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Open Source Computer Vision Library
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57 lines
1.9 KiB
57 lines
1.9 KiB
#ifndef _OPENCV_LBPFEATURES_H_ |
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#define _OPENCV_LBPFEATURES_H_ |
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#include "traincascade_features.h" |
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#define LBPF_NAME "lbpFeatureParams" |
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struct CvLBPFeatureParams : CvFeatureParams |
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{ |
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CvLBPFeatureParams(); |
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}; |
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class CvLBPEvaluator : public CvFeatureEvaluator |
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{ |
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public: |
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virtual ~CvLBPEvaluator() {} |
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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 featureIdx, int sampleIdx) const |
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{ return (float)features[featureIdx].calc( sum, sampleIdx); } |
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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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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 _block_w, int _block_h ); |
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uchar calc( const Mat& _sum, size_t y ) const; |
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void write( FileStorage &fs ) const; |
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Rect rect; |
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int p[16]; |
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}; |
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vector<Feature> features; |
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Mat sum; |
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}; |
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inline uchar CvLBPEvaluator::Feature::calc(const Mat &_sum, size_t y) const |
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{ |
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const int* sum = _sum.ptr<int>((int)y); |
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int cval = sum[p[5]] - sum[p[6]] - sum[p[9]] + sum[p[10]]; |
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return (uchar)((sum[p[0]] - sum[p[1]] - sum[p[4]] + sum[p[5]] >= cval ? 128 : 0) | // 0 |
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(sum[p[1]] - sum[p[2]] - sum[p[5]] + sum[p[6]] >= cval ? 64 : 0) | // 1 |
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(sum[p[2]] - sum[p[3]] - sum[p[6]] + sum[p[7]] >= cval ? 32 : 0) | // 2 |
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(sum[p[6]] - sum[p[7]] - sum[p[10]] + sum[p[11]] >= cval ? 16 : 0) | // 5 |
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(sum[p[10]] - sum[p[11]] - sum[p[14]] + sum[p[15]] >= cval ? 8 : 0) | // 8 |
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(sum[p[9]] - sum[p[10]] - sum[p[13]] + sum[p[14]] >= cval ? 4 : 0) | // 7 |
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(sum[p[8]] - sum[p[9]] - sum[p[12]] + sum[p[13]] >= cval ? 2 : 0) | // 6 |
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(sum[p[4]] - sum[p[5]] - sum[p[8]] + sum[p[9]] >= cval ? 1 : 0)); // 3 |
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} |
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#endif
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