718c41634f
1.项目后端整体迁移至PaddleOCR-NCNN算法，已通过基本的兼容性测试 2.工程改为使用CMake组织，后续为了更好地兼容第三方库，不再提供QMake工程 3.重整权利声明文件，重整代码工程，确保最小化侵权风险 Log: 切换后端至PaddleOCR-NCNN，切换工程为CMake Change-Id: I4d5d2c5d37505a4a24b389b1a4c5d12f17bfa38c
102 lines
3.9 KiB
C++
102 lines
3.9 KiB
C++
#ifndef _OPENCV_FEATURES_H_
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#define _OPENCV_FEATURES_H_
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#include "imagestorage.h"
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#include <stdio.h>
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#define FEATURES "features"
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#define CV_SUM_OFFSETS( p0, p1, p2, p3, rect, step ) \
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/* (x, y) */ \
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(p0) = (rect).x + (step) * (rect).y; \
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/* (x + w, y) */ \
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(p1) = (rect).x + (rect).width + (step) * (rect).y; \
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/* (x + w, y) */ \
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(p2) = (rect).x + (step) * ((rect).y + (rect).height); \
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/* (x + w, y + h) */ \
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(p3) = (rect).x + (rect).width + (step) * ((rect).y + (rect).height);
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#define CV_TILTED_OFFSETS( p0, p1, p2, p3, rect, step ) \
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/* (x, y) */ \
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(p0) = (rect).x + (step) * (rect).y; \
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/* (x - h, y + h) */ \
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(p1) = (rect).x - (rect).height + (step) * ((rect).y + (rect).height);\
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/* (x + w, y + w) */ \
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(p2) = (rect).x + (rect).width + (step) * ((rect).y + (rect).width); \
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/* (x + w - h, y + w + h) */ \
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(p3) = (rect).x + (rect).width - (rect).height \
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+ (step) * ((rect).y + (rect).width + (rect).height);
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float calcNormFactor( const cv::Mat& sum, const cv::Mat& sqSum );
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template<class Feature>
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void _writeFeatures( const std::vector<Feature> features, cv::FileStorage &fs, const cv::Mat& featureMap )
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{
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fs << FEATURES << "[";
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const cv::Mat_<int>& featureMap_ = (const cv::Mat_<int>&)featureMap;
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for ( int fi = 0; fi < featureMap.cols; fi++ )
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if ( featureMap_(0, fi) >= 0 )
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{
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fs << "{";
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features[fi].write( fs );
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fs << "}";
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}
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fs << "]";
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}
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class CvParams
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{
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public:
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CvParams();
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virtual ~CvParams() {}
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// from|to file
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virtual void write( cv::FileStorage &fs ) const = 0;
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virtual bool read( const cv::FileNode &node ) = 0;
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// from|to screen
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virtual void printDefaults() const;
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virtual void printAttrs() const;
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virtual bool scanAttr( const std::string prmName, const std::string val );
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std::string name;
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};
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class CvFeatureParams : public CvParams
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{
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public:
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enum { HAAR = 0, LBP = 1, HOG = 2 };
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CvFeatureParams();
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virtual void init( const CvFeatureParams& fp );
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virtual void write( cv::FileStorage &fs ) const;
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virtual bool read( const cv::FileNode &node );
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static cv::Ptr<CvFeatureParams> create( int featureType );
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int maxCatCount; // 0 in case of numerical features
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int featSize; // 1 in case of simple features (HAAR, LBP) and N_BINS(9)*N_CELLS(4) in case of Dalal's HOG features
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};
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class CvFeatureEvaluator
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{
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public:
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virtual ~CvFeatureEvaluator() {}
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virtual void init(const CvFeatureParams *_featureParams,
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int _maxSampleCount, cv::Size _winSize );
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virtual void setImage(const cv::Mat& img, uchar clsLabel, int idx);
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virtual void writeFeatures( cv::FileStorage &fs, const cv::Mat& featureMap ) const = 0;
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virtual float operator()(int featureIdx, int sampleIdx) const = 0;
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static cv::Ptr<CvFeatureEvaluator> create(int type);
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int getNumFeatures() const { return numFeatures; }
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int getMaxCatCount() const { return featureParams->maxCatCount; }
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int getFeatureSize() const { return featureParams->featSize; }
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const cv::Mat& getCls() const { return cls; }
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float getCls(int si) const { return cls.at<float>(si, 0); }
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protected:
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virtual void generateFeatures() = 0;
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int npos, nneg;
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int numFeatures;
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cv::Size winSize;
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CvFeatureParams *featureParams;
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cv::Mat cls;
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};
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#endif
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