The dataset viewer is not available for this split.
Error code: StreamingRowsError
Exception: TypeError
Message: Couldn't cast array of type
struct<ome: struct<version: string, _creator: struct<name: string, version: string, notes: null>, multiscales: list<item: struct<axes: list<item: struct<name: string, type: string, unit: string>>, datasets: list<item: struct<coordinateTransformations: list<item: struct<scale: list<item: double>, type: string>>, path: string>>, name: string>>, omero: struct<channels: list<item: struct<active: bool, coefficient: double, color: string, family: string, inverted: bool, label: string, window: struct<end: double, max: double, min: double, start: double>>>, id: int64, rdefs: struct<defaultT: int64, defaultZ: int64, model: string>>>>
to
{}
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
return get_rows(
^^^^^^^^^
File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "/src/services/worker/src/worker/utils.py", line 77, in get_rows
rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2690, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2227, in __iter__
for key, pa_table in self._iter_arrow():
^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2251, in _iter_arrow
for key, pa_table in self.ex_iterable._iter_arrow():
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 494, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 384, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 295, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 128, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2281, in table_cast
return cast_table_to_schema(table, schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2233, in cast_table_to_schema
cast_array_to_feature(
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 1804, in wrapper
return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2101, in cast_array_to_feature
raise TypeError(f"Couldn't cast array of type\n{_short_str(array.type)}\nto\n{_short_str(feature)}")
TypeError: Couldn't cast array of type
struct<ome: struct<version: string, _creator: struct<name: string, version: string, notes: null>, multiscales: list<item: struct<axes: list<item: struct<name: string, type: string, unit: string>>, datasets: list<item: struct<coordinateTransformations: list<item: struct<scale: list<item: double>, type: string>>, path: string>>, name: string>>, omero: struct<channels: list<item: struct<active: bool, coefficient: double, color: string, family: string, inverted: bool, label: string, window: struct<end: double, max: double, min: double, start: double>>>, id: int64, rdefs: struct<defaultT: int64, defaultZ: int64, model: string>>>>
to
{}Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
This image data has been taken from the IDR OME-NGFF Samples- Catalog of IDR images formatted as OME-NGFF (https://idr.github.io/ome-ngff-samples/) Sample id: ExpA_VIP_ASLM_on.zarr
This dataset is used to show the viability of Zarr image streaming and uploading using 🤗 datasets library corresponding to the PR: [Add Zarr / OME-Zarr Dataset Support
]
Zarr / OME-Zarr Data Repository
This repository stores Zarr / OME-Zarr array data for large-scale scientific imaging workflows.
The data in this repository is organized as chunked multidimensional Zarr stores. These stores are intended to be accessed lazily by reading only the chunks, slices, multiscale levels, thumbnails, or patches needed for analysis or model training.
For the standard 🤗 datasets workflow, use the companion lightweight index dataset instead of loading this repository directly. Index Dataset: LuciexJune/ome-vip-index
Recommended Access Pattern
This repository is the heavy data repository.
A separate index repository contains one row per sample, with metadata and an hf:// path pointing to the corresponding Zarr store in this repo.
Recommended workflow:
- Load the companion index dataset with
streaming=True. - Cast the Zarr path column to
datasets.Zarr. - Access array data lazily through the decoded proxy.
from datasets import Zarr, load_dataset
ds = load_dataset(
"USERNAME/INDEX_REPO_NAME",
split="train",
streaming=True,
)
ds = ds.cast_column("scan", Zarr())
sample = next(iter(ds))
proxy = sample["scan"]
print(proxy.shape)
print(proxy.dtype)
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