# SOMClassification

## Brief Description

SOM image classification.

## Tags

Segmentation,Learning

## Long Description

Unsupervised Self Organizing Map image classification.

## Parameters

- [param] -in <string> Input image to classify.. Mandatory: True. Default Value: ""
- [param] -out <string> Output classified image (each pixel contains the index of its corresponding vector in the SOM).. Mandatory: True. Default Value: ""
- [param] -vm <string> Validity mask (only pixels corresponding to a mask value greater than 0 will be used for learning). Mandatory: False. Default Value: ""
- [param] -tp <float> Probability for a sample to be selected in the training set. Mandatory: False. Default Value: "1"
- [param] -ts <int32> Maximum training set size (in pixels). Mandatory: False. Default Value: "0"
- [param] -sl <int32> Number of lines in each streaming block (used during data sampling). Mandatory: False. Default Value: "0"
- [param] -som <string> Output image containing the Self-Organizing Map. Mandatory: False. Default Value: ""
- [param] -sx <int32> X size of the SOM map. Mandatory: False. Default Value: "32"
- [param] -sy <int32> Y size of the SOM map. Mandatory: False. Default Value: "32"
- [param] -nx <int32> X size of the initial neighborhood in the SOM map. Mandatory: False. Default Value: "10"
- [param] -ny <int32> Y size of the initial neighborhood in the SOM map. Mandatory: True. Default Value: "10"
- [param] -ni <int32> Number of iterations for SOM learning. Mandatory: False. Default Value: "5"
- [param] -bi <float> Initial learning coefficient. Mandatory: False. Default Value: "1"
- [param] -bf <float> Final learning coefficient. Mandatory: False. Default Value: "0.1"
- [param] -iv <float> Maximum initial neuron weight. Mandatory: False. Default Value: "0"
- [param] -ram <int32> Available memory for processing (in MB). Mandatory: False. Default Value: "128"
- [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

- out: SOMClassification.tif

- tp: 1.0

- ts: 16384

- sl: 32

- sx: 32

- sy: 32

- nx: 10

- ny: 10

- ni: 5

- bi: 1.0

- bf: 0.1

- iv: 0