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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:

python -m pip install "hemispec-toolkit[model]"
hemispec models --install

For source development, clone with Git LFS and use python -m pip install -e .[model].

Inputs

  • Preprocessed *_GM_masked.nii.gz files.
  • 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 Do not publish additional trained weights until their release policy, provenance, checksums, and license notes are approved.