The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
image: struct<bytes: binary, path: string>
child 0, bytes: binary
child 1, path: string
annotation: struct<description: string, objects: list<element: struct<bitmap: struct<data: string, origin: list<element: int64>>, classId: int64, classTitle: string, createdAt: string, description: string, geometryType: string, id: int64, labelerLogin: string, points: struct<exterior: list<element: list<element: int64>>, interior: list<element: list<element: list<element: int64>>>>, tags: list<element: null>, updatedAt: string>>, size: struct<height: int64, width: int64>, tags: list<element: struct<createdAt: string, id: int64, labelerLogin: string, name: string, tagId: int64, updatedAt: string, value: null>>>
child 0, description: string
child 1, objects: list<element: struct<bitmap: struct<data: string, origin: list<element: int64>>, classId: int64, classTitle: string, createdAt: string, description: string, geometryType: string, id: int64, labelerLogin: string, points: struct<exterior: list<element: list<element: int64>>, interior: list<element: list<element: list<element: int64>>>>, tags: list<element: null>, updatedAt: string>>
child 0, element: struct<bitmap: struct<data: string, origin: list<element: int64>>, classId: int64, classTitle: string, createdAt: string, description: string, geometryType: string, id: int64, labelerLogin: string, points: struct<exterior: list<element: list<element: int64>>, interior: list<element: list<element: list<element: int64>>>>, tags: li
...
d 0, element: list<element: int64>
child 0, element: int64
child 1, interior: list<element: list<element: list<element: int64>>>
child 0, element: list<element: list<element: int64>>
child 0, element: list<element: int64>
child 0, element: int64
child 9, tags: list<element: null>
child 0, element: null
child 10, updatedAt: string
child 2, size: struct<height: int64, width: int64>
child 0, height: int64
child 1, width: int64
child 3, tags: list<element: struct<createdAt: string, id: int64, labelerLogin: string, name: string, tagId: int64, updatedAt: string, value: null>>
child 0, element: struct<createdAt: string, id: int64, labelerLogin: string, name: string, tagId: int64, updatedAt: string, value: null>
child 0, createdAt: string
child 1, id: int64
child 2, labelerLogin: string
child 3, name: string
child 4, tagId: int64
child 5, updatedAt: string
child 6, value: null
filename: string
embedding: list<element: float>
child 0, element: float
cropped: struct<bytes: binary, path: string>
child 0, bytes: binary
child 1, path: string
text: string
conditioning_image: struct<bytes: binary, path: string>
child 0, bytes: binary
child 1, path: string
-- schema metadata --
huggingface: '{"info": {"features": {"image": {"_type": "Image"}, "annota' + 1713
to
{'image': Image(mode=None, decode=True, id=None), 'annotation': {'description': Value(dtype='string', id=None), 'objects': [{'bitmap': {'data': Value(dtype='string', id=None), 'origin': Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None)}, 'classId': Value(dtype='int64', id=None), 'classTitle': Value(dtype='string', id=None), 'createdAt': Value(dtype='string', id=None), 'description': Value(dtype='string', id=None), 'geometryType': Value(dtype='string', id=None), 'id': Value(dtype='int64', id=None), 'labelerLogin': Value(dtype='string', id=None), 'points': {'exterior': Sequence(feature=Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), length=-1, id=None), 'interior': Sequence(feature=Sequence(feature=Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), length=-1, id=None), length=-1, id=None)}, 'tags': Sequence(feature=Value(dtype='null', id=None), length=-1, id=None), 'updatedAt': Value(dtype='string', id=None)}], 'size': {'height': Value(dtype='int64', id=None), 'width': Value(dtype='int64', id=None)}, 'tags': [{'createdAt': Value(dtype='string', id=None), 'id': Value(dtype='int64', id=None), 'labelerLogin': Value(dtype='string', id=None), 'name': Value(dtype='string', id=None), 'tagId': Value(dtype='int64', id=None), 'updatedAt': Value(dtype='string', id=None), 'value': Value(dtype='null', id=None)}]}, 'filename': Value(dtype='string', id=None), 'embedding': Sequence(feature=Value(dtype='float32', id=None), length=-1, id=None), 'cropped': Image(mode=None, decode=True, id=None), 'text': Value(dtype='string', id=None)}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 322, in compute
compute_first_rows_from_parquet_response(
File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 88, in compute_first_rows_from_parquet_response
rows_index = indexer.get_rows_index(
File "/src/libs/libcommon/src/libcommon/parquet_utils.py", line 640, in get_rows_index
return RowsIndex(
File "/src/libs/libcommon/src/libcommon/parquet_utils.py", line 521, in __init__
self.parquet_index = self._init_parquet_index(
File "/src/libs/libcommon/src/libcommon/parquet_utils.py", line 538, in _init_parquet_index
response = get_previous_step_or_raise(
File "/src/libs/libcommon/src/libcommon/simple_cache.py", line 591, in get_previous_step_or_raise
raise CachedArtifactError(
libcommon.simple_cache.CachedArtifactError: The previous step failed.
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 96, in get_rows_or_raise
return get_rows(
File "/src/libs/libcommon/src/libcommon/utils.py", line 197, in decorator
return func(*args, **kwargs)
File "/src/services/worker/src/worker/utils.py", line 73, in get_rows
rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1389, in __iter__
for key, example in ex_iterable:
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 282, in __iter__
for key, pa_table in self.generate_tables_fn(**self.kwargs):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/parquet/parquet.py", line 97, in _generate_tables
yield f"{file_idx}_{batch_idx}", self._cast_table(pa_table)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/parquet/parquet.py", line 75, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2302, in table_cast
return cast_table_to_schema(table, schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2256, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
image: struct<bytes: binary, path: string>
child 0, bytes: binary
child 1, path: string
annotation: struct<description: string, objects: list<element: struct<bitmap: struct<data: string, origin: list<element: int64>>, classId: int64, classTitle: string, createdAt: string, description: string, geometryType: string, id: int64, labelerLogin: string, points: struct<exterior: list<element: list<element: int64>>, interior: list<element: list<element: list<element: int64>>>>, tags: list<element: null>, updatedAt: string>>, size: struct<height: int64, width: int64>, tags: list<element: struct<createdAt: string, id: int64, labelerLogin: string, name: string, tagId: int64, updatedAt: string, value: null>>>
child 0, description: string
child 1, objects: list<element: struct<bitmap: struct<data: string, origin: list<element: int64>>, classId: int64, classTitle: string, createdAt: string, description: string, geometryType: string, id: int64, labelerLogin: string, points: struct<exterior: list<element: list<element: int64>>, interior: list<element: list<element: list<element: int64>>>>, tags: list<element: null>, updatedAt: string>>
child 0, element: struct<bitmap: struct<data: string, origin: list<element: int64>>, classId: int64, classTitle: string, createdAt: string, description: string, geometryType: string, id: int64, labelerLogin: string, points: struct<exterior: list<element: list<element: int64>>, interior: list<element: list<element: list<element: int64>>>>, tags: li
...
d 0, element: list<element: int64>
child 0, element: int64
child 1, interior: list<element: list<element: list<element: int64>>>
child 0, element: list<element: list<element: int64>>
child 0, element: list<element: int64>
child 0, element: int64
child 9, tags: list<element: null>
child 0, element: null
child 10, updatedAt: string
child 2, size: struct<height: int64, width: int64>
child 0, height: int64
child 1, width: int64
child 3, tags: list<element: struct<createdAt: string, id: int64, labelerLogin: string, name: string, tagId: int64, updatedAt: string, value: null>>
child 0, element: struct<createdAt: string, id: int64, labelerLogin: string, name: string, tagId: int64, updatedAt: string, value: null>
child 0, createdAt: string
child 1, id: int64
child 2, labelerLogin: string
child 3, name: string
child 4, tagId: int64
child 5, updatedAt: string
child 6, value: null
filename: string
embedding: list<element: float>
child 0, element: float
cropped: struct<bytes: binary, path: string>
child 0, bytes: binary
child 1, path: string
text: string
conditioning_image: struct<bytes: binary, path: string>
child 0, bytes: binary
child 1, path: string
-- schema metadata --
huggingface: '{"info": {"features": {"image": {"_type": "Image"}, "annota' + 1713
to
{'image': Image(mode=None, decode=True, id=None), 'annotation': {'description': Value(dtype='string', id=None), 'objects': [{'bitmap': {'data': Value(dtype='string', id=None), 'origin': Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None)}, 'classId': Value(dtype='int64', id=None), 'classTitle': Value(dtype='string', id=None), 'createdAt': Value(dtype='string', id=None), 'description': Value(dtype='string', id=None), 'geometryType': Value(dtype='string', id=None), 'id': Value(dtype='int64', id=None), 'labelerLogin': Value(dtype='string', id=None), 'points': {'exterior': Sequence(feature=Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), length=-1, id=None), 'interior': Sequence(feature=Sequence(feature=Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), length=-1, id=None), length=-1, id=None)}, 'tags': Sequence(feature=Value(dtype='null', id=None), length=-1, id=None), 'updatedAt': Value(dtype='string', id=None)}], 'size': {'height': Value(dtype='int64', id=None), 'width': Value(dtype='int64', id=None)}, 'tags': [{'createdAt': Value(dtype='string', id=None), 'id': Value(dtype='int64', id=None), 'labelerLogin': Value(dtype='string', id=None), 'name': Value(dtype='string', id=None), 'tagId': Value(dtype='int64', id=None), 'updatedAt': Value(dtype='string', id=None), 'value': Value(dtype='null', id=None)}]}, 'filename': Value(dtype='string', id=None), 'embedding': Sequence(feature=Value(dtype='float32', id=None), length=-1, id=None), 'cropped': Image(mode=None, decode=True, id=None), 'text': Value(dtype='string', id=None)}
because column names don't matchNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.