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name: planning-preprocessing description: "Plan and preprocess prepared nnU-Net v2 datasets: fingerprint extraction, experiment planning, plans files, preprocessing configurations, worker choices, and rerun decisions." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

Planning and Preprocessing

Use this sub-skill after a dataset has already been converted and validated into nnU-Net raw format. It covers dataset fingerprints, experiment planners, plans identifiers, preprocessing configurations, normalization/resampling consequences, and inspection of nnUNet_preprocessed outputs.

Route here when

• The user needs nnUNetv2_plan_and_preprocess, nnUNetv2_extract_fingerprint, nnUNetv2_plan_experiment, or nnUNetv2_preprocess commands.
• The user asks what dataset_fingerprint.json, nnUNetPlans.json, plans_identifier, data_identifier, spacing, normalization_schemes, or preprocessor_name means.
• The user needs to decide whether to rerun fingerprint extraction, planning, preprocessing, or only training.
• The user is choosing configurations such as 2d, 3d_fullres, 3d_lowres, residual encoder planners, worker counts, progress bars, or custom plans names.

Boundaries

• Dataset conversion, dataset IDs, dataset.json, labels, file endings, and raw data layout belong to data-preparation.
• Training, folds, checkpoints, validation, inference, and using -p during train/predict belong to training-configuration.
• Implementing custom planner, preprocessor, normalization, reader/writer, or resampling classes belongs to customization-extension.

Fast paths

• New dataset, first safe pass: nnUNetv2_plan_and_preprocess -d DATASET_ID --verify_dataset_integrity.
• Fresh fingerprint and plans but stale preprocessed arrays: run only nnUNetv2_preprocess -d DATASET_ID -c CONFIGS.
• Changed target spacing, planner, preprocessor, normalization, resampling, or data_identifier: plan again with a distinct plans name when appropriate, then rerun preprocessing for affected configurations.
• Need generated commands without running them: use scripts/build_plan_preprocess_command.py.

References

• references/cli-reference.md for exact CLI/API boundaries and command patterns.
• references/plans-and-preprocessing.md for plans files, presets, normalization, resampling, and inspection.
• references/troubleshooting.md for common failures and rerun decisions.