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Cannot load the dataset split (in streaming mode) to extract the first rows.
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 match

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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_camera and right_positions_camera contain the 21 hand joints in the released camera-reference coordinates.
  • left_quaternions_camera_xyzw and right_quaternions_camera_xyzw contain the corresponding joint orientations in XYZW order.
  • camera_position_world and camera_quaternion_world_xyzw contain the tracked camera-reference pose.
  • left_valid, right_valid, and camera_valid indicate 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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Paper for WorldOracle/worldoracle-validation