Datasets:
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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
action: struct<min: list<item: double>, max: list<item: double>, mean: list<item: double>, std: list<item: d (... 158 chars omitted)
child 0, min: list<item: double>
child 0, item: double
child 1, max: list<item: double>
child 0, item: double
child 2, mean: list<item: double>
child 0, item: double
child 3, std: list<item: double>
child 0, item: double
child 4, count: list<item: int64>
child 0, item: int64
child 5, q01: list<item: double>
child 0, item: double
child 6, q10: list<item: double>
child 0, item: double
child 7, q50: list<item: double>
child 0, item: double
child 8, q90: list<item: double>
child 0, item: double
child 9, q99: list<item: double>
child 0, item: double
observation.state: struct<min: list<item: double>, max: list<item: double>, mean: list<item: double>, std: list<item: d (... 158 chars omitted)
child 0, min: list<item: double>
child 0, item: double
child 1, max: list<item: double>
child 0, item: double
child 2, mean: list<item: double>
child 0, item: double
child 3, std: list<item: double>
child 0, item: double
child 4, count: list<item: int64>
child 0, item: int64
child 5, q01: list<item: double>
child 0, item: double
child 6, q10: list<item: double>
child 0, item: double
child 7, q50: list<item: double>
child 0, item: double
child 8, q90: list<item: double>
child 0, item: double
child 9, q99: list<ite
...
child 2, names: list<item: string>
child 0, item: string
child 3, info: struct<video.height: int64, video.width: int64, video.codec: string, video.pix_fmt: string, video.is (... 75 chars omitted)
child 0, video.height: int64
child 1, video.width: int64
child 2, video.codec: string
child 3, video.pix_fmt: string
child 4, video.is_depth_map: bool
child 5, video.fps: int64
child 6, video.channels: int64
child 7, has_audio: bool
child 2, observation.images.base: struct<dtype: string, shape: list<item: int64>, names: list<item: string>, info: struct<video.height (... 157 chars omitted)
child 0, dtype: string
child 1, shape: list<item: int64>
child 0, item: int64
child 2, names: list<item: string>
child 0, item: string
child 3, info: struct<video.height: int64, video.width: int64, video.codec: string, video.pix_fmt: string, video.is (... 75 chars omitted)
child 0, video.height: int64
child 1, video.width: int64
child 2, video.codec: string
child 3, video.pix_fmt: string
child 4, video.is_depth_map: bool
child 5, video.fps: int64
child 6, video.channels: int64
child 7, has_audio: bool
child 16, original_video_source: string
child 17, video_policy: string
to
{'codebase_version': Value('string'), 'robot_type': Value('string'), 'total_episodes': Value('int64'), 'total_frames': Value('int64'), 'total_tasks': Value('int64'), 'chunks_size': Value('int64'), 'data_files_size_in_mb': Value('int64'), 'video_files_size_in_mb': Value('int64'), 'fps': Value('int64'), 'splits': {'train': Value('string')}, 'data_path': Value('string'), 'features': {'Time': {'dtype': Value('string'), 'shape': List(Value('int64')), 'tsfile_role': Value('string'), 'unit': Value('string')}, 'episode_index': {'dtype': Value('string'), 'shape': List(Value('int64')), 'tsfile_role': Value('string')}, 'task_index': {'dtype': Value('string'), 'shape': List(Value('int64')), 'tsfile_role': Value('string')}, 'frame_index': {'dtype': Value('string'), 'shape': List(Value('int64')), 'tsfile_role': Value('string')}, 'sample_index': {'dtype': Value('string'), 'shape': List(Value('int64')), 'tsfile_role': Value('string')}, 'action_0': {'dtype': Value('string'), 'shape': List(Value('int64')), 'tsfile_role': Value('string')}, 'action_1': {'dtype': Value('string'), 'shape': List(Value('int64')), 'tsfile_role': Value('string')}, 'action_2': {'dtype': Value('string'), 'shape': List(Value('int64')), 'tsfile_role': Value('string')}, 'action_3': {'dtype': Value('string'), 'shape': List(Value('int64')), 'tsfile_role': Value('string')}, 'action_4': {'dtype': Value('string'), 'shape': List(Value('int64')), 'tsfile_role': Value('string')}, 'action_5': {'dtype': Value('string'), 'shape': Lis
...
ring')), 'observation.state': List(Value('string'))}, 'renamed_features': {'index': Value('string')}, 'dropped_features': List(Value('string')), 'omitted_features': List(Value('string')), 'original_video_path': Value('string'), 'original_video_features': {'observation.images.left_wrist': {'dtype': Value('string'), 'shape': List(Value('int64')), 'names': List(Value('string')), 'info': {'video.height': Value('int64'), 'video.width': Value('int64'), 'video.codec': Value('string'), 'video.pix_fmt': Value('string'), 'video.is_depth_map': Value('bool'), 'video.fps': Value('int64'), 'video.channels': Value('int64'), 'has_audio': Value('bool')}}, 'observation.images.right_wrist': {'dtype': Value('string'), 'shape': List(Value('int64')), 'names': List(Value('string')), 'info': {'video.height': Value('int64'), 'video.width': Value('int64'), 'video.codec': Value('string'), 'video.pix_fmt': Value('string'), 'video.is_depth_map': Value('bool'), 'video.fps': Value('int64'), 'video.channels': Value('int64'), 'has_audio': Value('bool')}}, 'observation.images.base': {'dtype': Value('string'), 'shape': List(Value('int64')), 'names': List(Value('string')), 'info': {'video.height': Value('int64'), 'video.width': Value('int64'), 'video.codec': Value('string'), 'video.pix_fmt': Value('string'), 'video.is_depth_map': Value('bool'), 'video.fps': Value('int64'), 'video.channels': Value('int64'), 'has_audio': Value('bool')}}}, 'original_video_source': Value('string'), 'video_policy': Value('string')}}
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
action: struct<min: list<item: double>, max: list<item: double>, mean: list<item: double>, std: list<item: d (... 158 chars omitted)
child 0, min: list<item: double>
child 0, item: double
child 1, max: list<item: double>
child 0, item: double
child 2, mean: list<item: double>
child 0, item: double
child 3, std: list<item: double>
child 0, item: double
child 4, count: list<item: int64>
child 0, item: int64
child 5, q01: list<item: double>
child 0, item: double
child 6, q10: list<item: double>
child 0, item: double
child 7, q50: list<item: double>
child 0, item: double
child 8, q90: list<item: double>
child 0, item: double
child 9, q99: list<item: double>
child 0, item: double
observation.state: struct<min: list<item: double>, max: list<item: double>, mean: list<item: double>, std: list<item: d (... 158 chars omitted)
child 0, min: list<item: double>
child 0, item: double
child 1, max: list<item: double>
child 0, item: double
child 2, mean: list<item: double>
child 0, item: double
child 3, std: list<item: double>
child 0, item: double
child 4, count: list<item: int64>
child 0, item: int64
child 5, q01: list<item: double>
child 0, item: double
child 6, q10: list<item: double>
child 0, item: double
child 7, q50: list<item: double>
child 0, item: double
child 8, q90: list<item: double>
child 0, item: double
child 9, q99: list<ite
...
child 2, names: list<item: string>
child 0, item: string
child 3, info: struct<video.height: int64, video.width: int64, video.codec: string, video.pix_fmt: string, video.is (... 75 chars omitted)
child 0, video.height: int64
child 1, video.width: int64
child 2, video.codec: string
child 3, video.pix_fmt: string
child 4, video.is_depth_map: bool
child 5, video.fps: int64
child 6, video.channels: int64
child 7, has_audio: bool
child 2, observation.images.base: struct<dtype: string, shape: list<item: int64>, names: list<item: string>, info: struct<video.height (... 157 chars omitted)
child 0, dtype: string
child 1, shape: list<item: int64>
child 0, item: int64
child 2, names: list<item: string>
child 0, item: string
child 3, info: struct<video.height: int64, video.width: int64, video.codec: string, video.pix_fmt: string, video.is (... 75 chars omitted)
child 0, video.height: int64
child 1, video.width: int64
child 2, video.codec: string
child 3, video.pix_fmt: string
child 4, video.is_depth_map: bool
child 5, video.fps: int64
child 6, video.channels: int64
child 7, has_audio: bool
child 16, original_video_source: string
child 17, video_policy: string
to
{'codebase_version': Value('string'), 'robot_type': Value('string'), 'total_episodes': Value('int64'), 'total_frames': Value('int64'), 'total_tasks': Value('int64'), 'chunks_size': Value('int64'), 'data_files_size_in_mb': Value('int64'), 'video_files_size_in_mb': Value('int64'), 'fps': Value('int64'), 'splits': {'train': Value('string')}, 'data_path': Value('string'), 'features': {'Time': {'dtype': Value('string'), 'shape': List(Value('int64')), 'tsfile_role': Value('string'), 'unit': Value('string')}, 'episode_index': {'dtype': Value('string'), 'shape': List(Value('int64')), 'tsfile_role': Value('string')}, 'task_index': {'dtype': Value('string'), 'shape': List(Value('int64')), 'tsfile_role': Value('string')}, 'frame_index': {'dtype': Value('string'), 'shape': List(Value('int64')), 'tsfile_role': Value('string')}, 'sample_index': {'dtype': Value('string'), 'shape': List(Value('int64')), 'tsfile_role': Value('string')}, 'action_0': {'dtype': Value('string'), 'shape': List(Value('int64')), 'tsfile_role': Value('string')}, 'action_1': {'dtype': Value('string'), 'shape': List(Value('int64')), 'tsfile_role': Value('string')}, 'action_2': {'dtype': Value('string'), 'shape': List(Value('int64')), 'tsfile_role': Value('string')}, 'action_3': {'dtype': Value('string'), 'shape': List(Value('int64')), 'tsfile_role': Value('string')}, 'action_4': {'dtype': Value('string'), 'shape': List(Value('int64')), 'tsfile_role': Value('string')}, 'action_5': {'dtype': Value('string'), 'shape': Lis
...
ring')), 'observation.state': List(Value('string'))}, 'renamed_features': {'index': Value('string')}, 'dropped_features': List(Value('string')), 'omitted_features': List(Value('string')), 'original_video_path': Value('string'), 'original_video_features': {'observation.images.left_wrist': {'dtype': Value('string'), 'shape': List(Value('int64')), 'names': List(Value('string')), 'info': {'video.height': Value('int64'), 'video.width': Value('int64'), 'video.codec': Value('string'), 'video.pix_fmt': Value('string'), 'video.is_depth_map': Value('bool'), 'video.fps': Value('int64'), 'video.channels': Value('int64'), 'has_audio': Value('bool')}}, 'observation.images.right_wrist': {'dtype': Value('string'), 'shape': List(Value('int64')), 'names': List(Value('string')), 'info': {'video.height': Value('int64'), 'video.width': Value('int64'), 'video.codec': Value('string'), 'video.pix_fmt': Value('string'), 'video.is_depth_map': Value('bool'), 'video.fps': Value('int64'), 'video.channels': Value('int64'), 'has_audio': Value('bool')}}, 'observation.images.base': {'dtype': Value('string'), 'shape': List(Value('int64')), 'names': List(Value('string')), 'info': {'video.height': Value('int64'), 'video.width': Value('int64'), 'video.codec': Value('string'), 'video.pix_fmt': Value('string'), 'video.is_depth_map': Value('bool'), 'video.fps': Value('int64'), 'video.channels': Value('int64'), 'has_audio': Value('bool')}}}, 'original_video_source': Value('string'), 'video_policy': Value('string')}}
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.
dagger_final_1_21 (TsFile)
Apache TsFile version of the LeRobot dataset
lerobot-data-collection/dagger_final_1_21.
Overview
Bimanual openarms-follower demonstrations (LeRobot v3.0).
- Robot: openarms_follower (bimanual)
- Episodes: 1
- Frames: 841
- Sampling rate: 30 fps
- Tasks: 1
Schema (TsFile structure)
- Time (INT64, milliseconds) —
round(timestamp * 1000), restarting per episode. - episode_index / task_index (TAG) — the device dimension. Query a single episode with
WHERE episode_index=N. - FIELD —
frame_index,sample_index, and the flattened state/action vectors (observation_state_0..15,action_0..15) as single-precision FLOAT.
The robot's the left_wrist / right_wrist / base camera streams are time-series-irrelevant and not uploaded to this repository;
get them from the original dataset (its videos/ directory). The source meta/ is mirrored here.
Usage
Read the .tsfile files with the Apache TsFile Java or Python SDK.
Source & license
- Original dataset:
lerobot-data-collection/dagger_final_1_21 - Author / publisher: lerobot-data-collection
- License: not declared by the original dataset; please defer to the original.
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