org.opencv.features2d

Class BOWTrainer

java.lang.Object

org.opencv.features2d.BOWTrainer

Direct Known Subclasses:

BOWKMeansTrainer

public class BOWTrainer
extends Object

Abstract base class for training the *bag of visual words* vocabulary from a set of descriptors. For details, see, for example, *Visual Categorization with Bags of Keypoints* by Gabriella Csurka, Christopher R. Dance, Lixin Fan, Jutta Willamowski, Cedric Bray, 2004. :

Field Summary

Fields

Modifier and Type	Field and Description
protected long	nativeObj

Constructor Summary

Constructors

Modifier	Constructor and Description
protected	BOWTrainer(long addr)

Method Summary

Modifier and Type	Method and Description
static BOWTrainer	__fromPtr__(long addr)
void	add(Mat descriptors) Adds descriptors to a training set.
void	clear()
Mat	cluster()
Mat	cluster(Mat descriptors) Clusters train descriptors.
int	descriptorsCount() Returns the count of all descriptors stored in the training set.
protected void	finalize()
List<Mat>	getDescriptors() Returns a training set of descriptors.
long	getNativeObjAddr()

Methods inherited from class java.lang.Object

clone, equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

nativeObj

protected final long nativeObj

Constructor Detail

BOWTrainer

protected BOWTrainer(long addr)

Method Detail

getNativeObjAddr

public long getNativeObjAddr()

__fromPtr__

public static BOWTrainer __fromPtr__(long addr)

cluster

public Mat cluster(Mat descriptors)

Clusters train descriptors.

Parameters:

descriptors - Descriptors to cluster. Each row of the descriptors matrix is a descriptor. Descriptors are not added to the inner train descriptor set. The vocabulary consists of cluster centers. So, this method returns the vocabulary. In the first variant of the method, train descriptors stored in the object are clustered. In the second variant, input descriptors are clustered.

Returns:

automatically generated

cluster

public Mat cluster()

descriptorsCount

public int descriptorsCount()

Returns the count of all descriptors stored in the training set.

Returns:

automatically generated

getDescriptors

public List<Mat> getDescriptors()

Returns a training set of descriptors.

Returns:

automatically generated

add

public void add(Mat descriptors)

Adds descriptors to a training set.

Parameters:

descriptors - Descriptors to add to a training set. Each row of the descriptors matrix is a descriptor. The training set is clustered using clustermethod to construct the vocabulary.

clear

public void clear()

finalize

protected void finalize()
                 throws Throwable

Overrides:

finalize in class Object

Throws:

Throwable