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Merge pull request #1879 from LeszekSwirski:traincascade-2.4

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This commit is contained in:
Roman Donchenko 2013-11-28 12:24:44 +04:00 committed by OpenCV Buildbot
commit 70c1b700d9
15 changed files with 148 additions and 124 deletions
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2
apps/traincascade/HOGfeatures.cpp
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@ -4,6 +4,8 @@
#include "HOGfeatures.h"
#include "cascadeclassifier.h"
using namespace std;
using namespace cv;
CvHOGFeatureParams::CvHOGFeatureParams()
{

24
apps/traincascade/HOGfeatures.h
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@ -20,33 +20,33 @@ class CvHOGEvaluator : public CvFeatureEvaluator
public:
virtual ~CvHOGEvaluator() {}
virtual void init(const CvFeatureParams *_featureParams,
int _maxSampleCount, Size _winSize );
virtual void setImage(const Mat& img, uchar clsLabel, int idx);
int _maxSampleCount, cv::Size _winSize );
virtual void setImage(const cv::Mat& img, uchar clsLabel, int idx);
virtual float operator()(int varIdx, int sampleIdx) const;
virtual void writeFeatures( FileStorage &fs, const Mat& featureMap ) const;
virtual void writeFeatures( cv::FileStorage &fs, const cv::Mat& featureMap ) const;
protected:
virtual void generateFeatures();
virtual void integralHistogram(const Mat &img, vector<Mat> &histogram, Mat &norm, int nbins) const;
virtual void integralHistogram(const cv::Mat &img, std::vector<cv::Mat> &histogram, cv::Mat &norm, int nbins) const;
class Feature
{
public:
Feature();
Feature( int offset, int x, int y, int cellW, int cellH );
float calc( const vector<Mat> &_hists, const Mat &_normSum, size_t y, int featComponent ) const;
void write( FileStorage &fs ) const;
void write( FileStorage &fs, int varIdx ) const;
float calc( const std::vector<cv::Mat> &_hists, const cv::Mat &_normSum, size_t y, int featComponent ) const;
void write( cv::FileStorage &fs ) const;
void write( cv::FileStorage &fs, int varIdx ) const;
Rect rect[N_CELLS]; //cells
cv::Rect rect[N_CELLS]; //cells
struct
{
int p0, p1, p2, p3;
} fastRect[N_CELLS];
};
vector<Feature> features;
std::vector<Feature> features;
Mat normSum; //for nomalization calculation (L1 or L2)
vector<Mat> hist;
cv::Mat normSum; //for nomalization calculation (L1 or L2)
std::vector<cv::Mat> hist;
};
inline float CvHOGEvaluator::operator()(int varIdx, int sampleIdx) const
@ -57,7 +57,7 @@ inline float CvHOGEvaluator::operator()(int varIdx, int sampleIdx) const
return features[featureIdx].calc( hist, normSum, sampleIdx, componentIdx);
}
inline float CvHOGEvaluator::Feature::calc( const vector<Mat>& _hists, const Mat& _normSum, size_t y, int featComponent ) const
inline float CvHOGEvaluator::Feature::calc( const std::vector<cv::Mat>& _hists, const cv::Mat& _normSum, size_t y, int featComponent ) const
{
float normFactor;
float res;

25
apps/traincascade/boost.cpp
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@ -1,6 +1,19 @@
#include "opencv2/core/core.hpp"
#include "opencv2/core/internal.hpp"
using cv::Size;
using cv::Mat;
using cv::Point;
using cv::FileStorage;
using cv::Rect;
using cv::Ptr;
using cv::FileNode;
using cv::Mat_;
using cv::Range;
using cv::FileNodeIterator;
using cv::ParallelLoopBody;
#include "boost.h"
#include "cascadeclassifier.h"
#include <queue>
@ -160,10 +173,10 @@ CvCascadeBoostParams::CvCascadeBoostParams( int _boostType,
void CvCascadeBoostParams::write( FileStorage &fs ) const
{
String boostTypeStr = boost_type == CvBoost::DISCRETE ? CC_DISCRETE_BOOST :
string boostTypeStr = boost_type == CvBoost::DISCRETE ? CC_DISCRETE_BOOST :
boost_type == CvBoost::REAL ? CC_REAL_BOOST :
boost_type == CvBoost::LOGIT ? CC_LOGIT_BOOST :
boost_type == CvBoost::GENTLE ? CC_GENTLE_BOOST : String();
boost_type == CvBoost::GENTLE ? CC_GENTLE_BOOST : string();
CV_Assert( !boostTypeStr.empty() );
fs << CC_BOOST_TYPE << boostTypeStr;
fs << CC_MINHITRATE << minHitRate;
@ -175,7 +188,7 @@ void CvCascadeBoostParams::write( FileStorage &fs ) const
bool CvCascadeBoostParams::read( const FileNode &node )
{
String boostTypeStr;
string boostTypeStr;
FileNode rnode = node[CC_BOOST_TYPE];
rnode >> boostTypeStr;
boost_type = !boostTypeStr.compare( CC_DISCRETE_BOOST ) ? CvBoost::DISCRETE :
@ -213,10 +226,10 @@ void CvCascadeBoostParams::printDefaults() const
void CvCascadeBoostParams::printAttrs() const
{
String boostTypeStr = boost_type == CvBoost::DISCRETE ? CC_DISCRETE_BOOST :
string boostTypeStr = boost_type == CvBoost::DISCRETE ? CC_DISCRETE_BOOST :
boost_type == CvBoost::REAL ? CC_REAL_BOOST :
boost_type == CvBoost::LOGIT ? CC_LOGIT_BOOST :
boost_type == CvBoost::GENTLE ? CC_GENTLE_BOOST : String();
boost_type == CvBoost::GENTLE ? CC_GENTLE_BOOST : string();
CV_Assert( !boostTypeStr.empty() );
cout << "boostType: " << boostTypeStr << endl;
cout << "minHitRate: " << minHitRate << endl;
@ -226,7 +239,7 @@ void CvCascadeBoostParams::printAttrs() const
cout << "maxWeakCount: " << weak_count << endl;
}
bool CvCascadeBoostParams::scanAttr( const String prmName, const String val)
bool CvCascadeBoostParams::scanAttr( const string prmName, const string val)
{
bool res = true;

20
apps/traincascade/boost.h
View File

@ -13,11 +13,11 @@ struct CvCascadeBoostParams : CvBoostParams
CvCascadeBoostParams( int _boostType, float _minHitRate, float _maxFalseAlarm,
double _weightTrimRate, int _maxDepth, int _maxWeakCount );
virtual ~CvCascadeBoostParams() {}
void write( FileStorage &fs ) const;
bool read( const FileNode &node );
void write( cv::FileStorage &fs ) const;
bool read( const cv::FileNode &node );
virtual void printDefaults() const;
virtual void printAttrs() const;
virtual bool scanAttr( const String prmName, const String val);
virtual bool scanAttr( const std::string prmName, const std::string val);
};
struct CvCascadeBoostTrainData : CvDTreeTrainData
@ -45,7 +45,7 @@ struct CvCascadeBoostTrainData : CvDTreeTrainData
virtual void free_train_data();
const CvFeatureEvaluator* featureEvaluator;
Mat valCache; // precalculated feature values (CV_32FC1)
cv::Mat valCache; // precalculated feature values (CV_32FC1)
CvMat _resp; // for casting
int numPrecalcVal, numPrecalcIdx;
};
@ -54,9 +54,9 @@ class CvCascadeBoostTree : public CvBoostTree
{
public:
virtual CvDTreeNode* predict( int sampleIdx ) const;
void write( FileStorage &fs, const Mat& featureMap );
void read( const FileNode &node, CvBoost* _ensemble, CvDTreeTrainData* _data );
void markFeaturesInMap( Mat& featureMap );
void write( cv::FileStorage &fs, const cv::Mat& featureMap );
void read( const cv::FileNode &node, CvBoost* _ensemble, CvDTreeTrainData* _data );
void markFeaturesInMap( cv::Mat& featureMap );
protected:
virtual void split_node_data( CvDTreeNode* n );
};
@ -70,10 +70,10 @@ public:
virtual float predict( int sampleIdx, bool returnSum = false ) const;
float getThreshold() const { return threshold; }
void write( FileStorage &fs, const Mat& featureMap ) const;
bool read( const FileNode &node, const CvFeatureEvaluator* _featureEvaluator,
void write( cv::FileStorage &fs, const cv::Mat& featureMap ) const;
bool read( const cv::FileNode &node, const CvFeatureEvaluator* _featureEvaluator,
const CvCascadeBoostParams& _params );
void markUsedFeaturesInMap( Mat& featureMap );
void markUsedFeaturesInMap( cv::Mat& featureMap );
protected:
virtual bool set_params( const CvBoostParams& _params );
virtual void update_weights( CvBoostTree* tree );

19
apps/traincascade/cascadeclassifier.cpp
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@ -5,6 +5,7 @@
#include <queue>
using namespace std;
using namespace cv;
static const char* stageTypes[] = { CC_BOOST };
static const char* featureTypes[] = { CC_HAAR, CC_LBP, CC_HOG };
@ -24,10 +25,10 @@ CvCascadeParams::CvCascadeParams( int _stageType, int _featureType ) : stageType
void CvCascadeParams::write( FileStorage &fs ) const
{
String stageTypeStr = stageType == BOOST ? CC_BOOST : String();
string stageTypeStr = stageType == BOOST ? CC_BOOST : string();
CV_Assert( !stageTypeStr.empty() );
fs << CC_STAGE_TYPE << stageTypeStr;
String featureTypeStr = featureType == CvFeatureParams::HAAR ? CC_HAAR :
string featureTypeStr = featureType == CvFeatureParams::HAAR ? CC_HAAR :
featureType == CvFeatureParams::LBP ? CC_LBP :
featureType == CvFeatureParams::HOG ? CC_HOG :
0;
@ -41,7 +42,7 @@ bool CvCascadeParams::read( const FileNode &node )
{
if ( node.empty() )
return false;
String stageTypeStr, featureTypeStr;
string stageTypeStr, featureTypeStr;
FileNode rnode = node[CC_STAGE_TYPE];
if ( !rnode.isString() )
return false;
@ -96,7 +97,7 @@ void CvCascadeParams::printAttrs() const
cout << "sampleHeight: " << winSize.height << endl;
}
bool CvCascadeParams::scanAttr( const String prmName, const String val )
bool CvCascadeParams::scanAttr( const string prmName, const string val )
{
bool res = true;
if( !prmName.compare( "-stageType" ) )
@ -126,9 +127,9 @@ bool CvCascadeParams::scanAttr( const String prmName, const String val )
//---------------------------- CascadeClassifier --------------------------------------
bool CvCascadeClassifier::train( const String _cascadeDirName,
const String _posFilename,
const String _negFilename,
bool CvCascadeClassifier::train( const string _cascadeDirName,
const string _posFilename,
const string _negFilename,
int _numPos, int _numNeg,
int _precalcValBufSize, int _precalcIdxBufSize,
int _numStages,
@ -411,7 +412,7 @@ bool CvCascadeClassifier::readStages( const FileNode &node)
#define ICV_HAAR_PARENT_NAME "parent"
#define ICV_HAAR_NEXT_NAME "next"
void CvCascadeClassifier::save( const String filename, bool baseFormat )
void CvCascadeClassifier::save( const string filename, bool baseFormat )
{
FileStorage fs( filename, FileStorage::WRITE );
@ -503,7 +504,7 @@ void CvCascadeClassifier::save( const String filename, bool baseFormat )
fs << "}";
}
bool CvCascadeClassifier::load( const String cascadeDirName )
bool CvCascadeClassifier::load( const string cascadeDirName )
{
FileStorage fs( cascadeDirName + CC_PARAMS_FILENAME, FileStorage::READ );
if ( !fs.isOpened() )

38
apps/traincascade/cascadeclassifier.h
View File

@ -72,24 +72,24 @@ public:
CvCascadeParams();
CvCascadeParams( int _stageType, int _featureType );
void write( FileStorage &fs ) const;
bool read( const FileNode &node );
void write( cv::FileStorage &fs ) const;
bool read( const cv::FileNode &node );
void printDefaults() const;
void printAttrs() const;
bool scanAttr( const String prmName, const String val );
bool scanAttr( const std::string prmName, const std::string val );
int stageType;
int featureType;
Size winSize;
cv::Size winSize;
};
class CvCascadeClassifier
{
public:
bool train( const String _cascadeDirName,
const String _posFilename,
const String _negFilename,
bool train( const std::string _cascadeDirName,
const std::string _posFilename,
const std::string _negFilename,
int _numPos, int _numNeg,
int _precalcValBufSize, int _precalcIdxBufSize,
int _numStages,
@ -99,25 +99,25 @@ public:
bool baseFormatSave = false );
private:
int predict( int sampleIdx );
void save( const String cascadeDirName, bool baseFormat = false );
bool load( const String cascadeDirName );
void save( const std::string cascadeDirName, bool baseFormat = false );
bool load( const std::string cascadeDirName );
bool updateTrainingSet( double& acceptanceRatio );
int fillPassedSamples( int first, int count, bool isPositive, int64& consumed );
void writeParams( FileStorage &fs ) const;
void writeStages( FileStorage &fs, const Mat& featureMap ) const;
void writeFeatures( FileStorage &fs, const Mat& featureMap ) const;
bool readParams( const FileNode &node );
bool readStages( const FileNode &node );
void writeParams( cv::FileStorage &fs ) const;
void writeStages( cv::FileStorage &fs, const cv::Mat& featureMap ) const;
void writeFeatures( cv::FileStorage &fs, const cv::Mat& featureMap ) const;
bool readParams( const cv::FileNode &node );
bool readStages( const cv::FileNode &node );
void getUsedFeaturesIdxMap( Mat& featureMap );
void getUsedFeaturesIdxMap( cv::Mat& featureMap );
CvCascadeParams cascadeParams;
Ptr<CvFeatureParams> featureParams;
Ptr<CvCascadeBoostParams> stageParams;
cv::Ptr<CvFeatureParams> featureParams;
cv::Ptr<CvCascadeBoostParams> stageParams;
Ptr<CvFeatureEvaluator> featureEvaluator;
vector< Ptr<CvCascadeBoost> > stageClassifiers;
cv::Ptr<CvFeatureEvaluator> featureEvaluator;
std::vector< cv::Ptr<CvCascadeBoost> > stageClassifiers;
CvCascadeImageReader imgReader;
int numStages, curNumSamples;
int numPos, numNeg;

3
apps/traincascade/features.cpp
View File

@ -5,6 +5,7 @@
#include "cascadeclassifier.h"
using namespace std;
using namespace cv;
float calcNormFactor( const Mat& sum, const Mat& sqSum )
{
@ -24,7 +25,7 @@ CvParams::CvParams() : name( "params" ) {}
void CvParams::printDefaults() const
{ cout << "--" << name << "--" << endl; }
void CvParams::printAttrs() const {}
bool CvParams::scanAttr( const String, const String ) { return false; }
bool CvParams::scanAttr( const string, const string ) { return false; }
//---------------------------- FeatureParams --------------------------------------

11
apps/traincascade/haarfeatures.cpp
View File

@ -5,6 +5,7 @@
#include "cascadeclassifier.h"
using namespace std;
using namespace cv;
CvHaarFeatureParams::CvHaarFeatureParams() : mode(BASIC)
{
@ -25,9 +26,9 @@ void CvHaarFeatureParams::init( const CvFeatureParams& fp )
void CvHaarFeatureParams::write( FileStorage &fs ) const
{
CvFeatureParams::write( fs );
String modeStr = mode == BASIC ? CC_MODE_BASIC :
string modeStr = mode == BASIC ? CC_MODE_BASIC :
mode == CORE ? CC_MODE_CORE :
mode == ALL ? CC_MODE_ALL : String();
mode == ALL ? CC_MODE_ALL : string();
CV_Assert( !modeStr.empty() );
fs << CC_MODE << modeStr;
}
@ -40,7 +41,7 @@ bool CvHaarFeatureParams::read( const FileNode &node )
FileNode rnode = node[CC_MODE];
if( !rnode.isString() )
return false;
String modeStr;
string modeStr;
rnode >> modeStr;
mode = !modeStr.compare( CC_MODE_BASIC ) ? BASIC :
!modeStr.compare( CC_MODE_CORE ) ? CORE :
@ -58,13 +59,13 @@ void CvHaarFeatureParams::printDefaults() const
void CvHaarFeatureParams::printAttrs() const
{
CvFeatureParams::printAttrs();
String mode_str = mode == BASIC ? CC_MODE_BASIC :
string mode_str = mode == BASIC ? CC_MODE_BASIC :
mode == CORE ? CC_MODE_CORE :
mode == ALL ? CC_MODE_ALL : 0;
cout << "mode: " << mode_str << endl;
}
bool CvHaarFeatureParams::scanAttr( const String prmName, const String val)
bool CvHaarFeatureParams::scanAttr( const string prmName, const string val)
{
if ( !CvFeatureParams::scanAttr( prmName, val ) )
{

30
apps/traincascade/haarfeatures.h
View File

@ -18,12 +18,12 @@ public:
CvHaarFeatureParams( int _mode );
virtual void init( const CvFeatureParams& fp );
virtual void write( FileStorage &fs ) const;
virtual bool read( const FileNode &node );
virtual void write( cv::FileStorage &fs ) const;
virtual bool read( const cv::FileNode &node );
virtual void printDefaults() const;
virtual void printAttrs() const;
virtual bool scanAttr( const String prm, const String val);
virtual bool scanAttr( const std::string prm, const std::string val);
int mode;
};
@ -32,11 +32,11 @@ class CvHaarEvaluator : public CvFeatureEvaluator
{
public:
virtual void init(const CvFeatureParams *_featureParams,
int _maxSampleCount, Size _winSize );
virtual void setImage(const Mat& img, uchar clsLabel, int idx);
int _maxSampleCount, cv::Size _winSize );
virtual void setImage(const cv::Mat& img, uchar clsLabel, int idx);
virtual float operator()(int featureIdx, int sampleIdx) const;
virtual void writeFeatures( FileStorage &fs, const Mat& featureMap ) const;
void writeFeature( FileStorage &fs, int fi ) const; // for old file fornat
virtual void writeFeatures( cv::FileStorage &fs, const cv::Mat& featureMap ) const;
void writeFeature( cv::FileStorage &fs, int fi ) const; // for old file fornat
protected:
virtual void generateFeatures();
@ -48,13 +48,13 @@ protected:
int x0, int y0, int w0, int h0, float wt0,
int x1, int y1, int w1, int h1, float wt1,
int x2 = 0, int y2 = 0, int w2 = 0, int h2 = 0, float wt2 = 0.0F );
float calc( const Mat &sum, const Mat &tilted, size_t y) const;
void write( FileStorage &fs ) const;
float calc( const cv::Mat &sum, const cv::Mat &tilted, size_t y) const;
void write( cv::FileStorage &fs ) const;
bool tilted;
struct
{
Rect r;
cv::Rect r;
float weight;
} rect[CV_HAAR_FEATURE_MAX];
@ -64,10 +64,10 @@ protected:
} fastRect[CV_HAAR_FEATURE_MAX];
};
vector<Feature> features;
Mat sum; /* sum images (each row represents image) */
Mat tilted; /* tilted sum images (each row represents image) */
Mat normfactor; /* normalization factor */
std::vector<Feature> features;
cv::Mat sum; /* sum images (each row represents image) */
cv::Mat tilted; /* tilted sum images (each row represents image) */
cv::Mat normfactor; /* normalization factor */
};
inline float CvHaarEvaluator::operator()(int featureIdx, int sampleIdx) const
@ -76,7 +76,7 @@ inline float CvHaarEvaluator::operator()(int featureIdx, int sampleIdx) const
return !nf ? 0.0f : (features[featureIdx].calc( sum, tilted, sampleIdx)/nf);
}
inline float CvHaarEvaluator::Feature::calc( const Mat &_sum, const Mat &_tilted, size_t y) const
inline float CvHaarEvaluator::Feature::calc( const cv::Mat &_sum, const cv::Mat &_tilted, size_t y) const
{
const int* img = tilted ? _tilted.ptr<int>((int)y) : _sum.ptr<int>((int)y);
float ret = rect[0].weight * (img[fastRect[0].p0] - img[fastRect[0].p1] - img[fastRect[0].p2] + img[fastRect[0].p3] ) +

19
apps/traincascade/imagestorage.cpp
View File

@ -7,7 +7,10 @@
#include <iostream>
#include <fstream>
bool CvCascadeImageReader::create( const String _posFilename, const String _negFilename, Size _winSize )
using namespace std;
using namespace cv;
bool CvCascadeImageReader::create( const string _posFilename, const string _negFilename, Size _winSize )
{
return posReader.create(_posFilename) && negReader.create(_negFilename, _winSize);
}
@ -22,21 +25,21 @@ CvCascadeImageReader::NegReader::NegReader()
stepFactor = 0.5F;
}
bool CvCascadeImageReader::NegReader::create( const String _filename, Size _winSize )
bool CvCascadeImageReader::NegReader::create( const string _filename, Size _winSize )
{
String dirname, str;
string dirname, str;
std::ifstream file(_filename.c_str());
if ( !file.is_open() )
return false;
size_t pos = _filename.rfind('\\');
char dlmrt = '\\';
if (pos == String::npos)
if (pos == string::npos)
{
pos = _filename.rfind('/');
dlmrt = '/';
}
dirname = pos == String::npos ? "" : _filename.substr(0, pos) + dlmrt;
dirname = pos == string::npos ? "" : _filename.substr(0, pos) + dlmrt;
while( !file.eof() )
{
std::getline(file, str);
@ -64,8 +67,8 @@ bool CvCascadeImageReader::NegReader::nextImg()
round = round % (winSize.width * winSize.height);
last %= count;
_offset.x = min( (int)round % winSize.width, src.cols - winSize.width );
_offset.y = min( (int)round / winSize.width, src.rows - winSize.height );
_offset.x = std::min( (int)round % winSize.width, src.cols - winSize.width );
_offset.y = std::min( (int)round / winSize.width, src.rows - winSize.height );
if( !src.empty() && src.type() == CV_8UC1
&& offset.x >= 0 && offset.y >= 0 )
break;
@ -126,7 +129,7 @@ CvCascadeImageReader::PosReader::PosReader()
vec = 0;
}
bool CvCascadeImageReader::PosReader::create( const String _filename )
bool CvCascadeImageReader::PosReader::create( const string _filename )
{
if ( file )
fclose( file );

24
apps/traincascade/imagestorage.h
View File

@ -3,15 +3,15 @@
#include "highgui.h"
using namespace cv;
class CvCascadeImageReader
{
public:
bool create( const String _posFilename, const String _negFilename, Size _winSize );
bool create( const std::string _posFilename, const std::string _negFilename, cv::Size _winSize );
void restart() { posReader.restart(); }
bool getNeg(Mat &_img) { return negReader.get( _img ); }
bool getPos(Mat &_img) { return posReader.get( _img ); }
bool getNeg(cv::Mat &_img) { return negReader.get( _img ); }
bool getPos(cv::Mat &_img) { return posReader.get( _img ); }
private:
class PosReader
@ -19,8 +19,8 @@ private:
public:
PosReader();
virtual ~PosReader();
bool create( const String _filename );
bool get( Mat &_img );
bool create( const std::string _filename );
bool get( cv::Mat &_img );
void restart();
short* vec;
@ -35,18 +35,18 @@ private:
{
public:
NegReader();
bool create( const String _filename, Size _winSize );
bool get( Mat& _img );
bool create( const std::string _filename, cv::Size _winSize );
bool get( cv::Mat& _img );
bool nextImg();
Mat src, img;
vector<String> imgFilenames;
Point offset, point;
cv::Mat src, img;
std::vector<std::string> imgFilenames;
cv::Point offset, point;
float scale;
float scaleFactor;
float stepFactor;
size_t last, round;
Size winSize;
cv::Size winSize;
} negReader;
};

2
apps/traincascade/lbpfeatures.cpp
View File

@ -4,6 +4,8 @@
#include "lbpfeatures.h"
#include "cascadeclassifier.h"
using namespace cv;
CvLBPFeatureParams::CvLBPFeatureParams()
{
maxCatCount = 256;

18
apps/traincascade/lbpfeatures.h
View File

@ -15,11 +15,11 @@ class CvLBPEvaluator : public CvFeatureEvaluator
public:
virtual ~CvLBPEvaluator() {}
virtual void init(const CvFeatureParams *_featureParams,
int _maxSampleCount, Size _winSize );
virtual void setImage(const Mat& img, uchar clsLabel, int idx);
int _maxSampleCount, cv::Size _winSize );
virtual void setImage(const cv::Mat& img, uchar clsLabel, int idx);
virtual float operator()(int featureIdx, int sampleIdx) const
{ return (float)features[featureIdx].calc( sum, sampleIdx); }
virtual void writeFeatures( FileStorage &fs, const Mat& featureMap ) const;
virtual void writeFeatures( cv::FileStorage &fs, const cv::Mat& featureMap ) const;
protected:
virtual void generateFeatures();
@ -28,18 +28,18 @@ protected:
public:
Feature();
Feature( int offset, int x, int y, int _block_w, int _block_h );
uchar calc( const Mat& _sum, size_t y ) const;
void write( FileStorage &fs ) const;
uchar calc( const cv::Mat& _sum, size_t y ) const;
void write( cv::FileStorage &fs ) const;
Rect rect;
cv::Rect rect;
int p[16];
};
vector<Feature> features;
std::vector<Feature> features;
Mat sum;
cv::Mat sum;
};
inline uchar CvLBPEvaluator::Feature::calc(const Mat &_sum, size_t y) const
inline uchar CvLBPEvaluator::Feature::calc(const cv::Mat &_sum, size_t y) const
{
const int* psum = _sum.ptr<int>((int)y);
int cval = psum[p[5]] - psum[p[6]] - psum[p[9]] + psum[p[10]];

3
apps/traincascade/traincascade.cpp
View File

@ -5,11 +5,12 @@
#include "cascadeclassifier.h"
using namespace std;
using namespace cv;
int main( int argc, char* argv[] )
{
CvCascadeClassifier classifier;
String cascadeDirName, vecName, bgName;
string cascadeDirName, vecName, bgName;
int numPos = 2000;
int numNeg = 1000;
int numStages = 20;

34
apps/traincascade/traincascade_features.h
View File

@ -30,13 +30,13 @@
(p3) = (rect).x + (rect).width - (rect).height \
+ (step) * ((rect).y + (rect).width + (rect).height);
float calcNormFactor( const Mat& sum, const Mat& sqSum );
float calcNormFactor( const cv::Mat& sum, const cv::Mat& sqSum );
template<class Feature>
void _writeFeatures( const vector<Feature> features, FileStorage &fs, const Mat& featureMap )
void _writeFeatures( const std::vector<Feature> features, cv::FileStorage &fs, const cv::Mat& featureMap )
{
fs << FEATURES << "[";
const Mat_<int>& featureMap_ = (const Mat_<int>&)featureMap;
const cv::Mat_<int>& featureMap_ = (const cv::Mat_<int>&)featureMap;
for ( int fi = 0; fi < featureMap.cols; fi++ )
if ( featureMap_(0, fi) >= 0 )
{
@ -53,13 +53,13 @@ public:
CvParams();
virtual ~CvParams() {}
// from|to file
virtual void write( FileStorage &fs ) const = 0;
virtual bool read( const FileNode &node ) = 0;
virtual void write( cv::FileStorage &fs ) const = 0;
virtual bool read( const cv::FileNode &node ) = 0;
// from|to screen
virtual void printDefaults() const;
virtual void printAttrs() const;
virtual bool scanAttr( const String prmName, const String val );
String name;
virtual bool scanAttr( const std::string prmName, const std::string val );
std::string name;
};
class CvFeatureParams : public CvParams
@ -68,9 +68,9 @@ public:
enum { HAAR = 0, LBP = 1, HOG = 2 };
CvFeatureParams();
virtual void init( const CvFeatureParams& fp );
virtual void write( FileStorage &fs ) const;
virtual bool read( const FileNode &node );
static Ptr<CvFeatureParams> create( int featureType );
virtual void write( cv::FileStorage &fs ) const;
virtual bool read( const cv::FileNode &node );
static cv::Ptr<CvFeatureParams> create( int featureType );
int maxCatCount; // 0 in case of numerical features
int featSize; // 1 in case of simple features (HAAR, LBP) and N_BINS(9)*N_CELLS(4) in case of Dalal's HOG features
};
@ -80,25 +80,25 @@ class CvFeatureEvaluator
public:
virtual ~CvFeatureEvaluator() {}
virtual void init(const CvFeatureParams *_featureParams,
int _maxSampleCount, Size _winSize );
virtual void setImage(const Mat& img, uchar clsLabel, int idx);
virtual void writeFeatures( FileStorage &fs, const Mat& featureMap ) const = 0;
int _maxSampleCount, cv::Size _winSize );
virtual void setImage(const cv::Mat& img, uchar clsLabel, int idx);
virtual void writeFeatures( cv::FileStorage &fs, const cv::Mat& featureMap ) const = 0;
virtual float operator()(int featureIdx, int sampleIdx) const = 0;
static Ptr<CvFeatureEvaluator> create(int type);
static cv::Ptr<CvFeatureEvaluator> create(int type);
int getNumFeatures() const { return numFeatures; }
int getMaxCatCount() const { return featureParams->maxCatCount; }
int getFeatureSize() const { return featureParams->featSize; }
const Mat& getCls() const { return cls; }
const cv::Mat& getCls() const { return cls; }
float getCls(int si) const { return cls.at<float>(si, 0); }
protected:
virtual void generateFeatures() = 0;
int npos, nneg;
int numFeatures;
Size winSize;
cv::Size winSize;
CvFeatureParams *featureParams;
Mat cls;
cv::Mat cls;
};
#endif