# KMeansClassification

## Brief Description

Unsupervised KMeans image classification

## Tags

Segmentation,Learning

## Long Description

Performs unsupervised KMeans image classification.

## Parameters

- [param] -in <string> Input image to classify.. Mandatory: True. Default Value: ""
- [param] -out <string> Output image containing the class indexes.. Mandatory: True. Default Value: ""
- [param] -ram <int32> Available memory for processing (in MB). Mandatory: False. Default Value: "128"
- [param] -vm <string> Validity mask. Only non-zero pixels will be used to estimate KMeans modes.. Mandatory: False. Default Value: ""
- [param] -ts <int32> Size of the training set (in pixels).. Mandatory: False. Default Value: "100"
- [param] -nc <int32> Number of modes, which will be used to generate class membership.. Mandatory: True. Default Value: "5"
- [param] -maxit <int32> Maximum number of iterations for the learning step.. Mandatory: False. Default Value: "1000"
- [param] -ct <float> Convergence threshold for class centroid (L2 distance, by default 0.0001).. Mandatory: False. Default Value: "0.0001"
- [param] -outmeans <string> Output text file containing centroid positions. Mandatory: False. Default Value: ""
- [param] -rand <int32> Set specific seed. with integer value.. Mandatory: False. Default Value: "0"

## Limitations

None

## Authors

OTB-Team

## See Also

## Example of use

- in: QB_1_ortho.tif

- ts: 1000

- nc: 5

- maxit: 1000

- ct: 0.0001

- out: ClassificationFilterOutput.tif