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The layer signal and surface directions are model output, not a reading.

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Whole-volume completeness is not verified here.

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A field describes the shape of papyrus layers. It helps surface-fitting tools follow them.

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Every field, by scroll or fragment

One card per scroll or fragment. villa predict3d is the villa lasagna model itself, the reference. Lasagnetta 0.1.1 copies it and runs about 5 times faster: use its fields as a preview, and villa's where exact values matter.

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About these fields and credits

About these fields

A lasagna field is the input that the lasagna surface fit in villa reads. These are public so that nobody has to spend a GPU day before trying an idea on these scrolls: use them, compare against them, and tell us if you find a problem.

The scans are Vesuvius Challenge open data under CC BY-NC 4.0, and these derived fields are shared under the same terms. Model and code are ScrollPrize/villa's lasagna; credit to its authors. The fields listed from the open data are villa's own, published there by the Vesuvius Challenge; this page only links them. The other fields were computed and shared by Chase Hendrick, some with Lasagnetta, which was trained here to copy villa's lasagna.

How it was made every step ran on Hugging Face Jobs from scripts, with each part's record kept; nothing was edited by hand
Same settings as the published fields

The lasagna code in villa at commit db3dbea2, lasagna-preprocess predict3d --tile-size 192 with default chunks and levels, and the scrollprize/lasagna model model_current.pt at revision de45f011. On a test crop of PHerc0343 these settings reproduce the published lasagna field to within 2 of 255 at every voxel compared. Bigger tiles and torch.compile ran faster in testing but changed the output, so they were not used.

Split into parts that never share a chunk

Each scan was cut into boxes whose edges sit on multiples of 1,024 scan voxels, each small enough to finish in one Job. Because of that alignment, every chunk of every pyramid level is written by exactly one part, so the parts join without blending. PHerc0175A, the first scan, used an earlier layout whose coarsest level was rebuilt across tile edges; its card gives the details.

Predict on GPUs

One Job per part on an NVIDIA RTX PRO 6000, at the scan's native resolution with no resampling: parts in all.

Join and check

The parts were joined into one store, with a check that no chunk appears twice. A seam check then compares the step across each part edge with the steps beside it (1.0 means no step; the limit is 1.5). Finally the card's own load snippet was run on two real parts before upload.

One flag, checked properly

PHerc0841 flagged one edge: cos at z 1,024 stepped 1.62 times its neighbors. A single run straight across that edge gave the same field as the joined parts, byte for byte, in all 1,084 level-1 cos chunks and all 760 level-2 chunks of the four channels there. So that step is in the scan itself, not a seam.

Seven more scrolls, 29 October 2026

PHercMANBp and PHerc0343P got villa fields the same way from their 2.4 and 2.2 µm scans read at level 2, one 1,024-slice slab per part, with no step at any part edge (worst seam ratios 1.203 and 1.101). PHerc0009B, PHerc0172, PHerc0500P2, PHercMAN5 and PHercMANB got Lasagnetta 0.1.1 fields: three students averaged, cos blur 0.5, cos offset 0.04, part edges on multiples of 512 scan voxels, values kept only where the masked scan holds CT. Each card gives that scan's agreement with villa's net and what the release's self-check said there.

Publish with checksums, and unpacked for streaming

Each dataset carries SHA256SUMS, an index.json with every part's box and hash, the previews and the tested load example. The same parts were then unpacked into the public bucket, with the joined manifest written last, so tools can read chunks by URL.

Cite
Chase Hendrick (2026). Lasagna Fields: lasagna fields for Herculaneum scrolls.
Hugging Face. https://huggingface.co/spaces/SharpMeow/lasagna-fields
Computed with ScrollPrize/villa lasagna (db3dbea2) and scrollprize/lasagna (de45f011),
and with Lasagnetta 0.1.1 (SharpMeow/lasagnetta), on Vesuvius Challenge open data (CC BY-NC 4.0).
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