CLIJ2

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generateFeatureStack

Generates a feature stack for Trainable Weka Segmentation.

Use this terminology to specifiy which stacks should be generated:

Use sigma=0 to apply a filter to the original image. Feature definitions are not case sensitive.

Example: “original gaussianBlur=1 gaussianBlur=5 laplacianOfGaussian=1 laplacianOfGaussian=7 entropy=3”

Categories: Segmentation, Machine Learning

Usage in ImageJ macro

Ext.CLIJx_generateFeatureStack(Image input, Image feature_stack_destination, String feature_definitions);

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