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Class CompositeIndexParams

When using a parameters object of this type the index created combines the randomized kd-trees and the hierarchical k-means tree.

Inheritance
System.Object
DisposableObject
DisposableCvObject
IndexParams
CompositeIndexParams
Implements
ICvPtrHolder
Inherited Members
IndexParams.DisposeManaged()
IndexParams.GetString(String, String)
IndexParams.GetInt(String, Int32)
IndexParams.GetDouble(String, Double)
IndexParams.SetString(String, String)
IndexParams.SetInt(String, Int32)
IndexParams.SetDouble(String, Double)
IndexParams.SetFloat(String, Single)
IndexParams.SetBool(String, Boolean)
IndexParams.SetAlgorithm(Int32)
DisposableCvObject.ptr
DisposableCvObject.CvPtr
DisposableObject.DataHandle
DisposableObject.IsDisposed
DisposableObject.IsEnabledDispose
DisposableObject.AllocatedMemory
DisposableObject.AllocatedMemorySize
DisposableObject.Dispose()
DisposableObject.Dispose(Boolean)
DisposableObject.AllocGCHandle(Object)
DisposableObject.AllocMemory(Int32)
DisposableObject.NotifyMemoryPressure(Int64)
DisposableObject.ThrowIfDisposed()
Namespace: OpenCvSharp.Flann
Assembly: OpenCvSharp.dll
Syntax
public class CompositeIndexParams : IndexParams, ICvPtrHolder

Constructors

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CompositeIndexParams(Ptr)

Declaration
protected CompositeIndexParams(Ptr ptrObj)
Parameters
Type Name Description
Ptr ptrObj
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CompositeIndexParams(Int32, Int32, Int32, FlannCentersInit, Single)

Declaration
public CompositeIndexParams(int trees = 4, int branching = 32, int iterations = 11, FlannCentersInit centersInit = FlannCentersInit.Random, float cbIndex = 0.2F)
Parameters
Type Name Description
System.Int32 trees

The number of parallel kd-trees to use. Good values are in the range [1..16]

System.Int32 branching

The branching factor to use for the hierarchical k-means tree

System.Int32 iterations

The maximum number of iterations to use in the k-means clustering stage when building the k-means tree. A value of -1 used here means that the k-means clustering should be iterated until convergence

FlannCentersInit centersInit

The algorithm to use for selecting the initial centers when performing a k-means clustering step.

System.Single cbIndex

This parameter (cluster boundary index) influences the way exploration is performed in the hierarchical kmeans tree. When cb_index is zero the next kmeans domain to be explored is choosen to be the one with the closest center. A value greater then zero also takes into account the size of the domain.

Methods

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DisposeUnmanaged()

Declaration
protected override void DisposeUnmanaged()
Overrides
IndexParams.DisposeUnmanaged()
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Get()

Declaration
public override IntPtr Get()
Returns
Type Description
IntPtr
Overrides
IndexParams.Get()

Implements

ICvPtrHolder
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