Class DescriptorMatcher

Namespace

OpenCvSharp

Assembly

OpenCvSharp.dll

public class DescriptorMatcher : Algorithm, IDisposable

Inheritance

object

CvObject

CvPtrObject

Algorithm

DescriptorMatcher

Implements

IDisposable

Derived

BFMatcher

FlannBasedMatcher

LightGlueMatcher

Inherited Members

Algorithm.Write(FileStorage)

Algorithm.Read(FileNode)

Algorithm.Save(string)

Algorithm.GetDefaultName()

CvPtrObject.RawPtr

CvObject.IsDisposed

CvObject.ptr

CvObject.SetSafeHandle(OpenCvSafeHandle)

CvObject.SetPostReleaseAction(Action)

CvObject.Dispose()

CvObject.Dispose(bool)

CvObject.DisposeManaged()

CvObject.DisposeUnmanaged()

CvObject.ThrowIfDisposed()

CvObject.CvPtr

object.Equals(object)

object.Equals(object, object)

object.GetHashCode()

object.GetType()

object.MemberwiseClone()

object.ReferenceEquals(object, object)

object.ToString()

Constructors

DescriptorMatcher(nint, Action<nint>)

DescriptorMatcher(nint, nint, Action<nint>)

Methods

Add(IEnumerable<Mat>)

Add descriptors to train descriptor collection.

Clear()

Clear train descriptors collection.

Create(MatcherType)

Creates a descriptor matcher of a given type with the default parameters (using default constructor).

Create(string)

Create descriptor matcher by type name.

Empty()

Return true if there are not train descriptors in collection.

GetTrainDescriptors()

Get train descriptors collection.

IsMaskSupported()

Return true if the matcher supports mask in match methods.

KnnMatch(Mat, Mat, int, Mat?, bool)

Find k best matches for each query descriptor (in increasing order of distances). compactResult is used when mask is not empty. If compactResult is false matches vector will have the same size as queryDescriptors rows. If compactResult is true matches vector will not contain matches for fully masked out query descriptors.

KnnMatch(Mat, int, Mat[]?, bool)

Find k best matches for each query descriptor (in increasing order of distances). compactResult is used when mask is not empty. If compactResult is false matches vector will have the same size as queryDescriptors rows. If compactResult is true matches vector will not contain matches for fully masked out query descriptors.

Match(Mat, Mat, Mat?)

Find one best match for each query descriptor (if mask is empty).

Match(Mat, Mat[]?)

Find one best match for each query descriptor (if mask is empty).

RadiusMatch(Mat, Mat, float, Mat?, bool)

Find best matches for each query descriptor which have distance less than maxDistance (in increasing order of distances).

RadiusMatch(Mat, float, Mat[]?, bool)

Find best matches for each query descriptor which have distance less than maxDistance (in increasing order of distances).

Train()

Train matcher (e.g. train flann index). In all methods to match the method train() is run every time before matching. Some descriptor matchers (e.g. BruteForceMatcher) have empty implementation of this method, other matchers really train their inner structures (e.g. FlannBasedMatcher trains flann::Index). So nonempty implementation of train() should check the class object state and do traing/retraining only if the state requires that (e.g. FlannBasedMatcher trains flann::Index if it has not trained yet or if new descriptors have been added to the train collection).