| 123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140141142143144145146147148149150151152153154155156157158159160161162163164165166167168169170171172173174175176177178179180181182183184185186187188189190191192193194195196197198199200201202203204205206207208209210211212213214215216217218219220221222223224225226227228229230231232233234235236237238239240241242243244245246247248249250251252253254255256257258259260261262263264265266267268269270271272273274275276277278279280281282283284285 | /*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_STITCHING_SEAM_FINDERS_HPP#define OPENCV_STITCHING_SEAM_FINDERS_HPP#include <set>#include "opencv2/core.hpp"#include "opencv2/opencv_modules.hpp"namespace cv {namespace detail {//! @addtogroup stitching_seam//! @{/** @brief Base class for a seam estimator. */class CV_EXPORTS SeamFinder{public:    virtual ~SeamFinder() {}    /** @brief Estimates seams.    @param src Source images    @param corners Source image top-left corners    @param masks Source image masks to update     */    virtual void find(const std::vector<UMat> &src, const std::vector<Point> &corners,                      std::vector<UMat> &masks) = 0;};/** @brief Stub seam estimator which does nothing. */class CV_EXPORTS NoSeamFinder : public SeamFinder{public:    void find(const std::vector<UMat>&, const std::vector<Point>&, std::vector<UMat>&) {}};/** @brief Base class for all pairwise seam estimators. */class CV_EXPORTS PairwiseSeamFinder : public SeamFinder{public:    virtual void find(const std::vector<UMat> &src, const std::vector<Point> &corners,                      std::vector<UMat> &masks);protected:    void run();    /** @brief Resolves masks intersection of two specified images in the given ROI.    @param first First image index    @param second Second image index    @param roi Region of interest     */    virtual void findInPair(size_t first, size_t second, Rect roi) = 0;    std::vector<UMat> images_;    std::vector<Size> sizes_;    std::vector<Point> corners_;    std::vector<UMat> masks_;};/** @brief Voronoi diagram-based seam estimator. */class CV_EXPORTS VoronoiSeamFinder : public PairwiseSeamFinder{public:    virtual void find(const std::vector<UMat> &src, const std::vector<Point> &corners,                      std::vector<UMat> &masks);    virtual void find(const std::vector<Size> &size, const std::vector<Point> &corners,                      std::vector<UMat> &masks);private:    void findInPair(size_t first, size_t second, Rect roi);};class CV_EXPORTS DpSeamFinder : public SeamFinder{public:    enum CostFunction { COLOR, COLOR_GRAD };    DpSeamFinder(CostFunction costFunc = COLOR);    CostFunction costFunction() const { return costFunc_; }    void setCostFunction(CostFunction val) { costFunc_ = val; }    virtual void find(const std::vector<UMat> &src, const std::vector<Point> &corners,                      std::vector<UMat> &masks);private:    enum ComponentState    {        FIRST = 1, SECOND = 2, INTERS = 4,        INTERS_FIRST = INTERS | FIRST,        INTERS_SECOND = INTERS | SECOND    };    class ImagePairLess    {    public:        ImagePairLess(const std::vector<Mat> &images, const std::vector<Point> &corners)            : src_(&images[0]), corners_(&corners[0]) {}        bool operator() (const std::pair<size_t, size_t> &l, const std::pair<size_t, size_t> &r) const        {            Point c1 = corners_[l.first] + Point(src_[l.first].cols / 2, src_[l.first].rows / 2);            Point c2 = corners_[l.second] + Point(src_[l.second].cols / 2, src_[l.second].rows / 2);            int d1 = (c1 - c2).dot(c1 - c2);            c1 = corners_[r.first] + Point(src_[r.first].cols / 2, src_[r.first].rows / 2);            c2 = corners_[r.second] + Point(src_[r.second].cols / 2, src_[r.second].rows / 2);            int d2 = (c1 - c2).dot(c1 - c2);            return d1 < d2;        }    private:        const Mat *src_;        const Point *corners_;    };    class ClosePoints    {    public:        ClosePoints(int minDist) : minDist_(minDist) {}        bool operator() (const Point &p1, const Point &p2) const        {            int dist2 = (p1.x-p2.x) * (p1.x-p2.x) + (p1.y-p2.y) * (p1.y-p2.y);            return dist2 < minDist_ * minDist_;        }    private:        int minDist_;    };    void process(            const Mat &image1, const Mat &image2, Point tl1, Point tl2,  Mat &mask1, Mat &mask2);    void findComponents();    void findEdges();    void resolveConflicts(            const Mat &image1, const Mat &image2, Point tl1, Point tl2, Mat &mask1, Mat &mask2);    void computeGradients(const Mat &image1, const Mat &image2);    bool hasOnlyOneNeighbor(int comp);    bool closeToContour(int y, int x, const Mat_<uchar> &contourMask);    bool getSeamTips(int comp1, int comp2, Point &p1, Point &p2);    void computeCosts(            const Mat &image1, const Mat &image2, Point tl1, Point tl2,            int comp, Mat_<float> &costV, Mat_<float> &costH);    bool estimateSeam(            const Mat &image1, const Mat &image2, Point tl1, Point tl2, int comp,            Point p1, Point p2, std::vector<Point> &seam, bool &isHorizontal);    void updateLabelsUsingSeam(            int comp1, int comp2, const std::vector<Point> &seam, bool isHorizontalSeam);    CostFunction costFunc_;    // processing images pair data    Point unionTl_, unionBr_;    Size unionSize_;    Mat_<uchar> mask1_, mask2_;    Mat_<uchar> contour1mask_, contour2mask_;    Mat_<float> gradx1_, grady1_;    Mat_<float> gradx2_, grady2_;    // components data    int ncomps_;    Mat_<int> labels_;    std::vector<ComponentState> states_;    std::vector<Point> tls_, brs_;    std::vector<std::vector<Point> > contours_;    std::set<std::pair<int, int> > edges_;};/** @brief Base class for all minimum graph-cut-based seam estimators. */class CV_EXPORTS GraphCutSeamFinderBase{public:    enum CostType { COST_COLOR, COST_COLOR_GRAD };};/** @brief Minimum graph cut-based seam estimator. See details in @cite V03 . */class CV_EXPORTS GraphCutSeamFinder : public GraphCutSeamFinderBase, public SeamFinder{public:    GraphCutSeamFinder(int cost_type = COST_COLOR_GRAD, float terminal_cost = 10000.f,                       float bad_region_penalty = 1000.f);    ~GraphCutSeamFinder();    void find(const std::vector<UMat> &src, const std::vector<Point> &corners,              std::vector<UMat> &masks);private:    // To avoid GCGraph dependency    class Impl;    Ptr<PairwiseSeamFinder> impl_;};#ifdef HAVE_OPENCV_CUDALEGACYclass CV_EXPORTS GraphCutSeamFinderGpu : public GraphCutSeamFinderBase, public PairwiseSeamFinder{public:    GraphCutSeamFinderGpu(int cost_type = COST_COLOR_GRAD, float terminal_cost = 10000.f,                          float bad_region_penalty = 1000.f)                          : cost_type_(cost_type), terminal_cost_(terminal_cost),                            bad_region_penalty_(bad_region_penalty) {}    void find(const std::vector<cv::UMat> &src, const std::vector<cv::Point> &corners,              std::vector<cv::UMat> &masks);    void findInPair(size_t first, size_t second, Rect roi);private:    void setGraphWeightsColor(const cv::Mat &img1, const cv::Mat &img2, const cv::Mat &mask1, const cv::Mat &mask2,                              cv::Mat &terminals, cv::Mat &leftT, cv::Mat &rightT, cv::Mat &top, cv::Mat &bottom);    void setGraphWeightsColorGrad(const cv::Mat &img1, const cv::Mat &img2, const cv::Mat &dx1, const cv::Mat &dx2,                                  const cv::Mat &dy1, const cv::Mat &dy2, const cv::Mat &mask1, const cv::Mat &mask2,                                  cv::Mat &terminals, cv::Mat &leftT, cv::Mat &rightT, cv::Mat &top, cv::Mat &bottom);    std::vector<Mat> dx_, dy_;    int cost_type_;    float terminal_cost_;    float bad_region_penalty_;};#endif//! @}} // namespace detail} // namespace cv#endif // OPENCV_STITCHING_SEAM_FINDERS_HPP
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