 )
return;
fs.release ();
readAllDatasetsRunParams();
OneWayDescriptorBase *base = new OneWayDescriptorBase(patchSize, poseCount, pcaFilename,
trainPath, trainImagesList);
OneWayDescriptorMatch *match = new OneWayDescriptorMatch ();
match->initialize( OneWayDescriptorMatch::Params (), base );
defaultDescMatcher = match;
writeAllDatasetsRunParams();
}
void OneWayDescriptorQualityTest::writeDatasetRunParams( FileStorage& fs, int datasetIdx ) const
{
fs << IS_ACTIVE_PARAMS << commRunParams[datasetIdx].isActiveParams;
fs << KEYPOINTS_FILENAME << commRunParams[datasetIdx].keypontsFilename;
fs << PROJECT_KEYPOINTS_FROM_1IMAGE << commRunParams[datasetIdx].projectKeypointsFrom1Image;
fs << MATCH_FILTER << commRunParams[datasetIdx].matchFilter;
}
int main( int argc, char** argv )
{
if( argc != 2 )
{
cout << "Format: " << argv[0] << " testdata path (path to testdata/cv)" << endl;
return -1;
}
data_path = argv[1];
#ifdef WIN32
if( *data_path.rbegin() != '\\' )
data_path = data_path + "\\";
#else
if( *data_path.rbegin() != '/' )
data_path = data_path + "/";
#endif
Ptr<BaseQualityEvaluator> evals[] =
{
new DetectorQualityEvaluator( "FAST", "quality-detector-fast" ),
new DetectorQualityEvaluator( "GFTT", "quality-detector-gftt" ),
new DetectorQualityEvaluator( "HARRIS", "quality-detector-harris" ),
new DetectorQualityEvaluator( "MSER", "quality-detector-mser" ),
new DetectorQualityEvaluator( "STAR", "quality-detector-star" ),
new DetectorQualityEvaluator( "SIFT", "quality-detector-sift" ),
new DetectorQualityEvaluator( "SURF", "quality-detector-surf" ),
new DescriptorQualityEvaluator( "SIFT", "quality-descriptor-sift", "BruteForce" ),
new DescriptorQualityEvaluator( "SURF", "quality-descriptor-surf", "BruteForce" ),
new DescriptorQualityEvaluator( "FERN", "quality-descriptor-fern"),
new CalonderDescriptorQualityEvaluator()
};
for( size_t i = 0; i < sizeof(evals)/sizeof(evals[0]); i++ )
{
evals[i]->run();
cout << endl;
}
}
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