Open Source Computer Vision Library
https://opencv.org/
You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
259 lines
8.6 KiB
259 lines
8.6 KiB
/*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 { |
|
|
|
class CV_EXPORTS SeamFinder |
|
{ |
|
public: |
|
virtual ~SeamFinder() {} |
|
virtual void find(const std::vector<UMat> &src, const std::vector<Point> &corners, |
|
std::vector<UMat> &masks) = 0; |
|
}; |
|
|
|
|
|
class CV_EXPORTS NoSeamFinder : public SeamFinder |
|
{ |
|
public: |
|
void find(const std::vector<UMat>&, const std::vector<Point>&, std::vector<UMat>&) {} |
|
}; |
|
|
|
|
|
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(); |
|
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_; |
|
}; |
|
|
|
|
|
class CV_EXPORTS VoronoiSeamFinder : public PairwiseSeamFinder |
|
{ |
|
public: |
|
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_; |
|
}; |
|
|
|
|
|
class CV_EXPORTS GraphCutSeamFinderBase |
|
{ |
|
public: |
|
enum CostType { COST_COLOR, COST_COLOR_GRAD }; |
|
}; |
|
|
|
|
|
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_CUDA |
|
class 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__
|
|
|