This code is used to generate the command for model training automatically.
See more details from the official tutorial.
- Setup the parameters in main.py to adapt to your dataset.
- Automatically analyze the dataset, generate the model(s), and create the command used for model training by running:
python main.py- Setup your CUDA device ID, and train the model by running (FOR EXAMPLE):
bash segresnet_small_0.sh- The default train_params is set as {}, instead of NONE. Otherwise, the code will raise the error "undefined parameters" at here.
- Add sys.path.insert(0, os.path.join(algo_path, "algorithm_templates")) to line 328 at here.
- Set Resample=False here for segresnet to avoid the out-of-memory issue. (This is NOT a bug. After modification, the default resolution is not (1, 1, 1) anymore.)
- Add extra code here to convert all the list-based transform to REAL transform objects
- Adapt to Windows operation system here
- Add a small segresnet to assets where the initial_channel is set to 16, and the batch size is set as 1.