| """Load one snapped segment of SharpMeow/vesuvius-snapped-labels and compare it with its published mesh. |
| |
| pip install huggingface_hub numpy tifffile imagecodecs |
| python load_example.py # PHerc0841 w00, from the Hub |
| python load_example.py --root snapped-labels # a local copy made with `hf download` |
| python load_example.py --segment PHerc0139/20250108000000-w025_2025010863 # any path from index.json |
| """ |
|
|
| import argparse |
| import io |
| import json |
| import urllib.request |
| from pathlib import Path |
|
|
| import numpy as np |
| import tifffile |
|
|
| REPO = "SharpMeow/vesuvius-snapped-labels" |
|
|
|
|
| def opener(root): |
| """read(path) -> bytes, from a local copy or from the Hub (cached by huggingface_hub).""" |
| if root: |
| return lambda p: (Path(root) / p).read_bytes() |
| from huggingface_hub import hf_hub_download |
| return lambda p: Path(hf_hub_download(REPO, p, repo_type="dataset")).read_bytes() |
|
|
|
|
| def tif(b): |
| return tifffile.imread(io.BytesIO(b)) |
|
|
|
|
| def main(): |
| a = argparse.ArgumentParser(description=__doc__.splitlines()[0]) |
| a.add_argument("--root", help="a local copy of the dataset; default: read from the Hub") |
| a.add_argument("--segment", default="PHerc0841/20260220213127-w00", help="a segment path from index.json") |
| args = a.parse_args() |
| read = opener(args.root) |
|
|
| rec = json.loads(read(f"{args.segment}/release.json")) |
| snapped = np.stack([tif(read(f"{args.segment}/snapped.tifxyz/{c}.tif")) for c in "xyz"], -1) |
| mask = tif(read(f"{args.segment}/release_mask.tif")) |
| abstain = tif(read(f"{args.segment}/abstain.tif")) |
|
|
| |
| src = rec["source_mesh"].rstrip("/") |
| published = np.stack([tif(urllib.request.urlopen(f"{src}/{c}.tif").read()) for c in "xyz"], -1) |
|
|
| out = snapped[..., 0] != -1 |
| d = np.linalg.norm(snapped[out] - published[out], axis=1) |
| print(rec["scroll"], rec["segment"], rec["method"], "grid", snapped.shape[:2]) |
| print("released", int((mask == 0).sum()), "held back", int((mask == 1).sum()), "snapped", int(((abstain == 0) & out).sum()), |
| "filled", int((abstain == 2).sum()), "left in place", int((abstain == 1).sum())) |
| print("move, voxels, over released vertices: median %.2f, 90th percentile %.2f" % (np.median(d), np.percentile(d, 90))) |
| print("matches release.json:", round(float(np.median(d)), 3) == rec["summary"]["move_voxels"]["median"]) |
|
|
|
|
| if __name__ == "__main__": |
| main() |
|
|
