This example mainly shows a typical use case that brings customized python components (such as transform, network, metrics) in a configuration-based workflow.
Please note that this example depends on the spleen_segmentation bundle example and executes via overriding the config file of it.
To run the workflow with customized components, PYTHONPATH should be revised to include the path to the customized component:
export PYTHONPATH=$PYTHONPATH:"<path to 'custom_component/scripts'>"
And please make sure the folder custom_component/scripts is a valid python module (it has a __init__.py file in the folder).
Override the train config with the customized transform and execute training:
python -m monai.bundle run training --meta_file <spleen_configs_path>/metadata.json --config_file "['<spleen_configs_path>/train.json','configs/custom_train.json']" --logging_file <spleen_configs_path>/logging.conf