Dataset Viewer
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
schema_version: int64
dataset: string
upstream: struct<dataset: string, revision: string, source_parquet_sha256: string>
child 0, dataset: string
child 1, revision: string
child 2, source_parquet_sha256: string
annotation_exports: list<item: struct<source: string, sha256: string, clips: int64>>
child 0, item: struct<source: string, sha256: string, clips: int64>
child 0, source: string
child 1, sha256: string
child 2, clips: int64
rows: int64
segments: int64
families: struct<droid: int64, galaxea: int64, homer: int64>
child 0, droid: int64
child 1, galaxea: int64
child 2, homer: int64
privacy: struct<review_status_included: bool, reviewer_metadata_included: bool, internal_video_ids_included: (... 5 chars omitted)
child 0, review_status_included: bool
child 1, reviewer_metadata_included: bool
child 2, internal_video_ids_included: bool
files: struct<data/annotations.parquet: struct<bytes: int64, sha256: string>, data/corrected-annotations.js (... 41 chars omitted)
child 0, data/annotations.parquet: struct<bytes: int64, sha256: string>
child 0, bytes: int64
child 1, sha256: string
child 1, data/corrected-annotations.json: struct<bytes: int64, sha256: string>
child 0, bytes: int64
child 1, sha256: string
upstream_dataset: string
upstream_revision: string
episodes: list<item: struct<id: string, instruction: string, segments: list<item: struct<start_sec: double, en (... 88 chars omitted)
child 0, item: struct<id: string, instruction: string, segments: list<item: struct<start_sec: double, end_sec: doub (... 76 chars omitted)
child 0, id: string
child 1, instruction: string
child 2, segments: list<item: struct<start_sec: double, end_sec: double, subtask: string>>
child 0, item: struct<start_sec: double, end_sec: double, subtask: string>
child 0, start_sec: double
child 1, end_sec: double
child 2, subtask: string
child 3, episode_task_success: string
child 4, episode_quality: int64
to
{'schema_version': Value('int64'), 'dataset': Value('string'), 'upstream_dataset': Value('string'), 'upstream_revision': Value('string'), 'episodes': List({'id': Value('string'), 'instruction': Value('string'), 'segments': List({'start_sec': Value('float64'), 'end_sec': Value('float64'), 'subtask': Value('string')}), 'episode_task_success': Value('string'), 'episode_quality': Value('int64')})}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 147, 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 127, 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 483, 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 2840, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2373, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2398, 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 2378, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
schema_version: int64
dataset: string
upstream: struct<dataset: string, revision: string, source_parquet_sha256: string>
child 0, dataset: string
child 1, revision: string
child 2, source_parquet_sha256: string
annotation_exports: list<item: struct<source: string, sha256: string, clips: int64>>
child 0, item: struct<source: string, sha256: string, clips: int64>
child 0, source: string
child 1, sha256: string
child 2, clips: int64
rows: int64
segments: int64
families: struct<droid: int64, galaxea: int64, homer: int64>
child 0, droid: int64
child 1, galaxea: int64
child 2, homer: int64
privacy: struct<review_status_included: bool, reviewer_metadata_included: bool, internal_video_ids_included: (... 5 chars omitted)
child 0, review_status_included: bool
child 1, reviewer_metadata_included: bool
child 2, internal_video_ids_included: bool
files: struct<data/annotations.parquet: struct<bytes: int64, sha256: string>, data/corrected-annotations.js (... 41 chars omitted)
child 0, data/annotations.parquet: struct<bytes: int64, sha256: string>
child 0, bytes: int64
child 1, sha256: string
child 1, data/corrected-annotations.json: struct<bytes: int64, sha256: string>
child 0, bytes: int64
child 1, sha256: string
upstream_dataset: string
upstream_revision: string
episodes: list<item: struct<id: string, instruction: string, segments: list<item: struct<start_sec: double, en (... 88 chars omitted)
child 0, item: struct<id: string, instruction: string, segments: list<item: struct<start_sec: double, end_sec: doub (... 76 chars omitted)
child 0, id: string
child 1, instruction: string
child 2, segments: list<item: struct<start_sec: double, end_sec: double, subtask: string>>
child 0, item: struct<start_sec: double, end_sec: double, subtask: string>
child 0, start_sec: double
child 1, end_sec: double
child 2, subtask: string
child 3, episode_task_success: string
child 4, episode_quality: int64
to
{'schema_version': Value('int64'), 'dataset': Value('string'), 'upstream_dataset': Value('string'), 'upstream_revision': Value('string'), 'episodes': List({'id': Value('string'), 'instruction': Value('string'), 'segments': List({'start_sec': Value('float64'), 'end_sec': Value('float64'), 'subtask': Value('string')}), 'episode_task_success': Value('string'), 'episode_quality': 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.
WGO-Bench
MacroData's WGO-Bench is a benchmark for evaluating timestamped subtask annotations from robot and egocentric manipulation videos. MacroData describes the benchmark and its annotation approach in Segmenting Robot Video into Actionable Subtasks.
The upstream repository's summary.json states that its timeline reannotations were applied only to the 25 homer_* episodes, while the DROID and Galaxea rows were left unchanged. During our review of all 100 episodes, we found additional annotation issues. We discuss those issues and our reannotation process in the VideoDB WGO-Bench reannotation report.
This dataset retains the original videos and perception data and replaces the task and timestamped subtask annotations with our reviewed annotations.
Dataset
- Episodes: 100
- Corrected subtask segments: 534
- Families: 50 DROID, 25 Galaxea, and 25 HOMER
- Format: Parquet
- Videos: MP4 bytes embedded in each row
Each row contains the episode ID, video, high-level instruction, timestamped subtask segments, metadata, and available perception state.
License
The source dataset is licensed CC BY-NC-SA 4.0. This dataset uses the same license.
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