The dataset viewer is not available for this split.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
schema_version: string
generated_at: timestamp[s]
repository: string
contains_ground_truth: bool
visibility: string
datasets: struct<agibot: struct<episode_count: int64, tasks: struct<hangtowel: struct<count: int64, episodes: (... 2278 chars omitted)
child 0, agibot: struct<episode_count: int64, tasks: struct<hangtowel: struct<count: int64, episodes: list<item: stri (... 560 chars omitted)
child 0, episode_count: int64
child 1, tasks: struct<hangtowel: struct<count: int64, episodes: list<item: string>, archives: list<item: struct<epi (... 523 chars omitted)
child 0, hangtowel: struct<count: int64, episodes: list<item: string>, archives: list<item: struct<episode: string, path (... 41 chars omitted)
child 0, count: int64
child 1, episodes: list<item: string>
child 0, item: string
child 2, archives: list<item: struct<episode: string, path: string, bytes: int64, sha256: string>>
child 0, item: struct<episode: string, path: string, bytes: int64, sha256: string>
child 0, episode: string
child 1, path: string
child 2, bytes: int64
child 3, sha256: string
child 1, pickfruit: struct<count: int64, episodes: list<item: string>, archives: list<item: struct<episode: string, path (... 41 chars omitted)
child 0, count: int64
child 1, episodes: list<item: string>
...
em: struct<episode: string, path: string, bytes: int64, sha256: string>>
child 0, item: struct<episode: string, path: string, bytes: int64, sha256: string>
child 0, episode: string
child 1, path: string
child 2, bytes: int64
child 3, sha256: string
child 2, pourwater: struct<count: int64, episodes: list<item: string>, archives: list<item: struct<episode: string, path (... 41 chars omitted)
child 0, count: int64
child 1, episodes: list<item: string>
child 0, item: string
child 2, archives: list<item: struct<episode: string, path: string, bytes: int64, sha256: string>>
child 0, item: struct<episode: string, path: string, bytes: int64, sha256: string>
child 0, episode: string
child 1, path: string
child 2, bytes: int64
child 3, sha256: string
storage_format: struct<type: string, compression: string, layout: string, archive_count: int64>
child 0, type: string
child 1, compression: string
child 2, layout: string
child 3, archive_count: int64
remote_path: string
episode_count: int64
payload: string
human_hand_format: struct<pose_representation: string, contains_delta_action: bool>
child 0, pose_representation: string
child 1, contains_delta_action: bool
contains_ground_truth_target_video: bool
to
{'schema_version': Value('string'), 'generated_at': Value('timestamp[s]'), 'repository': Value('string'), 'remote_path': Value('string'), 'contains_ground_truth_target_video': Value('bool'), 'episode_count': Value('int64'), 'datasets': {'agibot': {'episode_count': Value('int64'), 'tasks': {'hangtowel': {'count': Value('int64'), 'episodes': List(Value('string'))}, 'pickfruit': {'count': Value('int64'), 'episodes': List(Value('string'))}, 'pourwater': {'count': Value('int64'), 'episodes': List(Value('string'))}, 'pulldrawer': {'count': Value('int64'), 'episodes': List(Value('string'))}}}, 'yam': {'episode_count': Value('int64'), 'tasks': {'hangtowel': {'count': Value('int64'), 'episodes': List(Value('string'))}, 'pickfruit': {'count': Value('int64'), 'episodes': List(Value('string'))}, 'pulldrawer': {'count': Value('int64'), 'episodes': List(Value('string'))}}}, 'human_hand': {'episode_count': Value('int64'), 'tasks': {'hangtowel': {'count': Value('int64'), 'episodes': List(Value('string'))}, 'pickfruit': {'count': Value('int64'), 'episodes': List(Value('string'))}, 'pourwater': {'count': Value('int64'), 'episodes': List(Value('string'))}, 'pulldrawer': {'count': Value('int64'), 'episodes': List(Value('string'))}}}, 'policy': {'episode_count': Value('int64'), 'tasks': {'hangtowel': {'count': Value('int64'), 'episodes': List(Value('string'))}, 'pickfruit': {'count': Value('int64'), 'episodes': List(Value('string'))}, 'pourwater': {'count': Value('int64'), 'episodes': List(Value('string'))}}}}, 'payload': Value('string'), 'human_hand_format': {'pose_representation': Value('string'), 'contains_delta_action': Value('bool')}}
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 544, 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 3052, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2559, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2584, 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 558, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 440, 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 361, 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 2381, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2309, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
schema_version: string
generated_at: timestamp[s]
repository: string
contains_ground_truth: bool
visibility: string
datasets: struct<agibot: struct<episode_count: int64, tasks: struct<hangtowel: struct<count: int64, episodes: (... 2278 chars omitted)
child 0, agibot: struct<episode_count: int64, tasks: struct<hangtowel: struct<count: int64, episodes: list<item: stri (... 560 chars omitted)
child 0, episode_count: int64
child 1, tasks: struct<hangtowel: struct<count: int64, episodes: list<item: string>, archives: list<item: struct<epi (... 523 chars omitted)
child 0, hangtowel: struct<count: int64, episodes: list<item: string>, archives: list<item: struct<episode: string, path (... 41 chars omitted)
child 0, count: int64
child 1, episodes: list<item: string>
child 0, item: string
child 2, archives: list<item: struct<episode: string, path: string, bytes: int64, sha256: string>>
child 0, item: struct<episode: string, path: string, bytes: int64, sha256: string>
child 0, episode: string
child 1, path: string
child 2, bytes: int64
child 3, sha256: string
child 1, pickfruit: struct<count: int64, episodes: list<item: string>, archives: list<item: struct<episode: string, path (... 41 chars omitted)
child 0, count: int64
child 1, episodes: list<item: string>
...
em: struct<episode: string, path: string, bytes: int64, sha256: string>>
child 0, item: struct<episode: string, path: string, bytes: int64, sha256: string>
child 0, episode: string
child 1, path: string
child 2, bytes: int64
child 3, sha256: string
child 2, pourwater: struct<count: int64, episodes: list<item: string>, archives: list<item: struct<episode: string, path (... 41 chars omitted)
child 0, count: int64
child 1, episodes: list<item: string>
child 0, item: string
child 2, archives: list<item: struct<episode: string, path: string, bytes: int64, sha256: string>>
child 0, item: struct<episode: string, path: string, bytes: int64, sha256: string>
child 0, episode: string
child 1, path: string
child 2, bytes: int64
child 3, sha256: string
storage_format: struct<type: string, compression: string, layout: string, archive_count: int64>
child 0, type: string
child 1, compression: string
child 2, layout: string
child 3, archive_count: int64
remote_path: string
episode_count: int64
payload: string
human_hand_format: struct<pose_representation: string, contains_delta_action: bool>
child 0, pose_representation: string
child 1, contains_delta_action: bool
contains_ground_truth_target_video: bool
to
{'schema_version': Value('string'), 'generated_at': Value('timestamp[s]'), 'repository': Value('string'), 'remote_path': Value('string'), 'contains_ground_truth_target_video': Value('bool'), 'episode_count': Value('int64'), 'datasets': {'agibot': {'episode_count': Value('int64'), 'tasks': {'hangtowel': {'count': Value('int64'), 'episodes': List(Value('string'))}, 'pickfruit': {'count': Value('int64'), 'episodes': List(Value('string'))}, 'pourwater': {'count': Value('int64'), 'episodes': List(Value('string'))}, 'pulldrawer': {'count': Value('int64'), 'episodes': List(Value('string'))}}}, 'yam': {'episode_count': Value('int64'), 'tasks': {'hangtowel': {'count': Value('int64'), 'episodes': List(Value('string'))}, 'pickfruit': {'count': Value('int64'), 'episodes': List(Value('string'))}, 'pulldrawer': {'count': Value('int64'), 'episodes': List(Value('string'))}}}, 'human_hand': {'episode_count': Value('int64'), 'tasks': {'hangtowel': {'count': Value('int64'), 'episodes': List(Value('string'))}, 'pickfruit': {'count': Value('int64'), 'episodes': List(Value('string'))}, 'pourwater': {'count': Value('int64'), 'episodes': List(Value('string'))}, 'pulldrawer': {'count': Value('int64'), 'episodes': List(Value('string'))}}}, 'policy': {'episode_count': Value('int64'), 'tasks': {'hangtowel': {'count': Value('int64'), 'episodes': List(Value('string'))}, 'pickfruit': {'count': Value('int64'), 'episodes': List(Value('string'))}, 'pourwater': {'count': Value('int64'), 'episodes': List(Value('string'))}}}}, 'payload': Value('string'), 'human_hand_format': {'pose_representation': Value('string'), 'contains_delta_action': Value('bool')}}
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.
WorldOracle Validation Ground Truth
This public dataset contains the frozen WorldOracle validation split and its ground-truth data. It contains validation episodes only and does not include test-set ground truth.
The data is stored as one uncompressed tar archive per episode. This keeps the
repository resumable and avoids hundreds of thousands of individual Hub files.
Extract an episode with tar -xf <episode>.tar -C <destination>.
Platforms
| Platform | Episodes |
|---|---|
| AgiBot | 20 |
| YAM | 15 |
| Human Hand | 20 |
| Policy | 12 |
| Total | 67 |
validation_manifest.json is the canonical inventory. It records the path,
size and SHA-256 of every episode archive. SHA256SUMS covers all repository
files except itself. Validation inputs are available under inputs/.
Human Hand absolute pose format
Human Hand validation inputs provide synchronized absolute hand and camera
poses in controls/hand_camera_poses.npz. Pose sample t corresponds directly
to validation video frame t.
left_positions_cameraandright_positions_cameracontain the 21 hand joints in the released camera-reference coordinates.left_quaternions_camera_xyzwandright_quaternions_camera_xyzwcontain the corresponding joint orientations in XYZW order.camera_position_worldandcamera_quaternion_world_xyzwcontain the tracked camera-reference pose.left_valid,right_valid, andcamera_validindicate whether each measurement is usable.
The leading initialization interval in which the pose tracking was invalid has been removed, so the first released sample is valid. Any unavailable measurements occurring later in an episode remain present and are marked by the validity arrays. Delta-action tensors, source-frame indices, internal source mappings, and cleaning records are not part of the public release.
Human Hand joint visualization
scripts/visualize_human_hand.py provides a
standalone example for projecting the released 3D hand joints onto the
rectified top_head frames of a public Human Hand validation episode. It reads
the episode's released hand_camera_poses.npz and calibration.json, applies
the tracked-camera, physical-fisheye, and virtual-camera transformations, and
renders the left- and right-hand 21-joint skeletons next to the original
frames.
Install the two runtime dependencies with:
python -m pip install numpy opencv-python
After extracting one of the public Human Hand validation archives, run:
python scripts/visualize_human_hand.py \
--npz inputs/human_hand/<task>/<episode>/controls/hand_camera_poses.npz \
--calibration inputs/human_hand/<task>/<episode>/calibration.json \
--frames-dir <extracted-episode>/video/top_head \
--output hand_joint_projection.mp4 \
--fps 15
The script requires the image sequence and NPZ arrays to have identical frame counts and respects the released hand- and camera-validity masks. It contains no hard-coded episode list or camera parameters; all geometry is read from the selected public validation episode.
License and Citation
All data in this repository are licensed under CC BY-NC-SA 4.0. If you find our benchmark useful in your research, please consider citing our work.
@article{duan2026worldoracle,
title={WorldOracle: Benchmarking Action-Conditioned World Models against Real-World Executions},
author={Duan, Haoyi and Chen, Liliang and Wang, Nan and Zhang, Yang and Lu, Yuhang and Chen, Xiaotong and Tseng, Wei-Cheng and Gao, Shenyuan and Li, Zhaoshuo and Jin, Jingyi and others},
journal={arXiv preprint arXiv:2610.18826},
year={2026}
}
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