This example mainly shows a typical use case that parses the config files in your own Python program, instantiates the Python components and executes the inference.
Parse the config files in the Python program and execute inference from the python program, using scripts/inference.py:
python -m scripts.inference run \
--config_file "['configs/data_loading.json','configs/net_inferer.yaml','configs/post_processing.json']" \
--ckpt_path <path_to_checkpoint>Before running above command, please check the script first and modify datalist and output_dir according to the actual paths.
Parse the config file content in Python and overriding the default values, using the entry point defined in scrips/train_demo.py.
python -m scripts.train_demo run \
--config_file=configs/net_inferer.yaml \
--network#in_channels=10