320 lines
13 KiB
C++
320 lines
13 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_STITCHER_HPP
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#define OPENCV_STITCHING_STITCHER_HPP
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#include "opencv2/core.hpp"
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#include "opencv2/features2d.hpp"
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#include "opencv2/stitching/warpers.hpp"
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#include "opencv2/stitching/detail/matchers.hpp"
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#include "opencv2/stitching/detail/motion_estimators.hpp"
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#include "opencv2/stitching/detail/exposure_compensate.hpp"
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#include "opencv2/stitching/detail/seam_finders.hpp"
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#include "opencv2/stitching/detail/blenders.hpp"
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#include "opencv2/stitching/detail/camera.hpp"
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#if defined(Status)
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# warning Detected X11 'Status' macro definition, it can cause build conflicts. Please, include this header before any X11 headers.
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#endif
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/**
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@defgroup stitching Images stitching
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This figure illustrates the stitching module pipeline implemented in the Stitcher class. Using that
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class it's possible to configure/remove some steps, i.e. adjust the stitching pipeline according to
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the particular needs. All building blocks from the pipeline are available in the detail namespace,
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one can combine and use them separately.
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The implemented stitching pipeline is very similar to the one proposed in @cite BL07 .
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Camera models
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-------------
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There are currently 2 camera models implemented in stitching pipeline.
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- _Homography model_ expecting perspective transformations between images
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implemented in @ref cv::detail::BestOf2NearestMatcher cv::detail::HomographyBasedEstimator
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cv::detail::BundleAdjusterReproj cv::detail::BundleAdjusterRay
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- _Affine model_ expecting affine transformation with 6 DOF or 4 DOF implemented in
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@ref cv::detail::AffineBestOf2NearestMatcher cv::detail::AffineBasedEstimator
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cv::detail::BundleAdjusterAffine cv::detail::BundleAdjusterAffinePartial cv::AffineWarper
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Homography model is useful for creating photo panoramas captured by camera,
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while affine-based model can be used to stitch scans and object captured by
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specialized devices. Use @ref cv::Stitcher::create to get preconfigured pipeline for one
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of those models.
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@note
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Certain detailed settings of @ref cv::Stitcher might not make sense. Especially
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you should not mix classes implementing affine model and classes implementing
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Homography model, as they work with different transformations.
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@{
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@defgroup stitching_match Features Finding and Images Matching
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@defgroup stitching_rotation Rotation Estimation
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@defgroup stitching_autocalib Autocalibration
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@defgroup stitching_warp Images Warping
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@defgroup stitching_seam Seam Estimation
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@defgroup stitching_exposure Exposure Compensation
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@defgroup stitching_blend Image Blenders
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@}
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*/
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namespace cv {
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//! @addtogroup stitching
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//! @{
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/** @brief High level image stitcher.
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It's possible to use this class without being aware of the entire stitching pipeline. However, to
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be able to achieve higher stitching stability and quality of the final images at least being
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familiar with the theory is recommended.
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@note
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- A basic example on image stitching can be found at
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opencv_source_code/samples/cpp/stitching.cpp
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- A detailed example on image stitching can be found at
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opencv_source_code/samples/cpp/stitching_detailed.cpp
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*/
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class CV_EXPORTS_W Stitcher
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{
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public:
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enum { ORIG_RESOL = -1 };
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enum Status
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{
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OK = 0,
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ERR_NEED_MORE_IMGS = 1,
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ERR_HOMOGRAPHY_EST_FAIL = 2,
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ERR_CAMERA_PARAMS_ADJUST_FAIL = 3
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};
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enum Mode
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{
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/** Mode for creating photo panoramas. Expects images under perspective
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transformation and projects resulting pano to sphere.
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@sa detail::BestOf2NearestMatcher SphericalWarper
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*/
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PANORAMA = 0,
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/** Mode for composing scans. Expects images under affine transformation does
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not compensate exposure by default.
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@sa detail::AffineBestOf2NearestMatcher AffineWarper
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*/
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SCANS = 1,
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};
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// Stitcher() {}
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/** @brief Creates a stitcher with the default parameters.
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@param try_use_gpu Flag indicating whether GPU should be used whenever it's possible.
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@return Stitcher class instance.
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*/
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static Stitcher createDefault(bool try_use_gpu = false);
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/** @brief Creates a Stitcher configured in one of the stitching modes.
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@param mode Scenario for stitcher operation. This is usually determined by source of images
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to stitch and their transformation. Default parameters will be chosen for operation in given
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scenario.
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@param try_use_gpu Flag indicating whether GPU should be used whenever it's possible.
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@return Stitcher class instance.
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*/
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static Ptr<Stitcher> create(Mode mode = PANORAMA, bool try_use_gpu = false);
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CV_WRAP double registrationResol() const { return registr_resol_; }
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CV_WRAP void setRegistrationResol(double resol_mpx) { registr_resol_ = resol_mpx; }
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CV_WRAP double seamEstimationResol() const { return seam_est_resol_; }
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CV_WRAP void setSeamEstimationResol(double resol_mpx) { seam_est_resol_ = resol_mpx; }
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CV_WRAP double compositingResol() const { return compose_resol_; }
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CV_WRAP void setCompositingResol(double resol_mpx) { compose_resol_ = resol_mpx; }
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CV_WRAP double panoConfidenceThresh() const { return conf_thresh_; }
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CV_WRAP void setPanoConfidenceThresh(double conf_thresh) { conf_thresh_ = conf_thresh; }
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CV_WRAP bool waveCorrection() const { return do_wave_correct_; }
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CV_WRAP void setWaveCorrection(bool flag) { do_wave_correct_ = flag; }
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detail::WaveCorrectKind waveCorrectKind() const { return wave_correct_kind_; }
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void setWaveCorrectKind(detail::WaveCorrectKind kind) { wave_correct_kind_ = kind; }
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Ptr<detail::FeaturesFinder> featuresFinder() { return features_finder_; }
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const Ptr<detail::FeaturesFinder> featuresFinder() const { return features_finder_; }
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void setFeaturesFinder(Ptr<detail::FeaturesFinder> features_finder)
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{ features_finder_ = features_finder; }
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Ptr<detail::FeaturesMatcher> featuresMatcher() { return features_matcher_; }
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const Ptr<detail::FeaturesMatcher> featuresMatcher() const { return features_matcher_; }
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void setFeaturesMatcher(Ptr<detail::FeaturesMatcher> features_matcher)
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{ features_matcher_ = features_matcher; }
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const cv::UMat& matchingMask() const { return matching_mask_; }
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void setMatchingMask(const cv::UMat &mask)
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{
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CV_Assert(mask.type() == CV_8U && mask.cols == mask.rows);
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matching_mask_ = mask.clone();
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}
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Ptr<detail::BundleAdjusterBase> bundleAdjuster() { return bundle_adjuster_; }
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const Ptr<detail::BundleAdjusterBase> bundleAdjuster() const { return bundle_adjuster_; }
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void setBundleAdjuster(Ptr<detail::BundleAdjusterBase> bundle_adjuster)
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{ bundle_adjuster_ = bundle_adjuster; }
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/* TODO OpenCV ABI 4.x
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Ptr<detail::Estimator> estimator() { return estimator_; }
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const Ptr<detail::Estimator> estimator() const { return estimator_; }
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void setEstimator(Ptr<detail::Estimator> estimator)
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{ estimator_ = estimator; }
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*/
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Ptr<WarperCreator> warper() { return warper_; }
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const Ptr<WarperCreator> warper() const { return warper_; }
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void setWarper(Ptr<WarperCreator> creator) { warper_ = creator; }
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Ptr<detail::ExposureCompensator> exposureCompensator() { return exposure_comp_; }
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const Ptr<detail::ExposureCompensator> exposureCompensator() const { return exposure_comp_; }
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void setExposureCompensator(Ptr<detail::ExposureCompensator> exposure_comp)
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{ exposure_comp_ = exposure_comp; }
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Ptr<detail::SeamFinder> seamFinder() { return seam_finder_; }
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const Ptr<detail::SeamFinder> seamFinder() const { return seam_finder_; }
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void setSeamFinder(Ptr<detail::SeamFinder> seam_finder) { seam_finder_ = seam_finder; }
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Ptr<detail::Blender> blender() { return blender_; }
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const Ptr<detail::Blender> blender() const { return blender_; }
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void setBlender(Ptr<detail::Blender> b) { blender_ = b; }
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/** @overload */
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CV_WRAP Status estimateTransform(InputArrayOfArrays images);
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/** @brief These functions try to match the given images and to estimate rotations of each camera.
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@note Use the functions only if you're aware of the stitching pipeline, otherwise use
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Stitcher::stitch.
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@param images Input images.
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@param rois Region of interest rectangles.
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@return Status code.
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*/
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Status estimateTransform(InputArrayOfArrays images, const std::vector<std::vector<Rect> > &rois);
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/** @overload */
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CV_WRAP Status composePanorama(OutputArray pano);
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/** @brief These functions try to compose the given images (or images stored internally from the other function
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calls) into the final pano under the assumption that the image transformations were estimated
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before.
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@note Use the functions only if you're aware of the stitching pipeline, otherwise use
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Stitcher::stitch.
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@param images Input images.
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@param pano Final pano.
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@return Status code.
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*/
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Status composePanorama(InputArrayOfArrays images, OutputArray pano);
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/** @overload */
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CV_WRAP Status stitch(InputArrayOfArrays images, OutputArray pano);
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/** @brief These functions try to stitch the given images.
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@param images Input images.
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@param rois Region of interest rectangles.
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@param pano Final pano.
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@return Status code.
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*/
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Status stitch(InputArrayOfArrays images, const std::vector<std::vector<Rect> > &rois, OutputArray pano);
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std::vector<int> component() const { return indices_; }
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std::vector<detail::CameraParams> cameras() const { return cameras_; }
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CV_WRAP double workScale() const { return work_scale_; }
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private:
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//Stitcher() {}
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Status matchImages();
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Status estimateCameraParams();
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double registr_resol_;
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double seam_est_resol_;
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double compose_resol_;
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double conf_thresh_;
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Ptr<detail::FeaturesFinder> features_finder_;
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Ptr<detail::FeaturesMatcher> features_matcher_;
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cv::UMat matching_mask_;
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Ptr<detail::BundleAdjusterBase> bundle_adjuster_;
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/* TODO OpenCV ABI 4.x
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Ptr<detail::Estimator> estimator_;
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*/
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bool do_wave_correct_;
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detail::WaveCorrectKind wave_correct_kind_;
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Ptr<WarperCreator> warper_;
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Ptr<detail::ExposureCompensator> exposure_comp_;
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Ptr<detail::SeamFinder> seam_finder_;
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Ptr<detail::Blender> blender_;
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std::vector<cv::UMat> imgs_;
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std::vector<std::vector<cv::Rect> > rois_;
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std::vector<cv::Size> full_img_sizes_;
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std::vector<detail::ImageFeatures> features_;
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std::vector<detail::MatchesInfo> pairwise_matches_;
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std::vector<cv::UMat> seam_est_imgs_;
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std::vector<int> indices_;
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std::vector<detail::CameraParams> cameras_;
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double work_scale_;
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double seam_scale_;
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double seam_work_aspect_;
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double warped_image_scale_;
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};
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CV_EXPORTS_W Ptr<Stitcher> createStitcher(bool try_use_gpu = false);
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//! @} stitching
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} // namespace cv
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#endif // OPENCV_STITCHING_STITCHER_HPP
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