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// For Open Source Computer Vision Library
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#ifndef __OPENCV_STITCHING_MOTION_ESTIMATORS_HPP__
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#define __OPENCV_STITCHING_MOTION_ESTIMATORS_HPP__
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#include "opencv2/core/core.hpp"
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#include "matchers.hpp"
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#include "util.hpp"
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#include "camera.hpp"
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namespace cv {
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namespace detail {
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class CV_EXPORTS Estimator
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{
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public:
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virtual ~Estimator() {}
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void operator ()(const std::vector<ImageFeatures> &features, const std::vector<MatchesInfo> &pairwise_matches,
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std::vector<CameraParams> &cameras)
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{ estimate(features, pairwise_matches, cameras); }
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protected:
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virtual void estimate(const std::vector<ImageFeatures> &features, const std::vector<MatchesInfo> &pairwise_matches,
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std::vector<CameraParams> &cameras) = 0;
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};
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class CV_EXPORTS HomographyBasedEstimator : public Estimator
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{
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public:
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HomographyBasedEstimator(bool is_focals_estimated = false)
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: is_focals_estimated_(is_focals_estimated) {}
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private:
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void estimate(const std::vector<ImageFeatures> &features, const std::vector<MatchesInfo> &pairwise_matches,
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std::vector<CameraParams> &cameras);
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bool is_focals_estimated_;
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};
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class CV_EXPORTS BundleAdjusterBase : public Estimator
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{
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public:
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const Mat refinementMask() const { return refinement_mask_.clone(); }
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void setRefinementMask(const Mat &mask)
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{
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CV_Assert(mask.type() == CV_8U && mask.size() == Size(3, 3));
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refinement_mask_ = mask.clone();
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}
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double confThresh() const { return conf_thresh_; }
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void setConfThresh(double conf_thresh) { conf_thresh_ = conf_thresh; }
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CvTermCriteria termCriteria() { return term_criteria_; }
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void setTermCriteria(const CvTermCriteria& term_criteria) { term_criteria_ = term_criteria; }
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protected:
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BundleAdjusterBase(int num_params_per_cam, int num_errs_per_measurement)
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: num_params_per_cam_(num_params_per_cam),
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num_errs_per_measurement_(num_errs_per_measurement)
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{
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setRefinementMask(Mat::ones(3, 3, CV_8U));
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setConfThresh(1.);
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setTermCriteria(cvTermCriteria(CV_TERMCRIT_EPS + CV_TERMCRIT_ITER, 1000, DBL_EPSILON));
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}
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// Runs bundle adjustment
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virtual void estimate(const std::vector<ImageFeatures> &features,
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const std::vector<MatchesInfo> &pairwise_matches,
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std::vector<CameraParams> &cameras);
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virtual void setUpInitialCameraParams(const std::vector<CameraParams> &cameras) = 0;
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virtual void obtainRefinedCameraParams(std::vector<CameraParams> &cameras) const = 0;
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virtual void calcError(Mat &err) = 0;
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virtual void calcJacobian(Mat &jac) = 0;
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// 3x3 8U mask, where 0 means don't refine respective parameter, != 0 means refine
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Mat refinement_mask_;
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int num_images_;
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int total_num_matches_;
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int num_params_per_cam_;
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int num_errs_per_measurement_;
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const ImageFeatures *features_;
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const MatchesInfo *pairwise_matches_;
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// Threshold to filter out poorly matched image pairs
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double conf_thresh_;
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//Levenberg–Marquardt algorithm termination criteria
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CvTermCriteria term_criteria_;
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// Camera parameters matrix (CV_64F)
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Mat cam_params_;
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// Connected images pairs
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std::vector<std::pair<int,int> > edges_;
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};
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// Minimizes reprojection error.
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// It can estimate focal length, aspect ratio, principal point.
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// You can affect only on them via the refinement mask.
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class CV_EXPORTS BundleAdjusterReproj : public BundleAdjusterBase
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{
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public:
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BundleAdjusterReproj() : BundleAdjusterBase(7, 2) {}
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private:
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void setUpInitialCameraParams(const std::vector<CameraParams> &cameras);
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void obtainRefinedCameraParams(std::vector<CameraParams> &cameras) const;
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void calcError(Mat &err);
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void calcJacobian(Mat &jac);
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Mat err1_, err2_;
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};
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// Minimizes sun of ray-to-ray distances.
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// It can estimate focal length. It ignores the refinement mask for now.
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class CV_EXPORTS BundleAdjusterRay : public BundleAdjusterBase
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{
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public:
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BundleAdjusterRay() : BundleAdjusterBase(4, 3) {}
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private:
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void setUpInitialCameraParams(const std::vector<CameraParams> &cameras);
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void obtainRefinedCameraParams(std::vector<CameraParams> &cameras) const;
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void calcError(Mat &err);
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void calcJacobian(Mat &jac);
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Mat err1_, err2_;
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};
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enum WaveCorrectKind
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{
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WAVE_CORRECT_HORIZ,
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WAVE_CORRECT_VERT
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};
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void CV_EXPORTS waveCorrect(std::vector<Mat> &rmats, WaveCorrectKind kind);
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//////////////////////////////////////////////////////////////////////////////
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// Auxiliary functions
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// Returns matches graph representation in DOT language
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std::string CV_EXPORTS matchesGraphAsString(std::vector<std::string> &pathes, std::vector<MatchesInfo> &pairwise_matches,
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float conf_threshold);
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std::vector<int> CV_EXPORTS leaveBiggestComponent(std::vector<ImageFeatures> &features, std::vector<MatchesInfo> &pairwise_matches,
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float conf_threshold);
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void CV_EXPORTS findMaxSpanningTree(int num_images, const std::vector<MatchesInfo> &pairwise_matches,
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Graph &span_tree, std::vector<int> ¢ers);
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} // namespace detail
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} // namespace cv
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#endif // __OPENCV_STITCHING_MOTION_ESTIMATORS_HPP__
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