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Open Source Computer Vision Library
https://opencv.org/
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250 lines
8.1 KiB
250 lines
8.1 KiB
Features Finding and Images Matching |
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==================================== |
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.. highlight:: cpp |
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detail::ImageFeatures |
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----------------------- |
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.. ocv:struct:: detail::ImageFeatures |
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Structure containing image keypoints and descriptors. :: |
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struct CV_EXPORTS ImageFeatures |
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{ |
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int img_idx; |
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Size img_size; |
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std::vector<KeyPoint> keypoints; |
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Mat descriptors; |
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}; |
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detail::FeaturesFinder |
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---------------------- |
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.. ocv:class:: detail::FeaturesFinder |
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Feature finders base class. :: |
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class CV_EXPORTS FeaturesFinder |
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{ |
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public: |
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virtual ~FeaturesFinder() {} |
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void operator ()(const Mat &image, ImageFeatures &features); |
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void operator ()(const Mat &image, ImageFeatures &features, const std::vector<cv::Rect> &rois); |
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virtual void collectGarbage() {} |
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protected: |
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virtual void find(const Mat &image, ImageFeatures &features) = 0; |
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}; |
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detail::FeaturesFinder::operator() |
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---------------------------------- |
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Finds features in the given image. |
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.. ocv:function:: void detail::FeaturesFinder::operator ()(InputArray image, ImageFeatures &features) |
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.. ocv:function:: void detail::FeaturesFinder::operator ()(InputArray image, ImageFeatures &features, const std::vector<cv::Rect> &rois) |
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:param image: Source image |
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:param features: Found features |
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:param rois: Regions of interest |
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.. seealso:: :ocv:struct:`detail::ImageFeatures`, :ocv:class:`Rect_` |
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detail::FeaturesFinder::collectGarbage |
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-------------------------------------- |
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Frees unused memory allocated before if there is any. |
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.. ocv:function:: void detail::FeaturesFinder::collectGarbage() |
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detail::FeaturesFinder::find |
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---------------------------- |
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This method must implement features finding logic in order to make the wrappers `detail::FeaturesFinder::operator()`_ work. |
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.. ocv:function:: void detail::FeaturesFinder::find(InputArray image, ImageFeatures &features) |
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:param image: Source image |
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:param features: Found features |
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.. seealso:: :ocv:struct:`detail::ImageFeatures` |
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detail::SurfFeaturesFinder |
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-------------------------- |
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.. ocv:class:: detail::SurfFeaturesFinder : public detail::FeaturesFinder |
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SURF features finder. :: |
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class CV_EXPORTS SurfFeaturesFinder : public FeaturesFinder |
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{ |
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public: |
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SurfFeaturesFinder(double hess_thresh = 300., int num_octaves = 3, int num_layers = 4, |
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int num_octaves_descr = /*4*/3, int num_layers_descr = /*2*/4); |
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private: |
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/* hidden */ |
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}; |
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.. seealso:: :ocv:class:`detail::FeaturesFinder`, :ocv:class:`SURF` |
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detail::OrbFeaturesFinder |
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------------------------- |
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.. ocv:class:: detail::OrbFeaturesFinder : public detail::FeaturesFinder |
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ORB features finder. :: |
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class CV_EXPORTS OrbFeaturesFinder : public FeaturesFinder |
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{ |
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public: |
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OrbFeaturesFinder(Size _grid_size = Size(3,1), size_t n_features = 1500, |
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const ORB::CommonParams &detector_params = ORB::CommonParams(1.3f, 5)); |
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private: |
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/* hidden */ |
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}; |
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.. seealso:: :ocv:class:`detail::FeaturesFinder`, :ocv:class:`ORB` |
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detail::MatchesInfo |
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------------------- |
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.. ocv:struct:: detail::MatchesInfo |
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Structure containing information about matches between two images. It's assumed that there is a homography between those images. :: |
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struct CV_EXPORTS MatchesInfo |
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{ |
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MatchesInfo(); |
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MatchesInfo(const MatchesInfo &other); |
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const MatchesInfo& operator =(const MatchesInfo &other); |
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int src_img_idx, dst_img_idx; // Images indices (optional) |
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std::vector<DMatch> matches; |
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std::vector<uchar> inliers_mask; // Geometrically consistent matches mask |
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int num_inliers; // Number of geometrically consistent matches |
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Mat H; // Estimated homography |
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double confidence; // Confidence two images are from the same panorama |
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}; |
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detail::FeaturesMatcher |
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----------------------- |
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.. ocv:class:: detail::FeaturesMatcher |
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Feature matchers base class. :: |
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class CV_EXPORTS FeaturesMatcher |
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{ |
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public: |
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virtual ~FeaturesMatcher() {} |
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void operator ()(const ImageFeatures &features1, const ImageFeatures &features2, |
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MatchesInfo& matches_info) { match(features1, features2, matches_info); } |
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void operator ()(const std::vector<ImageFeatures> &features, std::vector<MatchesInfo> &pairwise_matches, |
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const Mat &mask = cv::Mat()); |
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bool isThreadSafe() const { return is_thread_safe_; } |
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virtual void collectGarbage() {} |
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protected: |
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FeaturesMatcher(bool is_thread_safe = false) : is_thread_safe_(is_thread_safe) {} |
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virtual void match(const ImageFeatures &features1, const ImageFeatures &features2, |
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MatchesInfo& matches_info) = 0; |
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bool is_thread_safe_; |
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}; |
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detail::FeaturesMatcher::operator() |
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----------------------------------- |
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Performs images matching. |
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.. ocv:function:: void detail::FeaturesMatcher::operator ()(const ImageFeatures &features1, const ImageFeatures &features2, MatchesInfo& matches_info) |
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:param features1: First image features |
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:param features2: Second image features |
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:param matches_info: Found matches |
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.. ocv:function:: void detail::FeaturesMatcher::operator ()( const std::vector<ImageFeatures> & features, std::vector<MatchesInfo> & pairwise_matches, const UMat & mask=UMat() ) |
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:param features: Features of the source images |
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:param pairwise_matches: Found pairwise matches |
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:param mask: Mask indicating which image pairs must be matched |
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The function is parallelized with the TBB library. |
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.. seealso:: :ocv:struct:`detail::MatchesInfo` |
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detail::FeaturesMatcher::isThreadSafe |
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------------------------------------- |
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.. ocv:function:: bool detail::FeaturesMatcher::isThreadSafe() const |
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:return: True, if it's possible to use the same matcher instance in parallel, false otherwise |
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detail::FeaturesMatcher::collectGarbage |
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--------------------------------------- |
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Frees unused memory allocated before if there is any. |
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.. ocv:function:: void detail::FeaturesMatcher::collectGarbage() |
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detail::FeaturesMatcher::match |
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------------------------------ |
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This method must implement matching logic in order to make the wrappers `detail::FeaturesMatcher::operator()`_ work. |
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.. ocv:function:: void detail::FeaturesMatcher::match(const ImageFeatures &features1, const ImageFeatures &features2, MatchesInfo& matches_info) |
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:param features1: first image features |
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:param features2: second image features |
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:param matches_info: found matches |
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detail::BestOf2NearestMatcher |
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----------------------------- |
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.. ocv:class:: detail::BestOf2NearestMatcher : public detail::FeaturesMatcher |
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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``. :: |
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class CV_EXPORTS BestOf2NearestMatcher : public FeaturesMatcher |
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{ |
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public: |
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BestOf2NearestMatcher(bool try_use_gpu = false, float match_conf = 0.65f, |
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int num_matches_thresh1 = 6, int num_matches_thresh2 = 6); |
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void collectGarbage(); |
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protected: |
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void match(const ImageFeatures &features1, const ImageFeatures &features2, MatchesInfo &matches_info); |
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int num_matches_thresh1_; |
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int num_matches_thresh2_; |
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Ptr<FeaturesMatcher> impl_; |
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}; |
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.. seealso:: :ocv:class:`detail::FeaturesMatcher` |
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detail::BestOf2NearestMatcher::BestOf2NearestMatcher |
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---------------------------------------------------- |
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Constructs a "best of 2 nearest" matcher. |
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.. ocv:function:: detail::BestOf2NearestMatcher::BestOf2NearestMatcher(bool try_use_gpu = false, float match_conf = 0.3f, int num_matches_thresh1 = 6, int num_matches_thresh2 = 6) |
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:param try_use_gpu: Should try to use GPU or not |
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:param match_conf: Match distances ration threshold |
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:param num_matches_thresh1: Minimum number of matches required for the 2D projective transform estimation used in the inliers classification step |
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:param num_matches_thresh2: Minimum number of matches required for the 2D projective transform re-estimation on inliers
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