#ifndef _OPENCV_CASCADECLASSIFIER_H_ #define _OPENCV_CASCADECLASSIFIER_H_ #include #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 fillPassedSamles( 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 featureParams; Ptr stageParams; Ptr featureEvaluator; vector< Ptr > stageClassifiers; CvCascadeImageReader imgReader; int numStages, curNumSamples; int numPos, numNeg; }; #endif