Normalize line endings and whitespace

This commit is contained in:
OpenCV Buildbot
2012-10-17 11:12:04 +04:00
committed by Andrey Kamaev
parent 0442bca235
commit 81f826db2b
1511 changed files with 258678 additions and 258624 deletions

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifndef __OPENCV_STITCHING_AUTOCALIB_HPP__
#define __OPENCV_STITCHING_AUTOCALIB_HPP__
#include "opencv2/core/core.hpp"
#include "matchers.hpp"
namespace cv {
namespace detail {
// See "Construction of Panoramic Image Mosaics with Global and Local Alignment"
// by Heung-Yeung Shum and Richard Szeliski.
void CV_EXPORTS focalsFromHomography(const Mat &H, double &f0, double &f1, bool &f0_ok, bool &f1_ok);
void CV_EXPORTS estimateFocal(const std::vector<ImageFeatures> &features,
const std::vector<MatchesInfo> &pairwise_matches,
std::vector<double> &focals);
bool CV_EXPORTS calibrateRotatingCamera(const std::vector<Mat> &Hs, Mat &K);
} // namespace detail
} // namespace cv
#endif // __OPENCV_STITCHING_AUTOCALIB_HPP__
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifndef __OPENCV_STITCHING_AUTOCALIB_HPP__
#define __OPENCV_STITCHING_AUTOCALIB_HPP__
#include "opencv2/core/core.hpp"
#include "matchers.hpp"
namespace cv {
namespace detail {
// See "Construction of Panoramic Image Mosaics with Global and Local Alignment"
// by Heung-Yeung Shum and Richard Szeliski.
void CV_EXPORTS focalsFromHomography(const Mat &H, double &f0, double &f1, bool &f0_ok, bool &f1_ok);
void CV_EXPORTS estimateFocal(const std::vector<ImageFeatures> &features,
const std::vector<MatchesInfo> &pairwise_matches,
std::vector<double> &focals);
bool CV_EXPORTS calibrateRotatingCamera(const std::vector<Mat> &Hs, Mat &K);
} // namespace detail
} // namespace cv
#endif // __OPENCV_STITCHING_AUTOCALIB_HPP__

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifndef __OPENCV_STITCHING_BLENDERS_HPP__
#define __OPENCV_STITCHING_BLENDERS_HPP__
#include "opencv2/core/core.hpp"
namespace cv {
namespace detail {
// Simple blender which puts one image over another
class CV_EXPORTS Blender
{
public:
virtual ~Blender() {}
enum { NO, FEATHER, MULTI_BAND };
static Ptr<Blender> createDefault(int type, bool try_gpu = false);
void prepare(const std::vector<Point> &corners, const std::vector<Size> &sizes);
virtual void prepare(Rect dst_roi);
virtual void feed(const Mat &img, const Mat &mask, Point tl);
virtual void blend(Mat &dst, Mat &dst_mask);
protected:
Mat dst_, dst_mask_;
Rect dst_roi_;
};
class CV_EXPORTS FeatherBlender : public Blender
{
public:
FeatherBlender(float sharpness = 0.02f);
float sharpness() const { return sharpness_; }
void setSharpness(float val) { sharpness_ = val; }
void prepare(Rect dst_roi);
void feed(const Mat &img, const Mat &mask, Point tl);
void blend(Mat &dst, Mat &dst_mask);
// Creates weight maps for fixed set of source images by their masks and top-left corners.
// Final image can be obtained by simple weighting of the source images.
Rect createWeightMaps(const std::vector<Mat> &masks, const std::vector<Point> &corners,
std::vector<Mat> &weight_maps);
private:
float sharpness_;
Mat weight_map_;
Mat dst_weight_map_;
};
inline FeatherBlender::FeatherBlender(float _sharpness) { setSharpness(_sharpness); }
class CV_EXPORTS MultiBandBlender : public Blender
{
public:
MultiBandBlender(int try_gpu = false, int num_bands = 5, int weight_type = CV_32F);
int numBands() const { return actual_num_bands_; }
void setNumBands(int val) { actual_num_bands_ = val; }
void prepare(Rect dst_roi);
void feed(const Mat &img, const Mat &mask, Point tl);
void blend(Mat &dst, Mat &dst_mask);
private:
int actual_num_bands_, num_bands_;
std::vector<Mat> dst_pyr_laplace_;
std::vector<Mat> dst_band_weights_;
Rect dst_roi_final_;
bool can_use_gpu_;
int weight_type_; //CV_32F or CV_16S
};
//////////////////////////////////////////////////////////////////////////////
// Auxiliary functions
void CV_EXPORTS normalizeUsingWeightMap(const Mat& weight, Mat& src);
void CV_EXPORTS createWeightMap(const Mat& mask, float sharpness, Mat& weight);
void CV_EXPORTS createLaplacePyr(const Mat &img, int num_levels, std::vector<Mat>& pyr);
void CV_EXPORTS createLaplacePyrGpu(const Mat &img, int num_levels, std::vector<Mat>& pyr);
// Restores source image
void CV_EXPORTS restoreImageFromLaplacePyr(std::vector<Mat>& pyr);
void CV_EXPORTS restoreImageFromLaplacePyrGpu(std::vector<Mat>& pyr);
} // namespace detail
} // namespace cv
#endif // __OPENCV_STITCHING_BLENDERS_HPP__
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifndef __OPENCV_STITCHING_BLENDERS_HPP__
#define __OPENCV_STITCHING_BLENDERS_HPP__
#include "opencv2/core/core.hpp"
namespace cv {
namespace detail {
// Simple blender which puts one image over another
class CV_EXPORTS Blender
{
public:
virtual ~Blender() {}
enum { NO, FEATHER, MULTI_BAND };
static Ptr<Blender> createDefault(int type, bool try_gpu = false);
void prepare(const std::vector<Point> &corners, const std::vector<Size> &sizes);
virtual void prepare(Rect dst_roi);
virtual void feed(const Mat &img, const Mat &mask, Point tl);
virtual void blend(Mat &dst, Mat &dst_mask);
protected:
Mat dst_, dst_mask_;
Rect dst_roi_;
};
class CV_EXPORTS FeatherBlender : public Blender
{
public:
FeatherBlender(float sharpness = 0.02f);
float sharpness() const { return sharpness_; }
void setSharpness(float val) { sharpness_ = val; }
void prepare(Rect dst_roi);
void feed(const Mat &img, const Mat &mask, Point tl);
void blend(Mat &dst, Mat &dst_mask);
// Creates weight maps for fixed set of source images by their masks and top-left corners.
// Final image can be obtained by simple weighting of the source images.
Rect createWeightMaps(const std::vector<Mat> &masks, const std::vector<Point> &corners,
std::vector<Mat> &weight_maps);
private:
float sharpness_;
Mat weight_map_;
Mat dst_weight_map_;
};
inline FeatherBlender::FeatherBlender(float _sharpness) { setSharpness(_sharpness); }
class CV_EXPORTS MultiBandBlender : public Blender
{
public:
MultiBandBlender(int try_gpu = false, int num_bands = 5, int weight_type = CV_32F);
int numBands() const { return actual_num_bands_; }
void setNumBands(int val) { actual_num_bands_ = val; }
void prepare(Rect dst_roi);
void feed(const Mat &img, const Mat &mask, Point tl);
void blend(Mat &dst, Mat &dst_mask);
private:
int actual_num_bands_, num_bands_;
std::vector<Mat> dst_pyr_laplace_;
std::vector<Mat> dst_band_weights_;
Rect dst_roi_final_;
bool can_use_gpu_;
int weight_type_; //CV_32F or CV_16S
};
//////////////////////////////////////////////////////////////////////////////
// Auxiliary functions
void CV_EXPORTS normalizeUsingWeightMap(const Mat& weight, Mat& src);
void CV_EXPORTS createWeightMap(const Mat& mask, float sharpness, Mat& weight);
void CV_EXPORTS createLaplacePyr(const Mat &img, int num_levels, std::vector<Mat>& pyr);
void CV_EXPORTS createLaplacePyrGpu(const Mat &img, int num_levels, std::vector<Mat>& pyr);
// Restores source image
void CV_EXPORTS restoreImageFromLaplacePyr(std::vector<Mat>& pyr);
void CV_EXPORTS restoreImageFromLaplacePyrGpu(std::vector<Mat>& pyr);
} // namespace detail
} // namespace cv
#endif // __OPENCV_STITCHING_BLENDERS_HPP__

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifndef __OPENCV_STITCHING_EXPOSURE_COMPENSATE_HPP__
#define __OPENCV_STITCHING_EXPOSURE_COMPENSATE_HPP__
#include "opencv2/core/core.hpp"
namespace cv {
namespace detail {
class CV_EXPORTS ExposureCompensator
{
public:
virtual ~ExposureCompensator() {}
enum { NO, GAIN, GAIN_BLOCKS };
static Ptr<ExposureCompensator> createDefault(int type);
void feed(const std::vector<Point> &corners, const std::vector<Mat> &images,
const std::vector<Mat> &masks);
virtual void feed(const std::vector<Point> &corners, const std::vector<Mat> &images,
const std::vector<std::pair<Mat,uchar> > &masks) = 0;
virtual void apply(int index, Point corner, Mat &image, const Mat &mask) = 0;
};
class CV_EXPORTS NoExposureCompensator : public ExposureCompensator
{
public:
void feed(const std::vector<Point> &/*corners*/, const std::vector<Mat> &/*images*/,
const std::vector<std::pair<Mat,uchar> > &/*masks*/) {};
void apply(int /*index*/, Point /*corner*/, Mat &/*image*/, const Mat &/*mask*/) {};
};
class CV_EXPORTS GainCompensator : public ExposureCompensator
{
public:
void feed(const std::vector<Point> &corners, const std::vector<Mat> &images,
const std::vector<std::pair<Mat,uchar> > &masks);
void apply(int index, Point corner, Mat &image, const Mat &mask);
std::vector<double> gains() const;
private:
Mat_<double> gains_;
};
class CV_EXPORTS BlocksGainCompensator : public ExposureCompensator
{
public:
BlocksGainCompensator(int bl_width = 32, int bl_height = 32)
: bl_width_(bl_width), bl_height_(bl_height) {}
void feed(const std::vector<Point> &corners, const std::vector<Mat> &images,
const std::vector<std::pair<Mat,uchar> > &masks);
void apply(int index, Point corner, Mat &image, const Mat &mask);
private:
int bl_width_, bl_height_;
std::vector<Mat_<float> > gain_maps_;
};
} // namespace detail
} // namespace cv
#endif // __OPENCV_STITCHING_EXPOSURE_COMPENSATE_HPP__
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifndef __OPENCV_STITCHING_EXPOSURE_COMPENSATE_HPP__
#define __OPENCV_STITCHING_EXPOSURE_COMPENSATE_HPP__
#include "opencv2/core/core.hpp"
namespace cv {
namespace detail {
class CV_EXPORTS ExposureCompensator
{
public:
virtual ~ExposureCompensator() {}
enum { NO, GAIN, GAIN_BLOCKS };
static Ptr<ExposureCompensator> createDefault(int type);
void feed(const std::vector<Point> &corners, const std::vector<Mat> &images,
const std::vector<Mat> &masks);
virtual void feed(const std::vector<Point> &corners, const std::vector<Mat> &images,
const std::vector<std::pair<Mat,uchar> > &masks) = 0;
virtual void apply(int index, Point corner, Mat &image, const Mat &mask) = 0;
};
class CV_EXPORTS NoExposureCompensator : public ExposureCompensator
{
public:
void feed(const std::vector<Point> &/*corners*/, const std::vector<Mat> &/*images*/,
const std::vector<std::pair<Mat,uchar> > &/*masks*/) {};
void apply(int /*index*/, Point /*corner*/, Mat &/*image*/, const Mat &/*mask*/) {};
};
class CV_EXPORTS GainCompensator : public ExposureCompensator
{
public:
void feed(const std::vector<Point> &corners, const std::vector<Mat> &images,
const std::vector<std::pair<Mat,uchar> > &masks);
void apply(int index, Point corner, Mat &image, const Mat &mask);
std::vector<double> gains() const;
private:
Mat_<double> gains_;
};
class CV_EXPORTS BlocksGainCompensator : public ExposureCompensator
{
public:
BlocksGainCompensator(int bl_width = 32, int bl_height = 32)
: bl_width_(bl_width), bl_height_(bl_height) {}
void feed(const std::vector<Point> &corners, const std::vector<Mat> &images,
const std::vector<std::pair<Mat,uchar> > &masks);
void apply(int index, Point corner, Mat &image, const Mat &mask);
private:
int bl_width_, bl_height_;
std::vector<Mat_<float> > gain_maps_;
};
} // namespace detail
} // namespace cv
#endif // __OPENCV_STITCHING_EXPOSURE_COMPENSATE_HPP__

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@@ -1,188 +1,188 @@
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifndef __OPENCV_STITCHING_MATCHERS_HPP__
#define __OPENCV_STITCHING_MATCHERS_HPP__
#include "opencv2/core/core.hpp"
#include "opencv2/features2d/features2d.hpp"
#include "opencv2/opencv_modules.hpp"
#ifdef HAVE_OPENCV_GPU
#include "opencv2/gpu/gpu.hpp"
#endif
namespace cv {
namespace detail {
struct CV_EXPORTS ImageFeatures
{
int img_idx;
Size img_size;
std::vector<KeyPoint> keypoints;
Mat descriptors;
};
class CV_EXPORTS FeaturesFinder
{
public:
virtual ~FeaturesFinder() {}
void operator ()(const Mat &image, ImageFeatures &features);
void operator ()(const Mat &image, ImageFeatures &features, const std::vector<cv::Rect> &rois);
virtual void collectGarbage() {}
protected:
virtual void find(const Mat &image, ImageFeatures &features) = 0;
};
class CV_EXPORTS SurfFeaturesFinder : public FeaturesFinder
{
public:
SurfFeaturesFinder(double hess_thresh = 300., int num_octaves = 3, int num_layers = 4,
int num_octaves_descr = /*4*/3, int num_layers_descr = /*2*/4);
private:
void find(const Mat &image, ImageFeatures &features);
Ptr<FeatureDetector> detector_;
Ptr<DescriptorExtractor> extractor_;
Ptr<Feature2D> surf;
};
class CV_EXPORTS OrbFeaturesFinder : public FeaturesFinder
{
public:
OrbFeaturesFinder(Size _grid_size = Size(3,1), int nfeatures=1500, float scaleFactor=1.3f, int nlevels=5);
private:
void find(const Mat &image, ImageFeatures &features);
Ptr<ORB> orb;
Size grid_size;
};
#ifdef HAVE_OPENCV_GPU
class CV_EXPORTS SurfFeaturesFinderGpu : public FeaturesFinder
{
public:
SurfFeaturesFinderGpu(double hess_thresh = 300., int num_octaves = 3, int num_layers = 4,
int num_octaves_descr = 4, int num_layers_descr = 2);
void collectGarbage();
private:
void find(const Mat &image, ImageFeatures &features);
gpu::GpuMat image_;
gpu::GpuMat gray_image_;
gpu::SURF_GPU surf_;
gpu::GpuMat keypoints_;
gpu::GpuMat descriptors_;
int num_octaves_, num_layers_;
int num_octaves_descr_, num_layers_descr_;
};
#endif
struct CV_EXPORTS MatchesInfo
{
MatchesInfo();
MatchesInfo(const MatchesInfo &other);
const MatchesInfo& operator =(const MatchesInfo &other);
int src_img_idx, dst_img_idx; // Images indices (optional)
std::vector<DMatch> matches;
std::vector<uchar> inliers_mask; // Geometrically consistent matches mask
int num_inliers; // Number of geometrically consistent matches
Mat H; // Estimated homography
double confidence; // Confidence two images are from the same panorama
};
class CV_EXPORTS FeaturesMatcher
{
public:
virtual ~FeaturesMatcher() {}
void operator ()(const ImageFeatures &features1, const ImageFeatures &features2,
MatchesInfo& matches_info) { match(features1, features2, matches_info); }
void operator ()(const std::vector<ImageFeatures> &features, std::vector<MatchesInfo> &pairwise_matches,
const cv::Mat &mask = cv::Mat());
bool isThreadSafe() const { return is_thread_safe_; }
virtual void collectGarbage() {}
protected:
FeaturesMatcher(bool is_thread_safe = false) : is_thread_safe_(is_thread_safe) {}
virtual void match(const ImageFeatures &features1, const ImageFeatures &features2,
MatchesInfo& matches_info) = 0;
bool is_thread_safe_;
};
class CV_EXPORTS BestOf2NearestMatcher : public FeaturesMatcher
{
public:
BestOf2NearestMatcher(bool try_use_gpu = false, float match_conf = 0.3f, int num_matches_thresh1 = 6,
int num_matches_thresh2 = 6);
void collectGarbage();
protected:
void match(const ImageFeatures &features1, const ImageFeatures &features2, MatchesInfo &matches_info);
int num_matches_thresh1_;
int num_matches_thresh2_;
Ptr<FeaturesMatcher> impl_;
};
} // namespace detail
} // namespace cv
#endif // __OPENCV_STITCHING_MATCHERS_HPP__
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifndef __OPENCV_STITCHING_MATCHERS_HPP__
#define __OPENCV_STITCHING_MATCHERS_HPP__
#include "opencv2/core/core.hpp"
#include "opencv2/features2d/features2d.hpp"
#include "opencv2/opencv_modules.hpp"
#ifdef HAVE_OPENCV_GPU
#include "opencv2/gpu/gpu.hpp"
#endif
namespace cv {
namespace detail {
struct CV_EXPORTS ImageFeatures
{
int img_idx;
Size img_size;
std::vector<KeyPoint> keypoints;
Mat descriptors;
};
class CV_EXPORTS FeaturesFinder
{
public:
virtual ~FeaturesFinder() {}
void operator ()(const Mat &image, ImageFeatures &features);
void operator ()(const Mat &image, ImageFeatures &features, const std::vector<cv::Rect> &rois);
virtual void collectGarbage() {}
protected:
virtual void find(const Mat &image, ImageFeatures &features) = 0;
};
class CV_EXPORTS SurfFeaturesFinder : public FeaturesFinder
{
public:
SurfFeaturesFinder(double hess_thresh = 300., int num_octaves = 3, int num_layers = 4,
int num_octaves_descr = /*4*/3, int num_layers_descr = /*2*/4);
private:
void find(const Mat &image, ImageFeatures &features);
Ptr<FeatureDetector> detector_;
Ptr<DescriptorExtractor> extractor_;
Ptr<Feature2D> surf;
};
class CV_EXPORTS OrbFeaturesFinder : public FeaturesFinder
{
public:
OrbFeaturesFinder(Size _grid_size = Size(3,1), int nfeatures=1500, float scaleFactor=1.3f, int nlevels=5);
private:
void find(const Mat &image, ImageFeatures &features);
Ptr<ORB> orb;
Size grid_size;
};
#ifdef HAVE_OPENCV_GPU
class CV_EXPORTS SurfFeaturesFinderGpu : public FeaturesFinder
{
public:
SurfFeaturesFinderGpu(double hess_thresh = 300., int num_octaves = 3, int num_layers = 4,
int num_octaves_descr = 4, int num_layers_descr = 2);
void collectGarbage();
private:
void find(const Mat &image, ImageFeatures &features);
gpu::GpuMat image_;
gpu::GpuMat gray_image_;
gpu::SURF_GPU surf_;
gpu::GpuMat keypoints_;
gpu::GpuMat descriptors_;
int num_octaves_, num_layers_;
int num_octaves_descr_, num_layers_descr_;
};
#endif
struct CV_EXPORTS MatchesInfo
{
MatchesInfo();
MatchesInfo(const MatchesInfo &other);
const MatchesInfo& operator =(const MatchesInfo &other);
int src_img_idx, dst_img_idx; // Images indices (optional)
std::vector<DMatch> matches;
std::vector<uchar> inliers_mask; // Geometrically consistent matches mask
int num_inliers; // Number of geometrically consistent matches
Mat H; // Estimated homography
double confidence; // Confidence two images are from the same panorama
};
class CV_EXPORTS FeaturesMatcher
{
public:
virtual ~FeaturesMatcher() {}
void operator ()(const ImageFeatures &features1, const ImageFeatures &features2,
MatchesInfo& matches_info) { match(features1, features2, matches_info); }
void operator ()(const std::vector<ImageFeatures> &features, std::vector<MatchesInfo> &pairwise_matches,
const cv::Mat &mask = cv::Mat());
bool isThreadSafe() const { return is_thread_safe_; }
virtual void collectGarbage() {}
protected:
FeaturesMatcher(bool is_thread_safe = false) : is_thread_safe_(is_thread_safe) {}
virtual void match(const ImageFeatures &features1, const ImageFeatures &features2,
MatchesInfo& matches_info) = 0;
bool is_thread_safe_;
};
class CV_EXPORTS BestOf2NearestMatcher : public FeaturesMatcher
{
public:
BestOf2NearestMatcher(bool try_use_gpu = false, float match_conf = 0.3f, int num_matches_thresh1 = 6,
int num_matches_thresh2 = 6);
void collectGarbage();
protected:
void match(const ImageFeatures &features1, const ImageFeatures &features2, MatchesInfo &matches_info);
int num_matches_thresh1_;
int num_matches_thresh2_;
Ptr<FeaturesMatcher> impl_;
};
} // namespace detail
} // namespace cv
#endif // __OPENCV_STITCHING_MATCHERS_HPP__

View File

@@ -1,205 +1,205 @@
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifndef __OPENCV_STITCHING_MOTION_ESTIMATORS_HPP__
#define __OPENCV_STITCHING_MOTION_ESTIMATORS_HPP__
#include "opencv2/core/core.hpp"
#include "matchers.hpp"
#include "util.hpp"
#include "camera.hpp"
namespace cv {
namespace detail {
class CV_EXPORTS Estimator
{
public:
virtual ~Estimator() {}
void operator ()(const std::vector<ImageFeatures> &features, const std::vector<MatchesInfo> &pairwise_matches,
std::vector<CameraParams> &cameras)
{ estimate(features, pairwise_matches, cameras); }
protected:
virtual void estimate(const std::vector<ImageFeatures> &features, const std::vector<MatchesInfo> &pairwise_matches,
std::vector<CameraParams> &cameras) = 0;
};
class CV_EXPORTS HomographyBasedEstimator : public Estimator
{
public:
HomographyBasedEstimator(bool is_focals_estimated = false)
: is_focals_estimated_(is_focals_estimated) {}
private:
void estimate(const std::vector<ImageFeatures> &features, const std::vector<MatchesInfo> &pairwise_matches,
std::vector<CameraParams> &cameras);
bool is_focals_estimated_;
};
class CV_EXPORTS BundleAdjusterBase : public Estimator
{
public:
const Mat refinementMask() const { return refinement_mask_.clone(); }
void setRefinementMask(const Mat &mask)
{
CV_Assert(mask.type() == CV_8U && mask.size() == Size(3, 3));
refinement_mask_ = mask.clone();
}
double confThresh() const { return conf_thresh_; }
void setConfThresh(double conf_thresh) { conf_thresh_ = conf_thresh; }
CvTermCriteria termCriteria() { return term_criteria_; }
void setTermCriteria(const CvTermCriteria& term_criteria) { term_criteria_ = term_criteria; }
protected:
BundleAdjusterBase(int num_params_per_cam, int num_errs_per_measurement)
: num_params_per_cam_(num_params_per_cam),
num_errs_per_measurement_(num_errs_per_measurement)
{
setRefinementMask(Mat::ones(3, 3, CV_8U));
setConfThresh(1.);
setTermCriteria(cvTermCriteria(CV_TERMCRIT_EPS + CV_TERMCRIT_ITER, 1000, DBL_EPSILON));
}
// Runs bundle adjustment
virtual void estimate(const std::vector<ImageFeatures> &features,
const std::vector<MatchesInfo> &pairwise_matches,
std::vector<CameraParams> &cameras);
virtual void setUpInitialCameraParams(const std::vector<CameraParams> &cameras) = 0;
virtual void obtainRefinedCameraParams(std::vector<CameraParams> &cameras) const = 0;
virtual void calcError(Mat &err) = 0;
virtual void calcJacobian(Mat &jac) = 0;
// 3x3 8U mask, where 0 means don't refine respective parameter, != 0 means refine
Mat refinement_mask_;
int num_images_;
int total_num_matches_;
int num_params_per_cam_;
int num_errs_per_measurement_;
const ImageFeatures *features_;
const MatchesInfo *pairwise_matches_;
// Threshold to filter out poorly matched image pairs
double conf_thresh_;
//LevenbergMarquardt algorithm termination criteria
CvTermCriteria term_criteria_;
// Camera parameters matrix (CV_64F)
Mat cam_params_;
// Connected images pairs
std::vector<std::pair<int,int> > edges_;
};
// Minimizes reprojection error.
// It can estimate focal length, aspect ratio, principal point.
// You can affect only on them via the refinement mask.
class CV_EXPORTS BundleAdjusterReproj : public BundleAdjusterBase
{
public:
BundleAdjusterReproj() : BundleAdjusterBase(7, 2) {}
private:
void setUpInitialCameraParams(const std::vector<CameraParams> &cameras);
void obtainRefinedCameraParams(std::vector<CameraParams> &cameras) const;
void calcError(Mat &err);
void calcJacobian(Mat &jac);
Mat err1_, err2_;
};
// Minimizes sun of ray-to-ray distances.
// It can estimate focal length. It ignores the refinement mask for now.
class CV_EXPORTS BundleAdjusterRay : public BundleAdjusterBase
{
public:
BundleAdjusterRay() : BundleAdjusterBase(4, 3) {}
private:
void setUpInitialCameraParams(const std::vector<CameraParams> &cameras);
void obtainRefinedCameraParams(std::vector<CameraParams> &cameras) const;
void calcError(Mat &err);
void calcJacobian(Mat &jac);
Mat err1_, err2_;
};
enum WaveCorrectKind
{
WAVE_CORRECT_HORIZ,
WAVE_CORRECT_VERT
};
void CV_EXPORTS waveCorrect(std::vector<Mat> &rmats, WaveCorrectKind kind);
//////////////////////////////////////////////////////////////////////////////
// Auxiliary functions
// Returns matches graph representation in DOT language
std::string CV_EXPORTS matchesGraphAsString(std::vector<std::string> &pathes, std::vector<MatchesInfo> &pairwise_matches,
float conf_threshold);
std::vector<int> CV_EXPORTS leaveBiggestComponent(std::vector<ImageFeatures> &features, std::vector<MatchesInfo> &pairwise_matches,
float conf_threshold);
void CV_EXPORTS findMaxSpanningTree(int num_images, const std::vector<MatchesInfo> &pairwise_matches,
Graph &span_tree, std::vector<int> &centers);
} // namespace detail
} // namespace cv
#endif // __OPENCV_STITCHING_MOTION_ESTIMATORS_HPP__
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifndef __OPENCV_STITCHING_MOTION_ESTIMATORS_HPP__
#define __OPENCV_STITCHING_MOTION_ESTIMATORS_HPP__
#include "opencv2/core/core.hpp"
#include "matchers.hpp"
#include "util.hpp"
#include "camera.hpp"
namespace cv {
namespace detail {
class CV_EXPORTS Estimator
{
public:
virtual ~Estimator() {}
void operator ()(const std::vector<ImageFeatures> &features, const std::vector<MatchesInfo> &pairwise_matches,
std::vector<CameraParams> &cameras)
{ estimate(features, pairwise_matches, cameras); }
protected:
virtual void estimate(const std::vector<ImageFeatures> &features, const std::vector<MatchesInfo> &pairwise_matches,
std::vector<CameraParams> &cameras) = 0;
};
class CV_EXPORTS HomographyBasedEstimator : public Estimator
{
public:
HomographyBasedEstimator(bool is_focals_estimated = false)
: is_focals_estimated_(is_focals_estimated) {}
private:
void estimate(const std::vector<ImageFeatures> &features, const std::vector<MatchesInfo> &pairwise_matches,
std::vector<CameraParams> &cameras);
bool is_focals_estimated_;
};
class CV_EXPORTS BundleAdjusterBase : public Estimator
{
public:
const Mat refinementMask() const { return refinement_mask_.clone(); }
void setRefinementMask(const Mat &mask)
{
CV_Assert(mask.type() == CV_8U && mask.size() == Size(3, 3));
refinement_mask_ = mask.clone();
}
double confThresh() const { return conf_thresh_; }
void setConfThresh(double conf_thresh) { conf_thresh_ = conf_thresh; }
CvTermCriteria termCriteria() { return term_criteria_; }
void setTermCriteria(const CvTermCriteria& term_criteria) { term_criteria_ = term_criteria; }
protected:
BundleAdjusterBase(int num_params_per_cam, int num_errs_per_measurement)
: num_params_per_cam_(num_params_per_cam),
num_errs_per_measurement_(num_errs_per_measurement)
{
setRefinementMask(Mat::ones(3, 3, CV_8U));
setConfThresh(1.);
setTermCriteria(cvTermCriteria(CV_TERMCRIT_EPS + CV_TERMCRIT_ITER, 1000, DBL_EPSILON));
}
// Runs bundle adjustment
virtual void estimate(const std::vector<ImageFeatures> &features,
const std::vector<MatchesInfo> &pairwise_matches,
std::vector<CameraParams> &cameras);
virtual void setUpInitialCameraParams(const std::vector<CameraParams> &cameras) = 0;
virtual void obtainRefinedCameraParams(std::vector<CameraParams> &cameras) const = 0;
virtual void calcError(Mat &err) = 0;
virtual void calcJacobian(Mat &jac) = 0;
// 3x3 8U mask, where 0 means don't refine respective parameter, != 0 means refine
Mat refinement_mask_;
int num_images_;
int total_num_matches_;
int num_params_per_cam_;
int num_errs_per_measurement_;
const ImageFeatures *features_;
const MatchesInfo *pairwise_matches_;
// Threshold to filter out poorly matched image pairs
double conf_thresh_;
//LevenbergMarquardt algorithm termination criteria
CvTermCriteria term_criteria_;
// Camera parameters matrix (CV_64F)
Mat cam_params_;
// Connected images pairs
std::vector<std::pair<int,int> > edges_;
};
// Minimizes reprojection error.
// It can estimate focal length, aspect ratio, principal point.
// You can affect only on them via the refinement mask.
class CV_EXPORTS BundleAdjusterReproj : public BundleAdjusterBase
{
public:
BundleAdjusterReproj() : BundleAdjusterBase(7, 2) {}
private:
void setUpInitialCameraParams(const std::vector<CameraParams> &cameras);
void obtainRefinedCameraParams(std::vector<CameraParams> &cameras) const;
void calcError(Mat &err);
void calcJacobian(Mat &jac);
Mat err1_, err2_;
};
// Minimizes sun of ray-to-ray distances.
// It can estimate focal length. It ignores the refinement mask for now.
class CV_EXPORTS BundleAdjusterRay : public BundleAdjusterBase
{
public:
BundleAdjusterRay() : BundleAdjusterBase(4, 3) {}
private:
void setUpInitialCameraParams(const std::vector<CameraParams> &cameras);
void obtainRefinedCameraParams(std::vector<CameraParams> &cameras) const;
void calcError(Mat &err);
void calcJacobian(Mat &jac);
Mat err1_, err2_;
};
enum WaveCorrectKind
{
WAVE_CORRECT_HORIZ,
WAVE_CORRECT_VERT
};
void CV_EXPORTS waveCorrect(std::vector<Mat> &rmats, WaveCorrectKind kind);
//////////////////////////////////////////////////////////////////////////////
// Auxiliary functions
// Returns matches graph representation in DOT language
std::string CV_EXPORTS matchesGraphAsString(std::vector<std::string> &pathes, std::vector<MatchesInfo> &pairwise_matches,
float conf_threshold);
std::vector<int> CV_EXPORTS leaveBiggestComponent(std::vector<ImageFeatures> &features, std::vector<MatchesInfo> &pairwise_matches,
float conf_threshold);
void CV_EXPORTS findMaxSpanningTree(int num_images, const std::vector<MatchesInfo> &pairwise_matches,
Graph &span_tree, std::vector<int> &centers);
} // namespace detail
} // namespace cv
#endif // __OPENCV_STITCHING_MOTION_ESTIMATORS_HPP__

View File

@@ -1,259 +1,259 @@
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifndef __OPENCV_STITCHING_SEAM_FINDERS_HPP__
#define __OPENCV_STITCHING_SEAM_FINDERS_HPP__
#include <set>
#include "opencv2/core/core.hpp"
#include "opencv2/opencv_modules.hpp"
namespace cv {
namespace detail {
class CV_EXPORTS SeamFinder
{
public:
virtual ~SeamFinder() {}
virtual void find(const std::vector<Mat> &src, const std::vector<Point> &corners,
std::vector<Mat> &masks) = 0;
};
class CV_EXPORTS NoSeamFinder : public SeamFinder
{
public:
void find(const std::vector<Mat>&, const std::vector<Point>&, std::vector<Mat>&) {}
};
class CV_EXPORTS PairwiseSeamFinder : public SeamFinder
{
public:
virtual void find(const std::vector<Mat> &src, const std::vector<Point> &corners,
std::vector<Mat> &masks);
protected:
void run();
virtual void findInPair(size_t first, size_t second, Rect roi) = 0;
std::vector<Mat> images_;
std::vector<Size> sizes_;
std::vector<Point> corners_;
std::vector<Mat> masks_;
};
class CV_EXPORTS VoronoiSeamFinder : public PairwiseSeamFinder
{
public:
virtual void find(const std::vector<Size> &size, const std::vector<Point> &corners,
std::vector<Mat> &masks);
private:
void findInPair(size_t first, size_t second, Rect roi);
};
class CV_EXPORTS DpSeamFinder : public SeamFinder
{
public:
enum CostFunction { COLOR, COLOR_GRAD };
DpSeamFinder(CostFunction costFunc = COLOR);
CostFunction costFunction() const { return costFunc_; }
void setCostFunction(CostFunction val) { costFunc_ = val; }
virtual void find(const std::vector<Mat> &src, const std::vector<Point> &corners,
std::vector<Mat> &masks);
private:
enum ComponentState
{
FIRST = 1, SECOND = 2, INTERS = 4,
INTERS_FIRST = INTERS | FIRST,
INTERS_SECOND = INTERS | SECOND
};
class ImagePairLess
{
public:
ImagePairLess(const std::vector<Mat> &images, const std::vector<Point> &corners)
: src_(&images[0]), corners_(&corners[0]) {}
bool operator() (const std::pair<size_t, size_t> &l, const std::pair<size_t, size_t> &r) const
{
Point c1 = corners_[l.first] + Point(src_[l.first].cols / 2, src_[l.first].rows / 2);
Point c2 = corners_[l.second] + Point(src_[l.second].cols / 2, src_[l.second].rows / 2);
int d1 = (c1 - c2).dot(c1 - c2);
c1 = corners_[r.first] + Point(src_[r.first].cols / 2, src_[r.first].rows / 2);
c2 = corners_[r.second] + Point(src_[r.second].cols / 2, src_[r.second].rows / 2);
int d2 = (c1 - c2).dot(c1 - c2);
return d1 < d2;
}
private:
const Mat *src_;
const Point *corners_;
};
class ClosePoints
{
public:
ClosePoints(int minDist) : minDist_(minDist) {}
bool operator() (const Point &p1, const Point &p2) const
{
int dist2 = (p1.x-p2.x) * (p1.x-p2.x) + (p1.y-p2.y) * (p1.y-p2.y);
return dist2 < minDist_ * minDist_;
}
private:
int minDist_;
};
void process(
const Mat &image1, const Mat &image2, Point tl1, Point tl2, Mat &mask1, Mat &mask2);
void findComponents();
void findEdges();
void resolveConflicts(
const Mat &image1, const Mat &image2, Point tl1, Point tl2, Mat &mask1, Mat &mask2);
void computeGradients(const Mat &image1, const Mat &image2);
bool hasOnlyOneNeighbor(int comp);
bool closeToContour(int y, int x, const Mat_<uchar> &contourMask);
bool getSeamTips(int comp1, int comp2, Point &p1, Point &p2);
void computeCosts(
const Mat &image1, const Mat &image2, Point tl1, Point tl2,
int comp, Mat_<float> &costV, Mat_<float> &costH);
bool estimateSeam(
const Mat &image1, const Mat &image2, Point tl1, Point tl2, int comp,
Point p1, Point p2, std::vector<Point> &seam, bool &isHorizontal);
void updateLabelsUsingSeam(
int comp1, int comp2, const std::vector<Point> &seam, bool isHorizontalSeam);
CostFunction costFunc_;
// processing images pair data
Point unionTl_, unionBr_;
Size unionSize_;
Mat_<uchar> mask1_, mask2_;
Mat_<uchar> contour1mask_, contour2mask_;
Mat_<float> gradx1_, grady1_;
Mat_<float> gradx2_, grady2_;
// components data
int ncomps_;
Mat_<int> labels_;
std::vector<ComponentState> states_;
std::vector<Point> tls_, brs_;
std::vector<std::vector<Point> > contours_;
std::set<std::pair<int, int> > edges_;
};
class CV_EXPORTS GraphCutSeamFinderBase
{
public:
enum { COST_COLOR, COST_COLOR_GRAD };
};
class CV_EXPORTS GraphCutSeamFinder : public GraphCutSeamFinderBase, public SeamFinder
{
public:
GraphCutSeamFinder(int cost_type = COST_COLOR_GRAD, float terminal_cost = 10000.f,
float bad_region_penalty = 1000.f);
~GraphCutSeamFinder();
void find(const std::vector<Mat> &src, const std::vector<Point> &corners,
std::vector<Mat> &masks);
private:
// To avoid GCGraph dependency
class Impl;
Ptr<PairwiseSeamFinder> impl_;
};
#ifdef HAVE_OPENCV_GPU
class CV_EXPORTS GraphCutSeamFinderGpu : public GraphCutSeamFinderBase, public PairwiseSeamFinder
{
public:
GraphCutSeamFinderGpu(int cost_type = COST_COLOR_GRAD, float terminal_cost = 10000.f,
float bad_region_penalty = 1000.f)
: cost_type_(cost_type), terminal_cost_(terminal_cost),
bad_region_penalty_(bad_region_penalty) {}
void find(const std::vector<cv::Mat> &src, const std::vector<cv::Point> &corners,
std::vector<cv::Mat> &masks);
void findInPair(size_t first, size_t second, Rect roi);
private:
void setGraphWeightsColor(const cv::Mat &img1, const cv::Mat &img2, const cv::Mat &mask1, const cv::Mat &mask2,
cv::Mat &terminals, cv::Mat &leftT, cv::Mat &rightT, cv::Mat &top, cv::Mat &bottom);
void setGraphWeightsColorGrad(const cv::Mat &img1, const cv::Mat &img2, const cv::Mat &dx1, const cv::Mat &dx2,
const cv::Mat &dy1, const cv::Mat &dy2, const cv::Mat &mask1, const cv::Mat &mask2,
cv::Mat &terminals, cv::Mat &leftT, cv::Mat &rightT, cv::Mat &top, cv::Mat &bottom);
std::vector<Mat> dx_, dy_;
int cost_type_;
float terminal_cost_;
float bad_region_penalty_;
};
#endif
} // namespace detail
} // namespace cv
#endif // __OPENCV_STITCHING_SEAM_FINDERS_HPP__
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifndef __OPENCV_STITCHING_SEAM_FINDERS_HPP__
#define __OPENCV_STITCHING_SEAM_FINDERS_HPP__
#include <set>
#include "opencv2/core/core.hpp"
#include "opencv2/opencv_modules.hpp"
namespace cv {
namespace detail {
class CV_EXPORTS SeamFinder
{
public:
virtual ~SeamFinder() {}
virtual void find(const std::vector<Mat> &src, const std::vector<Point> &corners,
std::vector<Mat> &masks) = 0;
};
class CV_EXPORTS NoSeamFinder : public SeamFinder
{
public:
void find(const std::vector<Mat>&, const std::vector<Point>&, std::vector<Mat>&) {}
};
class CV_EXPORTS PairwiseSeamFinder : public SeamFinder
{
public:
virtual void find(const std::vector<Mat> &src, const std::vector<Point> &corners,
std::vector<Mat> &masks);
protected:
void run();
virtual void findInPair(size_t first, size_t second, Rect roi) = 0;
std::vector<Mat> images_;
std::vector<Size> sizes_;
std::vector<Point> corners_;
std::vector<Mat> masks_;
};
class CV_EXPORTS VoronoiSeamFinder : public PairwiseSeamFinder
{
public:
virtual void find(const std::vector<Size> &size, const std::vector<Point> &corners,
std::vector<Mat> &masks);
private:
void findInPair(size_t first, size_t second, Rect roi);
};
class CV_EXPORTS DpSeamFinder : public SeamFinder
{
public:
enum CostFunction { COLOR, COLOR_GRAD };
DpSeamFinder(CostFunction costFunc = COLOR);
CostFunction costFunction() const { return costFunc_; }
void setCostFunction(CostFunction val) { costFunc_ = val; }
virtual void find(const std::vector<Mat> &src, const std::vector<Point> &corners,
std::vector<Mat> &masks);
private:
enum ComponentState
{
FIRST = 1, SECOND = 2, INTERS = 4,
INTERS_FIRST = INTERS | FIRST,
INTERS_SECOND = INTERS | SECOND
};
class ImagePairLess
{
public:
ImagePairLess(const std::vector<Mat> &images, const std::vector<Point> &corners)
: src_(&images[0]), corners_(&corners[0]) {}
bool operator() (const std::pair<size_t, size_t> &l, const std::pair<size_t, size_t> &r) const
{
Point c1 = corners_[l.first] + Point(src_[l.first].cols / 2, src_[l.first].rows / 2);
Point c2 = corners_[l.second] + Point(src_[l.second].cols / 2, src_[l.second].rows / 2);
int d1 = (c1 - c2).dot(c1 - c2);
c1 = corners_[r.first] + Point(src_[r.first].cols / 2, src_[r.first].rows / 2);
c2 = corners_[r.second] + Point(src_[r.second].cols / 2, src_[r.second].rows / 2);
int d2 = (c1 - c2).dot(c1 - c2);
return d1 < d2;
}
private:
const Mat *src_;
const Point *corners_;
};
class ClosePoints
{
public:
ClosePoints(int minDist) : minDist_(minDist) {}
bool operator() (const Point &p1, const Point &p2) const
{
int dist2 = (p1.x-p2.x) * (p1.x-p2.x) + (p1.y-p2.y) * (p1.y-p2.y);
return dist2 < minDist_ * minDist_;
}
private:
int minDist_;
};
void process(
const Mat &image1, const Mat &image2, Point tl1, Point tl2, Mat &mask1, Mat &mask2);
void findComponents();
void findEdges();
void resolveConflicts(
const Mat &image1, const Mat &image2, Point tl1, Point tl2, Mat &mask1, Mat &mask2);
void computeGradients(const Mat &image1, const Mat &image2);
bool hasOnlyOneNeighbor(int comp);
bool closeToContour(int y, int x, const Mat_<uchar> &contourMask);
bool getSeamTips(int comp1, int comp2, Point &p1, Point &p2);
void computeCosts(
const Mat &image1, const Mat &image2, Point tl1, Point tl2,
int comp, Mat_<float> &costV, Mat_<float> &costH);
bool estimateSeam(
const Mat &image1, const Mat &image2, Point tl1, Point tl2, int comp,
Point p1, Point p2, std::vector<Point> &seam, bool &isHorizontal);
void updateLabelsUsingSeam(
int comp1, int comp2, const std::vector<Point> &seam, bool isHorizontalSeam);
CostFunction costFunc_;
// processing images pair data
Point unionTl_, unionBr_;
Size unionSize_;
Mat_<uchar> mask1_, mask2_;
Mat_<uchar> contour1mask_, contour2mask_;
Mat_<float> gradx1_, grady1_;
Mat_<float> gradx2_, grady2_;
// components data
int ncomps_;
Mat_<int> labels_;
std::vector<ComponentState> states_;
std::vector<Point> tls_, brs_;
std::vector<std::vector<Point> > contours_;
std::set<std::pair<int, int> > edges_;
};
class CV_EXPORTS GraphCutSeamFinderBase
{
public:
enum { COST_COLOR, COST_COLOR_GRAD };
};
class CV_EXPORTS GraphCutSeamFinder : public GraphCutSeamFinderBase, public SeamFinder
{
public:
GraphCutSeamFinder(int cost_type = COST_COLOR_GRAD, float terminal_cost = 10000.f,
float bad_region_penalty = 1000.f);
~GraphCutSeamFinder();
void find(const std::vector<Mat> &src, const std::vector<Point> &corners,
std::vector<Mat> &masks);
private:
// To avoid GCGraph dependency
class Impl;
Ptr<PairwiseSeamFinder> impl_;
};
#ifdef HAVE_OPENCV_GPU
class CV_EXPORTS GraphCutSeamFinderGpu : public GraphCutSeamFinderBase, public PairwiseSeamFinder
{
public:
GraphCutSeamFinderGpu(int cost_type = COST_COLOR_GRAD, float terminal_cost = 10000.f,
float bad_region_penalty = 1000.f)
: cost_type_(cost_type), terminal_cost_(terminal_cost),
bad_region_penalty_(bad_region_penalty) {}
void find(const std::vector<cv::Mat> &src, const std::vector<cv::Point> &corners,
std::vector<cv::Mat> &masks);
void findInPair(size_t first, size_t second, Rect roi);
private:
void setGraphWeightsColor(const cv::Mat &img1, const cv::Mat &img2, const cv::Mat &mask1, const cv::Mat &mask2,
cv::Mat &terminals, cv::Mat &leftT, cv::Mat &rightT, cv::Mat &top, cv::Mat &bottom);
void setGraphWeightsColorGrad(const cv::Mat &img1, const cv::Mat &img2, const cv::Mat &dx1, const cv::Mat &dx2,
const cv::Mat &dy1, const cv::Mat &dy2, const cv::Mat &mask1, const cv::Mat &mask2,
cv::Mat &terminals, cv::Mat &leftT, cv::Mat &rightT, cv::Mat &top, cv::Mat &bottom);
std::vector<Mat> dx_, dy_;
int cost_type_;
float terminal_cost_;
float bad_region_penalty_;
};
#endif
} // namespace detail
} // namespace cv
#endif // __OPENCV_STITCHING_SEAM_FINDERS_HPP__

View File

@@ -1,162 +1,162 @@
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifndef __OPENCV_STITCHING_UTIL_HPP__
#define __OPENCV_STITCHING_UTIL_HPP__
#include <list>
#include "opencv2/core/core.hpp"
#define ENABLE_LOG 0
// TODO remove LOG macros, add logging class
#if ENABLE_LOG
#ifdef ANDROID
#include <iostream>
#include <sstream>
#include <android/log.h>
#define LOG_STITCHING_MSG(msg) \
do { \
std::stringstream _os; \
_os << msg; \
__android_log_print(ANDROID_LOG_DEBUG, "STITCHING", "%s", _os.str().c_str()); \
} while(0);
#else
#include <iostream>
#define LOG_STITCHING_MSG(msg) for(;;) { std::cout << msg; std::cout.flush(); break; }
#endif
#else
#define LOG_STITCHING_MSG(msg)
#endif
#define LOG_(_level, _msg) \
for(;;) \
{ \
if ((_level) >= ::cv::detail::stitchingLogLevel()) \
{ \
LOG_STITCHING_MSG(_msg); \
} \
break; \
}
#define LOG(msg) LOG_(1, msg)
#define LOG_CHAT(msg) LOG_(0, msg)
#define LOGLN(msg) LOG(msg << std::endl)
#define LOGLN_CHAT(msg) LOG_CHAT(msg << std::endl)
//#if DEBUG_LOG_CHAT
// #define LOG_CHAT(msg) LOG(msg)
// #define LOGLN_CHAT(msg) LOGLN(msg)
//#else
// #define LOG_CHAT(msg) do{}while(0)
// #define LOGLN_CHAT(msg) do{}while(0)
//#endif
namespace cv {
namespace detail {
class CV_EXPORTS DisjointSets
{
public:
DisjointSets(int elem_count = 0) { createOneElemSets(elem_count); }
void createOneElemSets(int elem_count);
int findSetByElem(int elem);
int mergeSets(int set1, int set2);
std::vector<int> parent;
std::vector<int> size;
private:
std::vector<int> rank_;
};
struct CV_EXPORTS GraphEdge
{
GraphEdge(int from, int to, float weight);
bool operator <(const GraphEdge& other) const { return weight < other.weight; }
bool operator >(const GraphEdge& other) const { return weight > other.weight; }
int from, to;
float weight;
};
inline GraphEdge::GraphEdge(int _from, int _to, float _weight) : from(_from), to(_to), weight(_weight) {}
class CV_EXPORTS Graph
{
public:
Graph(int num_vertices = 0) { create(num_vertices); }
void create(int num_vertices) { edges_.assign(num_vertices, std::list<GraphEdge>()); }
int numVertices() const { return static_cast<int>(edges_.size()); }
void addEdge(int from, int to, float weight);
template <typename B> B forEach(B body) const;
template <typename B> B walkBreadthFirst(int from, B body) const;
private:
std::vector< std::list<GraphEdge> > edges_;
};
//////////////////////////////////////////////////////////////////////////////
// Auxiliary functions
CV_EXPORTS bool overlapRoi(Point tl1, Point tl2, Size sz1, Size sz2, Rect &roi);
CV_EXPORTS Rect resultRoi(const std::vector<Point> &corners, const std::vector<Mat> &images);
CV_EXPORTS Rect resultRoi(const std::vector<Point> &corners, const std::vector<Size> &sizes);
CV_EXPORTS Point resultTl(const std::vector<Point> &corners);
// Returns random 'count' element subset of the {0,1,...,size-1} set
CV_EXPORTS void selectRandomSubset(int count, int size, std::vector<int> &subset);
CV_EXPORTS int& stitchingLogLevel();
} // namespace detail
} // namespace cv
#include "util_inl.hpp"
#endif // __OPENCV_STITCHING_UTIL_HPP__
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifndef __OPENCV_STITCHING_UTIL_HPP__
#define __OPENCV_STITCHING_UTIL_HPP__
#include <list>
#include "opencv2/core/core.hpp"
#define ENABLE_LOG 0
// TODO remove LOG macros, add logging class
#if ENABLE_LOG
#ifdef ANDROID
#include <iostream>
#include <sstream>
#include <android/log.h>
#define LOG_STITCHING_MSG(msg) \
do { \
std::stringstream _os; \
_os << msg; \
__android_log_print(ANDROID_LOG_DEBUG, "STITCHING", "%s", _os.str().c_str()); \
} while(0);
#else
#include <iostream>
#define LOG_STITCHING_MSG(msg) for(;;) { std::cout << msg; std::cout.flush(); break; }
#endif
#else
#define LOG_STITCHING_MSG(msg)
#endif
#define LOG_(_level, _msg) \
for(;;) \
{ \
if ((_level) >= ::cv::detail::stitchingLogLevel()) \
{ \
LOG_STITCHING_MSG(_msg); \
} \
break; \
}
#define LOG(msg) LOG_(1, msg)
#define LOG_CHAT(msg) LOG_(0, msg)
#define LOGLN(msg) LOG(msg << std::endl)
#define LOGLN_CHAT(msg) LOG_CHAT(msg << std::endl)
//#if DEBUG_LOG_CHAT
// #define LOG_CHAT(msg) LOG(msg)
// #define LOGLN_CHAT(msg) LOGLN(msg)
//#else
// #define LOG_CHAT(msg) do{}while(0)
// #define LOGLN_CHAT(msg) do{}while(0)
//#endif
namespace cv {
namespace detail {
class CV_EXPORTS DisjointSets
{
public:
DisjointSets(int elem_count = 0) { createOneElemSets(elem_count); }
void createOneElemSets(int elem_count);
int findSetByElem(int elem);
int mergeSets(int set1, int set2);
std::vector<int> parent;
std::vector<int> size;
private:
std::vector<int> rank_;
};
struct CV_EXPORTS GraphEdge
{
GraphEdge(int from, int to, float weight);
bool operator <(const GraphEdge& other) const { return weight < other.weight; }
bool operator >(const GraphEdge& other) const { return weight > other.weight; }
int from, to;
float weight;
};
inline GraphEdge::GraphEdge(int _from, int _to, float _weight) : from(_from), to(_to), weight(_weight) {}
class CV_EXPORTS Graph
{
public:
Graph(int num_vertices = 0) { create(num_vertices); }
void create(int num_vertices) { edges_.assign(num_vertices, std::list<GraphEdge>()); }
int numVertices() const { return static_cast<int>(edges_.size()); }
void addEdge(int from, int to, float weight);
template <typename B> B forEach(B body) const;
template <typename B> B walkBreadthFirst(int from, B body) const;
private:
std::vector< std::list<GraphEdge> > edges_;
};
//////////////////////////////////////////////////////////////////////////////
// Auxiliary functions
CV_EXPORTS bool overlapRoi(Point tl1, Point tl2, Size sz1, Size sz2, Rect &roi);
CV_EXPORTS Rect resultRoi(const std::vector<Point> &corners, const std::vector<Mat> &images);
CV_EXPORTS Rect resultRoi(const std::vector<Point> &corners, const std::vector<Size> &sizes);
CV_EXPORTS Point resultTl(const std::vector<Point> &corners);
// Returns random 'count' element subset of the {0,1,...,size-1} set
CV_EXPORTS void selectRandomSubset(int count, int size, std::vector<int> &subset);
CV_EXPORTS int& stitchingLogLevel();
} // namespace detail
} // namespace cv
#include "util_inl.hpp"
#endif // __OPENCV_STITCHING_UTIL_HPP__

View File

@@ -1,127 +1,127 @@
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifndef __OPENCV_STITCHING_UTIL_INL_HPP__
#define __OPENCV_STITCHING_UTIL_INL_HPP__
#include <queue>
#include "opencv2/core/core.hpp"
#include "util.hpp" // Make your IDE see declarations
namespace cv {
namespace detail {
template <typename B>
B Graph::forEach(B body) const
{
for (int i = 0; i < numVertices(); ++i)
{
std::list<GraphEdge>::const_iterator edge = edges_[i].begin();
for (; edge != edges_[i].end(); ++edge)
body(*edge);
}
return body;
}
template <typename B>
B Graph::walkBreadthFirst(int from, B body) const
{
std::vector<bool> was(numVertices(), false);
std::queue<int> vertices;
was[from] = true;
vertices.push(from);
while (!vertices.empty())
{
int vertex = vertices.front();
vertices.pop();
std::list<GraphEdge>::const_iterator edge = edges_[vertex].begin();
for (; edge != edges_[vertex].end(); ++edge)
{
if (!was[edge->to])
{
body(*edge);
was[edge->to] = true;
vertices.push(edge->to);
}
}
}
return body;
}
//////////////////////////////////////////////////////////////////////////////
// Some auxiliary math functions
static inline
float normL2(const Point3f& a)
{
return a.x * a.x + a.y * a.y + a.z * a.z;
}
static inline
float normL2(const Point3f& a, const Point3f& b)
{
return normL2(a - b);
}
static inline
double normL2sq(const Mat &r)
{
return r.dot(r);
}
static inline int sqr(int x) { return x * x; }
static inline float sqr(float x) { return x * x; }
static inline double sqr(double x) { return x * x; }
} // namespace detail
} // namespace cv
#endif // __OPENCV_STITCHING_UTIL_INL_HPP__
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifndef __OPENCV_STITCHING_UTIL_INL_HPP__
#define __OPENCV_STITCHING_UTIL_INL_HPP__
#include <queue>
#include "opencv2/core/core.hpp"
#include "util.hpp" // Make your IDE see declarations
namespace cv {
namespace detail {
template <typename B>
B Graph::forEach(B body) const
{
for (int i = 0; i < numVertices(); ++i)
{
std::list<GraphEdge>::const_iterator edge = edges_[i].begin();
for (; edge != edges_[i].end(); ++edge)
body(*edge);
}
return body;
}
template <typename B>
B Graph::walkBreadthFirst(int from, B body) const
{
std::vector<bool> was(numVertices(), false);
std::queue<int> vertices;
was[from] = true;
vertices.push(from);
while (!vertices.empty())
{
int vertex = vertices.front();
vertices.pop();
std::list<GraphEdge>::const_iterator edge = edges_[vertex].begin();
for (; edge != edges_[vertex].end(); ++edge)
{
if (!was[edge->to])
{
body(*edge);
was[edge->to] = true;
vertices.push(edge->to);
}
}
}
return body;
}
//////////////////////////////////////////////////////////////////////////////
// Some auxiliary math functions
static inline
float normL2(const Point3f& a)
{
return a.x * a.x + a.y * a.y + a.z * a.z;
}
static inline
float normL2(const Point3f& a, const Point3f& b)
{
return normL2(a - b);
}
static inline
double normL2sq(const Mat &r)
{
return r.dot(r);
}
static inline int sqr(int x) { return x * x; }
static inline float sqr(float x) { return x * x; }
static inline double sqr(double x) { return x * x; }
} // namespace detail
} // namespace cv
#endif // __OPENCV_STITCHING_UTIL_INL_HPP__

View File

@@ -218,7 +218,7 @@ public:
struct CV_EXPORTS CompressedRectilinearProjector : ProjectorBase
{
float a, b;
float a, b;
void mapForward(float x, float y, float &u, float &v);
void mapBackward(float u, float v, float &x, float &y);
@@ -239,7 +239,7 @@ public:
struct CV_EXPORTS CompressedRectilinearPortraitProjector : ProjectorBase
{
float a, b;
float a, b;
void mapForward(float x, float y, float &u, float &v);
void mapBackward(float u, float v, float &x, float &y);
@@ -251,8 +251,8 @@ class CV_EXPORTS CompressedRectilinearPortraitWarper : public RotationWarperBase
public:
CompressedRectilinearPortraitWarper(float scale, float A = 1, float B = 1)
{
projector_.a = A;
projector_.b = B;
projector_.a = A;
projector_.b = B;
projector_.scale = scale;
}
};
@@ -260,7 +260,7 @@ public:
struct CV_EXPORTS PaniniProjector : ProjectorBase
{
float a, b;
float a, b;
void mapForward(float x, float y, float &u, float &v);
void mapBackward(float u, float v, float &x, float &y);
@@ -272,8 +272,8 @@ class CV_EXPORTS PaniniWarper : public RotationWarperBase<PaniniProjector>
public:
PaniniWarper(float scale, float A = 1, float B = 1)
{
projector_.a = A;
projector_.b = B;
projector_.a = A;
projector_.b = B;
projector_.scale = scale;
}
};
@@ -281,7 +281,7 @@ public:
struct CV_EXPORTS PaniniPortraitProjector : ProjectorBase
{
float a, b;
float a, b;
void mapForward(float x, float y, float &u, float &v);
void mapBackward(float u, float v, float &x, float &y);
@@ -293,8 +293,8 @@ class CV_EXPORTS PaniniPortraitWarper : public RotationWarperBase<PaniniPortrait
public:
PaniniPortraitWarper(float scale, float A = 1, float B = 1)
{
projector_.a = A;
projector_.b = B;
projector_.a = A;
projector_.b = B;
projector_.scale = scale;
}

View File

@@ -302,27 +302,27 @@ void CylindricalProjector::mapBackward(float u, float v, float &x, float &y)
inline
void FisheyeProjector::mapForward(float x, float y, float &u, float &v)
{
float x_ = r_kinv[0] * x + r_kinv[1] * y + r_kinv[2];
float x_ = r_kinv[0] * x + r_kinv[1] * y + r_kinv[2];
float y_ = r_kinv[3] * x + r_kinv[4] * y + r_kinv[5];
float z_ = r_kinv[6] * x + r_kinv[7] * y + r_kinv[8];
float u_ = atan2f(x_, z_);
float u_ = atan2f(x_, z_);
float v_ = (float)CV_PI - acosf(y_ / sqrtf(x_ * x_ + y_ * y_ + z_ * z_));
u = scale * v_ * cosf(u_);
v = scale * v_ * sinf(u_);
u = scale * v_ * cosf(u_);
v = scale * v_ * sinf(u_);
}
inline
void FisheyeProjector::mapBackward(float u, float v, float &x, float &y)
{
u /= scale;
u /= scale;
v /= scale;
float u_ = atan2f(v, u);
float v_ = sqrtf(u*u + v*v);
float u_ = atan2f(v, u);
float v_ = sqrtf(u*u + v*v);
float sinv = sinf((float)CV_PI - v_);
float sinv = sinf((float)CV_PI - v_);
float x_ = sinv * sinf(u_);
float y_ = cosf((float)CV_PI - v_);
float z_ = sinv * cosf(u_);
@@ -332,37 +332,37 @@ void FisheyeProjector::mapBackward(float u, float v, float &x, float &y)
y = k_rinv[3] * x_ + k_rinv[4] * y_ + k_rinv[5] * z_;
z = k_rinv[6] * x_ + k_rinv[7] * y_ + k_rinv[8] * z_;
if (z > 0) { x /= z; y /= z; }
if (z > 0) { x /= z; y /= z; }
else x = y = -1;
}
inline
void StereographicProjector::mapForward(float x, float y, float &u, float &v)
{
float x_ = r_kinv[0] * x + r_kinv[1] * y + r_kinv[2];
float x_ = r_kinv[0] * x + r_kinv[1] * y + r_kinv[2];
float y_ = r_kinv[3] * x + r_kinv[4] * y + r_kinv[5];
float z_ = r_kinv[6] * x + r_kinv[7] * y + r_kinv[8];
float u_ = atan2f(x_, z_);
float u_ = atan2f(x_, z_);
float v_ = (float)CV_PI - acosf(y_ / sqrtf(x_ * x_ + y_ * y_ + z_ * z_));
float r = sinf(v_) / (1 - cosf(v_));
float r = sinf(v_) / (1 - cosf(v_));
u = scale * r * cos(u_);
v = scale * r * sin(u_);
u = scale * r * cos(u_);
v = scale * r * sin(u_);
}
inline
void StereographicProjector::mapBackward(float u, float v, float &x, float &y)
{
u /= scale;
u /= scale;
v /= scale;
float u_ = atan2f(v, u);
float r = sqrtf(u*u + v*v);
float v_ = 2 * atanf(1.f / r);
float u_ = atan2f(v, u);
float r = sqrtf(u*u + v*v);
float v_ = 2 * atanf(1.f / r);
float sinv = sinf((float)CV_PI - v_);
float sinv = sinf((float)CV_PI - v_);
float x_ = sinv * sinf(u_);
float y_ = cosf((float)CV_PI - v_);
float z_ = sinv * cosf(u_);
@@ -372,33 +372,33 @@ void StereographicProjector::mapBackward(float u, float v, float &x, float &y)
y = k_rinv[3] * x_ + k_rinv[4] * y_ + k_rinv[5] * z_;
z = k_rinv[6] * x_ + k_rinv[7] * y_ + k_rinv[8] * z_;
if (z > 0) { x /= z; y /= z; }
if (z > 0) { x /= z; y /= z; }
else x = y = -1;
}
inline
void CompressedRectilinearProjector::mapForward(float x, float y, float &u, float &v)
{
float x_ = r_kinv[0] * x + r_kinv[1] * y + r_kinv[2];
float x_ = r_kinv[0] * x + r_kinv[1] * y + r_kinv[2];
float y_ = r_kinv[3] * x + r_kinv[4] * y + r_kinv[5];
float z_ = r_kinv[6] * x + r_kinv[7] * y + r_kinv[8];
float u_ = atan2f(x_, z_);
float v_ = asinf(y_ / sqrtf(x_ * x_ + y_ * y_ + z_ * z_));
u = scale * a * tanf(u_ / a);
v = scale * b * tanf(v_) / cosf(u_);
u = scale * a * tanf(u_ / a);
v = scale * b * tanf(v_) / cosf(u_);
}
inline
void CompressedRectilinearProjector::mapBackward(float u, float v, float &x, float &y)
{
u /= scale;
u /= scale;
v /= scale;
float aatg = a * atanf(u / a);
float u_ = aatg;
float v_ = atanf(v * cosf(aatg) / b);
float aatg = a * atanf(u / a);
float u_ = aatg;
float v_ = atanf(v * cosf(aatg) / b);
float cosv = cosf(v_);
float x_ = cosv * sinf(u_);
@@ -417,26 +417,26 @@ void CompressedRectilinearProjector::mapBackward(float u, float v, float &x, flo
inline
void CompressedRectilinearPortraitProjector::mapForward(float x, float y, float &u, float &v)
{
float y_ = r_kinv[0] * x + r_kinv[1] * y + r_kinv[2];
float y_ = r_kinv[0] * x + r_kinv[1] * y + r_kinv[2];
float x_ = r_kinv[3] * x + r_kinv[4] * y + r_kinv[5];
float z_ = r_kinv[6] * x + r_kinv[7] * y + r_kinv[8];
float u_ = atan2f(x_, z_);
float v_ = asinf(y_ / sqrtf(x_ * x_ + y_ * y_ + z_ * z_));
u = - scale * a * tanf(u_ / a);
v = scale * b * tanf(v_) / cosf(u_);
u = - scale * a * tanf(u_ / a);
v = scale * b * tanf(v_) / cosf(u_);
}
inline
void CompressedRectilinearPortraitProjector::mapBackward(float u, float v, float &x, float &y)
{
u /= - scale;
u /= - scale;
v /= scale;
float aatg = a * atanf(u / a);
float u_ = aatg;
float v_ = atanf(v * cosf( aatg ) / b);
float aatg = a * atanf(u / a);
float u_ = aatg;
float v_ = atanf(v * cosf( aatg ) / b);
float cosv = cosf(v_);
float y_ = cosv * sinf(u_);
@@ -455,37 +455,37 @@ void CompressedRectilinearPortraitProjector::mapBackward(float u, float v, float
inline
void PaniniProjector::mapForward(float x, float y, float &u, float &v)
{
float x_ = r_kinv[0] * x + r_kinv[1] * y + r_kinv[2];
float x_ = r_kinv[0] * x + r_kinv[1] * y + r_kinv[2];
float y_ = r_kinv[3] * x + r_kinv[4] * y + r_kinv[5];
float z_ = r_kinv[6] * x + r_kinv[7] * y + r_kinv[8];
float u_ = atan2f(x_, z_);
float v_ = asinf(y_ / sqrtf(x_ * x_ + y_ * y_ + z_ * z_));
float tg = a * tanf(u_ / a);
u = scale * tg;
float tg = a * tanf(u_ / a);
u = scale * tg;
float sinu = sinf(u_);
if ( fabs(sinu) < 1E-7 )
v = scale * b * tanf(v_);
else
v = scale * b * tg * tanf(v_) / sinu;
float sinu = sinf(u_);
if ( fabs(sinu) < 1E-7 )
v = scale * b * tanf(v_);
else
v = scale * b * tg * tanf(v_) / sinu;
}
inline
void PaniniProjector::mapBackward(float u, float v, float &x, float &y)
{
u /= scale;
u /= scale;
v /= scale;
float lamda = a * atanf(u / a);
float u_ = lamda;
float lamda = a * atanf(u / a);
float u_ = lamda;
float v_;
if ( fabs(lamda) > 1E-7)
v_ = atanf(v * sinf(lamda) / (b * a * tanf(lamda / a)));
else
v_ = atanf(v / b);
float v_;
if ( fabs(lamda) > 1E-7)
v_ = atanf(v * sinf(lamda) / (b * a * tanf(lamda / a)));
else
v_ = atanf(v / b);
float cosv = cosf(v_);
float x_ = cosv * sinf(u_);
@@ -504,37 +504,37 @@ void PaniniProjector::mapBackward(float u, float v, float &x, float &y)
inline
void PaniniPortraitProjector::mapForward(float x, float y, float &u, float &v)
{
float y_ = r_kinv[0] * x + r_kinv[1] * y + r_kinv[2];
float y_ = r_kinv[0] * x + r_kinv[1] * y + r_kinv[2];
float x_ = r_kinv[3] * x + r_kinv[4] * y + r_kinv[5];
float z_ = r_kinv[6] * x + r_kinv[7] * y + r_kinv[8];
float u_ = atan2f(x_, z_);
float v_ = asinf(y_ / sqrtf(x_ * x_ + y_ * y_ + z_ * z_));
float tg = a * tanf(u_ / a);
u = - scale * tg;
float tg = a * tanf(u_ / a);
u = - scale * tg;
float sinu = sinf( u_ );
if ( fabs(sinu) < 1E-7 )
v = scale * b * tanf(v_);
else
v = scale * b * tg * tanf(v_) / sinu;
float sinu = sinf( u_ );
if ( fabs(sinu) < 1E-7 )
v = scale * b * tanf(v_);
else
v = scale * b * tg * tanf(v_) / sinu;
}
inline
void PaniniPortraitProjector::mapBackward(float u, float v, float &x, float &y)
{
u /= - scale;
u /= - scale;
v /= scale;
float lamda = a * atanf(u / a);
float u_ = lamda;
float lamda = a * atanf(u / a);
float u_ = lamda;
float v_;
if ( fabs(lamda) > 1E-7)
v_ = atanf(v * sinf(lamda) / (b * a * tanf(lamda/a)));
else
v_ = atanf(v / b);
float v_;
if ( fabs(lamda) > 1E-7)
v_ = atanf(v * sinf(lamda) / (b * a * tanf(lamda/a)));
else
v_ = atanf(v / b);
float cosv = cosf(v_);
float y_ = cosv * sinf(u_);
@@ -553,25 +553,25 @@ void PaniniPortraitProjector::mapBackward(float u, float v, float &x, float &y)
inline
void MercatorProjector::mapForward(float x, float y, float &u, float &v)
{
float x_ = r_kinv[0] * x + r_kinv[1] * y + r_kinv[2];
float x_ = r_kinv[0] * x + r_kinv[1] * y + r_kinv[2];
float y_ = r_kinv[3] * x + r_kinv[4] * y + r_kinv[5];
float z_ = r_kinv[6] * x + r_kinv[7] * y + r_kinv[8];
float u_ = atan2f(x_, z_);
float v_ = asinf(y_ / sqrtf(x_ * x_ + y_ * y_ + z_ * z_));
u = scale * u_;
v = scale * logf( tanf( (float)(CV_PI/4) + v_/2 ) );
u = scale * u_;
v = scale * logf( tanf( (float)(CV_PI/4) + v_/2 ) );
}
inline
void MercatorProjector::mapBackward(float u, float v, float &x, float &y)
{
u /= scale;
u /= scale;
v /= scale;
float v_ = atanf( sinhf(v) );
float u_ = u;
float v_ = atanf( sinhf(v) );
float u_ = u;
float cosv = cosf(v_);
float x_ = cosv * sinf(u_);
@@ -590,27 +590,27 @@ void MercatorProjector::mapBackward(float u, float v, float &x, float &y)
inline
void TransverseMercatorProjector::mapForward(float x, float y, float &u, float &v)
{
float x_ = r_kinv[0] * x + r_kinv[1] * y + r_kinv[2];
float x_ = r_kinv[0] * x + r_kinv[1] * y + r_kinv[2];
float y_ = r_kinv[3] * x + r_kinv[4] * y + r_kinv[5];
float z_ = r_kinv[6] * x + r_kinv[7] * y + r_kinv[8];
float u_ = atan2f(x_, z_);
float v_ = asinf(y_ / sqrtf(x_ * x_ + y_ * y_ + z_ * z_));
float B = cosf(v_) * sinf(u_);
float B = cosf(v_) * sinf(u_);
u = scale / 2 * logf( (1+B) / (1-B) );
v = scale * atan2f(tanf(v_), cosf(u_));
u = scale / 2 * logf( (1+B) / (1-B) );
v = scale * atan2f(tanf(v_), cosf(u_));
}
inline
void TransverseMercatorProjector::mapBackward(float u, float v, float &x, float &y)
{
u /= scale;
u /= scale;
v /= scale;
float v_ = asinf( sinf(v) / coshf(u) );
float u_ = atan2f( sinhf(u), cos(v) );
float v_ = asinf( sinf(v) / coshf(u) );
float u_ = atan2f( sinhf(u), cos(v) );
float cosv = cosf(v_);
float x_ = cosv * sinf(u_);

View File

@@ -89,45 +89,45 @@ public:
class CompressedRectilinearWarper: public WarperCreator
{
float a, b;
float a, b;
public:
CompressedRectilinearWarper(float A = 1, float B = 1)
{
a = A; b = B;
}
CompressedRectilinearWarper(float A = 1, float B = 1)
{
a = A; b = B;
}
Ptr<detail::RotationWarper> create(float scale) const { return new detail::CompressedRectilinearWarper(scale, a, b); }
};
class CompressedRectilinearPortraitWarper: public WarperCreator
{
float a, b;
float a, b;
public:
CompressedRectilinearPortraitWarper(float A = 1, float B = 1)
{
a = A; b = B;
}
CompressedRectilinearPortraitWarper(float A = 1, float B = 1)
{
a = A; b = B;
}
Ptr<detail::RotationWarper> create(float scale) const { return new detail::CompressedRectilinearPortraitWarper(scale, a, b); }
};
class PaniniWarper: public WarperCreator
{
float a, b;
float a, b;
public:
PaniniWarper(float A = 1, float B = 1)
{
a = A; b = B;
}
PaniniWarper(float A = 1, float B = 1)
{
a = A; b = B;
}
Ptr<detail::RotationWarper> create(float scale) const { return new detail::PaniniWarper(scale, a, b); }
};
class PaniniPortraitWarper: public WarperCreator
{
float a, b;
float a, b;
public:
PaniniPortraitWarper(float A = 1, float B = 1)
{
a = A; b = B;
}
PaniniPortraitWarper(float A = 1, float B = 1)
{
a = A; b = B;
}
Ptr<detail::RotationWarper> create(float scale) const { return new detail::PaniniPortraitWarper(scale, a, b); }
};