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#ifndef _OPENCV_HAARFEATURES_H_
#define _OPENCV_HAARFEATURES_H_
#include "traincascade_features.h"
#define CV_HAAR_FEATURE_MAX 3
#define HFP_NAME "haarFeatureParams"
class CvHaarFeatureParams : public CvFeatureParams
{
public:
enum { BASIC = 0, CORE = 1, ALL = 2 };
/* 0 - BASIC = Viola
* 1 - CORE = All upright
* 2 - ALL = All features */
CvHaarFeatureParams();
CvHaarFeatureParams( int _mode );
virtual void init( const CvFeatureParams& fp );
virtual void write( cv::FileStorage &fs ) const;
virtual bool read( const cv::FileNode &node );
virtual void printDefaults() const;
virtual void printAttrs() const;
virtual bool scanAttr( const std::string prm, const std::string val);
int mode;
};
class CvHaarEvaluator : public CvFeatureEvaluator
{
public:
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;
virtual void writeFeatures( cv::FileStorage &fs, const cv::Mat& featureMap ) const;
void writeFeature( cv::FileStorage &fs, int fi ) const; // for old file fornat
protected:
virtual void generateFeatures();
class Feature
{
public:
Feature();
Feature( int offset, bool _tilted,
int x0, int y0, int w0, int h0, float wt0,
int x1, int y1, int w1, int h1, float wt1,
int x2 = 0, int y2 = 0, int w2 = 0, int h2 = 0, float wt2 = 0.0F );
float calc( const cv::Mat &sum, const cv::Mat &tilted, size_t y) const;
void write( cv::FileStorage &fs ) const;
bool tilted;
struct
{
cv::Rect r;
float weight;
} rect[CV_HAAR_FEATURE_MAX];
struct
{
int p0, p1, p2, p3;
} fastRect[CV_HAAR_FEATURE_MAX];
};
std::vector<Feature> features;
cv::Mat sum; /* sum images (each row represents image) */
cv::Mat tilted; /* tilted sum images (each row represents image) */
cv::Mat normfactor; /* normalization factor */
};
inline float CvHaarEvaluator::operator()(int featureIdx, int sampleIdx) const
{
float nf = normfactor.at<float>(0, sampleIdx);
return !nf ? 0.0f : (features[featureIdx].calc( sum, tilted, sampleIdx)/nf);
}
inline float CvHaarEvaluator::Feature::calc( const cv::Mat &_sum, const cv::Mat &_tilted, size_t y) const
{
const int* img = tilted ? _tilted.ptr<int>((int)y) : _sum.ptr<int>((int)y);
float ret = rect[0].weight * (img[fastRect[0].p0] - img[fastRect[0].p1] - img[fastRect[0].p2] + img[fastRect[0].p3] ) +
rect[1].weight * (img[fastRect[1].p0] - img[fastRect[1].p1] - img[fastRect[1].p2] + img[fastRect[1].p3] );
if( rect[2].weight != 0.0f )
ret += rect[2].weight * (img[fastRect[2].p0] - img[fastRect[2].p1] - img[fastRect[2].p2] + img[fastRect[2].p3] );
return ret;
}
#endif
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