The full dataset viewer is not available (click to read why). Only showing a preview of the rows.
Error code: DatasetGenerationError
Exception: TypeError
Message: int() argument must be a string, a bytes-like object or a real number, not 'NoneType'
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1539, in _prepare_split_single
for key, record in generator:
^^^^^^^^^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 621, in wrapped
for item in generator(*args, **kwargs):
~~~~~~~~~^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 131, in _generate_examples
for example_idx, example in enumerate(self._get_pipeline_from_tar(tar_path, tar_iterator)):
~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 32, in _get_pipeline_from_tar
for filename, f in tar_iterator:
^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/utils/track.py", line 49, in __iter__
for x in self.generator(*self.args):
~~~~~~~~~~~~~~^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/utils/file_utils.py", line 1419, in _iter_from_urlpath
with xopen(urlpath, "rb", download_config=download_config, block_size=0) as f:
~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/utils/file_utils.py", line 976, in xopen
file_obj = fs.open(paths[0], mode)
File "<string>", line 3, in open
File "/usr/local/lib/python3.14/unittest/mock.py", line 1176, in __call__
return self._mock_call(*args, **kwargs)
~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/unittest/mock.py", line 1180, in _mock_call
return self._execute_mock_call(*args, **kwargs)
~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/unittest/mock.py", line 1247, in _execute_mock_call
result = effect(*args, **kwargs)
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 794, in wrapped
tracker.files[urlpath] = {"read": 0, "size": int(f.size)}
~~~^^^^^^^^
TypeError: int() argument must be a string, a bytes-like object or a real number, not 'NoneType'
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1379, in compute_config_parquet_and_info_response
parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
~~~~~~~~~~~~~~~~~~~~~~~~~^
builder, max_dataset_size_bytes=max_dataset_size_bytes
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 956, in stream_convert_to_parquet
builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1401, in _prepare_split
for job_id, done, content in self._prepare_split_single(
~~~~~~~~~~~~~~~~~~~~~~~~~~^
gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
):
^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1579, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.exceptions.DatasetGenerationError: An error occurred while generating the datasetNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
__key__ string | __url__ string | lasagna.json dict |
|---|---|---|
PHercMANBp | hf://datasets/SharpMeow/phercmanbp-lasagna@a59c4b5ed482e229893ae87763573b7b464a7435/PHercMANBp-lasagna-pyramid-fix.tar | {
"version": 2,
"source_to_base": 1,
"grad_mag_encode_scale": 1000,
"grad_mag_factor": 1,
"groups": {
"cos": {
"zarr": "PHercMANBp_cos.ome.zarr/1",
"scaledown": 1,
"channels": [
"cos"
]
},
"grad_mag": {
"zarr": "PHercMANBp_grad_mag.ome.zarr/2",
"scaledow... |
PHercMANBp | hf://datasets/SharpMeow/phercmanbp-lasagna@a59c4b5ed482e229893ae87763573b7b464a7435/parts/PHercMANBp-lasagna-t000.tar | {
"version": 2,
"source_to_base": 1,
"grad_mag_encode_scale": 1000,
"grad_mag_factor": 1,
"groups": {
"cos": {
"zarr": "PHercMANBp_cos.ome.zarr/1",
"scaledown": 1,
"channels": [
"cos"
]
},
"grad_mag": {
"zarr": "PHercMANBp_grad_mag.ome.zarr/2",
"scaledow... |
inference | hf://datasets/SharpMeow/phercmanbp-lasagna@a59c4b5ed482e229893ae87763573b7b464a7435/parts/PHercMANBp-lasagna-t000.tar | null |
PHercMANBp | hf://datasets/SharpMeow/phercmanbp-lasagna@a59c4b5ed482e229893ae87763573b7b464a7435/parts/PHercMANBp-lasagna-t001.tar | {
"version": 2,
"source_to_base": 1,
"grad_mag_encode_scale": 1000,
"grad_mag_factor": 1,
"groups": {
"cos": {
"zarr": "PHercMANBp_cos.ome.zarr/1",
"scaledown": 1,
"channels": [
"cos"
]
},
"grad_mag": {
"zarr": "PHercMANBp_grad_mag.ome.zarr/2",
"scaledow... |
inference | hf://datasets/SharpMeow/phercmanbp-lasagna@a59c4b5ed482e229893ae87763573b7b464a7435/parts/PHercMANBp-lasagna-t001.tar | null |
PHercMANBp | hf://datasets/SharpMeow/phercmanbp-lasagna@a59c4b5ed482e229893ae87763573b7b464a7435/parts/PHercMANBp-lasagna-t002.tar | {
"version": 2,
"source_to_base": 1,
"grad_mag_encode_scale": 1000,
"grad_mag_factor": 1,
"groups": {
"cos": {
"zarr": "PHercMANBp_cos.ome.zarr/1",
"scaledown": 1,
"channels": [
"cos"
]
},
"grad_mag": {
"zarr": "PHercMANBp_grad_mag.ome.zarr/2",
"scaledow... |
inference | hf://datasets/SharpMeow/phercmanbp-lasagna@a59c4b5ed482e229893ae87763573b7b464a7435/parts/PHercMANBp-lasagna-t002.tar | null |
PHercMANBp | hf://datasets/SharpMeow/phercmanbp-lasagna@a59c4b5ed482e229893ae87763573b7b464a7435/parts/PHercMANBp-lasagna-t003.tar | {
"version": 2,
"source_to_base": 1,
"grad_mag_encode_scale": 1000,
"grad_mag_factor": 1,
"groups": {
"cos": {
"zarr": "PHercMANBp_cos.ome.zarr/1",
"scaledown": 1,
"channels": [
"cos"
]
},
"grad_mag": {
"zarr": "PHercMANBp_grad_mag.ome.zarr/2",
"scaledow... |
inference | hf://datasets/SharpMeow/phercmanbp-lasagna@a59c4b5ed482e229893ae87763573b7b464a7435/parts/PHercMANBp-lasagna-t003.tar | null |
PHercMANBp | hf://datasets/SharpMeow/phercmanbp-lasagna@a59c4b5ed482e229893ae87763573b7b464a7435/parts/PHercMANBp-lasagna-t004.tar | {
"version": 2,
"source_to_base": 1,
"grad_mag_encode_scale": 1000,
"grad_mag_factor": 1,
"groups": {
"cos": {
"zarr": "PHercMANBp_cos.ome.zarr/1",
"scaledown": 1,
"channels": [
"cos"
]
},
"grad_mag": {
"zarr": "PHercMANBp_grad_mag.ome.zarr/2",
"scaledow... |
inference | hf://datasets/SharpMeow/phercmanbp-lasagna@a59c4b5ed482e229893ae87763573b7b464a7435/parts/PHercMANBp-lasagna-t004.tar | null |
PHercMANBp lasagna field
villa's lasagna predict3d output for the whole PHercMANBp scan, in villa's own layout, so you can point lasagna or the
spiral fit at it without running the model yourself. The open data has no lasagna field for this scan.
Get it
hf download SharpMeow/phercmanbp-lasagna --repo-type dataset --local-dir phercmanbp-lasagna
cd phercmanbp-lasagna && sha256sum -c SHA256SUMS
for f in parts/*.tar; do tar -xf "$f"; done
tar -xf PHercMANBp-lasagna-pyramid-fix.tar # last: the joined PHercMANBp.lasagna.json
You end up with PHercMANBp.lasagna.json and PHercMANBp_{cos,grad_mag,nx,ny}.ome.zarr, 375 MB in all.
Load it
Here the scan is level 2 of the 2.399 um volume (9.60 um voxels), as villa reads its fine scans; every coordinate below is in that grid.
import numpy as np
import zarr
cos = zarr.open("PHercMANBp_cos.ome.zarr/1", mode="r") # every 2nd scan voxel
nx = zarr.open("PHercMANBp_nx.ome.zarr/2", mode="r") # every 4th scan voxel
ny = zarr.open("PHercMANBp_ny.ome.zarr/2", mode="r")
print("cos", cos.shape, "normals", nx.shape)
z, y, x = 1536, 1572, 1572 # a point in full-resolution scan voxels
patch = cos[z // 2, y // 2 - 256:y // 2 + 256, x // 2 - 256:x // 2 + 256]
a = (float(nx[z // 4, y // 4, x // 4]) - 128) / 127
b = (float(ny[z // 4, y // 4, x // 4]) - 128) / 127
print("cos patch", patch.shape, "mean", round(float(patch.mean()), 1))
print("normal", round(a, 3), round(b, 3), round(float(np.sqrt(max(0.0, 1 - a * a - b * b))), 3))
load_example.py is this snippet; it was run on the real parts before upload.
What it is
- Scan: PHercMANBp,
20251216152116-2.399um-0.2m-78keV-masked.zarr, level 2, Vesuvius Challenge open data - Model:
scrollprize/lasagnamodel_current.ptat revision de45f011 (sha256 4cc0c40a...) - Code: ScrollPrize/villa lasagna at db3dbea2,
lasagna-preprocess predict3d --tile-size 192, default chunks and levels - Channels: cos at OME-Zarr level 1 (2x down); grad_mag, nx, ny at level 2 (4x down); each with its pyramid
- Run: 5 parts on Hugging Face Jobs (RTX PRO 6000), one 1,024-slice slab each. Every part edge sits on a multiple of 1,024 scan voxels, so every chunk of every level, level 4 included, was written by exactly one part, and the parts together are the whole field. A seam check across every part edge found no step (worst ratio 1.203 against a 1.5 limit).
- Settings check: the same code and settings reproduce villa's published PHerc0343 lasagna field on a test crop (cos within 2 of 255 at every voxel compared).
- Previews: xy at z 2,144 and xz at y 1,572 (scan voxels of the level read).
Notes
Raw model output; nobody has checked it by eye. Regions the masked scan leaves empty are absent (fill 0). The model ran on the scan at the level named above with no resampling.
Related
villa lasagna fields for ten more scans are on the Lasagna Fields page.
Credit and terms
The scan is Vesuvius Challenge open data, CC BY-NC 4.0; this derived field is shared under the same terms. Model and code are ScrollPrize/villa's lasagna, credit to its authors. Shared by Chase Hendrick.
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