Remove all using directives for STL namespace and members
Made all STL usages explicit to be able automatically find all usages of particular class or function.
This commit is contained in:
Andrey Kamaev
@@ -270,17 +270,17 @@ namespace cv
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};
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Octree();
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Octree( const vector<Point3f>& points, int maxLevels = 10, int minPoints = 20 );
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Octree( const std::vector<Point3f>& points, int maxLevels = 10, int minPoints = 20 );
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virtual ~Octree();
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virtual void buildTree( const vector<Point3f>& points, int maxLevels = 10, int minPoints = 20 );
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virtual void buildTree( const std::vector<Point3f>& points, int maxLevels = 10, int minPoints = 20 );
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virtual void getPointsWithinSphere( const Point3f& center, float radius,
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vector<Point3f>& points ) const;
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const vector<Node>& getNodes() const { return nodes; }
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std::vector<Point3f>& points ) const;
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const std::vector<Node>& getNodes() const { return nodes; }
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private:
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int minPoints;
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vector<Point3f> points;
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vector<Node> nodes;
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std::vector<Point3f> points;
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std::vector<Node> nodes;
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virtual void buildNext(size_t node_ind);
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};
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@@ -292,19 +292,19 @@ namespace cv
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struct EmptyMeshException {};
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Mesh3D();
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Mesh3D(const vector<Point3f>& vtx);
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Mesh3D(const std::vector<Point3f>& vtx);
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~Mesh3D();
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void buildOctree();
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void clearOctree();
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float estimateResolution(float tryRatio = 0.1f);
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void computeNormals(float normalRadius, int minNeighbors = 20);
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void computeNormals(const vector<int>& subset, float normalRadius, int minNeighbors = 20);
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void computeNormals(const std::vector<int>& subset, float normalRadius, int minNeighbors = 20);
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void writeAsVrml(const String& file, const vector<Scalar>& colors = vector<Scalar>()) const;
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void writeAsVrml(const std::string& file, const std::vector<Scalar>& colors = std::vector<Scalar>()) const;
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vector<Point3f> vtx;
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vector<Point3f> normals;
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std::vector<Point3f> vtx;
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std::vector<Point3f> normals;
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float resolution;
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Octree octree;
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@@ -335,10 +335,10 @@ namespace cv
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void setLogger(std::ostream* log);
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void selectRandomSubset(float ratio);
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void setSubset(const vector<int>& subset);
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void setSubset(const std::vector<int>& subset);
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void compute();
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void match(const SpinImageModel& scene, vector< vector<Vec2i> >& result);
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void match(const SpinImageModel& scene, std::vector< std::vector<Vec2i> >& result);
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Mat packRandomScaledSpins(bool separateScale = false, size_t xCount = 10, size_t yCount = 10) const;
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@@ -368,12 +368,12 @@ namespace cv
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protected:
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void defaultParams();
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void matchSpinToModel(const Mat& spin, vector<int>& indeces,
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vector<float>& corrCoeffs, bool useExtremeOutliers = true) const;
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void matchSpinToModel(const Mat& spin, std::vector<int>& indeces,
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std::vector<float>& corrCoeffs, bool useExtremeOutliers = true) const;
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void repackSpinImages(const vector<uchar>& mask, Mat& spinImages, bool reAlloc = true) const;
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void repackSpinImages(const std::vector<uchar>& mask, Mat& spinImages, bool reAlloc = true) const;
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vector<int> subset;
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std::vector<int> subset;
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Mesh3D mesh;
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Mat spinImages;
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std::ostream* out;
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@@ -416,8 +416,8 @@ namespace cv
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size_t getDescriptorSize() const;
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Size getGridSize( Size imgsize, Size winStride ) const;
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virtual void compute(const Mat& img, vector<float>& descriptors, Size winStride=Size(),
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const vector<Point>& locations=vector<Point>()) const;
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virtual void compute(const Mat& img, std::vector<float>& descriptors, Size winStride=Size(),
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const std::vector<Point>& locations=std::vector<Point>()) const;
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virtual void computeLogPolarMapping(Mat& mappingMask) const;
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virtual void SSD(const Mat& img, Point pt, Mat& ssd) const;
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@@ -486,13 +486,13 @@ namespace cv
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virtual void clear();
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// useful function to do simple bundle adjustment tasks
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static void bundleAdjust(vector<Point3d>& points, // positions of points in global coordinate system (input and output)
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const vector<vector<Point2d> >& imagePoints, // projections of 3d points for every camera
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const vector<vector<int> >& visibility, // visibility of 3d points for every camera
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vector<Mat>& cameraMatrix, // intrinsic matrices of all cameras (input and output)
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vector<Mat>& R, // rotation matrices of all cameras (input and output)
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vector<Mat>& T, // translation vector of all cameras (input and output)
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vector<Mat>& distCoeffs, // distortion coefficients of all cameras (input and output)
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static void bundleAdjust(std::vector<Point3d>& points, // positions of points in global coordinate system (input and output)
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const std::vector<std::vector<Point2d> >& imagePoints, // projections of 3d points for every camera
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const std::vector<std::vector<int> >& visibility, // visibility of 3d points for every camera
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std::vector<Mat>& cameraMatrix, // intrinsic matrices of all cameras (input and output)
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std::vector<Mat>& R, // rotation matrices of all cameras (input and output)
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std::vector<Mat>& T, // translation vector of all cameras (input and output)
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std::vector<Mat>& distCoeffs, // distortion coefficients of all cameras (input and output)
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const TermCriteria& criteria=
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TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, 30, DBL_EPSILON),
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BundleAdjustCallback cb = 0, void* user_data = 0);
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@@ -558,7 +558,7 @@ namespace cv
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};
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CV_EXPORTS_W int chamerMatching( Mat& img, Mat& templ,
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CV_OUT vector<vector<Point> >& results, CV_OUT vector<float>& cost,
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CV_OUT std::vector<std::vector<Point> >& results, CV_OUT std::vector<float>& cost,
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double templScale=1, int maxMatches = 20,
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double minMatchDistance = 1.0, int padX = 3,
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int padY = 3, int scales = 5, double minScale = 0.6, double maxScale = 1.6,
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@@ -757,9 +757,9 @@ namespace cv
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Mat Rsri;
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Mat Csri;
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vector<int> Rsr;
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vector<int> Csr;
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vector<double> Wsr;
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std::vector<int> Rsr;
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std::vector<int> Csr;
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std::vector<double> Wsr;
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int S, R, M, N, ind1;
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int top, bottom,left,right;
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@@ -768,13 +768,13 @@ namespace cv
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struct kernel
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{
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kernel() { w = 0; }
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vector<double> weights;
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std::vector<double> weights;
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int w;
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};
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Mat ETAyx;
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Mat CSIyx;
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vector<kernel> w_ker_2D;
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std::vector<kernel> w_ker_2D;
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void create_map(int M, int N, int R, int S, double ro0);
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};
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@@ -838,8 +838,8 @@ namespace cv
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int S, R, M, N;
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int top, bottom,left,right;
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double ro0, romax, a, q;
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vector<vector<pixel> > L;
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vector<double> A;
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std::vector<std::vector<pixel> > L;
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std::vector<double> A;
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void subdivide_recursively(double x, double y, int i, int j, double length, double smin);
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bool get_uv(double x, double y, int&u, int&v);
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@@ -869,10 +869,10 @@ namespace cv
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}
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// Serializes this object to a given filename.
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void save(const string& filename) const;
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void save(const std::string& filename) const;
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// Deserializes this object from a given filename.
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void load(const string& filename);
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void load(const std::string& filename);
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// Serializes this object to a given cv::FileStorage.
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void save(FileStorage& fs) const;
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@@ -926,10 +926,10 @@ namespace cv
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CV_WRAP virtual void predict(InputArray src, CV_OUT int &label, CV_OUT double &confidence) const = 0;
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// Serializes this object to a given filename.
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CV_WRAP virtual void save(const string& filename) const;
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CV_WRAP virtual void save(const std::string& filename) const;
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// Deserializes this object from a given filename.
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CV_WRAP virtual void load(const string& filename);
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CV_WRAP virtual void load(const std::string& filename);
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// Serializes this object to a given cv::FileStorage.
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virtual void save(FileStorage& fs) const = 0;
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@@ -76,9 +76,9 @@ struct CV_EXPORTS CvMeanShiftTrackerParams
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CvTermCriteria term_crit = CvTermCriteria());
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int tracking_type;
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vector<float> h_range;
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vector<float> s_range;
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vector<float> v_range;
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std::vector<float> h_range;
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std::vector<float> s_range;
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std::vector<float> v_range;
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CvTermCriteria term_crit;
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};
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@@ -145,7 +145,7 @@ class CV_EXPORTS CvFeatureTracker
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private:
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Ptr<Feature2D> dd;
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Ptr<DescriptorMatcher> matcher;
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vector<DMatch> matches;
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std::vector<DMatch> matches;
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Mat prev_image;
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Mat prev_image_bw;
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@@ -153,7 +153,7 @@ private:
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Point2d prev_center;
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int ittr;
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vector<Point2f> features[2];
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std::vector<Point2f> features[2];
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public:
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Mat disp_matches;
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@@ -65,10 +65,6 @@ namespace cv {
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namespace of2 {
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using std::list;
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using std::map;
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using std::multiset;
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/*
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Return data format of a FABMAP compare call
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*/
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@@ -115,50 +111,50 @@ public:
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//methods to add training data for sampling method
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virtual void addTraining(const Mat& queryImgDescriptor);
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virtual void addTraining(const vector<Mat>& queryImgDescriptors);
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virtual void addTraining(const std::vector<Mat>& queryImgDescriptors);
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//methods to add to the test data
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virtual void add(const Mat& queryImgDescriptor);
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virtual void add(const vector<Mat>& queryImgDescriptors);
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virtual void add(const std::vector<Mat>& queryImgDescriptors);
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//accessors
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const vector<Mat>& getTrainingImgDescriptors() const;
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const vector<Mat>& getTestImgDescriptors() const;
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const std::vector<Mat>& getTrainingImgDescriptors() const;
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const std::vector<Mat>& getTestImgDescriptors() const;
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//Main FabMap image comparison
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void compare(const Mat& queryImgDescriptor,
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vector<IMatch>& matches, bool addQuery = false,
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std::vector<IMatch>& matches, bool addQuery = false,
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const Mat& mask = Mat());
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void compare(const Mat& queryImgDescriptor,
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const Mat& testImgDescriptors, vector<IMatch>& matches,
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const Mat& testImgDescriptors, std::vector<IMatch>& matches,
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const Mat& mask = Mat());
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void compare(const Mat& queryImgDescriptor,
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const vector<Mat>& testImgDescriptors,
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vector<IMatch>& matches, const Mat& mask = Mat());
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void compare(const vector<Mat>& queryImgDescriptors, vector<
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const std::vector<Mat>& testImgDescriptors,
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std::vector<IMatch>& matches, const Mat& mask = Mat());
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void compare(const std::vector<Mat>& queryImgDescriptors, std::vector<
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IMatch>& matches, bool addQuery = false, const Mat& mask =
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Mat());
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void compare(const vector<Mat>& queryImgDescriptors,
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const vector<Mat>& testImgDescriptors,
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vector<IMatch>& matches, const Mat& mask = Mat());
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void compare(const std::vector<Mat>& queryImgDescriptors,
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const std::vector<Mat>& testImgDescriptors,
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std::vector<IMatch>& matches, const Mat& mask = Mat());
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protected:
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void compareImgDescriptor(const Mat& queryImgDescriptor,
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int queryIndex, const vector<Mat>& testImgDescriptors,
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vector<IMatch>& matches);
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int queryIndex, const std::vector<Mat>& testImgDescriptors,
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std::vector<IMatch>& matches);
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void addImgDescriptor(const Mat& queryImgDescriptor);
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//the getLikelihoods method is overwritten for each different FabMap
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//method.
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virtual void getLikelihoods(const Mat& queryImgDescriptor,
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const vector<Mat>& testImgDescriptors,
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vector<IMatch>& matches);
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const std::vector<Mat>& testImgDescriptors,
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std::vector<IMatch>& matches);
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virtual double getNewPlaceLikelihood(const Mat& queryImgDescriptor);
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//turn likelihoods into probabilities (also add in motion model if used)
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void normaliseDistribution(vector<IMatch>& matches);
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void normaliseDistribution(std::vector<IMatch>& matches);
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//Chow-Liu Tree
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int pq(int q);
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@@ -174,9 +170,9 @@ protected:
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//data
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Mat clTree;
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vector<Mat> trainingImgDescriptors;
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vector<Mat> testImgDescriptors;
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vector<IMatch> priorMatches;
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std::vector<Mat> trainingImgDescriptors;
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std::vector<Mat> testImgDescriptors;
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std::vector<IMatch> priorMatches;
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//parameters
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double PzGe;
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@@ -203,8 +199,8 @@ public:
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protected:
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//FabMap1 implementation of likelihood comparison
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void getLikelihoods(const Mat& queryImgDescriptor, const vector<
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Mat>& testImgDescriptors, vector<IMatch>& matches);
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void getLikelihoods(const Mat& queryImgDescriptor, const std::vector<
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Mat>& testImgDescriptors, std::vector<IMatch>& matches);
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};
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/*
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@@ -219,8 +215,8 @@ public:
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protected:
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//FabMap look-up-table implementation of the likelihood comparison
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void getLikelihoods(const Mat& queryImgDescriptor, const vector<
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Mat>& testImgDescriptors, vector<IMatch>& matches);
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void getLikelihoods(const Mat& queryImgDescriptor, const std::vector<
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Mat>& testImgDescriptors, std::vector<IMatch>& matches);
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//precomputed data
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int (*table)[8];
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@@ -243,8 +239,8 @@ public:
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protected:
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//FabMap Fast Bail-out implementation of the likelihood comparison
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void getLikelihoods(const Mat& queryImgDescriptor, const vector<
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Mat>& testImgDescriptors, vector<IMatch>& matches);
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void getLikelihoods(const Mat& queryImgDescriptor, const std::vector<
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Mat>& testImgDescriptors, std::vector<IMatch>& matches);
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//stucture used to determine word comparison order
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struct WordStats {
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@@ -268,7 +264,7 @@ protected:
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};
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//private fast bail-out necessary functions
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void setWordStatistics(const Mat& queryImgDescriptor, multiset<WordStats>& wordData);
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void setWordStatistics(const Mat& queryImgDescriptor, std::multiset<WordStats>& wordData);
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double limitbisection(double v, double m);
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double bennettInequality(double v, double m, double delta);
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static bool compInfo(const WordStats& first, const WordStats& second);
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@@ -295,39 +291,39 @@ public:
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void addTraining(const Mat& queryImgDescriptors) {
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FabMap::addTraining(queryImgDescriptors);
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}
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void addTraining(const vector<Mat>& queryImgDescriptors);
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void addTraining(const std::vector<Mat>& queryImgDescriptors);
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void add(const Mat& queryImgDescriptors) {
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FabMap::add(queryImgDescriptors);
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}
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void add(const vector<Mat>& queryImgDescriptors);
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void add(const std::vector<Mat>& queryImgDescriptors);
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protected:
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//FabMap2 implementation of the likelihood comparison
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void getLikelihoods(const Mat& queryImgDescriptor, const vector<
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Mat>& testImgDescriptors, vector<IMatch>& matches);
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void getLikelihoods(const Mat& queryImgDescriptor, const std::vector<
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Mat>& testImgDescriptors, std::vector<IMatch>& matches);
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double getNewPlaceLikelihood(const Mat& queryImgDescriptor);
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//the likelihood function using the inverted index
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void getIndexLikelihoods(const Mat& queryImgDescriptor, vector<
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double>& defaults, map<int, vector<int> >& invertedMap,
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vector<IMatch>& matches);
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void getIndexLikelihoods(const Mat& queryImgDescriptor, std::vector<
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double>& defaults, std::map<int, std::vector<int> >& invertedMap,
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std::vector<IMatch>& matches);
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void addToIndex(const Mat& queryImgDescriptor,
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vector<double>& defaults,
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map<int, vector<int> >& invertedMap);
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std::vector<double>& defaults,
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std::map<int, std::vector<int> >& invertedMap);
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//data
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vector<double> d1, d2, d3, d4;
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vector<vector<int> > children;
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std::vector<double> d1, d2, d3, d4;
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std::vector<std::vector<int> > children;
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// TODO: inverted map a vector?
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vector<double> trainingDefaults;
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map<int, vector<int> > trainingInvertedMap;
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std::vector<double> trainingDefaults;
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std::map<int, std::vector<int> > trainingInvertedMap;
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vector<double> testDefaults;
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map<int, vector<int> > testInvertedMap;
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std::vector<double> testDefaults;
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std::map<int, std::vector<int> > testInvertedMap;
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};
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/*
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@@ -342,14 +338,14 @@ public:
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//add data to the chow-liu tree before calling make
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void add(const Mat& imgDescriptor);
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void add(const vector<Mat>& imgDescriptors);
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void add(const std::vector<Mat>& imgDescriptors);
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const vector<Mat>& getImgDescriptors() const;
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const std::vector<Mat>& getImgDescriptors() const;
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Mat make(double infoThreshold = 0.0);
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private:
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vector<Mat> imgDescriptors;
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std::vector<Mat> imgDescriptors;
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Mat mergedImgDescriptors;
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typedef struct info {
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@@ -364,18 +360,18 @@ private:
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double CP(int a, bool za, int b, bool zb); // a | b
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//calculating mutual information of all edges
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void createBaseEdges(list<info>& edges, double infoThreshold);
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void createBaseEdges(std::list<info>& edges, double infoThreshold);
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double calcMutInfo(int word1, int word2);
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static bool sortInfoScores(const info& first, const info& second);
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//selecting minimum spanning egdges with maximum information
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bool reduceEdgesToMinSpan(list<info>& edges);
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bool reduceEdgesToMinSpan(std::list<info>& edges);
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//building the tree sctructure
|
||||
Mat buildTree(int root_word, list<info> &edges);
|
||||
Mat buildTree(int root_word, std::list<info> &edges);
|
||||
void recAddToTree(Mat &cltree, int q, int pq,
|
||||
list<info> &remaining_edges);
|
||||
vector<int> extractChildren(list<info> &remaining_edges, int q);
|
||||
std::list<info> &remaining_edges);
|
||||
std::vector<int> extractChildren(std::list<info> &remaining_edges, int q);
|
||||
|
||||
};
|
||||
|
||||
|
||||
Reference in New Issue
Block a user