#ifndef _OPENCV_FEATURES_H_ #define _OPENCV_FEATURES_H_ #include "imagestorage.h" #include "cxcore.h" #include "cv.h" #include "ml.h" #include #define FEATURES "features" #define CV_SUM_OFFSETS( p0, p1, p2, p3, rect, step ) \ /* (x, y) */ \ (p0) = (rect).x + (step) * (rect).y; \ /* (x + w, y) */ \ (p1) = (rect).x + (rect).width + (step) * (rect).y; \ /* (x + w, y) */ \ (p2) = (rect).x + (step) * ((rect).y + (rect).height); \ /* (x + w, y + h) */ \ (p3) = (rect).x + (rect).width + (step) * ((rect).y + (rect).height); #define CV_TILTED_OFFSETS( p0, p1, p2, p3, rect, step ) \ /* (x, y) */ \ (p0) = (rect).x + (step) * (rect).y; \ /* (x - h, y + h) */ \ (p1) = (rect).x - (rect).height + (step) * ((rect).y + (rect).height);\ /* (x + w, y + w) */ \ (p2) = (rect).x + (rect).width + (step) * ((rect).y + (rect).width); \ /* (x + w - h, y + w + h) */ \ (p3) = (rect).x + (rect).width - (rect).height \ + (step) * ((rect).y + (rect).width + (rect).height); float calcNormFactor( const Mat& sum, const Mat& sqSum ); template void _writeFeatures( const std::vector features, FileStorage &fs, const Mat& featureMap ) { fs << FEATURES << "["; const Mat_& featureMap_ = (const Mat_&)featureMap; for ( int fi = 0; fi < featureMap.cols; fi++ ) if ( featureMap_(0, fi) >= 0 ) { fs << "{"; features[fi].write( fs ); fs << "}"; } fs << "]"; } class CvParams { public: CvParams(); virtual ~CvParams() {} // from|to file virtual void write( FileStorage &fs ) const = 0; virtual bool read( const FileNode &node ) = 0; // from|to screen virtual void printDefaults() const; virtual void printAttrs() const; virtual bool scanAttr( const std::string prmName, const std::string val ); std::string name; }; class CvFeatureParams : public CvParams { 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 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 }; 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; virtual float operator()(int featureIdx, int sampleIdx) const = 0; static Ptr 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; } float getCls(int si) const { return cls.at(si, 0); } protected: virtual void generateFeatures() = 0; int npos, nneg; int numFeatures; Size winSize; CvFeatureParams *featureParams; Mat cls; }; #endif