From: Anatoly Baksheev Date: Sat, 16 Nov 2013 15:56:08 +0000 (+0400) Subject: Fixed compilation errors: removed using namespace from hpp file. This led to pulling... X-Git-Tag: accepted/tizen/ivi/20140515.103456~1^2~230^2 X-Git-Url: http://review.tizen.org/git/?a=commitdiff_plain;h=37a754621a8d0924a73b30e13acb99e6a950610d;p=profile%2Fivi%2Fopencv.git Fixed compilation errors: removed using namespace from hpp file. This led to pulling cv::ACCESS_MASK to global namespace where conflict with the same name in 'windows.h' Conflicts: apps/traincascade/boost.cpp --- diff --git a/apps/traincascade/HOGfeatures.cpp b/apps/traincascade/HOGfeatures.cpp index 8bbdee6..49af05c 100644 --- a/apps/traincascade/HOGfeatures.cpp +++ b/apps/traincascade/HOGfeatures.cpp @@ -5,6 +5,7 @@ #include "cascadeclassifier.h" using namespace std; +using namespace cv; CvHOGFeatureParams::CvHOGFeatureParams() { diff --git a/apps/traincascade/HOGfeatures.h b/apps/traincascade/HOGfeatures.h index 329c607..cdf7587 100644 --- a/apps/traincascade/HOGfeatures.h +++ b/apps/traincascade/HOGfeatures.h @@ -20,23 +20,23 @@ 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); + int _maxSampleCount, cv::Size _winSize ); + virtual void setImage(const cv::Mat& img, uchar clsLabel, int idx); virtual float operator()(int varIdx, int sampleIdx) const; - virtual void writeFeatures( FileStorage &fs, const Mat& featureMap ) const; + virtual void writeFeatures( cv::FileStorage &fs, const cv::Mat& featureMap ) const; protected: virtual void generateFeatures(); - virtual void integralHistogram(const Mat &img, std::vector &histogram, Mat &norm, int nbins) const; + virtual void integralHistogram(const cv::Mat &img, std::vector &histogram, cv::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 &_hists, const Mat &_normSum, size_t y, int featComponent ) const; - void write( FileStorage &fs ) const; - void write( FileStorage &fs, int varIdx ) const; + float calc( const std::vector &_hists, const cv::Mat &_normSum, size_t y, int featComponent ) const; + void write( cv::FileStorage &fs ) const; + void write( cv::FileStorage &fs, int varIdx ) const; - Rect rect[N_CELLS]; //cells + cv::Rect rect[N_CELLS]; //cells struct { @@ -45,8 +45,8 @@ protected: }; std::vector features; - Mat normSum; //for nomalization calculation (L1 or L2) - std::vector hist; + cv::Mat normSum; //for nomalization calculation (L1 or L2) + std::vector hist; }; inline float CvHOGEvaluator::operator()(int varIdx, int sampleIdx) const @@ -57,7 +57,7 @@ inline float CvHOGEvaluator::operator()(int varIdx, int sampleIdx) const return features[featureIdx].calc( hist, normSum, sampleIdx, componentIdx); } -inline float CvHOGEvaluator::Feature::calc( const std::vector& _hists, const Mat& _normSum, size_t y, int featComponent ) const +inline float CvHOGEvaluator::Feature::calc( const std::vector& _hists, const cv::Mat& _normSum, size_t y, int featComponent ) const { float normFactor; float res; diff --git a/apps/traincascade/boost.cpp b/apps/traincascade/boost.cpp index 6d11655..d1a2b3e 100644 --- a/apps/traincascade/boost.cpp +++ b/apps/traincascade/boost.cpp @@ -1,6 +1,19 @@ #include "opencv2/core/core.hpp" #include "opencv2/core/internal.hpp" +using cv::Size; +using cv::Mat; +using cv::Point; +using cv::FileStorage; +using cv::Rect; +using cv::Ptr; +using cv::FileNode; +using cv::Mat_; +using cv::Range; +using cv::FileNodeIterator; +using cv::ParallelLoopBody; + + #include "boost.h" #include "cascadeclassifier.h" #include diff --git a/apps/traincascade/boost.h b/apps/traincascade/boost.h index 2a08048..0edf776 100644 --- a/apps/traincascade/boost.h +++ b/apps/traincascade/boost.h @@ -13,8 +13,8 @@ struct CvCascadeBoostParams : CvBoostParams CvCascadeBoostParams( int _boostType, float _minHitRate, float _maxFalseAlarm, double _weightTrimRate, int _maxDepth, int _maxWeakCount ); virtual ~CvCascadeBoostParams() {} - void write( FileStorage &fs ) const; - bool read( const FileNode &node ); + void write( cv::FileStorage &fs ) const; + bool read( const cv::FileNode &node ); virtual void printDefaults() const; virtual void printAttrs() const; virtual bool scanAttr( const std::string prmName, const std::string val); @@ -45,7 +45,7 @@ struct CvCascadeBoostTrainData : CvDTreeTrainData virtual void free_train_data(); const CvFeatureEvaluator* featureEvaluator; - Mat valCache; // precalculated feature values (CV_32FC1) + cv::Mat valCache; // precalculated feature values (CV_32FC1) CvMat _resp; // for casting int numPrecalcVal, numPrecalcIdx; }; @@ -54,9 +54,9 @@ class CvCascadeBoostTree : public CvBoostTree { public: virtual CvDTreeNode* predict( int sampleIdx ) const; - void write( FileStorage &fs, const Mat& featureMap ); - void read( const FileNode &node, CvBoost* _ensemble, CvDTreeTrainData* _data ); - void markFeaturesInMap( Mat& featureMap ); + void write( cv::FileStorage &fs, const cv::Mat& featureMap ); + void read( const cv::FileNode &node, CvBoost* _ensemble, CvDTreeTrainData* _data ); + void markFeaturesInMap( cv::Mat& featureMap ); protected: virtual void split_node_data( CvDTreeNode* n ); }; @@ -70,10 +70,10 @@ public: virtual float predict( int sampleIdx, bool returnSum = false ) const; float getThreshold() const { return threshold; } - void write( FileStorage &fs, const Mat& featureMap ) const; - bool read( const FileNode &node, const CvFeatureEvaluator* _featureEvaluator, + void write( cv::FileStorage &fs, const cv::Mat& featureMap ) const; + bool read( const cv::FileNode &node, const CvFeatureEvaluator* _featureEvaluator, const CvCascadeBoostParams& _params ); - void markUsedFeaturesInMap( Mat& featureMap ); + void markUsedFeaturesInMap( cv::Mat& featureMap ); protected: virtual bool set_params( const CvBoostParams& _params ); virtual void update_weights( CvBoostTree* tree ); diff --git a/apps/traincascade/cascadeclassifier.cpp b/apps/traincascade/cascadeclassifier.cpp index 66f6876..69dd866 100644 --- a/apps/traincascade/cascadeclassifier.cpp +++ b/apps/traincascade/cascadeclassifier.cpp @@ -5,6 +5,7 @@ #include using namespace std; +using namespace cv; static const char* stageTypes[] = { CC_BOOST }; static const char* featureTypes[] = { CC_HAAR, CC_LBP, CC_HOG }; diff --git a/apps/traincascade/cascadeclassifier.h b/apps/traincascade/cascadeclassifier.h index 3eb50b5..93be478 100644 --- a/apps/traincascade/cascadeclassifier.h +++ b/apps/traincascade/cascadeclassifier.h @@ -72,8 +72,8 @@ public: CvCascadeParams(); CvCascadeParams( int _stageType, int _featureType ); - void write( FileStorage &fs ) const; - bool read( const FileNode &node ); + void write( cv::FileStorage &fs ) const; + bool read( const cv::FileNode &node ); void printDefaults() const; void printAttrs() const; @@ -81,7 +81,7 @@ public: int stageType; int featureType; - Size winSize; + cv::Size winSize; }; class CvCascadeClassifier @@ -104,20 +104,20 @@ private: bool updateTrainingSet( double& acceptanceRatio ); int fillPassedSamples( int first, int count, bool isPositive, int64& consumed ); - void writeParams( FileStorage &fs ) const; - void writeStages( FileStorage &fs, const Mat& featureMap ) const; - void writeFeatures( FileStorage &fs, const Mat& featureMap ) const; - bool readParams( const FileNode &node ); - bool readStages( const FileNode &node ); + void writeParams( cv::FileStorage &fs ) const; + void writeStages( cv::FileStorage &fs, const cv::Mat& featureMap ) const; + void writeFeatures( cv::FileStorage &fs, const cv::Mat& featureMap ) const; + bool readParams( const cv::FileNode &node ); + bool readStages( const cv::FileNode &node ); - void getUsedFeaturesIdxMap( Mat& featureMap ); + void getUsedFeaturesIdxMap( cv::Mat& featureMap ); CvCascadeParams cascadeParams; - Ptr featureParams; - Ptr stageParams; + cv::Ptr featureParams; + cv::Ptr stageParams; - Ptr featureEvaluator; - std::vector< Ptr > stageClassifiers; + cv::Ptr featureEvaluator; + std::vector< cv::Ptr > stageClassifiers; CvCascadeImageReader imgReader; int numStages, curNumSamples; int numPos, numNeg; diff --git a/apps/traincascade/features.cpp b/apps/traincascade/features.cpp index 9629509..a772aa3 100644 --- a/apps/traincascade/features.cpp +++ b/apps/traincascade/features.cpp @@ -5,6 +5,7 @@ #include "cascadeclassifier.h" using namespace std; +using namespace cv; float calcNormFactor( const Mat& sum, const Mat& sqSum ) { diff --git a/apps/traincascade/haarfeatures.cpp b/apps/traincascade/haarfeatures.cpp index 9f8bce0..d31db4f 100644 --- a/apps/traincascade/haarfeatures.cpp +++ b/apps/traincascade/haarfeatures.cpp @@ -5,6 +5,7 @@ #include "cascadeclassifier.h" using namespace std; +using namespace cv; CvHaarFeatureParams::CvHaarFeatureParams() : mode(BASIC) { diff --git a/apps/traincascade/haarfeatures.h b/apps/traincascade/haarfeatures.h index 472822b..0894d09 100644 --- a/apps/traincascade/haarfeatures.h +++ b/apps/traincascade/haarfeatures.h @@ -18,8 +18,8 @@ public: CvHaarFeatureParams( int _mode ); virtual void init( const CvFeatureParams& fp ); - virtual void write( FileStorage &fs ) const; - virtual bool read( const FileNode &node ); + virtual void write( cv::FileStorage &fs ) const; + virtual bool read( const cv::FileNode &node ); virtual void printDefaults() const; virtual void printAttrs() const; @@ -32,11 +32,11 @@ class CvHaarEvaluator : public CvFeatureEvaluator { public: virtual void init(const CvFeatureParams *_featureParams, - int _maxSampleCount, Size _winSize ); - virtual void setImage(const Mat& img, uchar clsLabel, int idx); + 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( FileStorage &fs, const Mat& featureMap ) const; - void writeFeature( FileStorage &fs, int fi ) const; // for old file fornat + 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(); @@ -48,13 +48,13 @@ protected: 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 Mat &sum, const Mat &tilted, size_t y) const; - void write( FileStorage &fs ) const; + float calc( const cv::Mat &sum, const cv::Mat &tilted, size_t y) const; + void write( cv::FileStorage &fs ) const; bool tilted; struct { - Rect r; + cv::Rect r; float weight; } rect[CV_HAAR_FEATURE_MAX]; @@ -65,9 +65,9 @@ protected: }; std::vector features; - Mat sum; /* sum images (each row represents image) */ - Mat tilted; /* tilted sum images (each row represents image) */ - Mat normfactor; /* normalization factor */ + 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 @@ -76,7 +76,7 @@ inline float CvHaarEvaluator::operator()(int featureIdx, int sampleIdx) const return !nf ? 0.0f : (features[featureIdx].calc( sum, tilted, sampleIdx)/nf); } -inline float CvHaarEvaluator::Feature::calc( const Mat &_sum, const Mat &_tilted, size_t y) const +inline float CvHaarEvaluator::Feature::calc( const cv::Mat &_sum, const cv::Mat &_tilted, size_t y) const { const int* img = tilted ? _tilted.ptr((int)y) : _sum.ptr((int)y); float ret = rect[0].weight * (img[fastRect[0].p0] - img[fastRect[0].p1] - img[fastRect[0].p2] + img[fastRect[0].p3] ) + diff --git a/apps/traincascade/imagestorage.cpp b/apps/traincascade/imagestorage.cpp index 9faf84a..394481b 100644 --- a/apps/traincascade/imagestorage.cpp +++ b/apps/traincascade/imagestorage.cpp @@ -8,6 +8,7 @@ #include using namespace std; +using namespace cv; bool CvCascadeImageReader::create( const string _posFilename, const string _negFilename, Size _winSize ) { diff --git a/apps/traincascade/imagestorage.h b/apps/traincascade/imagestorage.h index dd08e66..fb68e25 100644 --- a/apps/traincascade/imagestorage.h +++ b/apps/traincascade/imagestorage.h @@ -3,15 +3,15 @@ #include "highgui.h" -using namespace cv; + class CvCascadeImageReader { public: - bool create( const std::string _posFilename, const std::string _negFilename, Size _winSize ); + bool create( const std::string _posFilename, const std::string _negFilename, cv::Size _winSize ); void restart() { posReader.restart(); } - bool getNeg(Mat &_img) { return negReader.get( _img ); } - bool getPos(Mat &_img) { return posReader.get( _img ); } + bool getNeg(cv::Mat &_img) { return negReader.get( _img ); } + bool getPos(cv::Mat &_img) { return posReader.get( _img ); } private: class PosReader @@ -20,7 +20,7 @@ private: PosReader(); virtual ~PosReader(); bool create( const std::string _filename ); - bool get( Mat &_img ); + bool get( cv::Mat &_img ); void restart(); short* vec; @@ -35,18 +35,18 @@ private: { public: NegReader(); - bool create( const std::string _filename, Size _winSize ); - bool get( Mat& _img ); + bool create( const std::string _filename, cv::Size _winSize ); + bool get( cv::Mat& _img ); bool nextImg(); - Mat src, img; + cv::Mat src, img; std::vector imgFilenames; - Point offset, point; + cv::Point offset, point; float scale; float scaleFactor; float stepFactor; size_t last, round; - Size winSize; + cv::Size winSize; } negReader; }; diff --git a/apps/traincascade/lbpfeatures.cpp b/apps/traincascade/lbpfeatures.cpp index cf9bb7b..522d90a 100644 --- a/apps/traincascade/lbpfeatures.cpp +++ b/apps/traincascade/lbpfeatures.cpp @@ -4,6 +4,8 @@ #include "lbpfeatures.h" #include "cascadeclassifier.h" +using namespace cv; + CvLBPFeatureParams::CvLBPFeatureParams() { maxCatCount = 256; diff --git a/apps/traincascade/lbpfeatures.h b/apps/traincascade/lbpfeatures.h index d4397c4..3e36a58 100644 --- a/apps/traincascade/lbpfeatures.h +++ b/apps/traincascade/lbpfeatures.h @@ -15,11 +15,11 @@ 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); + int _maxSampleCount, cv::Size _winSize ); + virtual void setImage(const cv::Mat& img, uchar clsLabel, int idx); virtual float operator()(int featureIdx, int sampleIdx) const { return (float)features[featureIdx].calc( sum, sampleIdx); } - virtual void writeFeatures( FileStorage &fs, const Mat& featureMap ) const; + virtual void writeFeatures( cv::FileStorage &fs, const cv::Mat& featureMap ) const; protected: virtual void generateFeatures(); @@ -28,18 +28,18 @@ protected: 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; + uchar calc( const cv::Mat& _sum, size_t y ) const; + void write( cv::FileStorage &fs ) const; - Rect rect; + cv::Rect rect; int p[16]; }; std::vector features; - Mat sum; + cv::Mat sum; }; -inline uchar CvLBPEvaluator::Feature::calc(const Mat &_sum, size_t y) const +inline uchar CvLBPEvaluator::Feature::calc(const cv::Mat &_sum, size_t y) const { const int* psum = _sum.ptr((int)y); int cval = psum[p[5]] - psum[p[6]] - psum[p[9]] + psum[p[10]]; diff --git a/apps/traincascade/traincascade.cpp b/apps/traincascade/traincascade.cpp index dfb49b5..c051d3f 100644 --- a/apps/traincascade/traincascade.cpp +++ b/apps/traincascade/traincascade.cpp @@ -5,6 +5,7 @@ #include "cascadeclassifier.h" using namespace std; +using namespace cv; int main( int argc, char* argv[] ) { diff --git a/apps/traincascade/traincascade_features.h b/apps/traincascade/traincascade_features.h index dde0f1a..dfba7a3 100644 --- a/apps/traincascade/traincascade_features.h +++ b/apps/traincascade/traincascade_features.h @@ -30,13 +30,13 @@ (p3) = (rect).x + (rect).width - (rect).height \ + (step) * ((rect).y + (rect).width + (rect).height); -float calcNormFactor( const Mat& sum, const Mat& sqSum ); +float calcNormFactor( const cv::Mat& sum, const cv::Mat& sqSum ); template -void _writeFeatures( const std::vector features, FileStorage &fs, const Mat& featureMap ) +void _writeFeatures( const std::vector features, cv::FileStorage &fs, const cv::Mat& featureMap ) { fs << FEATURES << "["; - const Mat_& featureMap_ = (const Mat_&)featureMap; + const cv::Mat_& featureMap_ = (const cv::Mat_&)featureMap; for ( int fi = 0; fi < featureMap.cols; fi++ ) if ( featureMap_(0, fi) >= 0 ) { @@ -53,8 +53,8 @@ public: CvParams(); virtual ~CvParams() {} // from|to file - virtual void write( FileStorage &fs ) const = 0; - virtual bool read( const FileNode &node ) = 0; + 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; @@ -68,9 +68,9 @@ 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 create( int featureType ); + virtual void write( cv::FileStorage &fs ) const; + virtual bool read( const cv::FileNode &node ); + static cv::Ptr 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 }; @@ -80,25 +80,25 @@ 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; + 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 Ptr create(int type); + static cv::Ptr 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; } + const cv::Mat& getCls() const { return cls; } float getCls(int si) const { return cls.at(si, 0); } protected: virtual void generateFeatures() = 0; int npos, nneg; int numFeatures; - Size winSize; + cv::Size winSize; CvFeatureParams *featureParams; - Mat cls; + cv::Mat cls; }; #endif