opencv/modules/imgproc/include/opencv2/imgproc.hpp

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#ifndef __OPENCV_IMGPROC_HPP__
#define __OPENCV_IMGPROC_HPP__

#include "opencv2/core.hpp"

/*! \namespace cv
 Namespace where all the C++ OpenCV functionality resides
 */
namespace cv
{

//! type of morphological operation
enum { MORPH_ERODE    = 0,
       MORPH_DILATE   = 1,
       MORPH_OPEN     = 2,
       MORPH_CLOSE    = 3,
       MORPH_GRADIENT = 4,
       MORPH_TOPHAT   = 5,
       MORPH_BLACKHAT = 6
     };

//! shape of the structuring element
enum { MORPH_RECT    = 0,
       MORPH_CROSS   = 1,
       MORPH_ELLIPSE = 2
     };

//! interpolation algorithm
enum { INTER_NEAREST        = 0, //!< nearest neighbor interpolation
       INTER_LINEAR         = 1, //!< bilinear interpolation
       INTER_CUBIC          = 2, //!< bicubic interpolation
       INTER_AREA           = 3, //!< area-based (or super) interpolation
       INTER_LANCZOS4       = 4, //!< Lanczos interpolation over 8x8 neighborhood

       INTER_MAX            = 7, //!< mask for interpolation codes
       WARP_FILL_OUTLIERS   = 8,
       WARP_INVERSE_MAP     = 16
     };

enum { INTER_BITS      = 5,
       INTER_BITS2     = INTER_BITS * 2,
       INTER_TAB_SIZE  = 1 << INTER_BITS,
       INTER_TAB_SIZE2 = INTER_TAB_SIZE * INTER_TAB_SIZE
     };

//! Distance types for Distance Transform and M-estimators
enum { DIST_USER    = -1,  // User defined distance
       DIST_L1      = 1,   // distance = |x1-x2| + |y1-y2|
       DIST_L2      = 2,   // the simple euclidean distance
       DIST_C       = 3,   // distance = max(|x1-x2|,|y1-y2|)
       DIST_L12     = 4,   // L1-L2 metric: distance = 2(sqrt(1+x*x/2) - 1))
       DIST_FAIR    = 5,   // distance = c^2(|x|/c-log(1+|x|/c)), c = 1.3998
       DIST_WELSCH  = 6,   // distance = c^2/2(1-exp(-(x/c)^2)), c = 2.9846
       DIST_HUBER   = 7    // distance = |x|<c ? x^2/2 : c(|x|-c/2), c=1.345
};

//! Mask size for distance transform
enum { DIST_MASK_3       = 3,
       DIST_MASK_5       = 5,
       DIST_MASK_PRECISE = 0
     };

//! type of the threshold operation
enum { THRESH_BINARY     = 0, // value = value > threshold ? max_value : 0
       THRESH_BINARY_INV = 1, // value = value > threshold ? 0 : max_value
       THRESH_TRUNC      = 2, // value = value > threshold ? threshold : value
       THRESH_TOZERO     = 3, // value = value > threshold ? value : 0
       THRESH_TOZERO_INV = 4, // value = value > threshold ? 0 : value
       THRESH_MASK       = 7,
       THRESH_OTSU       = 8  // use Otsu algorithm to choose the optimal threshold value
     };

//! adaptive threshold algorithm
enum { ADAPTIVE_THRESH_MEAN_C     = 0,
       ADAPTIVE_THRESH_GAUSSIAN_C = 1
     };

enum { PROJ_SPHERICAL_ORTHO  = 0,
       PROJ_SPHERICAL_EQRECT = 1
     };

//! class of the pixel in GrabCut algorithm
enum { GC_BGD    = 0,  //!< background
       GC_FGD    = 1,  //!< foreground
       GC_PR_BGD = 2,  //!< most probably background
       GC_PR_FGD = 3   //!< most probably foreground
     };

//! GrabCut algorithm flags
enum { GC_INIT_WITH_RECT  = 0,
       GC_INIT_WITH_MASK  = 1,
       GC_EVAL            = 2
};

//! distanceTransform algorithm flags
enum { DIST_LABEL_CCOMP = 0,
       DIST_LABEL_PIXEL = 1
     };

//! floodfill algorithm flags
enum { FLOODFILL_FIXED_RANGE = 1 << 16,
       FLOODFILL_MASK_ONLY   = 1 << 17
     };

//! type of the template matching operation
enum { TM_SQDIFF        = 0,
       TM_SQDIFF_NORMED = 1,
       TM_CCORR         = 2,
       TM_CCORR_NORMED  = 3,
       TM_CCOEFF        = 4,
       TM_CCOEFF_NORMED = 5
     };

//! connected components algorithm output formats
enum { CC_STAT_LEFT   = 0,
       CC_STAT_TOP    = 1,
       CC_STAT_WIDTH  = 2,
       CC_STAT_HEIGHT = 3,
       CC_STAT_AREA   = 4,
       CC_STAT_MAX    = 5
     };

//! mode of the contour retrieval algorithm
enum { RETR_EXTERNAL  = 0, //!< retrieve only the most external (top-level) contours
       RETR_LIST      = 1, //!< retrieve all the contours without any hierarchical information
       RETR_CCOMP     = 2, //!< retrieve the connected components (that can possibly be nested)
       RETR_TREE      = 3, //!< retrieve all the contours and the whole hierarchy
       RETR_FLOODFILL = 4
     };

//! the contour approximation algorithm
enum { CHAIN_APPROX_NONE      = 1,
       CHAIN_APPROX_SIMPLE    = 2,
       CHAIN_APPROX_TC89_L1   = 3,
       CHAIN_APPROX_TC89_KCOS = 4
     };

//! Variants of a Hough transform
enum { HOUGH_STANDARD      = 0,
       HOUGH_PROBABILISTIC = 1,
       HOUGH_MULTI_SCALE   = 2,
       HOUGH_GRADIENT      = 3
     };

//! Variants of Line Segment Detector
enum { LSD_REFINE_NONE = 0,
       LSD_REFINE_STD  = 1,
       LSD_REFINE_ADV  = 2
     };

//! Histogram comparison methods
enum { HISTCMP_CORREL        = 0,
       HISTCMP_CHISQR        = 1,
       HISTCMP_INTERSECT     = 2,
       HISTCMP_BHATTACHARYYA = 3,
       HISTCMP_HELLINGER     = HISTCMP_BHATTACHARYYA,
       HISTCMP_CHISQR_ALT    = 4,
       HISTCMP_KL_DIV        = 5
     };

//! the color conversion code
enum { COLOR_BGR2BGRA     = 0,
       COLOR_RGB2RGBA     = COLOR_BGR2BGRA,

       COLOR_BGRA2BGR     = 1,
       COLOR_RGBA2RGB     = COLOR_BGRA2BGR,

       COLOR_BGR2RGBA     = 2,
       COLOR_RGB2BGRA     = COLOR_BGR2RGBA,

       COLOR_RGBA2BGR     = 3,
       COLOR_BGRA2RGB     = COLOR_RGBA2BGR,

       COLOR_BGR2RGB      = 4,
       COLOR_RGB2BGR      = COLOR_BGR2RGB,

       COLOR_BGRA2RGBA    = 5,
       COLOR_RGBA2BGRA    = COLOR_BGRA2RGBA,

       COLOR_BGR2GRAY     = 6,
       COLOR_RGB2GRAY     = 7,
       COLOR_GRAY2BGR     = 8,
       COLOR_GRAY2RGB     = COLOR_GRAY2BGR,
       COLOR_GRAY2BGRA    = 9,
       COLOR_GRAY2RGBA    = COLOR_GRAY2BGRA,
       COLOR_BGRA2GRAY    = 10,
       COLOR_RGBA2GRAY    = 11,

       COLOR_BGR2BGR565   = 12,
       COLOR_RGB2BGR565   = 13,
       COLOR_BGR5652BGR   = 14,
       COLOR_BGR5652RGB   = 15,
       COLOR_BGRA2BGR565  = 16,
       COLOR_RGBA2BGR565  = 17,
       COLOR_BGR5652BGRA  = 18,
       COLOR_BGR5652RGBA  = 19,

       COLOR_GRAY2BGR565  = 20,
       COLOR_BGR5652GRAY  = 21,

       COLOR_BGR2BGR555   = 22,
       COLOR_RGB2BGR555   = 23,
       COLOR_BGR5552BGR   = 24,
       COLOR_BGR5552RGB   = 25,
       COLOR_BGRA2BGR555  = 26,
       COLOR_RGBA2BGR555  = 27,
       COLOR_BGR5552BGRA  = 28,
       COLOR_BGR5552RGBA  = 29,

       COLOR_GRAY2BGR555  = 30,
       COLOR_BGR5552GRAY  = 31,

       COLOR_BGR2XYZ      = 32,
       COLOR_RGB2XYZ      = 33,
       COLOR_XYZ2BGR      = 34,
       COLOR_XYZ2RGB      = 35,

       COLOR_BGR2YCrCb    = 36,
       COLOR_RGB2YCrCb    = 37,
       COLOR_YCrCb2BGR    = 38,
       COLOR_YCrCb2RGB    = 39,

       COLOR_BGR2HSV      = 40,
       COLOR_RGB2HSV      = 41,

       COLOR_BGR2Lab      = 44,
       COLOR_RGB2Lab      = 45,

       COLOR_BGR2Luv      = 50,
       COLOR_RGB2Luv      = 51,
       COLOR_BGR2HLS      = 52,
       COLOR_RGB2HLS      = 53,

       COLOR_HSV2BGR      = 54,
       COLOR_HSV2RGB      = 55,

       COLOR_Lab2BGR      = 56,
       COLOR_Lab2RGB      = 57,
       COLOR_Luv2BGR      = 58,
       COLOR_Luv2RGB      = 59,
       COLOR_HLS2BGR      = 60,
       COLOR_HLS2RGB      = 61,

       COLOR_BGR2HSV_FULL = 66,
       COLOR_RGB2HSV_FULL = 67,
       COLOR_BGR2HLS_FULL = 68,
       COLOR_RGB2HLS_FULL = 69,

       COLOR_HSV2BGR_FULL = 70,
       COLOR_HSV2RGB_FULL = 71,
       COLOR_HLS2BGR_FULL = 72,
       COLOR_HLS2RGB_FULL = 73,

       COLOR_LBGR2Lab     = 74,
       COLOR_LRGB2Lab     = 75,
       COLOR_LBGR2Luv     = 76,
       COLOR_LRGB2Luv     = 77,

       COLOR_Lab2LBGR     = 78,
       COLOR_Lab2LRGB     = 79,
       COLOR_Luv2LBGR     = 80,
       COLOR_Luv2LRGB     = 81,

       COLOR_BGR2YUV      = 82,
       COLOR_RGB2YUV      = 83,
       COLOR_YUV2BGR      = 84,
       COLOR_YUV2RGB      = 85,

       // YUV 4:2:0 family to RGB
       COLOR_YUV2RGB_NV12  = 90,
       COLOR_YUV2BGR_NV12  = 91,
       COLOR_YUV2RGB_NV21  = 92,
       COLOR_YUV2BGR_NV21  = 93,
       COLOR_YUV420sp2RGB  = COLOR_YUV2RGB_NV21,
       COLOR_YUV420sp2BGR  = COLOR_YUV2BGR_NV21,

       COLOR_YUV2RGBA_NV12 = 94,
       COLOR_YUV2BGRA_NV12 = 95,
       COLOR_YUV2RGBA_NV21 = 96,
       COLOR_YUV2BGRA_NV21 = 97,
       COLOR_YUV420sp2RGBA = COLOR_YUV2RGBA_NV21,
       COLOR_YUV420sp2BGRA = COLOR_YUV2BGRA_NV21,

       COLOR_YUV2RGB_YV12  = 98,
       COLOR_YUV2BGR_YV12  = 99,
       COLOR_YUV2RGB_IYUV  = 100,
       COLOR_YUV2BGR_IYUV  = 101,
       COLOR_YUV2RGB_I420  = COLOR_YUV2RGB_IYUV,
       COLOR_YUV2BGR_I420  = COLOR_YUV2BGR_IYUV,
       COLOR_YUV420p2RGB   = COLOR_YUV2RGB_YV12,
       COLOR_YUV420p2BGR   = COLOR_YUV2BGR_YV12,

       COLOR_YUV2RGBA_YV12 = 102,
       COLOR_YUV2BGRA_YV12 = 103,
       COLOR_YUV2RGBA_IYUV = 104,
       COLOR_YUV2BGRA_IYUV = 105,
       COLOR_YUV2RGBA_I420 = COLOR_YUV2RGBA_IYUV,
       COLOR_YUV2BGRA_I420 = COLOR_YUV2BGRA_IYUV,
       COLOR_YUV420p2RGBA  = COLOR_YUV2RGBA_YV12,
       COLOR_YUV420p2BGRA  = COLOR_YUV2BGRA_YV12,

       COLOR_YUV2GRAY_420  = 106,
       COLOR_YUV2GRAY_NV21 = COLOR_YUV2GRAY_420,
       COLOR_YUV2GRAY_NV12 = COLOR_YUV2GRAY_420,
       COLOR_YUV2GRAY_YV12 = COLOR_YUV2GRAY_420,
       COLOR_YUV2GRAY_IYUV = COLOR_YUV2GRAY_420,
       COLOR_YUV2GRAY_I420 = COLOR_YUV2GRAY_420,
       COLOR_YUV420sp2GRAY = COLOR_YUV2GRAY_420,
       COLOR_YUV420p2GRAY  = COLOR_YUV2GRAY_420,

       // YUV 4:2:2 family to RGB
       COLOR_YUV2RGB_UYVY = 107,
       COLOR_YUV2BGR_UYVY = 108,
     //COLOR_YUV2RGB_VYUY = 109,
     //COLOR_YUV2BGR_VYUY = 110,
       COLOR_YUV2RGB_Y422 = COLOR_YUV2RGB_UYVY,
       COLOR_YUV2BGR_Y422 = COLOR_YUV2BGR_UYVY,
       COLOR_YUV2RGB_UYNV = COLOR_YUV2RGB_UYVY,
       COLOR_YUV2BGR_UYNV = COLOR_YUV2BGR_UYVY,

       COLOR_YUV2RGBA_UYVY = 111,
       COLOR_YUV2BGRA_UYVY = 112,
     //COLOR_YUV2RGBA_VYUY = 113,
     //COLOR_YUV2BGRA_VYUY = 114,
       COLOR_YUV2RGBA_Y422 = COLOR_YUV2RGBA_UYVY,
       COLOR_YUV2BGRA_Y422 = COLOR_YUV2BGRA_UYVY,
       COLOR_YUV2RGBA_UYNV = COLOR_YUV2RGBA_UYVY,
       COLOR_YUV2BGRA_UYNV = COLOR_YUV2BGRA_UYVY,

       COLOR_YUV2RGB_YUY2 = 115,
       COLOR_YUV2BGR_YUY2 = 116,
       COLOR_YUV2RGB_YVYU = 117,
       COLOR_YUV2BGR_YVYU = 118,
       COLOR_YUV2RGB_YUYV = COLOR_YUV2RGB_YUY2,
       COLOR_YUV2BGR_YUYV = COLOR_YUV2BGR_YUY2,
       COLOR_YUV2RGB_YUNV = COLOR_YUV2RGB_YUY2,
       COLOR_YUV2BGR_YUNV = COLOR_YUV2BGR_YUY2,

       COLOR_YUV2RGBA_YUY2 = 119,
       COLOR_YUV2BGRA_YUY2 = 120,
       COLOR_YUV2RGBA_YVYU = 121,
       COLOR_YUV2BGRA_YVYU = 122,
       COLOR_YUV2RGBA_YUYV = COLOR_YUV2RGBA_YUY2,
       COLOR_YUV2BGRA_YUYV = COLOR_YUV2BGRA_YUY2,
       COLOR_YUV2RGBA_YUNV = COLOR_YUV2RGBA_YUY2,
       COLOR_YUV2BGRA_YUNV = COLOR_YUV2BGRA_YUY2,

       COLOR_YUV2GRAY_UYVY = 123,
       COLOR_YUV2GRAY_YUY2 = 124,
     //CV_YUV2GRAY_VYUY    = CV_YUV2GRAY_UYVY,
       COLOR_YUV2GRAY_Y422 = COLOR_YUV2GRAY_UYVY,
       COLOR_YUV2GRAY_UYNV = COLOR_YUV2GRAY_UYVY,
       COLOR_YUV2GRAY_YVYU = COLOR_YUV2GRAY_YUY2,
       COLOR_YUV2GRAY_YUYV = COLOR_YUV2GRAY_YUY2,
       COLOR_YUV2GRAY_YUNV = COLOR_YUV2GRAY_YUY2,

       // alpha premultiplication
       COLOR_RGBA2mRGBA    = 125,
       COLOR_mRGBA2RGBA    = 126,

       // RGB to YUV 4:2:0 family
       COLOR_RGB2YUV_I420  = 127,
       COLOR_BGR2YUV_I420  = 128,
       COLOR_RGB2YUV_IYUV  = COLOR_RGB2YUV_I420,
       COLOR_BGR2YUV_IYUV  = COLOR_BGR2YUV_I420,

       COLOR_RGBA2YUV_I420 = 129,
       COLOR_BGRA2YUV_I420 = 130,
       COLOR_RGBA2YUV_IYUV = COLOR_RGBA2YUV_I420,
       COLOR_BGRA2YUV_IYUV = COLOR_BGRA2YUV_I420,
       COLOR_RGB2YUV_YV12  = 131,
       COLOR_BGR2YUV_YV12  = 132,
       COLOR_RGBA2YUV_YV12 = 133,
       COLOR_BGRA2YUV_YV12 = 134,

       // Demosaicing
       COLOR_BayerBG2BGR = 46,
       COLOR_BayerGB2BGR = 47,
       COLOR_BayerRG2BGR = 48,
       COLOR_BayerGR2BGR = 49,

       COLOR_BayerBG2RGB = COLOR_BayerRG2BGR,
       COLOR_BayerGB2RGB = COLOR_BayerGR2BGR,
       COLOR_BayerRG2RGB = COLOR_BayerBG2BGR,
       COLOR_BayerGR2RGB = COLOR_BayerGB2BGR,

       COLOR_BayerBG2GRAY = 86,
       COLOR_BayerGB2GRAY = 87,
       COLOR_BayerRG2GRAY = 88,
       COLOR_BayerGR2GRAY = 89,

       // Demosaicing using Variable Number of Gradients
       COLOR_BayerBG2BGR_VNG = 62,
       COLOR_BayerGB2BGR_VNG = 63,
       COLOR_BayerRG2BGR_VNG = 64,
       COLOR_BayerGR2BGR_VNG = 65,

       COLOR_BayerBG2RGB_VNG = COLOR_BayerRG2BGR_VNG,
       COLOR_BayerGB2RGB_VNG = COLOR_BayerGR2BGR_VNG,
       COLOR_BayerRG2RGB_VNG = COLOR_BayerBG2BGR_VNG,
       COLOR_BayerGR2RGB_VNG = COLOR_BayerGB2BGR_VNG,

       // Edge-Aware Demosaicing
       COLOR_BayerBG2BGR_EA  = 135,
       COLOR_BayerGB2BGR_EA  = 136,
       COLOR_BayerRG2BGR_EA  = 137,
       COLOR_BayerGR2BGR_EA  = 138,

       COLOR_BayerBG2RGB_EA  = COLOR_BayerRG2BGR_EA,
       COLOR_BayerGB2RGB_EA  = COLOR_BayerGR2BGR_EA,
       COLOR_BayerRG2RGB_EA  = COLOR_BayerBG2BGR_EA,
       COLOR_BayerGR2RGB_EA  = COLOR_BayerGB2BGR_EA,


       COLOR_COLORCVT_MAX  = 139
};

//! types of intersection between rectangles
enum { INTERSECT_NONE = 0,
       INTERSECT_PARTIAL  = 1,
       INTERSECT_FULL  = 2
     };

//! finds arbitrary template in the grayscale image using Generalized Hough Transform
class CV_EXPORTS GeneralizedHough : public Algorithm
{
public:
    //! set template to search
    virtual void setTemplate(InputArray templ, Point templCenter = Point(-1, -1)) = 0;
    virtual void setTemplate(InputArray edges, InputArray dx, InputArray dy, Point templCenter = Point(-1, -1)) = 0;

    //! find template on image
    virtual void detect(InputArray image, OutputArray positions, OutputArray votes = noArray()) = 0;
    virtual void detect(InputArray edges, InputArray dx, InputArray dy, OutputArray positions, OutputArray votes = noArray()) = 0;

    //! Canny low threshold.
    virtual void setCannyLowThresh(int cannyLowThresh) = 0;
    virtual int getCannyLowThresh() const = 0;

    //! Canny high threshold.
    virtual void setCannyHighThresh(int cannyHighThresh) = 0;
    virtual int getCannyHighThresh() const = 0;

    //! Minimum distance between the centers of the detected objects.
    virtual void setMinDist(double minDist) = 0;
    virtual double getMinDist() const = 0;

    //! Inverse ratio of the accumulator resolution to the image resolution.
    virtual void setDp(double dp) = 0;
    virtual double getDp() const = 0;

    //! Maximal size of inner buffers.
    virtual void setMaxBufferSize(int maxBufferSize) = 0;
    virtual int getMaxBufferSize() const = 0;
};

//! Ballard, D.H. (1981). Generalizing the Hough transform to detect arbitrary shapes. Pattern Recognition 13 (2): 111-122.
//! Detects position only without traslation and rotation
class CV_EXPORTS GeneralizedHoughBallard : public GeneralizedHough
{
public:
    //! R-Table levels.
    virtual void setLevels(int levels) = 0;
    virtual int getLevels() const = 0;

    //! The accumulator threshold for the template centers at the detection stage. The smaller it is, the more false positions may be detected.
    virtual void setVotesThreshold(int votesThreshold) = 0;
    virtual int getVotesThreshold() const = 0;
};

//! Guil, N., González-Linares, J.M. and Zapata, E.L. (1999). Bidimensional shape detection using an invariant approach. Pattern Recognition 32 (6): 1025-1038.
//! Detects position, traslation and rotation
class CV_EXPORTS GeneralizedHoughGuil : public GeneralizedHough
{
public:
    //! Angle difference in degrees between two points in feature.
    virtual void setXi(double xi) = 0;
    virtual double getXi() const = 0;

    //! Feature table levels.
    virtual void setLevels(int levels) = 0;
    virtual int getLevels() const = 0;

    //! Maximal difference between angles that treated as equal.
    virtual void setAngleEpsilon(double angleEpsilon) = 0;
    virtual double getAngleEpsilon() const = 0;

    //! Minimal rotation angle to detect in degrees.
    virtual void setMinAngle(double minAngle) = 0;
    virtual double getMinAngle() const = 0;

    //! Maximal rotation angle to detect in degrees.
    virtual void setMaxAngle(double maxAngle) = 0;
    virtual double getMaxAngle() const = 0;

    //! Angle step in degrees.
    virtual void setAngleStep(double angleStep) = 0;
    virtual double getAngleStep() const = 0;

    //! Angle votes threshold.
    virtual void setAngleThresh(int angleThresh) = 0;
    virtual int getAngleThresh() const = 0;

    //! Minimal scale to detect.
    virtual void setMinScale(double minScale) = 0;
    virtual double getMinScale() const = 0;

    //! Maximal scale to detect.
    virtual void setMaxScale(double maxScale) = 0;
    virtual double getMaxScale() const = 0;

    //! Scale step.
    virtual void setScaleStep(double scaleStep) = 0;
    virtual double getScaleStep() const = 0;

    //! Scale votes threshold.
    virtual void setScaleThresh(int scaleThresh) = 0;
    virtual int getScaleThresh() const = 0;

    //! Position votes threshold.
    virtual void setPosThresh(int posThresh) = 0;
    virtual int getPosThresh() const = 0;
};


class CV_EXPORTS_W CLAHE : public Algorithm
{
public:
    CV_WRAP virtual void apply(InputArray src, OutputArray dst) = 0;

    CV_WRAP virtual void setClipLimit(double clipLimit) = 0;
    CV_WRAP virtual double getClipLimit() const = 0;

    CV_WRAP virtual void setTilesGridSize(Size tileGridSize) = 0;
    CV_WRAP virtual Size getTilesGridSize() const = 0;

    CV_WRAP virtual void collectGarbage() = 0;
};


class CV_EXPORTS_W Subdiv2D
{
public:
    enum { PTLOC_ERROR        = -2,
           PTLOC_OUTSIDE_RECT = -1,
           PTLOC_INSIDE       = 0,
           PTLOC_VERTEX       = 1,
           PTLOC_ON_EDGE      = 2
         };

    enum { NEXT_AROUND_ORG   = 0x00,
           NEXT_AROUND_DST   = 0x22,
           PREV_AROUND_ORG   = 0x11,
           PREV_AROUND_DST   = 0x33,
           NEXT_AROUND_LEFT  = 0x13,
           NEXT_AROUND_RIGHT = 0x31,
           PREV_AROUND_LEFT  = 0x20,
           PREV_AROUND_RIGHT = 0x02
         };

    CV_WRAP Subdiv2D();
    CV_WRAP Subdiv2D(Rect rect);
    CV_WRAP void initDelaunay(Rect rect);

    CV_WRAP int insert(Point2f pt);
    CV_WRAP void insert(const std::vector<Point2f>& ptvec);
    CV_WRAP int locate(Point2f pt, CV_OUT int& edge, CV_OUT int& vertex);

    CV_WRAP int findNearest(Point2f pt, CV_OUT Point2f* nearestPt = 0);
    CV_WRAP void getEdgeList(CV_OUT std::vector<Vec4f>& edgeList) const;
    CV_WRAP void getTriangleList(CV_OUT std::vector<Vec6f>& triangleList) const;
    CV_WRAP void getVoronoiFacetList(const std::vector<int>& idx, CV_OUT std::vector<std::vector<Point2f> >& facetList,
                                     CV_OUT std::vector<Point2f>& facetCenters);

    CV_WRAP Point2f getVertex(int vertex, CV_OUT int* firstEdge = 0) const;

    CV_WRAP int getEdge( int edge, int nextEdgeType ) const;
    CV_WRAP int nextEdge(int edge) const;
    CV_WRAP int rotateEdge(int edge, int rotate) const;
    CV_WRAP int symEdge(int edge) const;
    CV_WRAP int edgeOrg(int edge, CV_OUT Point2f* orgpt = 0) const;
    CV_WRAP int edgeDst(int edge, CV_OUT Point2f* dstpt = 0) const;

protected:
    int newEdge();
    void deleteEdge(int edge);
    int newPoint(Point2f pt, bool isvirtual, int firstEdge = 0);
    void deletePoint(int vtx);
    void setEdgePoints( int edge, int orgPt, int dstPt );
    void splice( int edgeA, int edgeB );
    int connectEdges( int edgeA, int edgeB );
    void swapEdges( int edge );
    int isRightOf(Point2f pt, int edge) const;
    void calcVoronoi();
    void clearVoronoi();
    void checkSubdiv() const;

    struct CV_EXPORTS Vertex
    {
        Vertex();
        Vertex(Point2f pt, bool _isvirtual, int _firstEdge=0);
        bool isvirtual() const;
        bool isfree() const;

        int firstEdge;
        int type;
        Point2f pt;
    };

    struct CV_EXPORTS QuadEdge
    {
        QuadEdge();
        QuadEdge(int edgeidx);
        bool isfree() const;

        int next[4];
        int pt[4];
    };

    std::vector<Vertex> vtx;
    std::vector<QuadEdge> qedges;
    int freeQEdge;
    int freePoint;
    bool validGeometry;

    int recentEdge;
    Point2f topLeft;
    Point2f bottomRight;
};

class CV_EXPORTS_W LineSegmentDetector : public Algorithm
{
public:
/**
 * Detect lines in the input image.
 *
 * @param _image    A grayscale(CV_8UC1) input image.
 *                  If only a roi needs to be selected, use
 *                  lsd_ptr->detect(image(roi), ..., lines);
 *                  lines += Scalar(roi.x, roi.y, roi.x, roi.y);
 * @param _lines    Return: A vector of Vec4i elements specifying the beginning and ending point of a line.
 *                          Where Vec4i is (x1, y1, x2, y2), point 1 is the start, point 2 - end.
 *                          Returned lines are strictly oriented depending on the gradient.
 * @param width     Return: Vector of widths of the regions, where the lines are found. E.g. Width of line.
 * @param prec      Return: Vector of precisions with which the lines are found.
 * @param nfa       Return: Vector containing number of false alarms in the line region, with precision of 10%.
 *                          The bigger the value, logarithmically better the detection.
 *                              * -1 corresponds to 10 mean false alarms
 *                              * 0 corresponds to 1 mean false alarm
 *                              * 1 corresponds to 0.1 mean false alarms
 *                          This vector will be calculated _only_ when the objects type is REFINE_ADV
 */
    CV_WRAP virtual void detect(InputArray _image, OutputArray _lines,
                        OutputArray width = noArray(), OutputArray prec = noArray(),
                        OutputArray nfa = noArray()) = 0;

/**
 * Draw lines on the given canvas.
 *
 * @param image     The image, where lines will be drawn.
 *                  Should have the size of the image, where the lines were found
 * @param lines     The lines that need to be drawn
 */
    CV_WRAP virtual void drawSegments(InputOutputArray _image, InputArray lines) = 0;

/**
 * Draw both vectors on the image canvas. Uses blue for lines 1 and red for lines 2.
 *
 * @param size      The size of the image, where lines were found.
 * @param lines1    The first lines that need to be drawn. Color - Blue.
 * @param lines2    The second lines that need to be drawn. Color - Red.
 * @param image     Optional image, where lines will be drawn.
 *                  Should have the size of the image, where the lines were found
 * @return          The number of mismatching pixels between lines1 and lines2.
 */
    CV_WRAP virtual int compareSegments(const Size& size, InputArray lines1, InputArray lines2, InputOutputArray _image = noArray()) = 0;

    virtual ~LineSegmentDetector() { }
};

//! Returns a pointer to a LineSegmentDetector class.
CV_EXPORTS_W Ptr<LineSegmentDetector> createLineSegmentDetector(
    int _refine = LSD_REFINE_STD, double _scale = 0.8,
    double _sigma_scale = 0.6, double _quant = 2.0, double _ang_th = 22.5,
    double _log_eps = 0, double _density_th = 0.7, int _n_bins = 1024);

//! returns the Gaussian kernel with the specified parameters
CV_EXPORTS_W Mat getGaussianKernel( int ksize, double sigma, int ktype = CV_64F );

//! initializes kernels of the generalized Sobel operator
CV_EXPORTS_W void getDerivKernels( OutputArray kx, OutputArray ky,
                                   int dx, int dy, int ksize,
                                   bool normalize = false, int ktype = CV_32F );

//! returns the Gabor kernel with the specified parameters
CV_EXPORTS_W Mat getGaborKernel( Size ksize, double sigma, double theta, double lambd,
                                 double gamma, double psi = CV_PI*0.5, int ktype = CV_64F );

//! returns "magic" border value for erosion and dilation. It is automatically transformed to Scalar::all(-DBL_MAX) for dilation.
static inline Scalar morphologyDefaultBorderValue() { return Scalar::all(DBL_MAX); }

//! returns structuring element of the specified shape and size
CV_EXPORTS_W Mat getStructuringElement(int shape, Size ksize, Point anchor = Point(-1,-1));

//! smooths the image using median filter.
CV_EXPORTS_W void medianBlur( InputArray src, OutputArray dst, int ksize );

//! smooths the image using Gaussian filter.
CV_EXPORTS_W void GaussianBlur( InputArray src, OutputArray dst, Size ksize,
                                double sigmaX, double sigmaY = 0,
                                int borderType = BORDER_DEFAULT );

//! smooths the image using bilateral filter
CV_EXPORTS_W void bilateralFilter( InputArray src, OutputArray dst, int d,
                                   double sigmaColor, double sigmaSpace,
                                   int borderType = BORDER_DEFAULT );

//! smooths the image using the box filter. Each pixel is processed in O(1) time
CV_EXPORTS_W void boxFilter( InputArray src, OutputArray dst, int ddepth,
                             Size ksize, Point anchor = Point(-1,-1),
                             bool normalize = true,
                             int borderType = BORDER_DEFAULT );

CV_EXPORTS_W void sqrBoxFilter( InputArray _src, OutputArray _dst, int ddepth,
                                Size ksize, Point anchor = Point(-1, -1),
                                bool normalize = true,
                                int borderType = BORDER_DEFAULT );

//! a synonym for normalized box filter
CV_EXPORTS_W void blur( InputArray src, OutputArray dst,
                        Size ksize, Point anchor = Point(-1,-1),
                        int borderType = BORDER_DEFAULT );

//! applies non-separable 2D linear filter to the image
CV_EXPORTS_W void filter2D( InputArray src, OutputArray dst, int ddepth,
                            InputArray kernel, Point anchor = Point(-1,-1),
                            double delta = 0, int borderType = BORDER_DEFAULT );

//! applies separable 2D linear filter to the image
CV_EXPORTS_W void sepFilter2D( InputArray src, OutputArray dst, int ddepth,
                               InputArray kernelX, InputArray kernelY,
                               Point anchor = Point(-1,-1),
                               double delta = 0, int borderType = BORDER_DEFAULT );

//! applies generalized Sobel operator to the image
CV_EXPORTS_W void Sobel( InputArray src, OutputArray dst, int ddepth,
                         int dx, int dy, int ksize = 3,
                         double scale = 1, double delta = 0,
                         int borderType = BORDER_DEFAULT );

//! applies the vertical or horizontal Scharr operator to the image
CV_EXPORTS_W void Scharr( InputArray src, OutputArray dst, int ddepth,
                          int dx, int dy, double scale = 1, double delta = 0,
                          int borderType = BORDER_DEFAULT );

//! applies Laplacian operator to the image
CV_EXPORTS_W void Laplacian( InputArray src, OutputArray dst, int ddepth,
                             int ksize = 1, double scale = 1, double delta = 0,
                             int borderType = BORDER_DEFAULT );

//! applies Canny edge detector and produces the edge map.
CV_EXPORTS_W void Canny( InputArray image, OutputArray edges,
                         double threshold1, double threshold2,
                         int apertureSize = 3, bool L2gradient = false );

//! computes minimum eigen value of 2x2 derivative covariation matrix at each pixel - the cornerness criteria
CV_EXPORTS_W void cornerMinEigenVal( InputArray src, OutputArray dst,
                                     int blockSize, int ksize = 3,
                                     int borderType = BORDER_DEFAULT );

//! computes Harris cornerness criteria at each image pixel
CV_EXPORTS_W void cornerHarris( InputArray src, OutputArray dst, int blockSize,
                                int ksize, double k,
                                int borderType = BORDER_DEFAULT );

//! computes both eigenvalues and the eigenvectors of 2x2 derivative covariation matrix  at each pixel. The output is stored as 6-channel matrix.
CV_EXPORTS_W void cornerEigenValsAndVecs( InputArray src, OutputArray dst,
                                          int blockSize, int ksize,
                                          int borderType = BORDER_DEFAULT );

//! computes another complex cornerness criteria at each pixel
CV_EXPORTS_W void preCornerDetect( InputArray src, OutputArray dst, int ksize,
                                   int borderType = BORDER_DEFAULT );

//! adjusts the corner locations with sub-pixel accuracy to maximize the certain cornerness criteria
CV_EXPORTS_W void cornerSubPix( InputArray image, InputOutputArray corners,
                                Size winSize, Size zeroZone,
                                TermCriteria criteria );

//! finds the strong enough corners where the cornerMinEigenVal() or cornerHarris() report the local maxima
CV_EXPORTS_W void goodFeaturesToTrack( InputArray image, OutputArray corners,
                                     int maxCorners, double qualityLevel, double minDistance,
                                     InputArray mask = noArray(), int blockSize = 3,
                                     bool useHarrisDetector = false, double k = 0.04 );

//! finds lines in the black-n-white image using the standard or pyramid Hough transform
CV_EXPORTS_W void HoughLines( InputArray image, OutputArray lines,
                              double rho, double theta, int threshold,
                              double srn = 0, double stn = 0,
                              double min_theta = 0, double max_theta = CV_PI );

//! finds line segments in the black-n-white image using probabilistic Hough transform
CV_EXPORTS_W void HoughLinesP( InputArray image, OutputArray lines,
                               double rho, double theta, int threshold,
                               double minLineLength = 0, double maxLineGap = 0 );

//! finds circles in the grayscale image using 2+1 gradient Hough transform
CV_EXPORTS_W void HoughCircles( InputArray image, OutputArray circles,
                               int method, double dp, double minDist,
                               double param1 = 100, double param2 = 100,
                               int minRadius = 0, int maxRadius = 0 );

//! erodes the image (applies the local minimum operator)
CV_EXPORTS_W void erode( InputArray src, OutputArray dst, InputArray kernel,
                         Point anchor = Point(-1,-1), int iterations = 1,
                         int borderType = BORDER_CONSTANT,
                         const Scalar& borderValue = morphologyDefaultBorderValue() );

//! dilates the image (applies the local maximum operator)
CV_EXPORTS_W void dilate( InputArray src, OutputArray dst, InputArray kernel,
                          Point anchor = Point(-1,-1), int iterations = 1,
                          int borderType = BORDER_CONSTANT,
                          const Scalar& borderValue = morphologyDefaultBorderValue() );

//! applies an advanced morphological operation to the image
CV_EXPORTS_W void morphologyEx( InputArray src, OutputArray dst,
                                int op, InputArray kernel,
                                Point anchor = Point(-1,-1), int iterations = 1,
                                int borderType = BORDER_CONSTANT,
                                const Scalar& borderValue = morphologyDefaultBorderValue() );

//! resizes the image
CV_EXPORTS_W void resize( InputArray src, OutputArray dst,
                          Size dsize, double fx = 0, double fy = 0,
                          int interpolation = INTER_LINEAR );

//! warps the image using affine transformation
CV_EXPORTS_W void warpAffine( InputArray src, OutputArray dst,
                              InputArray M, Size dsize,
                              int flags = INTER_LINEAR,
                              int borderMode = BORDER_CONSTANT,
                              const Scalar& borderValue = Scalar());

//! warps the image using perspective transformation
CV_EXPORTS_W void warpPerspective( InputArray src, OutputArray dst,
                                   InputArray M, Size dsize,
                                   int flags = INTER_LINEAR,
                                   int borderMode = BORDER_CONSTANT,
                                   const Scalar& borderValue = Scalar());

//! warps the image using the precomputed maps. The maps are stored in either floating-point or integer fixed-point format
CV_EXPORTS_W void remap( InputArray src, OutputArray dst,
                         InputArray map1, InputArray map2,
                         int interpolation, int borderMode = BORDER_CONSTANT,
                         const Scalar& borderValue = Scalar());

//! converts maps for remap from floating-point to fixed-point format or backwards
CV_EXPORTS_W void convertMaps( InputArray map1, InputArray map2,
                               OutputArray dstmap1, OutputArray dstmap2,
                               int dstmap1type, bool nninterpolation = false );

//! returns 2x3 affine transformation matrix for the planar rotation.
CV_EXPORTS_W Mat getRotationMatrix2D( Point2f center, double angle, double scale );

//! returns 3x3 perspective transformation for the corresponding 4 point pairs.
CV_EXPORTS Mat getPerspectiveTransform( const Point2f src[], const Point2f dst[] );

//! returns 2x3 affine transformation for the corresponding 3 point pairs.
CV_EXPORTS Mat getAffineTransform( const Point2f src[], const Point2f dst[] );

//! computes 2x3 affine transformation matrix that is inverse to the specified 2x3 affine transformation.
CV_EXPORTS_W void invertAffineTransform( InputArray M, OutputArray iM );

CV_EXPORTS_W Mat getPerspectiveTransform( InputArray src, InputArray dst );

CV_EXPORTS_W Mat getAffineTransform( InputArray src, InputArray dst );

//! extracts rectangle from the image at sub-pixel location
CV_EXPORTS_W void getRectSubPix( InputArray image, Size patchSize,
                                 Point2f center, OutputArray patch, int patchType = -1 );

//! computes the log polar transform
CV_EXPORTS_W void logPolar( InputArray src, OutputArray dst,
                            Point2f center, double M, int flags );

//! computes the linear polar transform
CV_EXPORTS_W void linearPolar( InputArray src, OutputArray dst,
                               Point2f center, double maxRadius, int flags );

//! computes the integral image
CV_EXPORTS_W void integral( InputArray src, OutputArray sum, int sdepth = -1 );

//! computes the integral image and integral for the squared image
CV_EXPORTS_AS(integral2) void integral( InputArray src, OutputArray sum,
                                        OutputArray sqsum, int sdepth = -1, int sqdepth = -1 );

//! computes the integral image, integral for the squared image and the tilted integral image
CV_EXPORTS_AS(integral3) void integral( InputArray src, OutputArray sum,
                                        OutputArray sqsum, OutputArray tilted,
                                        int sdepth = -1, int sqdepth = -1 );

//! adds image to the accumulator (dst += src). Unlike cv::add, dst and src can have different types.
CV_EXPORTS_W void accumulate( InputArray src, InputOutputArray dst,
                              InputArray mask = noArray() );

//! adds squared src image to the accumulator (dst += src*src).
CV_EXPORTS_W void accumulateSquare( InputArray src, InputOutputArray dst,
                                    InputArray mask = noArray() );
//! adds product of the 2 images to the accumulator (dst += src1*src2).
CV_EXPORTS_W void accumulateProduct( InputArray src1, InputArray src2,
                                     InputOutputArray dst, InputArray mask=noArray() );

//! updates the running average (dst = dst*(1-alpha) + src*alpha)
CV_EXPORTS_W void accumulateWeighted( InputArray src, InputOutputArray dst,
                                      double alpha, InputArray mask = noArray() );

CV_EXPORTS_W Point2d phaseCorrelate(InputArray src1, InputArray src2,
                                    InputArray window = noArray(), CV_OUT double* response = 0);

CV_EXPORTS_W void createHanningWindow(OutputArray dst, Size winSize, int type);

//! applies fixed threshold to the image
CV_EXPORTS_W double threshold( InputArray src, OutputArray dst,
                               double thresh, double maxval, int type );


//! applies variable (adaptive) threshold to the image
CV_EXPORTS_W void adaptiveThreshold( InputArray src, OutputArray dst,
                                     double maxValue, int adaptiveMethod,
                                     int thresholdType, int blockSize, double C );

//! smooths and downsamples the image
CV_EXPORTS_W void pyrDown( InputArray src, OutputArray dst,
                           const Size& dstsize = Size(), int borderType = BORDER_DEFAULT );

//! upsamples and smoothes the image
CV_EXPORTS_W void pyrUp( InputArray src, OutputArray dst,
                         const Size& dstsize = Size(), int borderType = BORDER_DEFAULT );

//! builds the gaussian pyramid using pyrDown() as a basic operation
CV_EXPORTS void buildPyramid( InputArray src, OutputArrayOfArrays dst,
                              int maxlevel, int borderType = BORDER_DEFAULT );

//! corrects lens distortion for the given camera matrix and distortion coefficients
CV_EXPORTS_W void undistort( InputArray src, OutputArray dst,
                             InputArray cameraMatrix,
                             InputArray distCoeffs,
                             InputArray newCameraMatrix = noArray() );

//! initializes maps for cv::remap() to correct lens distortion and optionally rectify the image
CV_EXPORTS_W void initUndistortRectifyMap( InputArray cameraMatrix, InputArray distCoeffs,
                           InputArray R, InputArray newCameraMatrix,
                           Size size, int m1type, OutputArray map1, OutputArray map2 );

//! initializes maps for cv::remap() for wide-angle
CV_EXPORTS_W float initWideAngleProjMap( InputArray cameraMatrix, InputArray distCoeffs,
                                         Size imageSize, int destImageWidth,
                                         int m1type, OutputArray map1, OutputArray map2,
                                         int projType = PROJ_SPHERICAL_EQRECT, double alpha = 0);

//! returns the default new camera matrix (by default it is the same as cameraMatrix unless centerPricipalPoint=true)
CV_EXPORTS_W Mat getDefaultNewCameraMatrix( InputArray cameraMatrix, Size imgsize = Size(),
                                            bool centerPrincipalPoint = false );

//! returns points' coordinates after lens distortion correction
CV_EXPORTS_W void undistortPoints( InputArray src, OutputArray dst,
                                   InputArray cameraMatrix, InputArray distCoeffs,
                                   InputArray R = noArray(), InputArray P = noArray());

//! computes the joint dense histogram for a set of images.
CV_EXPORTS void calcHist( const Mat* images, int nimages,
                          const int* channels, InputArray mask,
                          OutputArray hist, int dims, const int* histSize,
                          const float** ranges, bool uniform = true, bool accumulate = false );

//! computes the joint sparse histogram for a set of images.
CV_EXPORTS void calcHist( const Mat* images, int nimages,
                          const int* channels, InputArray mask,
                          SparseMat& hist, int dims,
                          const int* histSize, const float** ranges,
                          bool uniform = true, bool accumulate = false );

CV_EXPORTS_W void calcHist( InputArrayOfArrays images,
                            const std::vector<int>& channels,
                            InputArray mask, OutputArray hist,
                            const std::vector<int>& histSize,
                            const std::vector<float>& ranges,
                            bool accumulate = false );

//! computes back projection for the set of images
CV_EXPORTS void calcBackProject( const Mat* images, int nimages,
                                 const int* channels, InputArray hist,
                                 OutputArray backProject, const float** ranges,
                                 double scale = 1, bool uniform = true );

//! computes back projection for the set of images
CV_EXPORTS void calcBackProject( const Mat* images, int nimages,
                                 const int* channels, const SparseMat& hist,
                                 OutputArray backProject, const float** ranges,
                                 double scale = 1, bool uniform = true );

CV_EXPORTS_W void calcBackProject( InputArrayOfArrays images, const std::vector<int>& channels,
                                   InputArray hist, OutputArray dst,
                                   const std::vector<float>& ranges,
                                   double scale );

//! compares two histograms stored in dense arrays
CV_EXPORTS_W double compareHist( InputArray H1, InputArray H2, int method );

//! compares two histograms stored in sparse arrays
CV_EXPORTS double compareHist( const SparseMat& H1, const SparseMat& H2, int method );

//! normalizes the grayscale image brightness and contrast by normalizing its histogram
CV_EXPORTS_W void equalizeHist( InputArray src, OutputArray dst );

CV_EXPORTS float EMD( InputArray signature1, InputArray signature2,
                      int distType, InputArray cost=noArray(),
                      float* lowerBound = 0, OutputArray flow = noArray() );

//! segments the image using watershed algorithm
CV_EXPORTS_W void watershed( InputArray image, InputOutputArray markers );

//! filters image using meanshift algorithm
CV_EXPORTS_W void pyrMeanShiftFiltering( InputArray src, OutputArray dst,
                                         double sp, double sr, int maxLevel = 1,
                                         TermCriteria termcrit=TermCriteria(TermCriteria::MAX_ITER+TermCriteria::EPS,5,1) );

//! segments the image using GrabCut algorithm
CV_EXPORTS_W void grabCut( InputArray img, InputOutputArray mask, Rect rect,
                           InputOutputArray bgdModel, InputOutputArray fgdModel,
                           int iterCount, int mode = GC_EVAL );


//! builds the discrete Voronoi diagram
CV_EXPORTS_AS(distanceTransformWithLabels) void distanceTransform( InputArray src, OutputArray dst,
                                     OutputArray labels, int distanceType, int maskSize,
                                     int labelType = DIST_LABEL_CCOMP );

//! computes the distance transform map
CV_EXPORTS_W void distanceTransform( InputArray src, OutputArray dst,
                                     int distanceType, int maskSize, int dstType=CV_32F);


//! fills the semi-uniform image region starting from the specified seed point
CV_EXPORTS int floodFill( InputOutputArray image,
                          Point seedPoint, Scalar newVal, CV_OUT Rect* rect = 0,
                          Scalar loDiff = Scalar(), Scalar upDiff = Scalar(),
                          int flags = 4 );

//! fills the semi-uniform image region and/or the mask starting from the specified seed point
CV_EXPORTS_W int floodFill( InputOutputArray image, InputOutputArray mask,
                            Point seedPoint, Scalar newVal, CV_OUT Rect* rect=0,
                            Scalar loDiff = Scalar(), Scalar upDiff = Scalar(),
                            int flags = 4 );

//! converts image from one color space to another
CV_EXPORTS_W void cvtColor( InputArray src, OutputArray dst, int code, int dstCn = 0 );

// main function for all demosaicing procceses
CV_EXPORTS_W void demosaicing(InputArray _src, OutputArray _dst, int code, int dcn = 0);

//! computes moments of the rasterized shape or a vector of points
CV_EXPORTS_W Moments moments( InputArray array, bool binaryImage = false );

//! computes 7 Hu invariants from the moments
CV_EXPORTS void HuMoments( const Moments& moments, double hu[7] );

CV_EXPORTS_W void HuMoments( const Moments& m, OutputArray hu );

//! computes the proximity map for the raster template and the image where the template is searched for
CV_EXPORTS_W void matchTemplate( InputArray image, InputArray templ,
                                 OutputArray result, int method );


// computes the connected components labeled image of boolean image ``image``
// with 4 or 8 way connectivity - returns N, the total
// number of labels [0, N-1] where 0 represents the background label.
// ltype specifies the output label image type, an important
// consideration based on the total number of labels or
// alternatively the total number of pixels in the source image.
CV_EXPORTS_W int connectedComponents(InputArray image, OutputArray labels,
                                     int connectivity = 8, int ltype = CV_32S);

CV_EXPORTS_W int connectedComponentsWithStats(InputArray image, OutputArray labels,
                                              OutputArray stats, OutputArray centroids,
                                              int connectivity = 8, int ltype = CV_32S);


//! retrieves contours and the hierarchical information from black-n-white image.
CV_EXPORTS_W void findContours( InputOutputArray image, OutputArrayOfArrays contours,
                              OutputArray hierarchy, int mode,
                              int method, Point offset = Point());

//! retrieves contours from black-n-white image.
CV_EXPORTS void findContours( InputOutputArray image, OutputArrayOfArrays contours,
                              int mode, int method, Point offset = Point());

//! approximates contour or a curve using Douglas-Peucker algorithm
CV_EXPORTS_W void approxPolyDP( InputArray curve,
                                OutputArray approxCurve,
                                double epsilon, bool closed );

//! computes the contour perimeter (closed=true) or a curve length
CV_EXPORTS_W double arcLength( InputArray curve, bool closed );

//! computes the bounding rectangle for a contour
CV_EXPORTS_W Rect boundingRect( InputArray points );

//! computes the contour area
CV_EXPORTS_W double contourArea( InputArray contour, bool oriented = false );

//! computes the minimal rotated rectangle for a set of points
CV_EXPORTS_W RotatedRect minAreaRect( InputArray points );

//! computes boxpoints
CV_EXPORTS_W void boxPoints(RotatedRect box, OutputArray points);

//! computes the minimal enclosing circle for a set of points
CV_EXPORTS_W void minEnclosingCircle( InputArray points,
                                      CV_OUT Point2f& center, CV_OUT float& radius );

//! computes the minimal enclosing triangle for a set of points and returns its area
CV_EXPORTS_W double minEnclosingTriangle( InputArray points, CV_OUT OutputArray triangle );

//! matches two contours using one of the available algorithms
CV_EXPORTS_W double matchShapes( InputArray contour1, InputArray contour2,
                                 int method, double parameter );

//! computes convex hull for a set of 2D points.
CV_EXPORTS_W void convexHull( InputArray points, OutputArray hull,
                              bool clockwise = false, bool returnPoints = true );

//! computes the contour convexity defects
CV_EXPORTS_W void convexityDefects( InputArray contour, InputArray convexhull, OutputArray convexityDefects );

//! returns true if the contour is convex. Does not support contours with self-intersection
CV_EXPORTS_W bool isContourConvex( InputArray contour );

//! finds intersection of two convex polygons
CV_EXPORTS_W float intersectConvexConvex( InputArray _p1, InputArray _p2,
                                          OutputArray _p12, bool handleNested = true );

//! fits ellipse to the set of 2D points
CV_EXPORTS_W RotatedRect fitEllipse( InputArray points );

//! fits line to the set of 2D points using M-estimator algorithm
CV_EXPORTS_W void fitLine( InputArray points, OutputArray line, int distType,
                           double param, double reps, double aeps );

//! checks if the point is inside the contour. Optionally computes the signed distance from the point to the contour boundary
CV_EXPORTS_W double pointPolygonTest( InputArray contour, Point2f pt, bool measureDist );

//! computes whether two rotated rectangles intersect and returns the vertices of the intersecting region
CV_EXPORTS_W int rotatedRectangleIntersection( const RotatedRect& rect1, const RotatedRect& rect2, OutputArray intersectingRegion  );

CV_EXPORTS_W Ptr<CLAHE> createCLAHE(double clipLimit = 40.0, Size tileGridSize = Size(8, 8));

//! Ballard, D.H. (1981). Generalizing the Hough transform to detect arbitrary shapes. Pattern Recognition 13 (2): 111-122.
//! Detects position only without traslation and rotation
CV_EXPORTS Ptr<GeneralizedHoughBallard> createGeneralizedHoughBallard();

//! Guil, N., González-Linares, J.M. and Zapata, E.L. (1999). Bidimensional shape detection using an invariant approach. Pattern Recognition 32 (6): 1025-1038.
//! Detects position, traslation and rotation
CV_EXPORTS Ptr<GeneralizedHoughGuil> createGeneralizedHoughGuil();

//! Performs linear blending of two images
CV_EXPORTS void blendLinear(InputArray src1, InputArray src2, InputArray weights1, InputArray weights2, OutputArray dst);

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);


//! draws the line segment (pt1, pt2) in the image
CV_EXPORTS_W void line(InputOutputArray img, Point pt1, Point pt2, const Scalar& color,
                     int thickness = 1, int lineType = LINE_8, int shift = 0);

//! draws an arrow from pt1 to pt2 in the image
CV_EXPORTS_W void arrowedLine(InputOutputArray img, Point pt1, Point pt2, const Scalar& color,
                     int thickness=1, int line_type=8, int shift=0, double tipLength=0.1);

//! draws the rectangle outline or a solid rectangle with the opposite corners pt1 and pt2 in the image
CV_EXPORTS_W void rectangle(InputOutputArray img, Point pt1, Point pt2,
                          const Scalar& color, int thickness = 1,
                          int lineType = LINE_8, int shift = 0);

//! draws the rectangle outline or a solid rectangle covering rec in the image
CV_EXPORTS void rectangle(CV_IN_OUT Mat& img, Rect rec,
                          const Scalar& color, int thickness = 1,
                          int lineType = LINE_8, int shift = 0);

//! draws the circle outline or a solid circle in the image
CV_EXPORTS_W void circle(InputOutputArray img, Point center, int radius,
                       const Scalar& color, int thickness = 1,
                       int lineType = LINE_8, int shift = 0);

//! draws an elliptic arc, ellipse sector or a rotated ellipse in the image
CV_EXPORTS_W void ellipse(InputOutputArray img, Point center, Size axes,
                        double angle, double startAngle, double endAngle,
                        const Scalar& color, int thickness = 1,
                        int lineType = LINE_8, int shift = 0);

//! draws a rotated ellipse in the image
CV_EXPORTS_W void ellipse(InputOutputArray img, const RotatedRect& box, const Scalar& color,
                        int thickness = 1, int lineType = LINE_8);

//! draws a filled convex polygon in the image
CV_EXPORTS void fillConvexPoly(Mat& img, const Point* pts, int npts,
                               const Scalar& color, int lineType = LINE_8,
                               int shift = 0);

CV_EXPORTS_W void fillConvexPoly(InputOutputArray img, InputArray points,
                                 const Scalar& color, int lineType = LINE_8,
                                 int shift = 0);

//! fills an area bounded by one or more polygons
CV_EXPORTS void fillPoly(Mat& img, const Point** pts,
                         const int* npts, int ncontours,
                         const Scalar& color, int lineType = LINE_8, int shift = 0,
                         Point offset = Point() );

CV_EXPORTS_W void fillPoly(InputOutputArray img, InputArrayOfArrays pts,
                           const Scalar& color, int lineType = LINE_8, int shift = 0,
                           Point offset = Point() );

//! draws one or more polygonal curves
CV_EXPORTS void polylines(Mat& img, const Point* const* pts, const int* npts,
                          int ncontours, bool isClosed, const Scalar& color,
                          int thickness = 1, int lineType = LINE_8, int shift = 0 );

CV_EXPORTS_W void polylines(InputOutputArray img, InputArrayOfArrays pts,
                            bool isClosed, const Scalar& color,
                            int thickness = 1, int lineType = LINE_8, int shift = 0 );

//! draws contours in the image
CV_EXPORTS_W void drawContours( InputOutputArray image, InputArrayOfArrays contours,
                              int contourIdx, const Scalar& color,
                              int thickness = 1, int lineType = LINE_8,
                              InputArray hierarchy = noArray(),
                              int maxLevel = INT_MAX, Point offset = Point() );

//! clips the line segment by the rectangle Rect(0, 0, imgSize.width, imgSize.height)
CV_EXPORTS bool clipLine(Size imgSize, CV_IN_OUT Point& pt1, CV_IN_OUT Point& pt2);

//! clips the line segment by the rectangle imgRect
CV_EXPORTS_W bool clipLine(Rect imgRect, CV_OUT CV_IN_OUT Point& pt1, CV_OUT CV_IN_OUT Point& pt2);

//! converts elliptic arc to a polygonal curve
CV_EXPORTS_W void ellipse2Poly( Point center, Size axes, int angle,
                                int arcStart, int arcEnd, int delta,
                                CV_OUT std::vector<Point>& pts );

//! renders text string in the image
CV_EXPORTS_W void putText( InputOutputArray img, const String& text, Point org,
                         int fontFace, double fontScale, Scalar color,
                         int thickness = 1, int lineType = LINE_8,
                         bool bottomLeftOrigin = false );

//! returns bounding box of the text string
CV_EXPORTS_W Size getTextSize(const String& text, int fontFace,
                            double fontScale, int thickness,
                            CV_OUT int* baseLine);

} // cv

#endif