tldr_migration_guide_from_v1.md

TLDR Migration Guide from nnU-Net V1

• nnU-Net V2 can be installed simultaneously with V1. They won't get in each other's way
• The environment variables needed for V2 have slightly different names. Read this.
• nnU-Net V2 datasets are called DatasetXXX_NAME. Not Task.
• Datasets have the same structure (imagesTr, labelsTr, dataset.json) but we now support more file types. The dataset.json is simplified. Use generate_dataset_json from nnunetv2.dataset_conversion.generate_dataset_json.py.
• Careful: labels are now no longer declared as value:name but name:value. This has to do with hierarchical labels.
• nnU-Net v2 commands start with nnUNetv2.... They work mostly (but not entirely) the same. Just use the -h option.
• You can transfer your V1 raw datasets to V2 with nnUNetv2_convert_old_nnUNet_dataset. You cannot transfer trained models. Continue to use the old nnU-Net Version for making inference with those.
• These are the commands you are most likely to be using (in that order)
  • nnUNetv2_plan_and_preprocess. Example: nnUNetv2_plan_and_preprocess -d 2
  • nnUNetv2_train. Example: nnUNetv2_train 2 3d_fullres 0
  • nnUNetv2_find_best_configuration. Example: nnUNetv2_find_best_configuration 2 -c 2d 3d_fullres. This command will now create a inference_instructions.txt file in your nnUNet_preprocessed/DatasetXXX_NAME/ folder which tells you exactly how to do inference.
  • nnUNetv2_predict. Example: nnUNetv2_predict -i INPUT_FOLDER -o OUTPUT_FOLDER -c 3d_fullres -d 2
  • nnUNetv2_apply_postprocessing (see inference_instructions.txt)