Module features2d

Expand description

§Features Framework

§Feature Detection and Description

§Descriptor Matchers

Matchers of keypoint descriptors in OpenCV have wrappers with a common interface that enables you to easily switch between different algorithms solving the same problem. This section is devoted to matching descriptors that are represented as vectors in a multidimensional space. All objects that implement vector descriptor matchers inherit the DescriptorMatcher interface.

§Drawing Function of Keypoints and Matches

§Hardware Acceleration Layer

§Approximate Nearest Neighbors Search in Multi-Dimensional Spaces

This section documents OpenCV’s interface to the Annoy. Annoy (Approximate Nearest Neighbors Oh Yeah) is a library to search for points in space that are close to a given query point. It also creates large read-only file-based data structures that are mmapped into memory so that many processes may share the same data.

Modules§

prelude

Structs§

ALIKED: ALIKED feature detector and descriptor extractor.
ALIKED_Params
ANNIndex
AffineFeature: Class for implementing the wrapper which makes detectors and extractors to be affine invariant, described as ASIFT in YM11 .
BFMatcher: Brute-force descriptor matcher.
DISK: DISK feature detector and descriptor, based on a DNN model.
DescriptorMatcher: Abstract base class for matching keypoint descriptors.
DrawMatchesFlags
FastFeatureDetector: Wrapping class for feature detection using the FAST method.
Feature2D: Abstract base class for 2D image feature detectors and descriptor extractors
FlannBasedMatcher: Flann-based descriptor matcher.
GFTTDetector: Wrapping class for feature detection using the goodFeaturesToTrack function. :
KeyPointsFilter: A class filters a vector of keypoints.
LightGlueMatcher: LightGlue feature matcher.
MSER: Maximally stable extremal region extractor
ORB: Class implementing the ORB (oriented BRIEF) keypoint detector and descriptor extractor
SIFT: Class for extracting keypoints and computing descriptors using the Scale Invariant Feature Transform (SIFT) algorithm by D. Lowe Lowe04 .
SimpleBlobDetector: Class for extracting blobs from an image. :
SimpleBlobDetector_Params

Enums§

ANNIndex_Distance: Metrics used to calculate the distance between two feature vectors.
DescriptorMatcher_MatcherType
FastFeatureDetector_DetectorType
ORB_ScoreType

Constants§

ANNIndex_DIST_ANGULAR
ANNIndex_DIST_DOTPRODUCT
ANNIndex_DIST_EUCLIDEAN
ANNIndex_DIST_HAMMING
ANNIndex_DIST_MANHATTAN
DescriptorMatcher_BRUTEFORCE
DescriptorMatcher_BRUTEFORCE_HAMMING
DescriptorMatcher_BRUTEFORCE_HAMMINGLUT
DescriptorMatcher_BRUTEFORCE_L1
DescriptorMatcher_BRUTEFORCE_SL2
DescriptorMatcher_FLANNBASED
DrawMatchesFlags_DEFAULT: Output image matrix will be created (Mat::create), i.e. existing memory of output image may be reused. Two source image, matches and single keypoints will be drawn. For each keypoint only the center point will be drawn (without the circle around keypoint with keypoint size and orientation).
DrawMatchesFlags_DRAW_OVER_OUTIMG: Output image matrix will not be created (Mat::create). Matches will be drawn on existing content of output image.
DrawMatchesFlags_DRAW_RICH_KEYPOINTS: For each keypoint the circle around keypoint with keypoint size and orientation will be drawn.
DrawMatchesFlags_NOT_DRAW_SINGLE_POINTS: Single keypoints will not be drawn.
FastFeatureDetector_FAST_N
FastFeatureDetector_NONMAX_SUPPRESSION
FastFeatureDetector_THRESHOLD
FastFeatureDetector_TYPE_5_8
FastFeatureDetector_TYPE_7_12
FastFeatureDetector_TYPE_9_16
ORB_FAST_SCORE
ORB_HARRIS_SCORE

Traits§

ALIKEDTrait: Mutable methods for crate::features::ALIKED
ALIKEDTraitConst: Constant methods for crate::features::ALIKED
ANNIndexTrait: Mutable methods for crate::features::ANNIndex
ANNIndexTraitConst: Constant methods for crate::features::ANNIndex
AffineFeatureTrait: Mutable methods for crate::features::AffineFeature
AffineFeatureTraitConst: Constant methods for crate::features::AffineFeature
BFMatcherTrait: Mutable methods for crate::features::BFMatcher
BFMatcherTraitConst: Constant methods for crate::features::BFMatcher
DISKTrait: Mutable methods for crate::features::DISK
DISKTraitConst: Constant methods for crate::features::DISK
DescriptorMatcherTrait: Mutable methods for crate::features::DescriptorMatcher
DescriptorMatcherTraitConst: Constant methods for crate::features::DescriptorMatcher
FastFeatureDetectorTrait: Mutable methods for crate::features::FastFeatureDetector
FastFeatureDetectorTraitConst: Constant methods for crate::features::FastFeatureDetector
Feature2DTrait: Mutable methods for crate::features::Feature2D
Feature2DTraitConst: Constant methods for crate::features::Feature2D
FlannBasedMatcherTrait: Mutable methods for crate::features::FlannBasedMatcher
FlannBasedMatcherTraitConst: Constant methods for crate::features::FlannBasedMatcher
GFTTDetectorTrait: Mutable methods for crate::features::GFTTDetector
GFTTDetectorTraitConst: Constant methods for crate::features::GFTTDetector
KeyPointsFilterTrait: Mutable methods for crate::features::KeyPointsFilter
KeyPointsFilterTraitConst: Constant methods for crate::features::KeyPointsFilter
LightGlueMatcherTrait: Mutable methods for crate::features::LightGlueMatcher
LightGlueMatcherTraitConst: Constant methods for crate::features::LightGlueMatcher
MSERTrait: Mutable methods for crate::features::MSER
MSERTraitConst: Constant methods for crate::features::MSER
ORBTrait: Mutable methods for crate::features::ORB
ORBTraitConst: Constant methods for crate::features::ORB
SIFTTrait: Mutable methods for crate::features::SIFT
SIFTTraitConst: Constant methods for crate::features::SIFT
SimpleBlobDetectorTrait: Mutable methods for crate::features::SimpleBlobDetector
SimpleBlobDetectorTraitConst: Constant methods for crate::features::SimpleBlobDetector

Functions§

compute_recall_precision_curve
draw_keypoints: Draws keypoints.
draw_keypoints_def: Draws keypoints.
draw_matches: Draws the found matches of keypoints from two images.
draw_matches_def: Draws the found matches of keypoints from two images.
draw_matches_knn: C++ default parameters
draw_matches_knn_def: Note
draw_matches_with_thickness: Draws the found matches of keypoints from two images.
draw_matches_with_thickness_def: Draws the found matches of keypoints from two images.
evaluate_feature_detector: C++ default parameters
evaluate_feature_detector_def: Note
fast_with_type: Detects corners using the FAST algorithm
fast_with_type_def: Detects corners using the FAST algorithm
get_nearest_point
get_recall
good_features_to_track: Determines strong corners on an image.
good_features_to_track_1: C++ default parameters
good_features_to_track_1_def: Note
good_features_to_track_def: Determines strong corners on an image.
good_features_to_track_with_quality: Same as above, but returns also quality measure of the detected corners.
good_features_to_track_with_quality_def: Same as above, but returns also quality measure of the detected corners.

Type Aliases§

AffineDescriptorExtractor
AffineFeatureDetector
DescriptorExtractor: Extractors of keypoint descriptors in OpenCV have wrappers with a common interface that enables you to easily switch between different algorithms solving the same problem. This section is devoted to computing descriptors represented as vectors in a multidimensional space. All objects that implement the vector descriptor extractors inherit the DescriptorExtractor interface.
FeatureDetector: Feature detectors in OpenCV have wrappers with a common interface that enables you to easily switch between different algorithms solving the same problem. All objects that implement keypoint detectors inherit the FeatureDetector interface.
SiftDescriptorExtractor
SiftFeatureDetector