added first version of public stitching API, added simple sample which uses that API, old sample renamed to stitching_detailed
Alexey Spizhevoy
14 years ago
parent
1449dd1f02
commit
c9a41c6802
19 changed files with 1281 additions and 535 deletions
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/*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/core.hpp" |
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#include "opencv2/features2d/features2d.hpp" |
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#include "warpers.hpp" |
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#include "detail/matchers.hpp" |
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#include "detail/exposure_compensate.hpp" |
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#include "detail/seam_finders.hpp" |
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#include "detail/blenders.hpp" |
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namespace cv { |
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class Stitcher |
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{ |
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public: |
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enum { ORIG_RESOL = -1 }; |
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enum Status { OK, ERR_NEED_MORE_IMGS }; |
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// Creates stitcher with default parameters
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static Stitcher createDefault(bool try_use_gpu = false); |
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// Stitches the biggest found pano. Returns status code.
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Status stitch(InputArray imgs, OutputArray pano); |
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double registrationResol() const { return registr_resol_; } |
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void setRegistrationResol(double resol_mpx) { registr_resol_ = resol_mpx; } |
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double seamEstimationResol() const { return seam_est_resol_; } |
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void setSeamEstimationResol(double resol_mpx) { seam_est_resol_ = resol_mpx; } |
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double compositingResol() const { return compose_resol_; } |
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void setCompositingResol(double resol_mpx) { compose_resol_ = resol_mpx; } |
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double panoConfidenceThresh() const { return conf_thresh_; } |
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void setPanoConfidenceThresh(double conf_thresh) { conf_thresh_ = conf_thresh; } |
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bool horizontalStrightening() const { return horiz_stright_; } |
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void setHorizontalStrightening(bool flag) { horiz_stright_ = flag; } |
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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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Ptr<WarperCreator> warper() { return warper_; } |
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const Ptr<WarperCreator> warper() const { return warper_; } |
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void setWarper(Ptr<WarperCreator> warper) { warper_ = warper; } |
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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 setExposureCompenstor(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> blender) { blender_ = blender; } |
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private: |
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Stitcher() {} |
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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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bool horiz_stright_; |
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Ptr<detail::FeaturesFinder> features_finder_; |
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Ptr<detail::FeaturesMatcher> features_matcher_; |
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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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}; |
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} // namespace cv
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#endif // __OPENCV_STITCHING_STITCHER_HPP__
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@ -0,0 +1,105 @@ |
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/*M///////////////////////////////////////////////////////////////////////////////////////
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//
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
|
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//
|
||||
// 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
|
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// For Open Source Computer Vision Library
|
||||
//
|
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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.
|
||||
// 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.
|
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//
|
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// * The name of the copyright holders may not be used to endorse or promote products
|
||||
// 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
|
||||
// any express or implied warranties, including, but not limited to, the implied
|
||||
// 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,
|
||||
// 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
|
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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_WARPER_CREATORS_HPP__ |
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#define __OPENCV_STITCHING_WARPER_CREATORS_HPP__ |
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#include "detail/warpers.hpp" |
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namespace cv { |
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class WarperCreator |
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{ |
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public: |
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virtual ~WarperCreator() {} |
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virtual Ptr<detail::Warper> createByFocalLength(double f) const = 0; |
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}; |
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class PlaneWarper : public WarperCreator |
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{ |
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public: |
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Ptr<detail::Warper> createByFocalLength(double f) const { return new detail::PlaneWarper(f); } |
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}; |
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class CylindricalWarper: public WarperCreator |
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{ |
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public: |
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Ptr<detail::Warper> createByFocalLength(double f) const { return new detail::CylindricalWarper(f); } |
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}; |
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class SphericalWarper: public WarperCreator |
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{ |
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public: |
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Ptr<detail::Warper> createByFocalLength(double f) const { return new detail::SphericalWarper(f); } |
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}; |
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#ifndef ANDROID |
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class PlaneWarperGpu: public WarperCreator |
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{ |
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public: |
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Ptr<detail::Warper> createByFocalLength(double f) const { return new detail::PlaneWarperGpu(f); } |
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}; |
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class CylindricalWarperGpu: public WarperCreator |
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{ |
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public: |
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Ptr<detail::Warper> createByFocalLength(double f) const { return new detail::CylindricalWarperGpu(f); } |
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}; |
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class SphericalWarperGpu: public WarperCreator |
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{ |
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public: |
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Ptr<detail::Warper> createByFocalLength(double f) const { return new detail::SphericalWarperGpu(f); } |
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}; |
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#endif |
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} // namespace cv
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#endif // __OPENCV_STITCHING_WARPER_CREATORS_HPP__
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@ -0,0 +1,352 @@ |
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/*M///////////////////////////////////////////////////////////////////////////////////////
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//
|
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// 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
|
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// 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.
|
||||
//
|
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// Redistribution and use in source and binary forms, with or without modification,
|
||||
// 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,
|
||||
// this list of conditions and the following disclaimer.
|
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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.
|
||||
// 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;
|
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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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#include "precomp.hpp" |
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using namespace std; |
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namespace cv { |
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// TODO put all #ifndef ANDROID here, avoid passing try_use_gpu
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Stitcher Stitcher::createDefault(bool try_use_gpu) |
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{ |
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Stitcher stitcher; |
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stitcher.setRegistrationResol(0.6); |
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stitcher.setSeamEstimationResol(0.1); |
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stitcher.setCompositingResol(ORIG_RESOL); |
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stitcher.setPanoConfidenceThresh(1); |
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stitcher.setHorizontalStrightening(true); |
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stitcher.setFeaturesFinder(new detail::SurfFeaturesFinder(try_use_gpu)); |
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stitcher.setFeaturesMatcher(new detail::BestOf2NearestMatcher(try_use_gpu)); |
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#ifndef ANDROID |
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bool must_use_gpu = try_use_gpu && (gpu::getCudaEnabledDeviceCount() > 0); |
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stitcher.setWarper(must_use_gpu ? static_cast<WarperCreator*>(new SphericalWarperGpu()) : |
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static_cast<WarperCreator*>(new SphericalWarper())); |
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#else |
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stitcher.setWarper(new SphericalWarper()); |
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#endif |
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stitcher.setExposureCompenstor(new detail::BlocksGainCompensator()); |
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stitcher.setSeamFinder(new detail::GraphCutSeamFinder()); |
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stitcher.setBlender(new detail::MultiBandBlender(try_use_gpu)); |
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return stitcher; |
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} |
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Stitcher::Status Stitcher::stitch(InputArray imgs_, OutputArray pano_) |
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{ |
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// TODO split this func
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vector<Mat> imgs; |
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imgs_.getMatVector(imgs); |
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Mat &pano = pano_.getMatRef(); |
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int64 app_start_time = getTickCount(); |
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int num_imgs = static_cast<int>(imgs.size()); |
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if (num_imgs < 2) |
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{ |
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LOGLN("Need more images"); |
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return ERR_NEED_MORE_IMGS; |
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} |
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double work_scale = 1, seam_scale = 1, compose_scale = 1; |
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bool is_work_scale_set = false, is_seam_scale_set = false, is_compose_scale_set = false; |
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LOGLN("Finding features..."); |
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int64 t = getTickCount(); |
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vector<detail::ImageFeatures> features(num_imgs); |
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Mat full_img, img; |
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vector<Mat> seam_est_imgs(num_imgs); |
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vector<Size> full_img_sizes(num_imgs); |
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double seam_work_aspect = 1; |
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for (int i = 0; i < num_imgs; ++i) |
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{ |
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full_img = imgs[i]; |
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full_img_sizes[i] = full_img.size(); |
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if (registr_resol_ < 0) |
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{ |
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img = full_img; |
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work_scale = 1; |
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is_work_scale_set = true; |
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} |
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else |
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{ |
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if (!is_work_scale_set) |
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{ |
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work_scale = min(1.0, sqrt(registr_resol_ * 1e6 / full_img.size().area())); |
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is_work_scale_set = true; |
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} |
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resize(full_img, img, Size(), work_scale, work_scale); |
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} |
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if (!is_seam_scale_set) |
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{ |
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seam_scale = min(1.0, sqrt(seam_est_resol_ * 1e6 / full_img.size().area())); |
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seam_work_aspect = seam_scale / work_scale; |
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is_seam_scale_set = true; |
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} |
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(*features_finder_)(img, features[i]); |
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features[i].img_idx = i; |
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LOGLN("Features in image #" << i+1 << ": " << features[i].keypoints.size()); |
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resize(full_img, img, Size(), seam_scale, seam_scale); |
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seam_est_imgs[i] = img.clone(); |
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} |
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features_finder_->collectGarbage(); |
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full_img.release(); |
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img.release(); |
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LOGLN("Finding features, time: " << ((getTickCount() - t) / getTickFrequency()) << " sec"); |
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LOG("Pairwise matching"); |
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t = getTickCount(); |
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vector<detail::MatchesInfo> pairwise_matches; |
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(*features_matcher_)(features, pairwise_matches); |
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features_matcher_->collectGarbage(); |
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LOGLN("Pairwise matching, time: " << ((getTickCount() - t) / getTickFrequency()) << " sec"); |
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// Leave only images we are sure are from the same panorama
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vector<int> indices = detail::leaveBiggestComponent(features, pairwise_matches, conf_thresh_); |
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vector<Mat> seam_est_imgs_subset; |
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vector<Mat> imgs_subset; |
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vector<Size> full_img_sizes_subset; |
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for (size_t i = 0; i < indices.size(); ++i) |
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{ |
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imgs_subset.push_back(imgs[indices[i]]); |
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seam_est_imgs_subset.push_back(seam_est_imgs[indices[i]]); |
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full_img_sizes_subset.push_back(full_img_sizes[indices[i]]); |
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} |
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seam_est_imgs = seam_est_imgs_subset; |
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imgs = imgs_subset; |
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full_img_sizes = full_img_sizes_subset; |
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num_imgs = static_cast<int>(imgs.size()); |
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if (num_imgs < 2) |
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{ |
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LOGLN("Need more images"); |
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return ERR_NEED_MORE_IMGS; |
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} |
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vector<detail::CameraParams> cameras; |
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detail::HomographyBasedEstimator estimator; |
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estimator(features, pairwise_matches, cameras); |
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for (size_t i = 0; i < cameras.size(); ++i) |
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{ |
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Mat R; |
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cameras[i].R.convertTo(R, CV_32F); |
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cameras[i].R = R; |
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LOGLN("Initial focal length #" << indices[i]+1 << ": " << cameras[i].focal); |
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} |
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detail::BundleAdjuster adjuster(detail::BundleAdjuster::FOCAL_RAY_SPACE, conf_thresh_); |
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adjuster(features, pairwise_matches, cameras); |
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// Find median focal length
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vector<double> focals; |
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for (size_t i = 0; i < cameras.size(); ++i) |
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{ |
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LOGLN("Camera #" << indices[i]+1 << " focal length: " << cameras[i].focal); |
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focals.push_back(cameras[i].focal); |
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} |
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nth_element(focals.begin(), focals.begin() + focals.size()/2, focals.end()); |
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float warped_image_scale = static_cast<float>(focals[focals.size() / 2]); |
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if (horiz_stright_) |
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{ |
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vector<Mat> rmats; |
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for (size_t i = 0; i < cameras.size(); ++i) |
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rmats.push_back(cameras[i].R); |
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detail::waveCorrect(rmats); |
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for (size_t i = 0; i < cameras.size(); ++i) |
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cameras[i].R = rmats[i]; |
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} |
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LOGLN("Warping images (auxiliary)... "); |
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t = getTickCount(); |
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vector<Point> corners(num_imgs); |
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vector<Mat> masks_warped(num_imgs); |
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vector<Mat> images_warped(num_imgs); |
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vector<Size> sizes(num_imgs); |
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vector<Mat> masks(num_imgs); |
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// Preapre images masks
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for (int i = 0; i < num_imgs; ++i) |
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{ |
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masks[i].create(seam_est_imgs[i].size(), CV_8U); |
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masks[i].setTo(Scalar::all(255)); |
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} |
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// Warp images and their masks
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Ptr<detail::Warper> warper = warper_->createByFocalLength(warped_image_scale * seam_work_aspect); |
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for (int i = 0; i < num_imgs; ++i) |
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{ |
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corners[i] = warper->warp(seam_est_imgs[i], static_cast<float>(cameras[i].focal * seam_work_aspect), |
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cameras[i].R, images_warped[i]); |
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sizes[i] = images_warped[i].size(); |
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warper->warp(masks[i], static_cast<float>(cameras[i].focal * seam_work_aspect), |
||||
cameras[i].R, masks_warped[i], INTER_NEAREST, BORDER_CONSTANT); |
||||
} |
||||
|
||||
vector<Mat> images_warped_f(num_imgs); |
||||
for (int i = 0; i < num_imgs; ++i) |
||||
images_warped[i].convertTo(images_warped_f[i], CV_32F); |
||||
|
||||
LOGLN("Warping images, time: " << ((getTickCount() - t) / getTickFrequency()) << " sec"); |
||||
|
||||
exposure_comp_->feed(corners, images_warped, masks_warped); |
||||
seam_finder_->find(images_warped_f, corners, masks_warped); |
||||
|
||||
// Release unused memory
|
||||
seam_est_imgs.clear(); |
||||
images_warped.clear(); |
||||
images_warped_f.clear(); |
||||
masks.clear(); |
||||
|
||||
LOGLN("Compositing..."); |
||||
t = getTickCount(); |
||||
|
||||
Mat img_warped, img_warped_s; |
||||
Mat dilated_mask, seam_mask, mask, mask_warped; |
||||
double compose_seam_aspect = 1; |
||||
double compose_work_aspect = 1; |
||||
bool is_blender_prepared = false; |
||||
|
||||
for (int img_idx = 0; img_idx < num_imgs; ++img_idx) |
||||
{ |
||||
LOGLN("Compositing image #" << indices[img_idx]+1); |
||||
|
||||
// Read image and resize it if necessary
|
||||
full_img = imgs[img_idx]; |
||||
if (!is_compose_scale_set) |
||||
{ |
||||
if (compose_resol_ > 0) |
||||
compose_scale = min(1.0, sqrt(compose_resol_ * 1e6 / full_img.size().area())); |
||||
is_compose_scale_set = true; |
||||
|
||||
// Compute relative scales
|
||||
compose_seam_aspect = compose_scale / seam_scale; |
||||
compose_work_aspect = compose_scale / work_scale; |
||||
|
||||
// Update warped image scale
|
||||
warped_image_scale *= static_cast<float>(compose_work_aspect); |
||||
warper = warper_->createByFocalLength(warped_image_scale); |
||||
|
||||
// Update corners and sizes
|
||||
for (int i = 0; i < num_imgs; ++i) |
||||
{ |
||||
// Update camera focal
|
||||
cameras[i].focal *= compose_work_aspect; |
||||
|
||||
// Update corner and size
|
||||
Size sz = full_img_sizes[i]; |
||||
if (std::abs(compose_scale - 1) > 1e-1) |
||||
{ |
||||
sz.width = cvRound(full_img_sizes[i].width * compose_scale); |
||||
sz.height = cvRound(full_img_sizes[i].height * compose_scale); |
||||
} |
||||
|
||||
Rect roi = warper->warpRoi(sz, static_cast<float>(cameras[i].focal), cameras[i].R); |
||||
corners[i] = roi.tl(); |
||||
sizes[i] = roi.size(); |
||||
} |
||||
} |
||||
if (std::abs(compose_scale - 1) > 1e-1) |
||||
resize(full_img, img, Size(), compose_scale, compose_scale); |
||||
else |
||||
img = full_img; |
||||
full_img.release(); |
||||
Size img_size = img.size(); |
||||
|
||||
// Warp the current image
|
||||
warper->warp(img, static_cast<float>(cameras[img_idx].focal), cameras[img_idx].R, |
||||
img_warped); |
||||
|
||||
// Warp the current image mask
|
||||
mask.create(img_size, CV_8U); |
||||
mask.setTo(Scalar::all(255)); |
||||
warper->warp(mask, static_cast<float>(cameras[img_idx].focal), cameras[img_idx].R, mask_warped, |
||||
INTER_NEAREST, BORDER_CONSTANT); |
||||
|
||||
// Compensate exposure
|
||||
exposure_comp_->apply(img_idx, corners[img_idx], img_warped, mask_warped); |
||||
|
||||
img_warped.convertTo(img_warped_s, CV_16S); |
||||
img_warped.release(); |
||||
img.release(); |
||||
mask.release(); |
||||
|
||||
dilate(masks_warped[img_idx], dilated_mask, Mat()); |
||||
resize(dilated_mask, seam_mask, mask_warped.size()); |
||||
mask_warped = seam_mask & mask_warped; |
||||
|
||||
if (!is_blender_prepared) |
||||
{ |
||||
blender_->prepare(corners, sizes); |
||||
is_blender_prepared = true; |
||||
} |
||||
|
||||
// Blend the current image
|
||||
blender_->feed(img_warped_s, mask_warped, corners[img_idx]); |
||||
} |
||||
|
||||
Mat result, result_mask; |
||||
blender_->blend(result, result_mask); |
||||
|
||||
LOGLN("Compositing, time: " << ((getTickCount() - t) / getTickFrequency()) << " sec"); |
||||
|
||||
// Preliminary result is in CV_16SC3 format, but all values are in [0,255] range,
|
||||
// so convert it to avoid user confusing
|
||||
result.convertTo(pano, CV_8U); |
||||
|
||||
LOGLN("Finished, total time: " << ((getTickCount() - app_start_time) / getTickFrequency()) << " sec"); |
||||
|
||||
return OK; |
||||
} |
||||
|
||||
} // namespace cv
|
||||
@ -0,0 +1,627 @@ |
||||
/*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*/
|
||||
|
||||
// We follow to these papers:
|
||||
// 1) Construction of panoramic mosaics with global and local alignment.
|
||||
// Heung-Yeung Shum and Richard Szeliski. 2000.
|
||||
// 2) Eliminating Ghosting and Exposure Artifacts in Image Mosaics.
|
||||
// Matthew Uyttendaele, Ashley Eden and Richard Szeliski. 2001.
|
||||
// 3) Automatic Panoramic Image Stitching using Invariant Features.
|
||||
// Matthew Brown and David G. Lowe. 2007.
|
||||
|
||||
#include <fstream> |
||||
#include "opencv2/highgui/highgui.hpp" |
||||
#include "opencv2/stitching/detail/autocalib.hpp" |
||||
#include "opencv2/stitching/detail/blenders.hpp" |
||||
#include "opencv2/stitching/detail/camera.hpp" |
||||
#include "opencv2/stitching/detail/exposure_compensate.hpp" |
||||
#include "opencv2/stitching/detail/matchers.hpp" |
||||
#include "opencv2/stitching/detail/motion_estimators.hpp" |
||||
#include "opencv2/stitching/detail/seam_finders.hpp" |
||||
#include "opencv2/stitching/detail/util.hpp" |
||||
#include "opencv2/stitching/detail/warpers.hpp" |
||||
|
||||
using namespace std; |
||||
using namespace cv; |
||||
using namespace cv::detail; |
||||
|
||||
void printUsage() |
||||
{ |
||||
cout << |
||||
"Rotation model images stitcher.\n\n" |
||||
"stitching_detailed img1 img2 [...imgN] [flags]\n\n" |
||||
"Flags:\n" |
||||
" --preview\n" |
||||
" Run stitching in the preview mode. Works faster than usual mode,\n" |
||||
" but output image will have lower resolution.\n" |
||||
" --try_gpu (yes|no)\n" |
||||
" Try to use GPU. The default value is 'no'. All default values\n" |
||||
" are for CPU mode.\n" |
||||
"\nMotion Estimation Flags:\n" |
||||
" --work_megapix <float>\n" |
||||
" Resolution for image registration step. The default is 0.6 Mpx.\n" |
||||
" --match_conf <float>\n" |
||||
" Confidence for feature matching step. The default is 0.65.\n" |
||||
" --conf_thresh <float>\n" |
||||
" Threshold for two images are from the same panorama confidence.\n" |
||||
" The default is 1.0.\n" |
||||
" --ba (no|ray|focal_ray)\n" |
||||
" Bundle adjustment cost function. The default is 'focal_ray'.\n" |
||||
" --wave_correct (no|yes)\n" |
||||
" Perform wave effect correction. The default is 'yes'.\n" |
||||
" --save_graph <file_name>\n" |
||||
" Save matches graph represented in DOT language to <file_name> file.\n" |
||||
" Labels description: Nm is number of matches, Ni is number of inliers,\n" |
||||
" C is confidence.\n" |
||||
"\nCompositing Flags:\n" |
||||
" --warp (plane|cylindrical|spherical)\n" |
||||
" Warp surface type. The default is 'spherical'.\n" |
||||
" --seam_megapix <float>\n" |
||||
" Resolution for seam estimation step. The default is 0.1 Mpx.\n" |
||||
" --seam (no|voronoi|gc_color|gc_colorgrad)\n" |
||||
" Seam estimation method. The default is 'gc_color'.\n" |
||||
" --compose_megapix <float>\n" |
||||
" Resolution for compositing step. Use -1 for original resolution.\n" |
||||
" The default is -1.\n" |
||||
" --expos_comp (no|gain|gain_blocks)\n" |
||||
" Exposure compensation method. The default is 'gain_blocks'.\n" |
||||
" --blend (no|feather|multiband)\n" |
||||
" Blending method. The default is 'multiband'.\n" |
||||
" --blend_strength <float>\n" |
||||
" Blending strength from [0,100] range. The default is 5.\n" |
||||
" --output <result_img>\n" |
||||
" The default is 'result.jpg'.\n"; |
||||
} |
||||
|
||||
|
||||
// Default command line args
|
||||
vector<string> img_names; |
||||
bool preview = false; |
||||
bool try_gpu = false; |
||||
double work_megapix = 0.6; |
||||
double seam_megapix = 0.1; |
||||
double compose_megapix = -1; |
||||
int ba_space = BundleAdjuster::FOCAL_RAY_SPACE; |
||||
float conf_thresh = 1.f; |
||||
bool wave_correct = true; |
||||
bool save_graph = false; |
||||
std::string save_graph_to; |
||||
int warp_type = Warper::SPHERICAL; |
||||
int expos_comp_type = ExposureCompensator::GAIN_BLOCKS; |
||||
float match_conf = 0.65f; |
||||
int seam_find_type = SeamFinder::GC_COLOR; |
||||
int blend_type = Blender::MULTI_BAND; |
||||
float blend_strength = 5; |
||||
string result_name = "result.jpg"; |
||||
|
||||
int parseCmdArgs(int argc, char** argv) |
||||
{ |
||||
if (argc == 1) |
||||
{ |
||||
printUsage(); |
||||
return -1; |
||||
} |
||||
for (int i = 1; i < argc; ++i) |
||||
{ |
||||
if (string(argv[i]) == "--help" || string(argv[i]) == "/?") |
||||
{ |
||||
printUsage(); |
||||
return -1; |
||||
} |
||||
else if (string(argv[i]) == "--preview") |
||||
{ |
||||
preview = true; |
||||
} |
||||
else if (string(argv[i]) == "--try_gpu") |
||||
{ |
||||
if (string(argv[i + 1]) == "no") |
||||
try_gpu = false; |
||||
else if (string(argv[i + 1]) == "yes") |
||||
try_gpu = true; |
||||
else |
||||
{ |
||||
cout << "Bad --try_gpu flag value\n"; |
||||
return -1; |
||||
} |
||||
i++; |
||||
} |
||||
else if (string(argv[i]) == "--work_megapix") |
||||
{ |
||||
work_megapix = atof(argv[i + 1]); |
||||
i++; |
||||
} |
||||
else if (string(argv[i]) == "--seam_megapix") |
||||
{ |
||||
seam_megapix = atof(argv[i + 1]); |
||||
i++; |
||||
} |
||||
else if (string(argv[i]) == "--compose_megapix") |
||||
{ |
||||
compose_megapix = atof(argv[i + 1]); |
||||
i++; |
||||
} |
||||
else if (string(argv[i]) == "--result") |
||||
{ |
||||
result_name = argv[i + 1]; |
||||
i++; |
||||
} |
||||
else if (string(argv[i]) == "--match_conf") |
||||
{ |
||||
match_conf = static_cast<float>(atof(argv[i + 1])); |
||||
i++; |
||||
} |
||||
else if (string(argv[i]) == "--ba") |
||||
{ |
||||
if (string(argv[i + 1]) == "no") |
||||
ba_space = BundleAdjuster::NO; |
||||
else if (string(argv[i + 1]) == "ray") |
||||
ba_space = BundleAdjuster::RAY_SPACE; |
||||
else if (string(argv[i + 1]) == "focal_ray") |
||||
ba_space = BundleAdjuster::FOCAL_RAY_SPACE; |
||||
else |
||||
{ |
||||
cout << "Bad bundle adjustment space\n"; |
||||
return -1; |
||||
} |
||||
i++; |
||||
} |
||||
else if (string(argv[i]) == "--conf_thresh") |
||||
{ |
||||
conf_thresh = static_cast<float>(atof(argv[i + 1])); |
||||
i++; |
||||
} |
||||
else if (string(argv[i]) == "--wave_correct") |
||||
{ |
||||
if (string(argv[i + 1]) == "no") |
||||
wave_correct = false; |
||||
else if (string(argv[i + 1]) == "yes") |
||||
wave_correct = true; |
||||
else |
||||
{ |
||||
cout << "Bad --wave_correct flag value\n"; |
||||
return -1; |
||||
} |
||||
i++; |
||||
} |
||||
else if (string(argv[i]) == "--save_graph") |
||||
{ |
||||
save_graph = true; |
||||
save_graph_to = argv[i + 1]; |
||||
i++; |
||||
} |
||||
else if (string(argv[i]) == "--warp") |
||||
{ |
||||
if (string(argv[i + 1]) == "plane") |
||||
warp_type = Warper::PLANE; |
||||
else if (string(argv[i + 1]) == "cylindrical") |
||||
warp_type = Warper::CYLINDRICAL; |
||||
else if (string(argv[i + 1]) == "spherical") |
||||
warp_type = Warper::SPHERICAL; |
||||
else |
||||
{ |
||||
cout << "Bad warping method\n"; |
||||
return -1; |
||||
} |
||||
i++; |
||||
} |
||||
else if (string(argv[i]) == "--expos_comp") |
||||
{ |
||||
if (string(argv[i + 1]) == "no") |
||||
expos_comp_type = ExposureCompensator::NO; |
||||
else if (string(argv[i + 1]) == "gain") |
||||
expos_comp_type = ExposureCompensator::GAIN; |
||||
else if (string(argv[i + 1]) == "gain_blocks") |
||||
expos_comp_type = ExposureCompensator::GAIN_BLOCKS; |
||||
else |
||||
{ |
||||
cout << "Bad exposure compensation method\n"; |
||||
return -1; |
||||
} |
||||
i++; |
||||
} |
||||
else if (string(argv[i]) == "--seam") |
||||
{ |
||||
if (string(argv[i + 1]) == "no") |
||||
seam_find_type = SeamFinder::NO; |
||||
else if (string(argv[i + 1]) == "voronoi") |
||||
seam_find_type = SeamFinder::VORONOI; |
||||
else if (string(argv[i + 1]) == "gc_color") |
||||
seam_find_type = SeamFinder::GC_COLOR; |
||||
else if (string(argv[i + 1]) == "gc_colorgrad") |
||||
seam_find_type = SeamFinder::GC_COLOR_GRAD; |
||||
else |
||||
{ |
||||
cout << "Bad seam finding method\n"; |
||||
return -1; |
||||
} |
||||
i++; |
||||
} |
||||
else if (string(argv[i]) == "--blend") |
||||
{ |
||||
if (string(argv[i + 1]) == "no") |
||||
blend_type = Blender::NO; |
||||
else if (string(argv[i + 1]) == "feather") |
||||
blend_type = Blender::FEATHER; |
||||
else if (string(argv[i + 1]) == "multiband") |
||||
blend_type = Blender::MULTI_BAND; |
||||
else |
||||
{ |
||||
cout << "Bad blending method\n"; |
||||
return -1; |
||||
} |
||||
i++; |
||||
} |
||||
else if (string(argv[i]) == "--blend_strength") |
||||
{ |
||||
blend_strength = static_cast<float>(atof(argv[i + 1])); |
||||
i++; |
||||
} |
||||
else if (string(argv[i]) == "--output") |
||||
{ |
||||
result_name = argv[i + 1]; |
||||
i++; |
||||
} |
||||
else |
||||
img_names.push_back(argv[i]); |
||||
} |
||||
if (preview) |
||||
{ |
||||
compose_megapix = 0.6; |
||||
} |
||||
return 0; |
||||
} |
||||
|
||||
|
||||
int main(int argc, char* argv[]) |
||||
{ |
||||
int64 app_start_time = getTickCount(); |
||||
cv::setBreakOnError(true); |
||||
|
||||
int retval = parseCmdArgs(argc, argv); |
||||
if (retval) |
||||
return retval; |
||||
|
||||
// Check if have enough images
|
||||
int num_images = static_cast<int>(img_names.size()); |
||||
if (num_images < 2) |
||||
{ |
||||
LOGLN("Need more images"); |
||||
return -1; |
||||
} |
||||
|
||||
double work_scale = 1, seam_scale = 1, compose_scale = 1; |
||||
bool is_work_scale_set = false, is_seam_scale_set = false, is_compose_scale_set = false; |
||||
|
||||
LOGLN("Finding features..."); |
||||
int64 t = getTickCount(); |
||||
|
||||
vector<ImageFeatures> features(num_images); |
||||
SurfFeaturesFinder finder(try_gpu); |
||||
Mat full_img, img; |
||||
|
||||
vector<Mat> images(num_images); |
||||
vector<Size> full_img_sizes(num_images); |
||||
double seam_work_aspect = 1; |
||||
|
||||
for (int i = 0; i < num_images; ++i) |
||||
{ |
||||
full_img = imread(img_names[i]); |
||||
full_img_sizes[i] = full_img.size(); |
||||
|
||||
if (full_img.empty()) |
||||
{ |
||||
LOGLN("Can't open image " << img_names[i]); |
||||
return -1; |
||||
} |
||||
if (work_megapix < 0) |
||||
{ |
||||
img = full_img; |
||||
work_scale = 1; |
||||
is_work_scale_set = true; |
||||
} |
||||
else |
||||
{ |
||||
if (!is_work_scale_set) |
||||
{ |
||||
work_scale = min(1.0, sqrt(work_megapix * 1e6 / full_img.size().area())); |
||||
is_work_scale_set = true; |
||||
} |
||||
resize(full_img, img, Size(), work_scale, work_scale); |
||||
} |
||||
if (!is_seam_scale_set) |
||||
{ |
||||
seam_scale = min(1.0, sqrt(seam_megapix * 1e6 / full_img.size().area())); |
||||
seam_work_aspect = seam_scale / work_scale; |
||||
is_seam_scale_set = true; |
||||
} |
||||
|
||||
finder(img, features[i]); |
||||
features[i].img_idx = i; |
||||
LOGLN("Features in image #" << i+1 << ": " << features[i].keypoints.size()); |
||||
|
||||
resize(full_img, img, Size(), seam_scale, seam_scale); |
||||
images[i] = img.clone(); |
||||
} |
||||
|
||||
finder.collectGarbage(); |
||||
|
||||
full_img.release(); |
||||
img.release(); |
||||
|
||||
LOGLN("Finding features, time: " << ((getTickCount() - t) / getTickFrequency()) << " sec"); |
||||
|
||||
LOG("Pairwise matching"); |
||||
t = getTickCount(); |
||||
vector<MatchesInfo> pairwise_matches; |
||||
BestOf2NearestMatcher matcher(try_gpu, match_conf); |
||||
matcher(features, pairwise_matches); |
||||
matcher.collectGarbage(); |
||||
LOGLN("Pairwise matching, time: " << ((getTickCount() - t) / getTickFrequency()) << " sec"); |
||||
|
||||
// Check if we should save matches graph
|
||||
if (save_graph) |
||||
{ |
||||
LOGLN("Saving matches graph..."); |
||||
ofstream f(save_graph_to.c_str()); |
||||
f << matchesGraphAsString(img_names, pairwise_matches, conf_thresh); |
||||
} |
||||
|
||||
// Leave only images we are sure are from the same panorama
|
||||
vector<int> indices = leaveBiggestComponent(features, pairwise_matches, conf_thresh); |
||||
vector<Mat> img_subset; |
||||
vector<string> img_names_subset; |
||||
vector<Size> full_img_sizes_subset; |
||||
for (size_t i = 0; i < indices.size(); ++i) |
||||
{ |
||||
img_names_subset.push_back(img_names[indices[i]]); |
||||
img_subset.push_back(images[indices[i]]); |
||||
full_img_sizes_subset.push_back(full_img_sizes[indices[i]]); |
||||
} |
||||
|
||||
images = img_subset; |
||||
img_names = img_names_subset; |
||||
full_img_sizes = full_img_sizes_subset; |
||||
|
||||
// Check if we still have enough images
|
||||
num_images = static_cast<int>(img_names.size()); |
||||
if (num_images < 2) |
||||
{ |
||||
LOGLN("Need more images"); |
||||
return -1; |
||||
} |
||||
|
||||
HomographyBasedEstimator estimator; |
||||
vector<CameraParams> cameras; |
||||
estimator(features, pairwise_matches, cameras); |
||||
|
||||
for (size_t i = 0; i < cameras.size(); ++i) |
||||
{ |
||||
Mat R; |
||||
cameras[i].R.convertTo(R, CV_32F); |
||||
cameras[i].R = R; |
||||
LOGLN("Initial focal length #" << indices[i]+1 << ": " << cameras[i].focal); |
||||
} |
||||
|
||||
BundleAdjuster adjuster(ba_space, conf_thresh); |
||||
adjuster(features, pairwise_matches, cameras); |
||||
|
||||
// Find median focal length
|
||||
vector<double> focals; |
||||
for (size_t i = 0; i < cameras.size(); ++i) |
||||
{ |
||||
LOGLN("Camera #" << indices[i]+1 << " focal length: " << cameras[i].focal); |
||||
focals.push_back(cameras[i].focal); |
||||
} |
||||
nth_element(focals.begin(), focals.begin() + focals.size()/2, focals.end()); |
||||
float warped_image_scale = static_cast<float>(focals[focals.size() / 2]); |
||||
|
||||
if (wave_correct) |
||||
{ |
||||
vector<Mat> rmats; |
||||
for (size_t i = 0; i < cameras.size(); ++i) |
||||
rmats.push_back(cameras[i].R); |
||||
waveCorrect(rmats); |
||||
for (size_t i = 0; i < cameras.size(); ++i) |
||||
cameras[i].R = rmats[i]; |
||||
} |
||||
|
||||
LOGLN("Warping images (auxiliary)... "); |
||||
t = getTickCount(); |
||||
|
||||
vector<Point> corners(num_images); |
||||
vector<Mat> masks_warped(num_images); |
||||
vector<Mat> images_warped(num_images); |
||||
vector<Size> sizes(num_images); |
||||
vector<Mat> masks(num_images); |
||||
|
||||
// Preapre images masks
|
||||
for (int i = 0; i < num_images; ++i) |
||||
{ |
||||
masks[i].create(images[i].size(), CV_8U); |
||||
masks[i].setTo(Scalar::all(255)); |
||||
} |
||||
|
||||
// Warp images and their masks
|
||||
Ptr<Warper> warper = Warper::createByCameraFocal(static_cast<float>(warped_image_scale * seam_work_aspect), |
||||
warp_type, try_gpu); |
||||
for (int i = 0; i < num_images; ++i) |
||||
{ |
||||
corners[i] = warper->warp(images[i], static_cast<float>(cameras[i].focal * seam_work_aspect), |
||||
cameras[i].R, images_warped[i]); |
||||
sizes[i] = images_warped[i].size(); |
||||
warper->warp(masks[i], static_cast<float>(cameras[i].focal * seam_work_aspect), |
||||
cameras[i].R, masks_warped[i], INTER_NEAREST, BORDER_CONSTANT); |
||||
} |
||||
|
||||
vector<Mat> images_warped_f(num_images); |
||||
for (int i = 0; i < num_images; ++i) |
||||
images_warped[i].convertTo(images_warped_f[i], CV_32F); |
||||
|
||||
LOGLN("Warping images, time: " << ((getTickCount() - t) / getTickFrequency()) << " sec"); |
||||
|
||||
Ptr<ExposureCompensator> compensator = ExposureCompensator::createDefault(expos_comp_type); |
||||
compensator->feed(corners, images_warped, masks_warped); |
||||
|
||||
Ptr<SeamFinder> seam_finder = SeamFinder::createDefault(seam_find_type); |
||||
seam_finder->find(images_warped_f, corners, masks_warped); |
||||
|
||||
// Release unused memory
|
||||
images.clear(); |
||||
images_warped.clear(); |
||||
images_warped_f.clear(); |
||||
masks.clear(); |
||||
|
||||
LOGLN("Compositing..."); |
||||
t = getTickCount(); |
||||
|
||||
Mat img_warped, img_warped_s; |
||||
Mat dilated_mask, seam_mask, mask, mask_warped; |
||||
Ptr<Blender> blender; |
||||
double compose_seam_aspect = 1; |
||||
double compose_work_aspect = 1; |
||||
|
||||
for (int img_idx = 0; img_idx < num_images; ++img_idx) |
||||
{ |
||||
LOGLN("Compositing image #" << indices[img_idx]+1); |
||||
|
||||
// Read image and resize it if necessary
|
||||
full_img = imread(img_names[img_idx]); |
||||
if (!is_compose_scale_set) |
||||
{ |
||||
if (compose_megapix > 0) |
||||
compose_scale = min(1.0, sqrt(compose_megapix * 1e6 / full_img.size().area())); |
||||
is_compose_scale_set = true; |
||||
|
||||
// Compute relative scales
|
||||
compose_seam_aspect = compose_scale / seam_scale; |
||||
compose_work_aspect = compose_scale / work_scale; |
||||
|
||||
// Update warped image scale
|
||||
warped_image_scale *= static_cast<float>(compose_work_aspect); |
||||
warper = Warper::createByCameraFocal(warped_image_scale, warp_type, try_gpu); |
||||
|
||||
// Update corners and sizes
|
||||
for (int i = 0; i < num_images; ++i) |
||||
{ |
||||
// Update camera focal
|
||||
cameras[i].focal *= compose_work_aspect; |
||||
|
||||
// Update corner and size
|
||||
Size sz = full_img_sizes[i]; |
||||
if (abs(compose_scale - 1) > 1e-1) |
||||
{ |
||||
sz.width = cvRound(full_img_sizes[i].width * compose_scale); |
||||
sz.height = cvRound(full_img_sizes[i].height * compose_scale); |
||||
} |
||||
|
||||
Rect roi = warper->warpRoi(sz, static_cast<float>(cameras[i].focal), cameras[i].R); |
||||
corners[i] = roi.tl(); |
||||
sizes[i] = roi.size(); |
||||
} |
||||
} |
||||
if (abs(compose_scale - 1) > 1e-1) |
||||
resize(full_img, img, Size(), compose_scale, compose_scale); |
||||
else |
||||
img = full_img; |
||||
full_img.release(); |
||||
Size img_size = img.size(); |
||||
|
||||
// Warp the current image
|
||||
warper->warp(img, static_cast<float>(cameras[img_idx].focal), cameras[img_idx].R, |
||||
img_warped); |
||||
|
||||
// Warp the current image mask
|
||||
mask.create(img_size, CV_8U); |
||||
mask.setTo(Scalar::all(255)); |
||||
warper->warp(mask, static_cast<float>(cameras[img_idx].focal), cameras[img_idx].R, mask_warped, |
||||
INTER_NEAREST, BORDER_CONSTANT); |
||||
|
||||
// Compensate exposure
|
||||
compensator->apply(img_idx, corners[img_idx], img_warped, mask_warped); |
||||
|
||||
img_warped.convertTo(img_warped_s, CV_16S); |
||||
img_warped.release(); |
||||
img.release(); |
||||
mask.release(); |
||||
|
||||
dilate(masks_warped[img_idx], dilated_mask, Mat()); |
||||
resize(dilated_mask, seam_mask, mask_warped.size()); |
||||
mask_warped = seam_mask & mask_warped; |
||||
|
||||
if (blender.empty()) |
||||
{ |
||||
blender = Blender::createDefault(blend_type, try_gpu); |
||||
Size dst_sz = resultRoi(corners, sizes).size(); |
||||
float blend_width = sqrt(static_cast<float>(dst_sz.area())) * blend_strength / 100.f; |
||||
if (blend_width < 1.f) |
||||
blender = Blender::createDefault(Blender::NO, try_gpu); |
||||
else if (blend_type == Blender::MULTI_BAND) |
||||
{ |
||||
MultiBandBlender* mb = dynamic_cast<MultiBandBlender*>(static_cast<Blender*>(blender)); |
||||
mb->setNumBands(static_cast<int>(ceil(log(blend_width)/log(2.)) - 1.)); |
||||
LOGLN("Multi-band blender, number of bands: " << mb->numBands()); |
||||
} |
||||
else if (blend_type == Blender::FEATHER) |
||||
{ |
||||
FeatherBlender* fb = dynamic_cast<FeatherBlender*>(static_cast<Blender*>(blender)); |
||||
fb->setSharpness(1.f/blend_width); |
||||
LOGLN("Feather blender, sharpness: " << fb->sharpness()); |
||||
} |
||||
blender->prepare(corners, sizes); |
||||
} |
||||
|
||||
// Blend the current image
|
||||
blender->feed(img_warped_s, mask_warped, corners[img_idx]); |
||||
} |
||||
|
||||
Mat result, result_mask; |
||||
blender->blend(result, result_mask); |
||||
|
||||
LOGLN("Compositing, time: " << ((getTickCount() - t) / getTickFrequency()) << " sec"); |
||||
|
||||
imwrite(result_name, result); |
||||
|
||||
LOGLN("Finished, total time: " << ((getTickCount() - app_start_time) / getTickFrequency()) << " sec"); |
||||
return 0; |
||||
} |
||||
|
||||
|
||||
Loading…
Reference in new issue