Connect your tool

Every center line, CT scan and lasagna field on this page reads straight from these URLs, with no account and no download step. Each scan card also has its own OME-Zarr URL and an Open in neuroglancer link.

Center lines (every line, every scan)

CC BY-NC 4.0 bundle; each file keeps its own license (MIT, CC BY 4.0 or CC BY-NC 4.0, listed in index.json) · Files under lines/ are in VC3D's umbilicus JSON format, level-0 voxels (x, y, z).

https://huggingface.co/datasets/SharpMeow/vesuvius-center-lines
Python (huggingface_hub)tested 2026-10-24 
# pip install huggingface_hub
from huggingface_hub import hf_hub_download, snapshot_download

path = hf_hub_download("SharpMeow/vesuvius-center-lines", "index.json", repo_type="dataset")  # one file, cached
folder = snapshot_download("SharpMeow/vesuvius-center-lines", repo_type="dataset")
Python (datasets)tested 2026-10-24 
# pip install datasets
from datasets import load_dataset

lines = load_dataset("SharpMeow/vesuvius-center-lines", "lines", split="train")
points = load_dataset("SharpMeow/vesuvius-center-lines", "points", split="train")
pandastested 2026-10-24 
# pip install pandas huggingface_hub
import pandas as pd

df = pd.read_json("hf://datasets/SharpMeow/vesuvius-center-lines/tables/points.jsonl", lines=True)
Command line (hf)tested 2026-10-24 
pip install -U huggingface_hub
hf download SharpMeow/vesuvius-center-lines index.json --repo-type dataset --local-dir vesuvius-center-lines
curltested 2026-10-24 
curl -L -O https://huggingface.co/datasets/SharpMeow/vesuvius-center-lines/resolve/main/index.json

X-ray CT, example PHerc0125 (each scan card has its own URL)

CC BY-NC 4.0 (Vesuvius Challenge open data) · Read live from the open-data bucket, never copied here. uint8, 128^3 chunks, no compressor, 6 levels. · browse

https://vesuvius-challenge-open-data.s3.us-east-1.amazonaws.com/PHerc0125/volumes/20250821151825-9.362um-1.2m-113keV-masked.zarr
Python (zarr)tested 2026-10-24 
# pip install "zarr>=3" fsspec aiohttp
import zarr

root = zarr.open_group("https://vesuvius-challenge-open-data.s3.us-east-1.amazonaws.com/PHerc0125/volumes/20250821151825-9.362um-1.2m-113keV-masked.zarr", mode="r")  # OME-Zarr, zarr v2
a = root["2"]  # level 0 is full resolution; level L is 2**L times coarser
print(a.shape, a.dtype, a.chunks)
block = a[2600:2664, 1000:1064, 1000:1064]  # (z, y, x); reads only the chunks it touches
villa's vesuvius packagetested 2026-10-24 
# pip install "vesuvius[volume-only]"
from vesuvius import Volume

v = Volume(type="zarr", path="https://vesuvius-challenge-open-data.s3.us-east-1.amazonaws.com/PHerc0125/volumes/20250821151825-9.362um-1.2m-113keV-masked.zarr/2")  # one pyramid level
block = v[2600:2664, 1000:1064, 1000:1064]
VC3Dfrom villa's source 
In VC3D (villa's volume-cartographer), open or create a project, then
File > Attach Remote Zarr... and paste:

https://vesuvius-challenge-open-data.s3.us-east-1.amazonaws.com/PHerc0125/volumes/20250821151825-9.362um-1.2m-113keV-masked.zarr

It accepts http, https and s3 OME-Zarr roots.
neuroglancertested 2026-10-24 Open in neuroglancer 
https://neuroglancer-demo.appspot.com/#!%7B%22layers%22%3A%5B%7B%22type%22%3A%22image%22%2C%22source%22%3A%22zarr%3A%2F%2Fhttps%3A%2F%2Fvesuvius-challenge-open-data.s3.us-east-1.amazonaws.com%2FPHerc0125%2Fvolumes%2F20250821151825-9.362um-1.2m-113keV-masked.zarr%2F%22%2C%22name%22%3A%22X-ray%20CT%2C%20example%20PHerc0125%20%28each%20scan%20card%20has%20its%20own%20URL%29%22%7D%5D%2C%22layout%22%3A%224panel%22%7D
curltested 2026-10-24 
curl -s https://vesuvius-challenge-open-data.s3.us-east-1.amazonaws.com/PHerc0125/volumes/20250821151825-9.362um-1.2m-113keV-masked.zarr/.zattrs            # OME multiscales metadata
curl -s https://vesuvius-challenge-open-data.s3.us-east-1.amazonaws.com/PHerc0125/volumes/20250821151825-9.362um-1.2m-113keV-masked.zarr/2/.zarray     # one level: shape, chunks, dtype, codec

Lasagna field, PHerc0175A

CC BY-NC 4.0 · villa lasagna predict3d output (scrollprize/lasagna); model output, not checked by eye.

https://huggingface.co/datasets/SharpMeow/pherc0175a-lasagna
Python (huggingface_hub)tested 2026-10-24 
# pip install huggingface_hub
from huggingface_hub import hf_hub_download, snapshot_download

path = hf_hub_download("SharpMeow/pherc0175a-lasagna", "README.md", repo_type="dataset")  # one file, cached
folder = snapshot_download("SharpMeow/pherc0175a-lasagna", repo_type="dataset")  # large; allow_patterns=[...] fetches part of it
Command line (hf)tested 2026-10-24 
pip install -U huggingface_hub
hf download SharpMeow/pherc0175a-lasagna README.md --repo-type dataset --local-dir pherc0175a-lasagna
curltested 2026-10-24 
curl -L -O https://huggingface.co/datasets/SharpMeow/pherc0175a-lasagna/resolve/main/README.md

Lasagna fields, ten scans

CC BY-NC 4.0 · villa lasagna predict3d output (model output) for ten scans, public and read live: each scan's cos, grad_mag, nx and ny fields as OME-Zarr plus a SCAN.lasagna.json for VC3D's Attach Remote Lasagna Manifest. That Space has its own Connect your tool section.

https://huggingface.co/spaces/SharpMeow/lasagna-fields
Links and embedtested 2026-10-24 
Lasagna Fields: every field's OME-Zarr URL, VC3D manifest and tested snippets: https://huggingface.co/spaces/SharpMeow/lasagna-fields

This page's own data and API

Page code Apache 2.0; data as above · In a browser or headless Chromium, window.umbilici has scans(), lines(scroll), at(scroll, z), csv(...) and more (Guide, For researchers).

https://sharpmeow-umbilici.static.hf.space/
Links and embedtested 2026-10-24 
Every line, scan and CT pyramid as one JSON: https://huggingface.co/spaces/SharpMeow/umbilici/resolve/main/data/lines.json
Open a scan in a given mode and height: https://sharpmeow-umbilici.static.hf.space/?mode=scan&scan=PHerc0191&z=10400
Page source and build scripts: https://huggingface.co/spaces/SharpMeow/umbilici/tree/main