The ten whole-scan fields in the public bucket read straight by URL, logged out, with no download step; villa's fields in the open data stream the same way from the run folders the Every field tab lists, and the other datasets download whole. The scans they came from are open data. The page is also an API and an MCP server that lists every field and makes a field for any box of any public scan.
https://huggingface.co/buckets/SharpMeow/lasagna-fields/resolve/PHerc0175A/representations/predictions/lasagna/20250521115057-lasagna-de45f011/PHerc0175A_cos.ome.zarr# pip install "zarr>=3" fsspec aiohttp
import zarr
root = zarr.open_group("https://huggingface.co/buckets/SharpMeow/lasagna-fields/resolve/PHerc0175A/representations/predictions/lasagna/20250521115057-lasagna-de45f011/PHerc0175A_cos.ome.zarr", mode="r") # OME-Zarr, zarr v2
a = root["1"] # level 0 is full resolution; level L is 2**L times coarser
print(a.shape, a.dtype, a.chunks)
block = a[3186:3250, 2900:2964, 2200:2264] # (z, y, x); reads only the chunks it touches# pip install "vesuvius[volume-only]"
from vesuvius import Volume
v = Volume(type="zarr", path="https://huggingface.co/buckets/SharpMeow/lasagna-fields/resolve/PHerc0175A/representations/predictions/lasagna/20250521115057-lasagna-de45f011/PHerc0175A_cos.ome.zarr/1") # one pyramid level
block = v[3186:3250, 2900:2964, 2200:2264]In VC3D (villa's volume-cartographer), open or create a project, then
File > Attach Remote Zarr... and paste:
https://huggingface.co/buckets/SharpMeow/lasagna-fields/resolve/PHerc0175A/representations/predictions/lasagna/20250521115057-lasagna-de45f011/PHerc0175A_cos.ome.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%2Fhuggingface.co%2Fbuckets%2FSharpMeow%2Flasagna-fields%2Fresolve%2FPHerc0175A%2Frepresentations%2Fpredictions%2Flasagna%2F20250521115057-lasagna-de45f011%2FPHerc0175A_cos.ome.zarr%2F%22%2C%22name%22%3A%22A%20whole-scan%20field%3A%20PHerc0175A%20cos%2C%20level%201%20%28every%202nd%20scan%20voxel%29%22%7D%5D%2C%22layout%22%3A%224panel%22%7Dcurl -s https://huggingface.co/buckets/SharpMeow/lasagna-fields/resolve/PHerc0175A/representations/predictions/lasagna/20250521115057-lasagna-de45f011/PHerc0175A_cos.ome.zarr/.zattrs # OME multiscales metadata
curl -s https://huggingface.co/buckets/SharpMeow/lasagna-fields/resolve/PHerc0175A/representations/predictions/lasagna/20250521115057-lasagna-de45f011/PHerc0175A_cos.ome.zarr/1/.zarray # one level: shape, chunks, dtype, codechttps://vesuvius-challenge-open-data.s3.us-east-1.amazonaws.com/PHerc0175A/volumes/20250521115057-8.640um-1.2m-116keV-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/PHerc0175A/volumes/20250521115057-8.640um-1.2m-116keV-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[1593:1657, 1170:1234, 1170:1234] # (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/PHerc0175A/volumes/20250521115057-8.640um-1.2m-116keV-masked.zarr/2") # one pyramid level
block = v[1593:1657, 1170:1234, 1170:1234]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/PHerc0175A/volumes/20250521115057-8.640um-1.2m-116keV-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%2FPHerc0175A%2Fvolumes%2F20250521115057-8.640um-1.2m-116keV-masked.zarr%2F%22%2C%22name%22%3A%22X-ray%20CT%20that%20field%20came%20from%2C%20PHerc0175A%208.640%20um%22%7D%5D%2C%22layout%22%3A%224panel%22%7Dcurl -s https://vesuvius-challenge-open-data.s3.us-east-1.amazonaws.com/PHerc0175A/volumes/20250521115057-8.640um-1.2m-116keV-masked.zarr/.zattrs # OME multiscales metadata
curl -s https://vesuvius-challenge-open-data.s3.us-east-1.amazonaws.com/PHerc0175A/volumes/20250521115057-8.640um-1.2m-116keV-masked.zarr/2/.zarray # one level: shape, chunks, dtype, codechttps://huggingface.co/spaces/SharpMeow/lasagna-fields# pip install gradio_client
from gradio_client import Client
client = Client("SharpMeow/lasagna-fields")
result = client.predict(api_name="/list_models")# pip install gradio_client
from gradio_client import Client
client = Client("SharpMeow/lasagna-fields")
result = client.predict(api_name="/example_points")# pip install gradio_client
from gradio_client import Client
client = Client("SharpMeow/lasagna-fields")
result = client.predict(volume="20260930100252", z=39424, y=10752, x=13824, size=256, model="lasagna", api_name="/plan_field")URL=https://sharpmeow-lasagna-fields.hf.space
EVENT=$(curl -s -X POST $URL/gradio_api/call/list_models -H 'Content-Type: application/json' \
-d '{"data": []}' | python3 -c 'import json,sys; print(json.load(sys.stdin)["event_id"])')
curl -sN $URL/gradio_api/call/list_models/$EVENT{
"mcpServers": {
"lasagna-fields": {
"url": "https://sharpmeow-lasagna-fields.hf.space/gradio_api/mcp/sse"
}
}
}
Tool list: https://sharpmeow-lasagna-fields.hf.space/gradio_api/mcp/schema