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251 lines
8.1 KiB
ReStructuredText
251 lines
8.1 KiB
ReStructuredText
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 ()(const Mat &image, ImageFeatures &features)
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.. ocv:function:: void detail::FeaturesFinder::operator ()(const Mat &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(const Mat &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 Mat & mask=Mat() )
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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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