79 lines
2.6 KiB
C
79 lines
2.6 KiB
C
|
#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, vector<Mat> &histogram, Mat &norm, int nbins) const;
|
||
|
|
class Feature
|
||
|
|
{
|
||
|
|
public:
|
||
|
|
Feature();
|
||
|
|
Feature( int offset, int x, int y, int cellW, int cellH );
|
||
|
|
float calc( const vector<Mat> &_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];
|
||
|
|
};
|
||
|
|
vector<Feature> features;
|
||
|
|
|
||
|
|
Mat normSum; //for nomalization calculation (L1 or L2)
|
||
|
|
vector<Mat> 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 vector<Mat>& _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 *hist = _hists[binIdx].ptr<float>(y);
|
||
|
|
res = hist[fastRect[cellIdx].p0] - hist[fastRect[cellIdx].p1] - hist[fastRect[cellIdx].p2] + hist[fastRect[cellIdx].p3];
|
||
|
|
|
||
|
|
const float *normSum = _normSum.ptr<float>(y);
|
||
|
|
normFactor = (float)(normSum[fastRect[0].p0] - normSum[fastRect[1].p1] - normSum[fastRect[2].p2] + normSum[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_
|