opencv/apps/traincascade/lbpfeatures.h

58 lines
2.0 KiB
C++

#ifndef _OPENCV_LBPFEATURES_H_
#define _OPENCV_LBPFEATURES_H_
#include "traincascade_features.h"
#define LBPF_NAME "lbpFeatureParams"
struct CvLBPFeatureParams : CvFeatureParams
{
CvLBPFeatureParams();
};
class CvLBPEvaluator : public CvFeatureEvaluator
{
public:
virtual ~CvLBPEvaluator() {}
virtual void init(const CvFeatureParams *_featureParams,
int _maxSampleCount, cv::Size _winSize );
virtual void setImage(const cv::Mat& img, uchar clsLabel, int idx);
virtual float operator()(int featureIdx, int sampleIdx) const
{ return (float)features[featureIdx].calc( sum, sampleIdx); }
virtual void writeFeatures( cv::FileStorage &fs, const cv::Mat& featureMap ) const;
protected:
virtual void generateFeatures();
class Feature
{
public:
Feature();
Feature( int offset, int x, int y, int _block_w, int _block_h );
uchar calc( const cv::Mat& _sum, size_t y ) const;
void write( cv::FileStorage &fs ) const;
cv::Rect rect;
int p[16];
};
std::vector<Feature> features;
cv::Mat sum;
};
inline uchar CvLBPEvaluator::Feature::calc(const cv::Mat &_sum, size_t y) const
{
const int* psum = _sum.ptr<int>((int)y);
int cval = psum[p[5]] - psum[p[6]] - psum[p[9]] + psum[p[10]];
return (uchar)((psum[p[0]] - psum[p[1]] - psum[p[4]] + psum[p[5]] >= cval ? 128 : 0) | // 0
(psum[p[1]] - psum[p[2]] - psum[p[5]] + psum[p[6]] >= cval ? 64 : 0) | // 1
(psum[p[2]] - psum[p[3]] - psum[p[6]] + psum[p[7]] >= cval ? 32 : 0) | // 2
(psum[p[6]] - psum[p[7]] - psum[p[10]] + psum[p[11]] >= cval ? 16 : 0) | // 5
(psum[p[10]] - psum[p[11]] - psum[p[14]] + psum[p[15]] >= cval ? 8 : 0) | // 8
(psum[p[9]] - psum[p[10]] - psum[p[13]] + psum[p[14]] >= cval ? 4 : 0) | // 7
(psum[p[8]] - psum[p[9]] - psum[p[12]] + psum[p[13]] >= cval ? 2 : 0) | // 6
(psum[p[4]] - psum[p[5]] - psum[p[8]] + psum[p[9]] >= cval ? 1 : 0)); // 3
}
#endif