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item-sort/opencv-apps/traincascade/traincascade_features.h

102 lines
3.9 KiB
C++

#ifndef _OPENCV_FEATURES_H_
#define _OPENCV_FEATURES_H_
#include "imagestorage.h"
#include <stdio.h>
#define FEATURES "features"
#define CV_SUM_OFFSETS( p0, p1, p2, p3, rect, step ) \
/* (x, y) */ \
(p0) = (rect).x + (step) * (rect).y; \
/* (x + w, y) */ \
(p1) = (rect).x + (rect).width + (step) * (rect).y; \
/* (x + w, y) */ \
(p2) = (rect).x + (step) * ((rect).y + (rect).height); \
/* (x + w, y + h) */ \
(p3) = (rect).x + (rect).width + (step) * ((rect).y + (rect).height);
#define CV_TILTED_OFFSETS( p0, p1, p2, p3, rect, step ) \
/* (x, y) */ \
(p0) = (rect).x + (step) * (rect).y; \
/* (x - h, y + h) */ \
(p1) = (rect).x - (rect).height + (step) * ((rect).y + (rect).height);\
/* (x + w, y + w) */ \
(p2) = (rect).x + (rect).width + (step) * ((rect).y + (rect).width); \
/* (x + w - h, y + w + h) */ \
(p3) = (rect).x + (rect).width - (rect).height \
+ (step) * ((rect).y + (rect).width + (rect).height);
float calcNormFactor( const cv::Mat& sum, const cv::Mat& sqSum );
template<class Feature>
void _writeFeatures( const std::vector<Feature> features, cv::FileStorage &fs, const cv::Mat& featureMap )
{
fs << FEATURES << "[";
const cv::Mat_<int>& featureMap_ = (const cv::Mat_<int>&)featureMap;
for ( int fi = 0; fi < featureMap.cols; fi++ )
if ( featureMap_(0, fi) >= 0 )
{
fs << "{";
features[fi].write( fs );
fs << "}";
}
fs << "]";
}
class CvParams
{
public:
CvParams();
virtual ~CvParams() {}
// from|to file
virtual void write( cv::FileStorage &fs ) const = 0;
virtual bool read( const cv::FileNode &node ) = 0;
// from|to screen
virtual void printDefaults() const;
virtual void printAttrs() const;
virtual bool scanAttr( const std::string prmName, const std::string val );
std::string name;
};
class CvFeatureParams : public CvParams
{
public:
enum { HAAR = 0, LBP = 1, HOG = 2 };
CvFeatureParams();
virtual void init( const CvFeatureParams& fp );
virtual void write( cv::FileStorage &fs ) const;
virtual bool read( const cv::FileNode &node );
static cv::Ptr<CvFeatureParams> create( int featureType );
int maxCatCount; // 0 in case of numerical features
int featSize; // 1 in case of simple features (HAAR, LBP) and N_BINS(9)*N_CELLS(4) in case of Dalal's HOG features
};
class CvFeatureEvaluator
{
public:
virtual ~CvFeatureEvaluator() {}
virtual void init(const CvFeatureParams *_featureParams,
int _maxSampleCount, cv::Size _winSize );
virtual void setImage(const cv::Mat& img, uchar clsLabel, int idx);
virtual void writeFeatures( cv::FileStorage &fs, const cv::Mat& featureMap ) const = 0;
virtual float operator()(int featureIdx, int sampleIdx) const = 0;
static cv::Ptr<CvFeatureEvaluator> create(int type);
int getNumFeatures() const { return numFeatures; }
int getMaxCatCount() const { return featureParams->maxCatCount; }
int getFeatureSize() const { return featureParams->featSize; }
const cv::Mat& getCls() const { return cls; }
float getCls(int si) const { return cls.at<float>(si, 0); }
protected:
virtual void generateFeatures() = 0;
int npos, nneg;
int numFeatures;
cv::Size winSize;
CvFeatureParams *featureParams;
cv::Mat cls;
};
#endif