The snapped meshes, their records and the CT they sit on read straight from these URLs, logged out. Every segment is a tifxyz folder, so VC3D, villa and anything that reads tifxyz opens it as it is.
https://huggingface.co/datasets/SharpMeow/vesuvius-snapped-labels# pip install huggingface_hub
from huggingface_hub import hf_hub_download, snapshot_download
path = hf_hub_download("SharpMeow/vesuvius-snapped-labels", "index.json", repo_type="dataset") # one file, cached
folder = snapshot_download("SharpMeow/vesuvius-snapped-labels", repo_type="dataset")pip install -U huggingface_hub
hf download SharpMeow/vesuvius-snapped-labels index.json --repo-type dataset --local-dir vesuvius-snapped-labelscurl -L -O https://huggingface.co/datasets/SharpMeow/vesuvius-snapped-labels/resolve/main/index.jsonhttps://huggingface.co/datasets/SharpMeow/vesuvius-snapped-labels/resolve/main/PHerc0841/20260220213127-w00/snapped.tifxyz# pip install numpy tifffile
import io, json, urllib.request
import numpy as np, tifffile
T = "https://huggingface.co/datasets/SharpMeow/vesuvius-snapped-labels/resolve/main/PHerc0841/20260220213127-w00/snapped.tifxyz"
meta = json.load(urllib.request.urlopen(T + "/meta.json")) # scale, bbox, format
get = lambda c: tifffile.imread(io.BytesIO(urllib.request.urlopen(f"{T}/{c}.tif").read()))
xyz = np.stack([get(c) for c in "xyz"], -1) # xyz[i, j] = (x, y, z) in scan voxels; -1 = no surfacehttps://vesuvius-challenge-open-data.s3.us-east-1.amazonaws.com/PHerc0841/volumes/20250821151531-9.366um-1.2m-113keV-masked.zarr# pip install "zarr>=3" fsspec aiohttp
import zarr
root = zarr.open_group("https://vesuvius-challenge-open-data.s3.us-east-1.amazonaws.com/PHerc0841/volumes/20250821151531-9.366um-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[3600:3664, 600:664, 500:564] # (z, y, x); reads only the chunks it touches# 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/PHerc0841/volumes/20250821151531-9.366um-1.2m-113keV-masked.zarr/2") # one pyramid level
block = v[3600:3664, 600:664, 500:564]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/PHerc0841/volumes/20250821151531-9.366um-1.2m-113keV-masked.zarr
It accepts http, https and s3 OME-Zarr roots.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%2FPHerc0841%2Fvolumes%2F20250821151531-9.366um-1.2m-113keV-masked.zarr%2F%22%2C%22name%22%3A%22The%20CT%20that%20mesh%20is%20in%2C%20PHerc0841%209.366%20um%22%7D%5D%2C%22layout%22%3A%224panel%22%7Dcurl -s https://vesuvius-challenge-open-data.s3.us-east-1.amazonaws.com/PHerc0841/volumes/20250821151531-9.366um-1.2m-113keV-masked.zarr/.zattrs # OME multiscales metadata
curl -s https://vesuvius-challenge-open-data.s3.us-east-1.amazonaws.com/PHerc0841/volumes/20250821151531-9.366um-1.2m-113keV-masked.zarr/2/.zarray # one level: shape, chunks, dtype, codechttps://sharpmeow-snapped-labels.static.hf.space/The dataset card: https://huggingface.co/datasets/SharpMeow/vesuvius-snapped-labels
A segment's cross sections for the viewer (float32 rows, see the .json beside it): https://huggingface.co/datasets/SharpMeow/vesuvius-snapped-labels/resolve/main/viewer/PHerc0841/20260220213127-w00.json
Page source: https://github.com/ChaseHendrick/Scrolls/tree/main/spaces/snapped-labels