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.
Inputs¶
[Mandatory]
- graph: a string or os.PathLike object ([‘File’] - mandatory)
input graph to segment
- roots: a string or os.PathLike object ([‘File’] - mandatory)
root file corresponding to the input graph
- model_file: a string or os.PathLike object ([‘File’] - mandatory)
file (.mdsm) storing neural network parameters
- param_file: a string or os.PathLike object ([‘File’] - mandatory)
file (.json) storing the hyperparameters (cutting threshold)
- skeleton: a string or os.PathLike object ([‘File’] - mandatory)
skeleton file corresponding to the input graph
- grey_white: a string or os.PathLike object ([‘File’] - mandatory)
grey white mask corresponding to the input graph
- hemi_cortex: a string or os.PathLike object ([‘File’] - mandatory)
grey+CSF mask corresponding to the input graph
- white_mesh: a string or os.PathLike object ([‘File’] - mandatory)
white surface corresponding to the input graph
- pial_mesh: a string or os.PathLike object ([‘File’] - mandatory)
pial surface corresponding to the input graph
- allow_multithreading: a boolean ([‘Bool’] - mandatory)
No description.
- cuda: an integer ([‘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
Outputs¶
- labelled_graph: a string or os.PathLike object ([‘File (filename: input)’] - mandatory)
output labelled graph