Abstract base class for training the bag of visual words vocabulary from a set of descriptors. More...

#include <features2d.hpp>

Inheritance diagram for cv::BOWTrainer:

Public Member Functions
	BOWTrainer ()

virtual	~BOWTrainer ()

CV_WRAP void	add (const Mat &descriptors)
	Adds descriptors to a training set. More...

CV_WRAP const std::vector< Mat > &	getDescriptors () const
	Returns a training set of descriptors. More...

CV_WRAP int	descriptorsCount () const
	Returns the count of all descriptors stored in the training set. More...

virtual CV_WRAP void	clear ()

virtual CV_WRAP Mat	cluster () const =0

virtual CV_WRAP Mat	cluster (const Mat &descriptors) const =0
	Clusters train descriptors. More...

Protected Attributes
std::vector< Mat >	descriptors

int	size

Detailed Description

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. :

Constructor & Destructor Documentation

◆ BOWTrainer()

cv::BOWTrainer::BOWTrainer ( )

◆ ~BOWTrainer()

virtual cv::BOWTrainer::~BOWTrainer ( )

virtual

Member Function Documentation

◆ add()

CV_WRAP void cv::BOWTrainer::add ( const 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()

virtual CV_WRAP void cv::BOWTrainer::clear ( )

virtual

◆ cluster() [1/2]

virtual CV_WRAP Mat cv::BOWTrainer::cluster ( ) const

pure virtual

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

Implemented in cv::BOWKMeansTrainer.

◆ cluster() [2/2]

virtual CV_WRAP Mat cv::BOWTrainer::cluster ( const Mat & descriptors ) const

pure virtual

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.

Implemented in cv::BOWKMeansTrainer.

◆ descriptorsCount()

CV_WRAP int cv::BOWTrainer::descriptorsCount ( ) const

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

◆ getDescriptors()

CV_WRAP const std::vector<Mat>& cv::BOWTrainer::getDescriptors ( ) const

Returns a training set of descriptors.

Member Data Documentation

◆ descriptors

std::vector<Mat> cv::BOWTrainer::descriptors

protected

◆ size

int cv::BOWTrainer::size