DGN inference¶
This tutorial shows how to apply released HemiSpec DGN model bundles to preprocessed gray-matter maps.
Install¶
For model-enabled PyPI installs, include the model extra and optionally pre-download released checkpoints:
For source development, clone with Git LFS and use python -m pip install -e .[model].
Inputs¶
- Preprocessed
*_GM_masked.nii.gzfiles. - A HemiSpec model bundle containing weights, model direction, preprocessing assumptions, and version metadata.
Outputs¶
- Reconstructed hemisphere maps.
- Source and target hemisphere records.
- Run manifest with model version, command, parameters, and output paths.
Current status¶
Released default model bundles are available through Git LFS source checkouts or first-run PyPI cache download. Do not publish additional trained weights until their release policy, provenance, checksums, and license notes are approved.