#ifndef _OPENCV_HOGFEATURES_H_ #define _OPENCV_HOGFEATURES_H_ #include "traincascade_features.h" //#define TEST_INTHIST_BUILD //#define TEST_FEAT_CALC #define N_BINS 9 #define N_CELLS 4 #define HOGF_NAME "HOGFeatureParams" struct CvHOGFeatureParams : public CvFeatureParams { CvHOGFeatureParams(); }; 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); virtual float operator()(int varIdx, int sampleIdx) const; virtual void writeFeatures( FileStorage &fs, const Mat& featureMap ) const; protected: virtual void generateFeatures(); virtual void integralHistogram(const Mat &img, std::vector &histogram, Mat &norm, int nbins) const; class Feature { public: Feature(); Feature( int offset, int x, int y, int cellW, int cellH ); float calc( const std::vector &_hists, const Mat &_normSum, size_t y, int featComponent ) const; void write( FileStorage &fs ) const; void write( FileStorage &fs, int varIdx ) const; Rect rect[N_CELLS]; //cells struct { int p0, p1, p2, p3; } fastRect[N_CELLS]; }; std::vector features; Mat normSum; //for nomalization calculation (L1 or L2) std::vector hist; }; inline float CvHOGEvaluator::operator()(int varIdx, int sampleIdx) const { int featureIdx = varIdx / (N_BINS * N_CELLS); int componentIdx = varIdx % (N_BINS * N_CELLS); //return features[featureIdx].calc( hist, sampleIdx, componentIdx); return features[featureIdx].calc( hist, normSum, sampleIdx, componentIdx); } inline float CvHOGEvaluator::Feature::calc( const std::vector& _hists, const Mat& _normSum, size_t y, int featComponent ) const { float normFactor; float res; int binIdx = featComponent % N_BINS; int cellIdx = featComponent / N_BINS; const float *phist = _hists[binIdx].ptr((int)y); res = phist[fastRect[cellIdx].p0] - phist[fastRect[cellIdx].p1] - phist[fastRect[cellIdx].p2] + phist[fastRect[cellIdx].p3]; const float *pnormSum = _normSum.ptr((int)y); normFactor = (float)(pnormSum[fastRect[0].p0] - pnormSum[fastRect[1].p1] - pnormSum[fastRect[2].p2] + pnormSum[fastRect[3].p3]); res = (res > 0.001f) ? ( res / (normFactor + 0.001f) ) : 0.f; //for cutting negative values, which apper due to floating precision return res; } #endif // _OPENCV_HOGFEATURES_H_