ml - Parallel classification

None

Parameters

Input_Features_Image: 3D Volume ( input )

Classification_Model: Any Type ( input )

Classes_Weights: ListOf( Float ) ( input )

n_jobs: Integer ( input )

Write_Segmented_Image: Boolean ( input )

Write_Probas_Image: Boolean ( input )

Output_Segmented_Image: 3D Volume ( optional, output )

Output_Probas_Image: 3D Volume ( optional, output )

Technical information

Toolbox : Bioprocessing

User level : 3

Identifier : ml_parallel_classify

File name : brainvisa/toolboxes/bioprocessing/processes/research/toolbox/machine_learning/ml_toolbox/ml_parallel_classify.py

Supported file formats :

Input_Features_Image :

gz compressed NIFTI-1 image, Aperio svs, DICOM image, Directory, ECAT i image, ECAT v image, FDF image, FreesurferMGH, FreesurferMGZ, GIS image, Hamamatsu ndpi, Hamamatsu vms, Hamamatsu vmu, JPEG image, Leica scn, MINC image, NIFTI-1 image, SPM image, Sakura svslide, TIFF image, TIFF image, TIFF(.tif) image, TIFF(.tif) image, Ventana bif, Zeiss czi, gz compressed MINC image, gz compressed NIFTI-1 image

Classification_Model :

pickle file, pickle file

Output_Segmented_Image :

gz compressed NIFTI-1 image, DICOM image, Directory, ECAT i image, ECAT v image, FDF image, GIS image, JPEG image, MINC image, NIFTI-1 image, SPM image, TIFF image, TIFF(.tif) image, gz compressed MINC image, gz compressed NIFTI-1 image

Output_Probas_Image :

gz compressed NIFTI-1 image, DICOM image, Directory, ECAT i image, ECAT v image, FDF image, GIS image, JPEG image, MINC image, NIFTI-1 image, SPM image, TIFF image, TIFF(.tif) image, gz compressed MINC image, gz compressed NIFTI-1 image