diff options
Diffstat (limited to 'thirdparty/linux/include/opencv2/tracking/feature.hpp')
| -rw-r--r-- | thirdparty/linux/include/opencv2/tracking/feature.hpp | 415 |
1 files changed, 415 insertions, 0 deletions
diff --git a/thirdparty/linux/include/opencv2/tracking/feature.hpp b/thirdparty/linux/include/opencv2/tracking/feature.hpp new file mode 100644 index 0000000..b354d62 --- /dev/null +++ b/thirdparty/linux/include/opencv2/tracking/feature.hpp @@ -0,0 +1,415 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// + // + // IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. + // + // By downloading, copying, installing or using the software you agree to this license. + // If you do not agree to this license, do not download, install, + // copy or use the software. + // + // + // License Agreement + // For Open Source Computer Vision Library + // + // Copyright (C) 2013, OpenCV Foundation, all rights reserved. + // Third party copyrights are property of their respective owners. + // + // Redistribution and use in source and binary forms, with or without modification, + // are permitted provided that the following conditions are met: + // + // * Redistribution's of source code must retain the above copyright notice, + // this list of conditions and the following disclaimer. + // + // * Redistribution's in binary form must reproduce the above copyright notice, + // this list of conditions and the following disclaimer in the documentation + // and/or other materials provided with the distribution. + // + // * The name of the copyright holders may not be used to endorse or promote products + // derived from this software without specific prior written permission. + // + // This software is provided by the copyright holders and contributors "as is" and + // any express or implied warranties, including, but not limited to, the implied + // warranties of merchantability and fitness for a particular purpose are disclaimed. + // In no event shall the Intel Corporation or contributors be liable for any direct, + // indirect, incidental, special, exemplary, or consequential damages + // (including, but not limited to, procurement of substitute goods or services; + // loss of use, data, or profits; or business interruption) however caused + // and on any theory of liability, whether in contract, strict liability, + // or tort (including negligence or otherwise) arising in any way out of + // the use of this software, even if advised of the possibility of such damage. + // + //M*/ + +#ifndef __OPENCV_FEATURE_HPP__ +#define __OPENCV_FEATURE_HPP__ + +#include "opencv2/core.hpp" +#include "opencv2/imgproc.hpp" +#include <iostream> +#include <string> +#include <time.h> + +/* + * TODO This implementation is based on apps/traincascade/ + * TODO Changed CvHaarEvaluator based on ADABOOSTING implementation (Grabner et al.) + */ + +namespace cv +{ + +//! @addtogroup tracking +//! @{ + +#define FEATURES "features" + +#define CC_FEATURES FEATURES +#define CC_FEATURE_PARAMS "featureParams" +#define CC_MAX_CAT_COUNT "maxCatCount" +#define CC_FEATURE_SIZE "featSize" +#define CC_NUM_FEATURES "numFeat" +#define CC_ISINTEGRAL "isIntegral" +#define CC_RECTS "rects" +#define CC_TILTED "tilted" +#define CC_RECT "rect" + +#define LBPF_NAME "lbpFeatureParams" +#define HOGF_NAME "HOGFeatureParams" +#define HFP_NAME "haarFeatureParams" + +#define CV_HAAR_FEATURE_MAX 3 +#define N_BINS 9 +#define N_CELLS 4 + +#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 Mat& sum, const Mat& sqSum ); + +template<class Feature> +void _writeFeatures( const std::vector<Feature> features, FileStorage &fs, const Mat& featureMap ) +{ + fs << FEATURES << "["; + const Mat_<int>& featureMap_ = (const 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( FileStorage &fs ) const = 0; + virtual bool read( const 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( FileStorage &fs ) const; + virtual bool read( const FileNode &node ); + static 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 + int numFeatures; +}; + +class CvFeatureEvaluator +{ + public: + virtual ~CvFeatureEvaluator() + { + } + virtual void init( const CvFeatureParams *_featureParams, int _maxSampleCount, Size _winSize ); + virtual void setImage( const Mat& img, uchar clsLabel, int idx ); + virtual void writeFeatures( FileStorage &fs, const Mat& featureMap ) const = 0; + virtual float operator()( int featureIdx, int sampleIdx ) = 0; + static Ptr<CvFeatureEvaluator> create( int type ); + + int getNumFeatures() const + { + return numFeatures; + } + int getMaxCatCount() const + { + return featureParams->maxCatCount; + } + int getFeatureSize() const + { + return featureParams->featSize; + } + const 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; + Size winSize; + CvFeatureParams *featureParams; + Mat cls; +}; + +class CvHaarFeatureParams : public CvFeatureParams +{ + public: + + CvHaarFeatureParams(); + + virtual void init( const CvFeatureParams& fp ); + virtual void write( FileStorage &fs ) const; + virtual bool read( const FileNode &node ); + + virtual void printDefaults() const; + virtual void printAttrs() const; + virtual bool scanAttr( const std::string prm, const std::string val ); + + bool isIntegral; +}; + +class CvHaarEvaluator : public CvFeatureEvaluator +{ + public: + + class FeatureHaar + { + + public: + + FeatureHaar( Size patchSize ); + bool eval( const Mat& image, Rect ROI, float* result ) const; + int getNumAreas(); + const std::vector<float>& getWeights() const; + const std::vector<Rect>& getAreas() const; + void write( FileStorage ) const + { + } + ; + float getInitMean() const; + float getInitSigma() const; + + private: + int m_type; + int m_numAreas; + std::vector<float> m_weights; + float m_initMean; + float m_initSigma; + void generateRandomFeature( Size imageSize ); + float getSum( const Mat& image, Rect imgROI ) const; + std::vector<Rect> m_areas; // areas within the patch over which to compute the feature + cv::Size m_initSize; // size of the patch used during training + cv::Size m_curSize; // size of the patches currently under investigation + float m_scaleFactorHeight; // scaling factor in vertical direction + float m_scaleFactorWidth; // scaling factor in horizontal direction + std::vector<Rect> m_scaleAreas; // areas after scaling + std::vector<float> m_scaleWeights; // weights after scaling + + }; + + virtual void init( const CvFeatureParams *_featureParams, int _maxSampleCount, Size _winSize ); + virtual void setImage( const Mat& img, uchar clsLabel = 0, int idx = 1 ); + virtual float operator()( int featureIdx, int sampleIdx ); + virtual void writeFeatures( FileStorage &fs, const Mat& featureMap ) const; + void writeFeature( FileStorage &fs ) const; // for old file format + const std::vector<CvHaarEvaluator::FeatureHaar>& getFeatures() const; + inline CvHaarEvaluator::FeatureHaar& getFeatures( int idx ) + { + return features[idx]; + } + void setWinSize( Size patchSize ); + Size setWinSize() const; + virtual void generateFeatures(); + + /** + * TODO new method + * \brief Overload the original generateFeatures in order to limit the number of the features + * @param numFeatures Number of the features + */ + + virtual void generateFeatures( int numFeatures ); + + protected: + bool isIntegral; + + /* TODO Added from MIL implementation */ + Mat _ii_img; + void compute_integral( const cv::Mat & img, std::vector<cv::Mat_<float> > & ii_imgs ) + { + Mat ii_img; + integral( img, ii_img, CV_32F ); + split( ii_img, ii_imgs ); + } + + std::vector<FeatureHaar> features; + Mat sum; /* sum images (each row represents image) */ +}; + +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 ); + virtual void writeFeatures( FileStorage &fs, const Mat& featureMap ) const; + protected: + virtual void generateFeatures(); + virtual void integralHistogram( const Mat &img, std::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 std::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]; + }; + std::vector<Feature> features; + + Mat normSum; //for nomalization calculation (L1 or L2) + std::vector<Mat> hist; +}; + +inline float CvHOGEvaluator::operator()( int varIdx, int sampleIdx ) +{ + 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 std::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 *phist = _hists[binIdx].ptr<float>( (int) y ); + res = phist[fastRect[cellIdx].p0] - phist[fastRect[cellIdx].p1] - phist[fastRect[cellIdx].p2] + phist[fastRect[cellIdx].p3]; + + const float *pnormSum = _normSum.ptr<float>( (int) y ); + normFactor = (float) ( pnormSum[fastRect[0].p0] - pnormSum[fastRect[1].p1] - pnormSum[fastRect[2].p2] + pnormSum[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; +} + +struct CvLBPFeatureParams : CvFeatureParams +{ + CvLBPFeatureParams(); + +}; + +class CvLBPEvaluator : public CvFeatureEvaluator +{ + public: + virtual ~CvLBPEvaluator() + { + } + virtual void init( const CvFeatureParams *_featureParams, int _maxSampleCount, Size _winSize ); + virtual void setImage( const Mat& img, uchar clsLabel, int idx ); + virtual float operator()( int featureIdx, int sampleIdx ) + { + return (float) features[featureIdx].calc( sum, sampleIdx ); + } + virtual void writeFeatures( FileStorage &fs, const 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 Mat& _sum, size_t y ) const; + void write( FileStorage &fs ) const; + + Rect rect; + int p[16]; + }; + std::vector<Feature> features; + + Mat sum; +}; + +inline uchar CvLBPEvaluator::Feature::calc( const 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 +} + +//! @} + +} /* namespace cv */ + +#endif |