opencv/doc/opencv1/py/core_clustering.rst

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Clustering
==========
.. highlight:: python
.. index:: KMeans2
.. _KMeans2:
KMeans2
-------
.. function:: KMeans2(samples,nclusters,labels,termcrit)-> None
Splits set of vectors by a given number of clusters.
:param samples: Floating-point matrix of input samples, one row per sample
:type samples: :class:`CvArr`
:param nclusters: Number of clusters to split the set by
:type nclusters: int
:param labels: Output integer vector storing cluster indices for every sample
:type labels: :class:`CvArr`
:param termcrit: Specifies maximum number of iterations and/or accuracy (distance the centers can move by between subsequent iterations)
:type termcrit: :class:`CvTermCriteria`
The function
``cvKMeans2``
implements a k-means algorithm that finds the
centers of
``nclusters``
clusters and groups the input samples
around the clusters. On output,
:math:`\texttt{labels}_i`
contains a cluster index for
samples stored in the i-th row of the
``samples``
matrix.