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