356 lines
12 KiB
C++
356 lines
12 KiB
C++
|
/*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.hpp"
|
||
|
|
#include "opencv2/features2d.hpp"
|
||
|
|
|
||
|
|
#include "opencv2/opencv_modules.hpp"
|
||
|
|
|
||
|
|
#ifdef HAVE_OPENCV_XFEATURES2D
|
||
|
|
# include "opencv2/xfeatures2d/cuda.hpp"
|
||
|
|
#endif
|
||
|
|
|
||
|
|
namespace cv {
|
||
|
|
namespace detail {
|
||
|
|
|
||
|
|
//! @addtogroup stitching_match
|
||
|
|
//! @{
|
||
|
|
|
||
|
|
/** @brief Structure containing image keypoints and descriptors. */
|
||
|
|
struct CV_EXPORTS ImageFeatures
|
||
|
|
{
|
||
|
|
int img_idx;
|
||
|
|
Size img_size;
|
||
|
|
std::vector<KeyPoint> keypoints;
|
||
|
|
UMat descriptors;
|
||
|
|
};
|
||
|
|
|
||
|
|
/** @brief Feature finders base class */
|
||
|
|
class CV_EXPORTS FeaturesFinder
|
||
|
|
{
|
||
|
|
public:
|
||
|
|
virtual ~FeaturesFinder() {}
|
||
|
|
/** @overload */
|
||
|
|
void operator ()(InputArray image, ImageFeatures &features);
|
||
|
|
/** @brief Finds features in the given image.
|
||
|
|
|
||
|
|
@param image Source image
|
||
|
|
@param features Found features
|
||
|
|
@param rois Regions of interest
|
||
|
|
|
||
|
|
@sa detail::ImageFeatures, Rect_
|
||
|
|
*/
|
||
|
|
void operator ()(InputArray image, ImageFeatures &features, const std::vector<cv::Rect> &rois);
|
||
|
|
/** @brief Finds features in the given images in parallel.
|
||
|
|
|
||
|
|
@param images Source images
|
||
|
|
@param features Found features for each image
|
||
|
|
@param rois Regions of interest for each image
|
||
|
|
|
||
|
|
@sa detail::ImageFeatures, Rect_
|
||
|
|
*/
|
||
|
|
void operator ()(InputArrayOfArrays images, std::vector<ImageFeatures> &features,
|
||
|
|
const std::vector<std::vector<cv::Rect> > &rois);
|
||
|
|
/** @overload */
|
||
|
|
void operator ()(InputArrayOfArrays images, std::vector<ImageFeatures> &features);
|
||
|
|
/** @brief Frees unused memory allocated before if there is any. */
|
||
|
|
virtual void collectGarbage() {}
|
||
|
|
|
||
|
|
/* TODO OpenCV ABI 4.x
|
||
|
|
reimplement this as public method similar to FeaturesMatcher and remove private function hack
|
||
|
|
@return True, if it's possible to use the same finder instance in parallel, false otherwise
|
||
|
|
bool isThreadSafe() const { return is_thread_safe_; }
|
||
|
|
*/
|
||
|
|
|
||
|
|
protected:
|
||
|
|
/** @brief This method must implement features finding logic in order to make the wrappers
|
||
|
|
detail::FeaturesFinder::operator()_ work.
|
||
|
|
|
||
|
|
@param image Source image
|
||
|
|
@param features Found features
|
||
|
|
|
||
|
|
@sa detail::ImageFeatures */
|
||
|
|
virtual void find(InputArray image, ImageFeatures &features) = 0;
|
||
|
|
/** @brief uses dynamic_cast to determine thread-safety
|
||
|
|
@return True, if it's possible to use the same finder instance in parallel, false otherwise
|
||
|
|
*/
|
||
|
|
bool isThreadSafe() const;
|
||
|
|
};
|
||
|
|
|
||
|
|
/** @brief SURF features finder.
|
||
|
|
|
||
|
|
@sa detail::FeaturesFinder, SURF
|
||
|
|
*/
|
||
|
|
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(InputArray image, ImageFeatures &features);
|
||
|
|
|
||
|
|
Ptr<FeatureDetector> detector_;
|
||
|
|
Ptr<DescriptorExtractor> extractor_;
|
||
|
|
Ptr<Feature2D> surf;
|
||
|
|
};
|
||
|
|
|
||
|
|
/** @brief ORB features finder. :
|
||
|
|
|
||
|
|
@sa detail::FeaturesFinder, ORB
|
||
|
|
*/
|
||
|
|
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(InputArray image, ImageFeatures &features);
|
||
|
|
|
||
|
|
Ptr<ORB> orb;
|
||
|
|
Size grid_size;
|
||
|
|
};
|
||
|
|
|
||
|
|
/** @brief AKAZE features finder. :
|
||
|
|
|
||
|
|
@sa detail::FeaturesFinder, AKAZE
|
||
|
|
*/
|
||
|
|
class CV_EXPORTS AKAZEFeaturesFinder : public detail::FeaturesFinder
|
||
|
|
{
|
||
|
|
public:
|
||
|
|
AKAZEFeaturesFinder(int descriptor_type = AKAZE::DESCRIPTOR_MLDB,
|
||
|
|
int descriptor_size = 0,
|
||
|
|
int descriptor_channels = 3,
|
||
|
|
float threshold = 0.001f,
|
||
|
|
int nOctaves = 4,
|
||
|
|
int nOctaveLayers = 4,
|
||
|
|
int diffusivity = KAZE::DIFF_PM_G2);
|
||
|
|
|
||
|
|
private:
|
||
|
|
void find(InputArray image, detail::ImageFeatures &features);
|
||
|
|
|
||
|
|
Ptr<AKAZE> akaze;
|
||
|
|
};
|
||
|
|
|
||
|
|
#ifdef HAVE_OPENCV_XFEATURES2D
|
||
|
|
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(InputArray image, ImageFeatures &features);
|
||
|
|
|
||
|
|
cuda::GpuMat image_;
|
||
|
|
cuda::GpuMat gray_image_;
|
||
|
|
cuda::SURF_CUDA surf_;
|
||
|
|
cuda::GpuMat keypoints_;
|
||
|
|
cuda::GpuMat descriptors_;
|
||
|
|
int num_octaves_, num_layers_;
|
||
|
|
int num_octaves_descr_, num_layers_descr_;
|
||
|
|
};
|
||
|
|
#endif
|
||
|
|
|
||
|
|
/** @brief Structure containing information about matches between two images.
|
||
|
|
|
||
|
|
It's assumed that there is a transformation between those images. Transformation may be
|
||
|
|
homography or affine transformation based on selected matcher.
|
||
|
|
|
||
|
|
@sa detail::FeaturesMatcher
|
||
|
|
*/
|
||
|
|
struct CV_EXPORTS MatchesInfo
|
||
|
|
{
|
||
|
|
MatchesInfo();
|
||
|
|
MatchesInfo(const MatchesInfo &other);
|
||
|
|
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 transformation
|
||
|
|
double confidence; //!< Confidence two images are from the same panorama
|
||
|
|
};
|
||
|
|
|
||
|
|
/** @brief Feature matchers base class. */
|
||
|
|
class CV_EXPORTS FeaturesMatcher
|
||
|
|
{
|
||
|
|
public:
|
||
|
|
virtual ~FeaturesMatcher() {}
|
||
|
|
|
||
|
|
/** @overload
|
||
|
|
@param features1 First image features
|
||
|
|
@param features2 Second image features
|
||
|
|
@param matches_info Found matches
|
||
|
|
*/
|
||
|
|
void operator ()(const ImageFeatures &features1, const ImageFeatures &features2,
|
||
|
|
MatchesInfo& matches_info) { match(features1, features2, matches_info); }
|
||
|
|
|
||
|
|
/** @brief Performs images matching.
|
||
|
|
|
||
|
|
@param features Features of the source images
|
||
|
|
@param pairwise_matches Found pairwise matches
|
||
|
|
@param mask Mask indicating which image pairs must be matched
|
||
|
|
|
||
|
|
The function is parallelized with the TBB library.
|
||
|
|
|
||
|
|
@sa detail::MatchesInfo
|
||
|
|
*/
|
||
|
|
void operator ()(const std::vector<ImageFeatures> &features, std::vector<MatchesInfo> &pairwise_matches,
|
||
|
|
const cv::UMat &mask = cv::UMat());
|
||
|
|
|
||
|
|
/** @return True, if it's possible to use the same matcher instance in parallel, false otherwise
|
||
|
|
*/
|
||
|
|
bool isThreadSafe() const { return is_thread_safe_; }
|
||
|
|
|
||
|
|
/** @brief Frees unused memory allocated before if there is any.
|
||
|
|
*/
|
||
|
|
virtual void collectGarbage() {}
|
||
|
|
|
||
|
|
protected:
|
||
|
|
FeaturesMatcher(bool is_thread_safe = false) : is_thread_safe_(is_thread_safe) {}
|
||
|
|
|
||
|
|
/** @brief This method must implement matching logic in order to make the wrappers
|
||
|
|
detail::FeaturesMatcher::operator()_ work.
|
||
|
|
|
||
|
|
@param features1 first image features
|
||
|
|
@param features2 second image features
|
||
|
|
@param matches_info found matches
|
||
|
|
*/
|
||
|
|
virtual void match(const ImageFeatures &features1, const ImageFeatures &features2,
|
||
|
|
MatchesInfo& matches_info) = 0;
|
||
|
|
|
||
|
|
bool is_thread_safe_;
|
||
|
|
};
|
||
|
|
|
||
|
|
/** @brief Features matcher which finds two best matches for each feature and leaves the best one only if the
|
||
|
|
ratio between descriptor distances is greater than the threshold match_conf
|
||
|
|
|
||
|
|
@sa detail::FeaturesMatcher
|
||
|
|
*/
|
||
|
|
class CV_EXPORTS BestOf2NearestMatcher : public FeaturesMatcher
|
||
|
|
{
|
||
|
|
public:
|
||
|
|
/** @brief Constructs a "best of 2 nearest" matcher.
|
||
|
|
|
||
|
|
@param try_use_gpu Should try to use GPU or not
|
||
|
|
@param match_conf Match distances ration threshold
|
||
|
|
@param num_matches_thresh1 Minimum number of matches required for the 2D projective transform
|
||
|
|
estimation used in the inliers classification step
|
||
|
|
@param num_matches_thresh2 Minimum number of matches required for the 2D projective transform
|
||
|
|
re-estimation on inliers
|
||
|
|
*/
|
||
|
|
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_;
|
||
|
|
};
|
||
|
|
|
||
|
|
class CV_EXPORTS BestOf2NearestRangeMatcher : public BestOf2NearestMatcher
|
||
|
|
{
|
||
|
|
public:
|
||
|
|
BestOf2NearestRangeMatcher(int range_width = 5, bool try_use_gpu = false, float match_conf = 0.3f,
|
||
|
|
int num_matches_thresh1 = 6, int num_matches_thresh2 = 6);
|
||
|
|
|
||
|
|
void operator ()(const std::vector<ImageFeatures> &features, std::vector<MatchesInfo> &pairwise_matches,
|
||
|
|
const cv::UMat &mask = cv::UMat());
|
||
|
|
|
||
|
|
|
||
|
|
protected:
|
||
|
|
int range_width_;
|
||
|
|
};
|
||
|
|
|
||
|
|
/** @brief Features matcher similar to cv::detail::BestOf2NearestMatcher which
|
||
|
|
finds two best matches for each feature and leaves the best one only if the
|
||
|
|
ratio between descriptor distances is greater than the threshold match_conf.
|
||
|
|
|
||
|
|
Unlike cv::detail::BestOf2NearestMatcher this matcher uses affine
|
||
|
|
transformation (affine trasformation estimate will be placed in matches_info).
|
||
|
|
|
||
|
|
@sa cv::detail::FeaturesMatcher cv::detail::BestOf2NearestMatcher
|
||
|
|
*/
|
||
|
|
class CV_EXPORTS AffineBestOf2NearestMatcher : public BestOf2NearestMatcher
|
||
|
|
{
|
||
|
|
public:
|
||
|
|
/** @brief Constructs a "best of 2 nearest" matcher that expects affine trasformation
|
||
|
|
between images
|
||
|
|
|
||
|
|
@param full_affine whether to use full affine transformation with 6 degress of freedom or reduced
|
||
|
|
transformation with 4 degrees of freedom using only rotation, translation and uniform scaling
|
||
|
|
@param try_use_gpu Should try to use GPU or not
|
||
|
|
@param match_conf Match distances ration threshold
|
||
|
|
@param num_matches_thresh1 Minimum number of matches required for the 2D affine transform
|
||
|
|
estimation used in the inliers classification step
|
||
|
|
|
||
|
|
@sa cv::estimateAffine2D cv::estimateAffinePartial2D
|
||
|
|
*/
|
||
|
|
AffineBestOf2NearestMatcher(bool full_affine = false, bool try_use_gpu = false,
|
||
|
|
float match_conf = 0.3f, int num_matches_thresh1 = 6) :
|
||
|
|
BestOf2NearestMatcher(try_use_gpu, match_conf, num_matches_thresh1, num_matches_thresh1),
|
||
|
|
full_affine_(full_affine) {}
|
||
|
|
|
||
|
|
protected:
|
||
|
|
void match(const ImageFeatures &features1, const ImageFeatures &features2, MatchesInfo &matches_info);
|
||
|
|
|
||
|
|
bool full_affine_;
|
||
|
|
};
|
||
|
|
|
||
|
|
//! @} stitching_match
|
||
|
|
|
||
|
|
} // namespace detail
|
||
|
|
} // namespace cv
|
||
|
|
|
||
|
|
#endif // OPENCV_STITCHING_MATCHERS_HPP
|