Unsupervised KMeans image classification

Описание

<put algortithm description here>

Parameters

Input Image [raster]
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Available RAM (Mb) [number]

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Default: 128

Validity Mask [raster]

Optional.

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Training set size [number]

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Default: 100

Number of classes [number]

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Default: 5

Maximum number of iterations [number]

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Default: 1000

Convergence threshold [number]

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Default: 0.0001

Outputs

Output Image [raster]
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Centroid filename [file]
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Console usage

processing.runalg('otb:unsupervisedkmeansimageclassification', -in, -ram, -vm, -ts, -nc, -maxit, -ct, -out, -outmeans)

See also