1 files changed, 0 insertions, 998 deletions
diff --git a/src/c/hardware/rasberrypi/libraries/opencv/opencv2/contrib/contrib.hpp b/src/c/hardware/rasberrypi/libraries/opencv/opencv2/contrib/contrib.hpp
deleted file mode 100644
index d5879424..00000000
--- a/src/c/hardware/rasberrypi/libraries/opencv/opencv2/contrib/contrib.hpp
+++ /dev/null
@@ -1,998 +0,0 @@
-/*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) 2000-2008, Intel Corporation, all rights reserved.
-// Copyright (C) 2009, Willow Garage Inc., 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_CONTRIB_HPP__
-#define __OPENCV_CONTRIB_HPP__
-
-#include "opencv2/core/core.hpp"
-#include "opencv2/imgproc/imgproc.hpp"
-#include "opencv2/features2d/features2d.hpp"
-#include "opencv2/objdetect/objdetect.hpp"
-
-#ifdef __cplusplus
-
-/****************************************************************************************\
-*                                   Adaptive Skin Detector                               *
-\****************************************************************************************/
-
-class CV_EXPORTS CvAdaptiveSkinDetector
-{
-private:
-    enum {
-        GSD_HUE_LT = 3,
-        GSD_HUE_UT = 33,
-        GSD_INTENSITY_LT = 15,
-        GSD_INTENSITY_UT = 250
-    };
-
-    class CV_EXPORTS Histogram
-    {
-    private:
-        enum {
-            HistogramSize = (GSD_HUE_UT - GSD_HUE_LT + 1)
-        };
-
-    protected:
-        int findCoverageIndex(double surfaceToCover, int defaultValue = 0);
-
-    public:
-        CvHistogram *fHistogram;
-        Histogram();
-        virtual ~Histogram();
-
-        void findCurveThresholds(int &x1, int &x2, double percent = 0.05);
-        void mergeWith(Histogram *source, double weight);
-    };
-
-    int nStartCounter, nFrameCount, nSkinHueLowerBound, nSkinHueUpperBound, nMorphingMethod, nSamplingDivider;
-    double fHistogramMergeFactor, fHuePercentCovered;
-    Histogram histogramHueMotion, skinHueHistogram;
-    IplImage *imgHueFrame, *imgSaturationFrame, *imgLastGrayFrame, *imgMotionFrame, *imgFilteredFrame;
-    IplImage *imgShrinked, *imgTemp, *imgGrayFrame, *imgHSVFrame;
-
-protected:
-    void initData(IplImage *src, int widthDivider, int heightDivider);
-    void adaptiveFilter();
-
-public:
-
-    enum {
-        MORPHING_METHOD_NONE = 0,
-        MORPHING_METHOD_ERODE = 1,
-        MORPHING_METHOD_ERODE_ERODE = 2,
-        MORPHING_METHOD_ERODE_DILATE = 3
-    };
-
-    CvAdaptiveSkinDetector(int samplingDivider = 1, int morphingMethod = MORPHING_METHOD_NONE);
-    virtual ~CvAdaptiveSkinDetector();
-
-    virtual void process(IplImage *inputBGRImage, IplImage *outputHueMask);
-};
-
-
-/****************************************************************************************\
- *                                  Fuzzy MeanShift Tracker                               *
- \****************************************************************************************/
-
-class CV_EXPORTS CvFuzzyPoint {
-public:
-    double x, y, value;
-
-    CvFuzzyPoint(double _x, double _y);
-};
-
-class CV_EXPORTS CvFuzzyCurve {
-private:
-    std::vector<CvFuzzyPoint> points;
-    double value, centre;
-
-    bool between(double x, double x1, double x2);
-
-public:
-    CvFuzzyCurve();
-    ~CvFuzzyCurve();
-
-    void setCentre(double _centre);
-    double getCentre();
-    void clear();
-    void addPoint(double x, double y);
-    double calcValue(double param);
-    double getValue();
-    void setValue(double _value);
-};
-
-class CV_EXPORTS CvFuzzyFunction {
-public:
-    std::vector<CvFuzzyCurve> curves;
-
-    CvFuzzyFunction();
-    ~CvFuzzyFunction();
-    void addCurve(CvFuzzyCurve *curve, double value = 0);
-    void resetValues();
-    double calcValue();
-    CvFuzzyCurve *newCurve();
-};
-
-class CV_EXPORTS CvFuzzyRule {
-private:
-    CvFuzzyCurve *fuzzyInput1, *fuzzyInput2;
-    CvFuzzyCurve *fuzzyOutput;
-public:
-    CvFuzzyRule();
-    ~CvFuzzyRule();
-    void setRule(CvFuzzyCurve *c1, CvFuzzyCurve *c2, CvFuzzyCurve *o1);
-    double calcValue(double param1, double param2);
-    CvFuzzyCurve *getOutputCurve();
-};
-
-class CV_EXPORTS CvFuzzyController {
-private:
-    std::vector<CvFuzzyRule*> rules;
-public:
-    CvFuzzyController();
-    ~CvFuzzyController();
-    void addRule(CvFuzzyCurve *c1, CvFuzzyCurve *c2, CvFuzzyCurve *o1);
-    double calcOutput(double param1, double param2);
-};
-
-class CV_EXPORTS CvFuzzyMeanShiftTracker
-{
-private:
-    class FuzzyResizer
-    {
-    private:
-        CvFuzzyFunction iInput, iOutput;
-        CvFuzzyController fuzzyController;
-    public:
-        FuzzyResizer();
-        int calcOutput(double edgeDensity, double density);
-    };
-
-    class SearchWindow
-    {
-    public:
-        FuzzyResizer *fuzzyResizer;
-        int x, y;
-        int width, height, maxWidth, maxHeight, ellipseHeight, ellipseWidth;
-        int ldx, ldy, ldw, ldh, numShifts, numIters;
-        int xGc, yGc;
-        long m00, m01, m10, m11, m02, m20;
-        double ellipseAngle;
-        double density;
-        unsigned int depthLow, depthHigh;
-        int verticalEdgeLeft, verticalEdgeRight, horizontalEdgeTop, horizontalEdgeBottom;
-
-        SearchWindow();
-        ~SearchWindow();
-        void setSize(int _x, int _y, int _width, int _height);
-        void initDepthValues(IplImage *maskImage, IplImage *depthMap);
-        bool shift();
-        void extractInfo(IplImage *maskImage, IplImage *depthMap, bool initDepth);
-        void getResizeAttribsEdgeDensityLinear(int &resizeDx, int &resizeDy, int &resizeDw, int &resizeDh);
-        void getResizeAttribsInnerDensity(int &resizeDx, int &resizeDy, int &resizeDw, int &resizeDh);
-        void getResizeAttribsEdgeDensityFuzzy(int &resizeDx, int &resizeDy, int &resizeDw, int &resizeDh);
-        bool meanShift(IplImage *maskImage, IplImage *depthMap, int maxIteration, bool initDepth);
-    };
-
-public:
-    enum TrackingState
-    {
-        tsNone          = 0,
-        tsSearching     = 1,
-        tsTracking      = 2,
-        tsSetWindow     = 3,
-        tsDisabled      = 10
-    };
-
-    enum ResizeMethod {
-        rmEdgeDensityLinear     = 0,
-        rmEdgeDensityFuzzy      = 1,
-        rmInnerDensity          = 2
-    };
-
-    enum {
-        MinKernelMass           = 1000
-    };
-
-    SearchWindow kernel;
-    int searchMode;
-
-private:
-    enum
-    {
-        MaxMeanShiftIteration   = 5,
-        MaxSetSizeIteration     = 5
-    };
-
-    void findOptimumSearchWindow(SearchWindow &searchWindow, IplImage *maskImage, IplImage *depthMap, int maxIteration, int resizeMethod, bool initDepth);
-
-public:
-    CvFuzzyMeanShiftTracker();
-    ~CvFuzzyMeanShiftTracker();
-
-    void track(IplImage *maskImage, IplImage *depthMap, int resizeMethod, bool resetSearch, int minKernelMass = MinKernelMass);
-};
-
-
-namespace cv
-{
-
-    class CV_EXPORTS Octree
-    {
-    public:
-        struct Node
-        {
-            Node() {}
-            int begin, end;
-            float x_min, x_max, y_min, y_max, z_min, z_max;
-            int maxLevels;
-            bool isLeaf;
-            int children[8];
-        };
-
-        Octree();
-        Octree( const vector<Point3f>& points, int maxLevels = 10, int minPoints = 20 );
-        virtual ~Octree();
-
-        virtual void buildTree( const vector<Point3f>& points, int maxLevels = 10, int minPoints = 20 );
-        virtual void getPointsWithinSphere( const Point3f& center, float radius,
-                                           vector<Point3f>& points ) const;
-        const vector<Node>& getNodes() const { return nodes; }
-    private:
-        int minPoints;
-        vector<Point3f> points;
-        vector<Node> nodes;
-
-        virtual void buildNext(size_t node_ind);
-    };
-
-
-    class CV_EXPORTS Mesh3D
-    {
-    public:
-        struct EmptyMeshException {};
-
-        Mesh3D();
-        Mesh3D(const vector<Point3f>& vtx);
-        ~Mesh3D();
-
-        void buildOctree();
-        void clearOctree();
-        float estimateResolution(float tryRatio = 0.1f);
-        void computeNormals(float normalRadius, int minNeighbors = 20);
-        void computeNormals(const vector<int>& subset, float normalRadius, int minNeighbors = 20);
-
-        void writeAsVrml(const String& file, const vector<Scalar>& colors = vector<Scalar>()) const;
-
-        vector<Point3f> vtx;
-        vector<Point3f> normals;
-        float resolution;
-        Octree octree;
-
-        const static Point3f allzero;
-    };
-
-    class CV_EXPORTS SpinImageModel
-    {
-    public:
-
-        /* model parameters, leave unset for default or auto estimate */
-        float normalRadius;
-        int minNeighbors;
-
-        float binSize;
-        int imageWidth;
-
-        float lambda;
-        float gamma;
-
-        float T_GeometriccConsistency;
-        float T_GroupingCorespondances;
-
-        /* public interface */
-        SpinImageModel();
-        explicit SpinImageModel(const Mesh3D& mesh);
-        ~SpinImageModel();
-
-        void setLogger(std::ostream* log);
-        void selectRandomSubset(float ratio);
-        void setSubset(const vector<int>& subset);
-        void compute();
-
-        void match(const SpinImageModel& scene, vector< vector<Vec2i> >& result);
-
-        Mat packRandomScaledSpins(bool separateScale = false, size_t xCount = 10, size_t yCount = 10) const;
-
-        size_t getSpinCount() const { return spinImages.rows; }
-        Mat getSpinImage(size_t index) const { return spinImages.row((int)index); }
-        const Point3f& getSpinVertex(size_t index) const { return mesh.vtx[subset[index]]; }
-        const Point3f& getSpinNormal(size_t index) const { return mesh.normals[subset[index]]; }
-
-        const Mesh3D& getMesh() const { return mesh; }
-        Mesh3D& getMesh() { return mesh; }
-
-        /* static utility functions */
-        static bool spinCorrelation(const Mat& spin1, const Mat& spin2, float lambda, float& result);
-
-        static Point2f calcSpinMapCoo(const Point3f& point, const Point3f& vertex, const Point3f& normal);
-
-        static float geometricConsistency(const Point3f& pointScene1, const Point3f& normalScene1,
-                                          const Point3f& pointModel1, const Point3f& normalModel1,
-                                          const Point3f& pointScene2, const Point3f& normalScene2,
-                                          const Point3f& pointModel2, const Point3f& normalModel2);
-
-        static float groupingCreteria(const Point3f& pointScene1, const Point3f& normalScene1,
-                                      const Point3f& pointModel1, const Point3f& normalModel1,
-                                      const Point3f& pointScene2, const Point3f& normalScene2,
-                                      const Point3f& pointModel2, const Point3f& normalModel2,
-                                      float gamma);
-    protected:
-        void defaultParams();
-
-        void matchSpinToModel(const Mat& spin, vector<int>& indeces,
-                              vector<float>& corrCoeffs, bool useExtremeOutliers = true) const;
-
-        void repackSpinImages(const vector<uchar>& mask, Mat& spinImages, bool reAlloc = true) const;
-
-        vector<int> subset;
-        Mesh3D mesh;
-        Mat spinImages;
-        std::ostream* out;
-    };
-
-    class CV_EXPORTS TickMeter
-    {
-    public:
-        TickMeter();
-        void start();
-        void stop();
-
-        int64 getTimeTicks() const;
-        double getTimeMicro() const;
-        double getTimeMilli() const;
-        double getTimeSec()   const;
-        int64 getCounter() const;
-
-        void reset();
-    private:
-        int64 counter;
-        int64 sumTime;
-        int64 startTime;
-    };
-
-    CV_EXPORTS std::ostream& operator<<(std::ostream& out, const TickMeter& tm);
-
-    class CV_EXPORTS SelfSimDescriptor
-    {
-    public:
-        SelfSimDescriptor();
-        SelfSimDescriptor(int _ssize, int _lsize,
-                          int _startDistanceBucket=DEFAULT_START_DISTANCE_BUCKET,
-                          int _numberOfDistanceBuckets=DEFAULT_NUM_DISTANCE_BUCKETS,
-                          int _nangles=DEFAULT_NUM_ANGLES);
-        SelfSimDescriptor(const SelfSimDescriptor& ss);
-        virtual ~SelfSimDescriptor();
-        SelfSimDescriptor& operator = (const SelfSimDescriptor& ss);
-
-        size_t getDescriptorSize() const;
-        Size getGridSize( Size imgsize, Size winStride ) const;
-
-        virtual void compute(const Mat& img, vector<float>& descriptors, Size winStride=Size(),
-                             const vector<Point>& locations=vector<Point>()) const;
-        virtual void computeLogPolarMapping(Mat& mappingMask) const;
-        virtual void SSD(const Mat& img, Point pt, Mat& ssd) const;
-
-        int smallSize;
-        int largeSize;
-        int startDistanceBucket;
-        int numberOfDistanceBuckets;
-        int numberOfAngles;
-
-        enum { DEFAULT_SMALL_SIZE = 5, DEFAULT_LARGE_SIZE = 41,
-            DEFAULT_NUM_ANGLES = 20, DEFAULT_START_DISTANCE_BUCKET = 3,
-            DEFAULT_NUM_DISTANCE_BUCKETS = 7 };
-    };
-
-
-    typedef bool (*BundleAdjustCallback)(int iteration, double norm_error, void* user_data);
-
-    class CV_EXPORTS LevMarqSparse {
-    public:
-        LevMarqSparse();
-        LevMarqSparse(int npoints, // number of points
-                      int ncameras, // number of cameras
-                      int nPointParams, // number of params per one point  (3 in case of 3D points)
-                      int nCameraParams, // number of parameters per one camera
-                      int nErrParams, // number of parameters in measurement vector
-                      // for 1 point at one camera (2 in case of 2D projections)
-                      Mat& visibility, // visibility matrix. rows correspond to points, columns correspond to cameras
-                      // 1 - point is visible for the camera, 0 - invisible
-                      Mat& P0, // starting vector of parameters, first cameras then points
-                      Mat& X, // measurements, in order of visibility. non visible cases are skipped
-                      TermCriteria criteria, // termination criteria
-
-                      // callback for estimation of Jacobian matrices
-                      void (CV_CDECL * fjac)(int i, int j, Mat& point_params,
-                                             Mat& cam_params, Mat& A, Mat& B, void* data),
-                      // callback for estimation of backprojection errors
-                      void (CV_CDECL * func)(int i, int j, Mat& point_params,
-                                             Mat& cam_params, Mat& estim, void* data),
-                      void* data, // user-specific data passed to the callbacks
-                      BundleAdjustCallback cb, void* user_data
-                      );
-
-        virtual ~LevMarqSparse();
-
-        virtual void run( int npoints, // number of points
-                         int ncameras, // number of cameras
-                         int nPointParams, // number of params per one point  (3 in case of 3D points)
-                         int nCameraParams, // number of parameters per one camera
-                         int nErrParams, // number of parameters in measurement vector
-                         // for 1 point at one camera (2 in case of 2D projections)
-                         Mat& visibility, // visibility matrix. rows correspond to points, columns correspond to cameras
-                         // 1 - point is visible for the camera, 0 - invisible
-                         Mat& P0, // starting vector of parameters, first cameras then points
-                         Mat& X, // measurements, in order of visibility. non visible cases are skipped
-                         TermCriteria criteria, // termination criteria
-
-                         // callback for estimation of Jacobian matrices
-                         void (CV_CDECL * fjac)(int i, int j, Mat& point_params,
-                                                Mat& cam_params, Mat& A, Mat& B, void* data),
-                         // callback for estimation of backprojection errors
-                         void (CV_CDECL * func)(int i, int j, Mat& point_params,
-                                                Mat& cam_params, Mat& estim, void* data),
-                         void* data // user-specific data passed to the callbacks
-                         );
-
-        virtual void clear();
-
-        // useful function to do simple bundle adjustment tasks
-        static void bundleAdjust(vector<Point3d>& points, // positions of points in global coordinate system (input and output)
-                                 const vector<vector<Point2d> >& imagePoints, // projections of 3d points for every camera
-                                 const vector<vector<int> >& visibility, // visibility of 3d points for every camera
-                                 vector<Mat>& cameraMatrix, // intrinsic matrices of all cameras (input and output)
-                                 vector<Mat>& R, // rotation matrices of all cameras (input and output)
-                                 vector<Mat>& T, // translation vector of all cameras (input and output)
-                                 vector<Mat>& distCoeffs, // distortion coefficients of all cameras (input and output)
-                                 const TermCriteria& criteria=
-                                 TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, 30, DBL_EPSILON),
-                                 BundleAdjustCallback cb = 0, void* user_data = 0);
-
-    public:
-        virtual void optimize(CvMat &_vis); //main function that runs minimization
-
-        //iteratively asks for measurement for visible camera-point pairs
-        void ask_for_proj(CvMat &_vis,bool once=false);
-        //iteratively asks for Jacobians for every camera_point pair
-        void ask_for_projac(CvMat &_vis);
-
-        CvMat* err; //error X-hX
-        double prevErrNorm, errNorm;
-        double lambda;
-        CvTermCriteria criteria;
-        int iters;
-
-        CvMat** U; //size of array is equal to number of cameras
-        CvMat** V; //size of array is equal to number of points
-        CvMat** inv_V_star; //inverse of V*
-
-        CvMat** A;
-        CvMat** B;
-        CvMat** W;
-
-        CvMat* X; //measurement
-        CvMat* hX; //current measurement extimation given new parameter vector
-
-        CvMat* prevP; //current already accepted parameter.
-        CvMat* P; // parameters used to evaluate function with new params
-        // this parameters may be rejected
-
-        CvMat* deltaP; //computed increase of parameters (result of normal system solution )
-
-        CvMat** ea; // sum_i  AijT * e_ij , used as right part of normal equation
-        // length of array is j = number of cameras
-        CvMat** eb; // sum_j  BijT * e_ij , used as right part of normal equation
-        // length of array is i = number of points
-
-        CvMat** Yj; //length of array is i = num_points
-
-        CvMat* S; //big matrix of block Sjk  , each block has size num_cam_params x num_cam_params
-
-        CvMat* JtJ_diag; //diagonal of JtJ,  used to backup diagonal elements before augmentation
-
-        CvMat* Vis_index; // matrix which element is index of measurement for point i and camera j
-
-        int num_cams;
-        int num_points;
-        int num_err_param;
-        int num_cam_param;
-        int num_point_param;
-
-        //target function and jacobian pointers, which needs to be initialized
-        void (*fjac)(int i, int j, Mat& point_params, Mat& cam_params, Mat& A, Mat& B, void* data);
-        void (*func)(int i, int j, Mat& point_params, Mat& cam_params, Mat& estim, void* data);
-
-        void* data;
-
-        BundleAdjustCallback cb;
-        void* user_data;
-    };
-
-    CV_EXPORTS_W int chamerMatching( Mat& img, Mat& templ,
-                                  CV_OUT vector<vector<Point> >& results, CV_OUT vector<float>& cost,
-                                  double templScale=1, int maxMatches = 20,
-                                  double minMatchDistance = 1.0, int padX = 3,
-                                  int padY = 3, int scales = 5, double minScale = 0.6, double maxScale = 1.6,
-                                  double orientationWeight = 0.5, double truncate = 20);
-
-
-    class CV_EXPORTS_W StereoVar
-    {
-    public:
-        // Flags
-        enum {USE_INITIAL_DISPARITY = 1, USE_EQUALIZE_HIST = 2, USE_SMART_ID = 4, USE_AUTO_PARAMS = 8, USE_MEDIAN_FILTERING = 16};
-        enum {CYCLE_O, CYCLE_V};
-        enum {PENALIZATION_TICHONOV, PENALIZATION_CHARBONNIER, PENALIZATION_PERONA_MALIK};
-
-        //! the default constructor
-        CV_WRAP StereoVar();
-
-        //! the full constructor taking all the necessary algorithm parameters
-        CV_WRAP StereoVar(int levels, double pyrScale, int nIt, int minDisp, int maxDisp, int poly_n, double poly_sigma, float fi, float lambda, int penalization, int cycle, int flags);
-
-        //! the destructor
-        virtual ~StereoVar();
-
-        //! the stereo correspondence operator that computes disparity map for the specified rectified stereo pair
-        CV_WRAP_AS(compute) virtual void operator()(const Mat& left, const Mat& right, CV_OUT Mat& disp);
-
-        CV_PROP_RW int      levels;
-        CV_PROP_RW double   pyrScale;
-        CV_PROP_RW int      nIt;
-        CV_PROP_RW int      minDisp;
-        CV_PROP_RW int      maxDisp;
-        CV_PROP_RW int      poly_n;
-        CV_PROP_RW double   poly_sigma;
-        CV_PROP_RW float    fi;
-        CV_PROP_RW float    lambda;
-        CV_PROP_RW int      penalization;
-        CV_PROP_RW int      cycle;
-        CV_PROP_RW int      flags;
-
-    private:
-        void autoParams();
-        void FMG(Mat &I1, Mat &I2, Mat &I2x, Mat &u, int level);
-        void VCycle_MyFAS(Mat &I1_h, Mat &I2_h, Mat &I2x_h, Mat &u_h, int level);
-        void VariationalSolver(Mat &I1_h, Mat &I2_h, Mat &I2x_h, Mat &u_h, int level);
-    };
-
-    CV_EXPORTS void polyfit(const Mat& srcx, const Mat& srcy, Mat& dst, int order);
-
-    class CV_EXPORTS Directory
-    {
-        public:
-            static std::vector<std::string> GetListFiles  ( const std::string& path, const std::string & exten = "*", bool addPath = true );
-            static std::vector<std::string> GetListFilesR ( const std::string& path, const std::string & exten = "*", bool addPath = true );
-            static std::vector<std::string> GetListFolders( const std::string& path, const std::string & exten = "*", bool addPath = true );
-    };
-
-    /*
-     * Generation of a set of different colors by the following way:
-     * 1) generate more then need colors (in "factor" times) in RGB,
-     * 2) convert them to Lab,
-     * 3) choose the needed count of colors from the set that are more different from
-     *    each other,
-     * 4) convert the colors back to RGB
-     */
-    CV_EXPORTS void generateColors( std::vector<Scalar>& colors, size_t count, size_t factor=100 );
-
-
-    /*
-     *  Estimate the rigid body motion from frame0 to frame1. The method is based on the paper
-     *  "Real-Time Visual Odometry from Dense RGB-D Images", F. Steinbucker, J. Strum, D. Cremers, ICCV, 2011.
-     */
-    enum { ROTATION          = 1,
-           TRANSLATION       = 2,
-           RIGID_BODY_MOTION = 4
-         };
-    CV_EXPORTS bool RGBDOdometry( Mat& Rt, const Mat& initRt,
-                                  const Mat& image0, const Mat& depth0, const Mat& mask0,
-                                  const Mat& image1, const Mat& depth1, const Mat& mask1,
-                                  const Mat& cameraMatrix, float minDepth=0.f, float maxDepth=4.f, float maxDepthDiff=0.07f,
-                                  const std::vector<int>& iterCounts=std::vector<int>(),
-                                  const std::vector<float>& minGradientMagnitudes=std::vector<float>(),
-                                  int transformType=RIGID_BODY_MOTION );
-
-    /**
-    *Bilinear interpolation technique.
-    *
-    *The value of a desired cortical pixel is obtained through a bilinear interpolation of the values
-    *of the four nearest neighbouring Cartesian pixels to the center of the RF.
-    *The same principle is applied to the inverse transformation.
-    *
-    *More details can be found in http://dx.doi.org/10.1007/978-3-642-23968-7_5
-    */
-    class CV_EXPORTS LogPolar_Interp
-    {
-    public:
-
-        LogPolar_Interp() {}
-
-        /**
-        *Constructor
-        *\param w the width of the input image
-        *\param h the height of the input image
-        *\param center the transformation center: where the output precision is maximal
-        *\param R the number of rings of the cortical image (default value 70 pixel)
-        *\param ro0 the radius of the blind spot (default value 3 pixel)
-        *\param interp interpolation algorithm
-        *\param full \a 1 (default value) means that the retinal image (the inverse transform) is computed within the circumscribing circle.
-        *            \a 0 means that the retinal image is computed within the inscribed circle.
-        *\param S the number of sectors of the cortical image (default value 70 pixel).
-        *         Its value is usually internally computed to obtain a pixel aspect ratio equals to 1.
-        *\param sp \a 1 (default value) means that the parameter \a S is internally computed.
-        *          \a 0 means that the parameter \a S is provided by the user.
-        */
-        LogPolar_Interp(int w, int h, Point2i center, int R=70, double ro0=3.0,
-                        int interp=INTER_LINEAR, int full=1, int S=117, int sp=1);
-        /**
-        *Transformation from Cartesian image to cortical (log-polar) image.
-        *\param source the Cartesian image
-        *\return the transformed image (cortical image)
-        */
-        const Mat to_cortical(const Mat &source);
-        /**
-        *Transformation from cortical image to retinal (inverse log-polar) image.
-        *\param source the cortical image
-        *\return the transformed image (retinal image)
-        */
-        const Mat to_cartesian(const Mat &source);
-        /**
-        *Destructor
-        */
-        ~LogPolar_Interp();
-
-    protected:
-
-        Mat Rsri;
-        Mat Csri;
-
-        int S, R, M, N;
-        int top, bottom,left,right;
-        double ro0, romax, a, q;
-        int interp;
-
-        Mat ETAyx;
-        Mat CSIyx;
-
-        void create_map(int M, int N, int R, int S, double ro0);
-    };
-
-    /**
-    *Overlapping circular receptive fields technique
-    *
-    *The Cartesian plane is divided in two regions: the fovea and the periphery.
-    *The fovea (oversampling) is handled by using the bilinear interpolation technique described above, whereas in
-    *the periphery we use the overlapping Gaussian circular RFs.
-    *
-    *More details can be found in http://dx.doi.org/10.1007/978-3-642-23968-7_5
-    */
-    class CV_EXPORTS LogPolar_Overlapping
-    {
-    public:
-        LogPolar_Overlapping() {}
-
-        /**
-        *Constructor
-        *\param w the width of the input image
-        *\param h the height of the input image
-        *\param center the transformation center: where the output precision is maximal
-        *\param R the number of rings of the cortical image (default value 70 pixel)
-        *\param ro0 the radius of the blind spot (default value 3 pixel)
-        *\param full \a 1 (default value) means that the retinal image (the inverse transform) is computed within the circumscribing circle.
-        *            \a 0 means that the retinal image is computed within the inscribed circle.
-        *\param S the number of sectors of the cortical image (default value 70 pixel).
-        *         Its value is usually internally computed to obtain a pixel aspect ratio equals to 1.
-        *\param sp \a 1 (default value) means that the parameter \a S is internally computed.
-        *          \a 0 means that the parameter \a S is provided by the user.
-        */
-        LogPolar_Overlapping(int w, int h, Point2i center, int R=70,
-                             double ro0=3.0, int full=1, int S=117, int sp=1);
-        /**
-        *Transformation from Cartesian image to cortical (log-polar) image.
-        *\param source the Cartesian image
-        *\return the transformed image (cortical image)
-        */
-        const Mat to_cortical(const Mat &source);
-        /**
-        *Transformation from cortical image to retinal (inverse log-polar) image.
-        *\param source the cortical image
-        *\return the transformed image (retinal image)
-        */
-        const Mat to_cartesian(const Mat &source);
-        /**
-        *Destructor
-        */
-        ~LogPolar_Overlapping();
-
-    protected:
-
-        Mat Rsri;
-        Mat Csri;
-        vector<int> Rsr;
-        vector<int> Csr;
-        vector<double> Wsr;
-
-        int S, R, M, N, ind1;
-        int top, bottom,left,right;
-        double ro0, romax, a, q;
-
-        struct kernel
-        {
-            kernel() { w = 0; }
-            vector<double> weights;
-            int w;
-        };
-
-        Mat ETAyx;
-        Mat CSIyx;
-        vector<kernel> w_ker_2D;
-
-        void create_map(int M, int N, int R, int S, double ro0);
-    };
-
-    /**
-    * Adjacent receptive fields technique
-    *
-    *All the Cartesian pixels, whose coordinates in the cortical domain share the same integer part, are assigned to the same RF.
-    *The precision of the boundaries of the RF can be improved by breaking each pixel into subpixels and assigning each of them to the correct RF.
-    *This technique is implemented from: Traver, V., Pla, F.: Log-polar mapping template design: From task-level requirements
-    *to geometry parameters. Image Vision Comput. 26(10) (2008) 1354-1370
-    *
-    *More details can be found in http://dx.doi.org/10.1007/978-3-642-23968-7_5
-    */
-    class CV_EXPORTS LogPolar_Adjacent
-    {
-    public:
-        LogPolar_Adjacent() {}
-
-        /**
-         *Constructor
-         *\param w the width of the input image
-         *\param h the height of the input image
-         *\param center the transformation center: where the output precision is maximal
-         *\param R the number of rings of the cortical image (default value 70 pixel)
-         *\param ro0 the radius of the blind spot (default value 3 pixel)
-         *\param smin the size of the subpixel (default value 0.25 pixel)
-         *\param full \a 1 (default value) means that the retinal image (the inverse transform) is computed within the circumscribing circle.
-         *            \a 0 means that the retinal image is computed within the inscribed circle.
-         *\param S the number of sectors of the cortical image (default value 70 pixel).
-         *         Its value is usually internally computed to obtain a pixel aspect ratio equals to 1.
-         *\param sp \a 1 (default value) means that the parameter \a S is internally computed.
-         *          \a 0 means that the parameter \a S is provided by the user.
-         */
-        LogPolar_Adjacent(int w, int h, Point2i center, int R=70, double ro0=3.0, double smin=0.25, int full=1, int S=117, int sp=1);
-        /**
-         *Transformation from Cartesian image to cortical (log-polar) image.
-         *\param source the Cartesian image
-         *\return the transformed image (cortical image)
-         */
-        const Mat to_cortical(const Mat &source);
-        /**
-         *Transformation from cortical image to retinal (inverse log-polar) image.
-         *\param source the cortical image
-         *\return the transformed image (retinal image)
-         */
-        const Mat to_cartesian(const Mat &source);
-        /**
-         *Destructor
-         */
-        ~LogPolar_Adjacent();
-
-    protected:
-        struct pixel
-        {
-            pixel() { u = v = 0; a = 0.; }
-            int u;
-            int v;
-            double a;
-        };
-        int S, R, M, N;
-        int top, bottom,left,right;
-        double ro0, romax, a, q;
-        vector<vector<pixel> > L;
-        vector<double> A;
-
-        void subdivide_recursively(double x, double y, int i, int j, double length, double smin);
-        bool get_uv(double x, double y, int&u, int&v);
-        void create_map(int M, int N, int R, int S, double ro0, double smin);
-    };
-
-    CV_EXPORTS Mat subspaceProject(InputArray W, InputArray mean, InputArray src);
-    CV_EXPORTS Mat subspaceReconstruct(InputArray W, InputArray mean, InputArray src);
-
-    class CV_EXPORTS LDA
-    {
-    public:
-        // Initializes a LDA with num_components (default 0).
-        LDA(int num_components = 0) :
-            _num_components(num_components) {};
-
-        // Initializes and performs a Discriminant Analysis with Fisher's
-        // Optimization Criterion on given data in src and corresponding labels
-        // in labels. If 0 (or less) number of components are given, they are
-        // automatically determined for given data in computation.
-        LDA(const Mat& src, vector<int> labels,
-                int num_components = 0) :
-                    _num_components(num_components)
-        {
-            this->compute(src, labels); //! compute eigenvectors and eigenvalues
-        }
-
-        // Initializes and performs a Discriminant Analysis with Fisher's
-        // Optimization Criterion on given data in src and corresponding labels
-        // in labels. If 0 (or less) number of components are given, they are
-        // automatically determined for given data in computation.
-        LDA(InputArrayOfArrays src, InputArray labels,
-                int num_components = 0) :
-                    _num_components(num_components)
-        {
-            this->compute(src, labels); //! compute eigenvectors and eigenvalues
-        }
-
-        // Serializes this object to a given filename.
-        void save(const string& filename) const;
-
-        // Deserializes this object from a given filename.
-        void load(const string& filename);
-
-        // Serializes this object to a given cv::FileStorage.
-        void save(FileStorage& fs) const;
-
-            // Deserializes this object from a given cv::FileStorage.
-        void load(const FileStorage& node);
-
-        // Destructor.
-        ~LDA() {}
-
-        /** Compute the discriminants for data in src (row aligned) and labels.
-          */
-        void compute(InputArrayOfArrays src, InputArray labels);
-
-        /** Projects samples into the LDA subspace.
-            src may be one or more row aligned samples.
-          */
-        Mat project(InputArray src);
-
-        /** Reconstructs projections from the LDA subspace.
-            src may be one or more row aligned projections.
-          */
-        Mat reconstruct(InputArray src);
-
-        // Returns the eigenvectors of this LDA.
-        Mat eigenvectors() const { return _eigenvectors; };
-
-        // Returns the eigenvalues of this LDA.
-        Mat eigenvalues() const { return _eigenvalues; }
-
-    protected:
-        bool _dataAsRow; // unused, but needed for ABI compatibility.
-        int _num_components;
-        Mat _eigenvectors;
-        Mat _eigenvalues;
-
-        void lda(InputArrayOfArrays src, InputArray labels);
-    };
-
-    class CV_EXPORTS_W FaceRecognizer : public Algorithm
-    {
-    public:
-        //! virtual destructor
-        virtual ~FaceRecognizer() {}
-
-        // Trains a FaceRecognizer.
-        CV_WRAP virtual void train(InputArrayOfArrays src, InputArray labels) = 0;
-
-        // Updates a FaceRecognizer.
-        CV_WRAP void update(InputArrayOfArrays src, InputArray labels);
-
-        // Gets a prediction from a FaceRecognizer.
-        virtual int predict(InputArray src) const = 0;
-
-        // Predicts the label and confidence for a given sample.
-        CV_WRAP virtual void predict(InputArray src, CV_OUT int &label, CV_OUT double &confidence) const = 0;
-
-        // Serializes this object to a given filename.
-        CV_WRAP virtual void save(const string& filename) const;
-
-        // Deserializes this object from a given filename.
-        CV_WRAP virtual void load(const string& filename);
-
-        // Serializes this object to a given cv::FileStorage.
-        virtual void save(FileStorage& fs) const = 0;
-
-        // Deserializes this object from a given cv::FileStorage.
-        virtual void load(const FileStorage& fs) = 0;
-
-        // Sets additional information as pairs label - info.
-        void setLabelsInfo(const std::map<int, string>& labelsInfo);
-
-        // Gets string information by label
-        string getLabelInfo(const int &label);
-
-        // Gets labels by string
-        vector<int> getLabelsByString(const string& str);
-    };
-
-    CV_EXPORTS_W Ptr<FaceRecognizer> createEigenFaceRecognizer(int num_components = 0, double threshold = DBL_MAX);
-    CV_EXPORTS_W Ptr<FaceRecognizer> createFisherFaceRecognizer(int num_components = 0, double threshold = DBL_MAX);
-    CV_EXPORTS_W Ptr<FaceRecognizer> createLBPHFaceRecognizer(int radius=1, int neighbors=8,
-                                                            int grid_x=8, int grid_y=8, double threshold = DBL_MAX);
-
-    enum
-    {
-        COLORMAP_AUTUMN = 0,
-        COLORMAP_BONE = 1,
-        COLORMAP_JET = 2,
-        COLORMAP_WINTER = 3,
-        COLORMAP_RAINBOW = 4,
-        COLORMAP_OCEAN = 5,
-        COLORMAP_SUMMER = 6,
-        COLORMAP_SPRING = 7,
-        COLORMAP_COOL = 8,
-        COLORMAP_HSV = 9,
-        COLORMAP_PINK = 10,
-        COLORMAP_HOT = 11
-    };
-
-    CV_EXPORTS_W void applyColorMap(InputArray src, OutputArray dst, int colormap);
-
-    CV_EXPORTS bool initModule_contrib();
-}
-
-#include "opencv2/contrib/retina.hpp"
-
-#include "opencv2/contrib/openfabmap.hpp"
-
-#endif
-
-#endif