Dataset Viewer
Full Screen Viewer
Full Screen
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 match
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.
- Downloads last month
- 41