.. AUTO-GENERATED FILE -- DO NOT EDIT!

:orphan:

.. currentmodule:: deepsulci.sulci_labeling.capsul.labeling


.. _deepsulci.sulci_labeling.capsul.labeling.SulciDeepLabeling:

deepsulci.sulci_labeling.capsul.labeling.SulciDeepLabeling
==========================================================

SulciDeepLabeling
-----------------



    Process to label a new graph using a 3D U-Net convolutional neural network.

    The process can work using a GPU or on CPU. It requires a fair amount of RAM
    memory (about 4-5 GB). If not enough memory can be allocated, the process
    will abort with an error (thus will not hang the whole machine).
    
    
    .. note::
    
        * Type 'SulciDeepLabeling.help()' for a full description of this process parameters.
        * Type '<SulciDeepLabeling>.get_input_spec()' for a full description of this process input trait types.
        * Type '<SulciDeepLabeling>.get_output_spec()' for a full description of this process output trait types.
    

.. _deepsulci.sulci_labeling.capsul.labeling.SulciDeepLabeling_inputs:


Inputs
~~~~~~

[Mandatory]

**graph**: a file name (['File'] - mandatory)
    input graph to segment
**roots**: a file name (['File'] - mandatory)
    root file corresponding to the input graph
**model_file**: a file name (['File'] - mandatory)
    file (.mdsm) storing neural network parameters
**param_file**: a file name (['File'] - mandatory)
    file (.json) storing the hyperparameters (cutting threshold)
**rebuild_attributes**: a boolean (['Bool'] - mandatory)
    No description.
**skeleton**: a file name (['File'] - mandatory)
    skeleton file corresponding to the input graph
**allow_multithreading**: a boolean (['Bool'] - mandatory)
    No description.
**cuda**: an integer (int or long) (['Int'] - mandatory)
    device on which to run the training(-1 for cpu, i>=0 for the i-th gpu)
**fix_random_seed**: a boolean (['Bool'] - mandatory)
    Use same random sequence

.. _deepsulci.sulci_labeling.capsul.labeling.SulciDeepLabeling_outputs:


Outputs
~~~~~~~

**labeled_graph**: a file name (['File (filename: input)'] - mandatory)
    output labeled graph