286 lines
9.5 KiB
C++
286 lines
9.5 KiB
C++
/*M///////////////////////////////////////////////////////////////////////////////////////
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//
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
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//
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// By downloading, copying, installing or using the software you agree to this license.
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// If you do not agree to this license, do not download, install,
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// copy or use the software.
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//
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//
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// License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
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// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
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// Third party copyrights are property of their respective owners.
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//
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// Redistribution and use in source and binary forms, with or without modification,
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// are permitted provided that the following conditions are met:
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//
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// * Redistribution's of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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//
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// * Redistribution's in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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//
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// * The name of the copyright holders may not be used to endorse or promote products
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// derived from this software without specific prior written permission.
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//
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// This software is provided by the copyright holders and contributors "as is" and
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// any express or implied warranties, including, but not limited to, the implied
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// warranties of merchantability and fitness for a particular purpose are disclaimed.
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// In no event shall the Intel Corporation or contributors be liable for any direct,
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// indirect, incidental, special, exemplary, or consequential damages
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// (including, but not limited to, procurement of substitute goods or services;
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// loss of use, data, or profits; or business interruption) however caused
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// and on any theory of liability, whether in contract, strict liability,
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// or tort (including negligence or otherwise) arising in any way out of
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// the use of this software, even if advised of the possibility of such damage.
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//
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//M*/
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#ifndef OPENCV_STITCHING_SEAM_FINDERS_HPP
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#define OPENCV_STITCHING_SEAM_FINDERS_HPP
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#include <set>
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#include "opencv2/core.hpp"
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#include "opencv2/opencv_modules.hpp"
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namespace cv {
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namespace detail {
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//! @addtogroup stitching_seam
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//! @{
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/** @brief Base class for a seam estimator.
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*/
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class CV_EXPORTS SeamFinder
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{
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public:
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virtual ~SeamFinder() {}
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/** @brief Estimates seams.
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@param src Source images
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@param corners Source image top-left corners
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@param masks Source image masks to update
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*/
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virtual void find(const std::vector<UMat> &src, const std::vector<Point> &corners,
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std::vector<UMat> &masks) = 0;
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};
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/** @brief Stub seam estimator which does nothing.
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*/
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class CV_EXPORTS NoSeamFinder : public SeamFinder
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{
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public:
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void find(const std::vector<UMat>&, const std::vector<Point>&, std::vector<UMat>&) {}
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};
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/** @brief Base class for all pairwise seam estimators.
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*/
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class CV_EXPORTS PairwiseSeamFinder : public SeamFinder
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{
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public:
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virtual void find(const std::vector<UMat> &src, const std::vector<Point> &corners,
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std::vector<UMat> &masks);
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protected:
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void run();
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/** @brief Resolves masks intersection of two specified images in the given ROI.
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@param first First image index
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@param second Second image index
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@param roi Region of interest
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*/
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virtual void findInPair(size_t first, size_t second, Rect roi) = 0;
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std::vector<UMat> images_;
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std::vector<Size> sizes_;
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std::vector<Point> corners_;
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std::vector<UMat> masks_;
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};
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/** @brief Voronoi diagram-based seam estimator.
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*/
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class CV_EXPORTS VoronoiSeamFinder : public PairwiseSeamFinder
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{
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public:
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virtual void find(const std::vector<UMat> &src, const std::vector<Point> &corners,
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std::vector<UMat> &masks);
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virtual void find(const std::vector<Size> &size, const std::vector<Point> &corners,
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std::vector<UMat> &masks);
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private:
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void findInPair(size_t first, size_t second, Rect roi);
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};
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class CV_EXPORTS DpSeamFinder : public SeamFinder
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{
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public:
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enum CostFunction { COLOR, COLOR_GRAD };
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DpSeamFinder(CostFunction costFunc = COLOR);
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CostFunction costFunction() const { return costFunc_; }
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void setCostFunction(CostFunction val) { costFunc_ = val; }
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virtual void find(const std::vector<UMat> &src, const std::vector<Point> &corners,
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std::vector<UMat> &masks);
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private:
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enum ComponentState
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{
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FIRST = 1, SECOND = 2, INTERS = 4,
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INTERS_FIRST = INTERS | FIRST,
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INTERS_SECOND = INTERS | SECOND
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};
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class ImagePairLess
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{
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public:
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ImagePairLess(const std::vector<Mat> &images, const std::vector<Point> &corners)
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: src_(&images[0]), corners_(&corners[0]) {}
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bool operator() (const std::pair<size_t, size_t> &l, const std::pair<size_t, size_t> &r) const
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{
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Point c1 = corners_[l.first] + Point(src_[l.first].cols / 2, src_[l.first].rows / 2);
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Point c2 = corners_[l.second] + Point(src_[l.second].cols / 2, src_[l.second].rows / 2);
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int d1 = (c1 - c2).dot(c1 - c2);
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c1 = corners_[r.first] + Point(src_[r.first].cols / 2, src_[r.first].rows / 2);
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c2 = corners_[r.second] + Point(src_[r.second].cols / 2, src_[r.second].rows / 2);
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int d2 = (c1 - c2).dot(c1 - c2);
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return d1 < d2;
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}
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private:
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const Mat *src_;
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const Point *corners_;
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};
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class ClosePoints
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{
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public:
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ClosePoints(int minDist) : minDist_(minDist) {}
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bool operator() (const Point &p1, const Point &p2) const
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{
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int dist2 = (p1.x-p2.x) * (p1.x-p2.x) + (p1.y-p2.y) * (p1.y-p2.y);
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return dist2 < minDist_ * minDist_;
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}
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private:
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int minDist_;
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};
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void process(
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const Mat &image1, const Mat &image2, Point tl1, Point tl2, Mat &mask1, Mat &mask2);
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void findComponents();
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void findEdges();
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void resolveConflicts(
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const Mat &image1, const Mat &image2, Point tl1, Point tl2, Mat &mask1, Mat &mask2);
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void computeGradients(const Mat &image1, const Mat &image2);
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bool hasOnlyOneNeighbor(int comp);
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bool closeToContour(int y, int x, const Mat_<uchar> &contourMask);
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bool getSeamTips(int comp1, int comp2, Point &p1, Point &p2);
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void computeCosts(
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const Mat &image1, const Mat &image2, Point tl1, Point tl2,
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int comp, Mat_<float> &costV, Mat_<float> &costH);
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bool estimateSeam(
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const Mat &image1, const Mat &image2, Point tl1, Point tl2, int comp,
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Point p1, Point p2, std::vector<Point> &seam, bool &isHorizontal);
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void updateLabelsUsingSeam(
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int comp1, int comp2, const std::vector<Point> &seam, bool isHorizontalSeam);
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CostFunction costFunc_;
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// processing images pair data
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Point unionTl_, unionBr_;
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Size unionSize_;
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Mat_<uchar> mask1_, mask2_;
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Mat_<uchar> contour1mask_, contour2mask_;
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Mat_<float> gradx1_, grady1_;
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Mat_<float> gradx2_, grady2_;
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// components data
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int ncomps_;
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Mat_<int> labels_;
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std::vector<ComponentState> states_;
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std::vector<Point> tls_, brs_;
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std::vector<std::vector<Point> > contours_;
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std::set<std::pair<int, int> > edges_;
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};
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/** @brief Base class for all minimum graph-cut-based seam estimators.
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*/
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class CV_EXPORTS GraphCutSeamFinderBase
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{
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public:
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enum CostType { COST_COLOR, COST_COLOR_GRAD };
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};
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/** @brief Minimum graph cut-based seam estimator. See details in @cite V03 .
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*/
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class CV_EXPORTS GraphCutSeamFinder : public GraphCutSeamFinderBase, public SeamFinder
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{
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public:
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GraphCutSeamFinder(int cost_type = COST_COLOR_GRAD, float terminal_cost = 10000.f,
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float bad_region_penalty = 1000.f);
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~GraphCutSeamFinder();
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void find(const std::vector<UMat> &src, const std::vector<Point> &corners,
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std::vector<UMat> &masks);
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private:
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// To avoid GCGraph dependency
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class Impl;
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Ptr<PairwiseSeamFinder> impl_;
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};
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#ifdef HAVE_OPENCV_CUDALEGACY
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class CV_EXPORTS GraphCutSeamFinderGpu : public GraphCutSeamFinderBase, public PairwiseSeamFinder
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{
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public:
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GraphCutSeamFinderGpu(int cost_type = COST_COLOR_GRAD, float terminal_cost = 10000.f,
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float bad_region_penalty = 1000.f)
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: cost_type_(cost_type), terminal_cost_(terminal_cost),
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bad_region_penalty_(bad_region_penalty) {}
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void find(const std::vector<cv::UMat> &src, const std::vector<cv::Point> &corners,
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std::vector<cv::UMat> &masks);
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void findInPair(size_t first, size_t second, Rect roi);
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private:
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void setGraphWeightsColor(const cv::Mat &img1, const cv::Mat &img2, const cv::Mat &mask1, const cv::Mat &mask2,
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cv::Mat &terminals, cv::Mat &leftT, cv::Mat &rightT, cv::Mat &top, cv::Mat &bottom);
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void setGraphWeightsColorGrad(const cv::Mat &img1, const cv::Mat &img2, const cv::Mat &dx1, const cv::Mat &dx2,
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const cv::Mat &dy1, const cv::Mat &dy2, const cv::Mat &mask1, const cv::Mat &mask2,
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cv::Mat &terminals, cv::Mat &leftT, cv::Mat &rightT, cv::Mat &top, cv::Mat &bottom);
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std::vector<Mat> dx_, dy_;
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int cost_type_;
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float terminal_cost_;
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float bad_region_penalty_;
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};
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#endif
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//! @}
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} // namespace detail
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} // namespace cv
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#endif // OPENCV_STITCHING_SEAM_FINDERS_HPP
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