Open Source Computer Vision Library https://opencv.org/
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#ifndef _OPENCV_CASCADECLASSIFIER_H_
#define _OPENCV_CASCADECLASSIFIER_H_
#include <ctime>
#include "traincascade_features.h"
#include "haarfeatures.h"
#include "lbpfeatures.h"
#include "boost.h"
#include "cv.h"
#include "cxcore.h"
#define CC_CASCADE_FILENAME "cascade.xml"
#define CC_PARAMS_FILENAME "params.xml"
#define CC_CASCADE_PARAMS "cascadeParams"
#define CC_STAGE_TYPE "stageType"
#define CC_FEATURE_TYPE "featureType"
#define CC_HEIGHT "height"
#define CC_WIDTH "width"
#define CC_STAGE_NUM "stageNum"
#define CC_STAGES "stages"
#define CC_STAGE_PARAMS "stageParams"
#define CC_BOOST "BOOST"
#define CC_BOOST_TYPE "boostType"
#define CC_DISCRETE_BOOST "DAB"
#define CC_REAL_BOOST "RAB"
#define CC_LOGIT_BOOST "LB"
#define CC_GENTLE_BOOST "GAB"
#define CC_MINHITRATE "minHitRate"
#define CC_MAXFALSEALARM "maxFalseAlarm"
#define CC_TRIM_RATE "weightTrimRate"
#define CC_MAX_DEPTH "maxDepth"
#define CC_WEAK_COUNT "maxWeakCount"
#define CC_STAGE_THRESHOLD "stageThreshold"
#define CC_WEAK_CLASSIFIERS "weakClassifiers"
#define CC_INTERNAL_NODES "internalNodes"
#define CC_LEAF_VALUES "leafValues"
#define CC_FEATURES FEATURES
#define CC_FEATURE_PARAMS "featureParams"
#define CC_MAX_CAT_COUNT "maxCatCount"
#define CC_HAAR "HAAR"
#define CC_MODE "mode"
#define CC_MODE_BASIC "BASIC"
#define CC_MODE_CORE "CORE"
#define CC_MODE_ALL "ALL"
#define CC_RECTS "rects"
#define CC_TILTED "tilted"
#define CC_LBP "LBP"
#define CC_RECT "rect"
#ifdef _WIN32
#define TIME( arg ) (((double) clock()) / CLOCKS_PER_SEC)
#else
#define TIME( arg ) (time( arg ))
#endif
class CvCascadeParams : public CvParams
{
public:
enum { BOOST = 0 };
static const int defaultStageType = BOOST;
static const int defaultFeatureType = CvFeatureParams::HAAR;
CvCascadeParams();
CvCascadeParams( int _stageType, int _featureType );
void write( FileStorage &fs ) const;
bool read( const FileNode &node );
void printDefaults() const;
void printAttrs() const;
bool scanAttr( const String prmName, const String val );
int stageType;
int featureType;
Size winSize;
};
class CvCascadeClassifier
{
public:
bool train( const String _cascadeDirName,
const String _posFilename,
const String _negFilename,
int _numPos, int _numNeg,
int _precalcValBufSize, int _precalcIdxBufSize,
int _numStages,
const CvCascadeParams& _cascadeParams,
const CvFeatureParams& _featureParams,
const CvCascadeBoostParams& _stageParams,
bool baseFormatSave = false );
private:
int predict( int sampleIdx );
void save( const String cascadeDirName, bool baseFormat = false );
bool load( const 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 getUsedFeaturesIdxMap( Mat& featureMap );
CvCascadeParams cascadeParams;
Ptr<CvFeatureParams> featureParams;
Ptr<CvCascadeBoostParams> stageParams;
Ptr<CvFeatureEvaluator> featureEvaluator;
vector< Ptr<CvCascadeBoost> > stageClassifiers;
CvCascadeImageReader imgReader;
int numStages, curNumSamples;
int numPos, numNeg;
};
#endif