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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
archive_size: int64
archive_url: string
bytes: int64
created_at: string
is_final: bool
next_tar_offset: int64
objects_per_shard: int64
padded_samples: int64
padding_rows: list<item: struct<donor_key: string, key: string>>
child 0, item: struct<donor_key: string, key: string>
child 0, donor_key: string
child 1, key: string
padding_strategy: string
repo_id: string
sample_keys: list<item: string>
child 0, item: string
samples: int64
schema: string
sha256: string
shard_index: int64
source: string
source_start_offset: int64
source_unique_samples: int64
to
{'archive_size': Value('int64'), 'archive_url': Value('string'), 'bytes': Value('int64'), 'created_at': Value('string'), 'is_final': Value('bool'), 'next_tar_offset': Value('int64'), 'objects_per_shard': Value('int64'), 'repo_id': Value('string'), 'sample_keys': List(Value('string')), 'samples': Value('int64'), 'schema': Value('string'), 'sha256': Value('string'), 'shard_index': Value('int64'), 'source': Value('string'), 'source_start_offset': Value('int64')}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 149, in get_rows_or_raise
return get_rows(
dataset=dataset,
...<4 lines>...
column_names=column_names,
)
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 129, in get_rows
rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
File "/src/services/worker/src/worker/utils.py", line 489, in safe_iter
yield from ds.decode(False) if ds.features else ds
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2818, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2355, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2380, in _iter_arrow
for key, pa_table in self.ex_iterable._iter_arrow():
~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2369, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
archive_size: int64
archive_url: string
bytes: int64
created_at: string
is_final: bool
next_tar_offset: int64
objects_per_shard: int64
padded_samples: int64
padding_rows: list<item: struct<donor_key: string, key: string>>
child 0, item: struct<donor_key: string, key: string>
child 0, donor_key: string
child 1, key: string
padding_strategy: string
repo_id: string
sample_keys: list<item: string>
child 0, item: string
samples: int64
schema: string
sha256: string
shard_index: int64
source: string
source_start_offset: int64
source_unique_samples: int64
to
{'archive_size': Value('int64'), 'archive_url': Value('string'), 'bytes': Value('int64'), 'created_at': Value('string'), 'is_final': Value('bool'), 'next_tar_offset': Value('int64'), 'objects_per_shard': Value('int64'), 'repo_id': Value('string'), 'sample_keys': List(Value('string')), 'samples': Value('int64'), 'schema': Value('string'), 'sha256': Value('string'), 'shard_index': Value('int64'), 'source': Value('string'), 'source_start_offset': Value('int64')}
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.
ABO material-intrinsics WebDataset
Preliminary publication smoke for the IDArb-compatible Amazon Berkeley Objects material-render conversion. The smoke shard contains 10 complete objects with 91 views and three environment lights per object.
Each tar member is one compressed NPZ containing rgb, albedo, roughness, metallic,
normal, mask, depth, and meta_json. Source-specific material channels, camera conventions,
normal axes, masks, and background compositing are normalized during conversion.
Source: Amazon Berkeley Objects. ABO is licensed under CC BY 4.0. Credit for the data must be given to Amazon.com; cite the ABO CVPR 2022 paper when using it.
Production publication is in progress. Root shard-*.tar files contain exactly 500 unique objects
except the final source remainder; matching provenance and SHA-256 records live under
manifests/. smoke/shard-000000.tar remains the independently verified validation artifact.
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