OpenCV  3.2.0
Open Source Computer Vision
Public Member Functions | Protected Attributes | List of all members
cv::BOWKMeansTrainer Class Reference

kmeans -based class to train visual vocabulary using the bag of visual words approach. : More...

#include "features2d.hpp"

Inheritance diagram for cv::BOWKMeansTrainer:

Public Member Functions

 BOWKMeansTrainer (int clusterCount, const TermCriteria &termcrit=TermCriteria(), int attempts=3, int flags=KMEANS_PP_CENTERS)
 The constructor. More...
virtual ~BOWKMeansTrainer ()
virtual Mat cluster () const
virtual Mat cluster (const Mat &descriptors) const
 Clusters train descriptors. More...
- Public Member Functions inherited from cv::BOWTrainer
 BOWTrainer ()
virtual ~BOWTrainer ()
void add (const Mat &descriptors)
 Adds descriptors to a training set. More...
virtual void clear ()
int descriptorsCount () const
 Returns the count of all descriptors stored in the training set. More...
const std::vector< Mat > & getDescriptors () const
 Returns a training set of descriptors. More...

Protected Attributes

int attempts
int clusterCount
int flags
TermCriteria termcrit
- Protected Attributes inherited from cv::BOWTrainer
std::vector< Matdescriptors
int size

Detailed Description

kmeans -based class to train visual vocabulary using the bag of visual words approach. :

Constructor & Destructor Documentation

§ BOWKMeansTrainer()

cv::BOWKMeansTrainer::BOWKMeansTrainer ( int  clusterCount,
const TermCriteria termcrit = TermCriteria(),
int  attempts = 3,
int  flags = KMEANS_PP_CENTERS 

The constructor.

See also

§ ~BOWKMeansTrainer()

virtual cv::BOWKMeansTrainer::~BOWKMeansTrainer ( )

Member Function Documentation

§ cluster() [1/2]

virtual Mat cv::BOWKMeansTrainer::cluster ( ) const

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

Implements cv::BOWTrainer.

§ cluster() [2/2]

virtual Mat cv::BOWKMeansTrainer::cluster ( const Mat descriptors) const

Clusters train descriptors.

descriptorsDescriptors 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.

Implements cv::BOWTrainer.

Member Data Documentation

§ attempts

int cv::BOWKMeansTrainer::attempts

§ clusterCount

int cv::BOWKMeansTrainer::clusterCount

§ flags

int cv::BOWKMeansTrainer::flags

§ termcrit

TermCriteria cv::BOWKMeansTrainer::termcrit

The documentation for this class was generated from the following file: