Search is not available for this dataset
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.
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