DGN inference¶
This tutorial shows how to apply released HemiSpec DGN model bundles to preprocessed gray-matter maps.
Install¶
From a source checkout, install 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 GitHub Release cache download. Do not publish additional trained weights until their release policy, provenance, checksums, and license notes are approved.