Datasets:
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
task: string
instruction: string
recording_fps: int64
hf_repo_id: string
replay_session: string
target_episodes: int64
final_sidecar_episodes: int64
sources: list<item: struct<accepted_name: string, source: string, episodes_used: int64, episodes_skipped_by_q (... 18 chars omitted)
child 0, item: struct<accepted_name: string, source: string, episodes_used: int64, episodes_skipped_by_quarantine: (... 6 chars omitted)
child 0, accepted_name: string
child 1, source: string
child 2, episodes_used: int64
child 3, episodes_skipped_by_quarantine: int64
chunks_size: int64
codebase_version: string
features: struct<Time: struct<dtype: string, shape: list<item: int64>, tsfile_role: string, unit: string>, epi (... 5434 chars omitted)
child 0, Time: struct<dtype: string, shape: list<item: int64>, tsfile_role: string, unit: string>
child 0, dtype: string
child 1, shape: list<item: int64>
child 0, item: int64
child 2, tsfile_role: string
child 3, unit: string
child 1, episode_index: struct<dtype: string, shape: list<item: int64>, tsfile_role: string>
child 0, dtype: string
child 1, shape: list<item: int64>
child 0, item: int64
child 2, tsfile_role: string
child 2, task_index: struct<dtype: string, shape: list<item: int64>, tsfile_role: string>
child 0, dtype: string
child 1, shape: list<item: int64>
child 0, item: int64
child 2, tsfile_role: string
child 3, frame_index
...
4, 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 1, observation.images.left_wrist: 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
total_tasks: int64
video_path_original: string
total_frames: int64
data_path: string
video_files_size_in_mb: int64
data_files_size_in_mb: int64
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')}, 'observation_gripper_binary': {'dtype': Value('string'), 'shape': List(Value('int64')), 'tsfile_role': Value('string')}, 'skill_natural_language': {'dtype': Value('string'), 'shape': List(Value('int64')), 'tsfile_role': Value('string')}, 'skill_verification_question': {'dtype': Value('string'), 'shape': List(Value('int64')), 'tsfile_role': Value('string')}, 'skill_type': {'dtype': Value('string'), 'shape': List(Value('int64')), 'tsfile_role': Value('string')}, 'skill_progress': {'dtype': Value('string'), 'shape': List(Value('int64')), 'tsfile_role': Value('str
...
'skill.goal_position.robot_xyzrpy': List(Value('string')), 'subtask.target_position': List(Value('string'))}, 'renamed_features': {'observation.gripper_binary': Value('string'), 'skill.natural_language': Value('string'), 'skill.verification_question': Value('string'), 'skill.type': Value('string'), 'skill.progress': Value('string'), 'skill.goal_position.gripper': Value('string'), 'subtask.natural_language': Value('string'), 'subtask.object_name': Value('string'), 'index': Value('string')}, 'dropped_features': List(Value('string')), 'omitted_features': List(Value('string')), 'original_video_path': Value('string'), 'original_video_features': {'observation.images.top': {'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.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')}}}, '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
task: string
instruction: string
recording_fps: int64
hf_repo_id: string
replay_session: string
target_episodes: int64
final_sidecar_episodes: int64
sources: list<item: struct<accepted_name: string, source: string, episodes_used: int64, episodes_skipped_by_q (... 18 chars omitted)
child 0, item: struct<accepted_name: string, source: string, episodes_used: int64, episodes_skipped_by_quarantine: (... 6 chars omitted)
child 0, accepted_name: string
child 1, source: string
child 2, episodes_used: int64
child 3, episodes_skipped_by_quarantine: int64
chunks_size: int64
codebase_version: string
features: struct<Time: struct<dtype: string, shape: list<item: int64>, tsfile_role: string, unit: string>, epi (... 5434 chars omitted)
child 0, Time: struct<dtype: string, shape: list<item: int64>, tsfile_role: string, unit: string>
child 0, dtype: string
child 1, shape: list<item: int64>
child 0, item: int64
child 2, tsfile_role: string
child 3, unit: string
child 1, episode_index: struct<dtype: string, shape: list<item: int64>, tsfile_role: string>
child 0, dtype: string
child 1, shape: list<item: int64>
child 0, item: int64
child 2, tsfile_role: string
child 2, task_index: struct<dtype: string, shape: list<item: int64>, tsfile_role: string>
child 0, dtype: string
child 1, shape: list<item: int64>
child 0, item: int64
child 2, tsfile_role: string
child 3, frame_index
...
4, 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 1, observation.images.left_wrist: 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
total_tasks: int64
video_path_original: string
total_frames: int64
data_path: string
video_files_size_in_mb: int64
data_files_size_in_mb: int64
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')}, 'observation_gripper_binary': {'dtype': Value('string'), 'shape': List(Value('int64')), 'tsfile_role': Value('string')}, 'skill_natural_language': {'dtype': Value('string'), 'shape': List(Value('int64')), 'tsfile_role': Value('string')}, 'skill_verification_question': {'dtype': Value('string'), 'shape': List(Value('int64')), 'tsfile_role': Value('string')}, 'skill_type': {'dtype': Value('string'), 'shape': List(Value('int64')), 'tsfile_role': Value('string')}, 'skill_progress': {'dtype': Value('string'), 'shape': List(Value('int64')), 'tsfile_role': Value('str
...
'skill.goal_position.robot_xyzrpy': List(Value('string')), 'subtask.target_position': List(Value('string'))}, 'renamed_features': {'observation.gripper_binary': Value('string'), 'skill.natural_language': Value('string'), 'skill.verification_question': Value('string'), 'skill.type': Value('string'), 'skill.progress': Value('string'), 'skill.goal_position.gripper': Value('string'), 'subtask.natural_language': Value('string'), 'subtask.object_name': Value('string'), 'index': Value('string')}, 'dropped_features': List(Value('string')), 'omitted_features': List(Value('string')), 'original_video_path': Value('string'), 'original_video_features': {'observation.images.top': {'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.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')}}}, '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.
phase1_pick_place_A1_10fps (TsFile)
Apache TsFile version of HyeonseokE/phase1_pick_place_A1_10fps.
Overview
A LeRobot robot manipulation dataset. Each frame holds the commanded action and observed observation.state joint positions; camera views are stored as videos in the original dataset.
- Episodes: 100
- Frames: 28459
- Sampling rate: 10 fps
- Tasks: 1
- Split: a single train split
- Robot: so101_follower
- Cameras (not uploaded): top, left_wrist
Schema (TsFile structure)
All episodes share one TsFile with episode_index and task_index as TAG columns; query a single episode with WHERE episode_index = N.
- Time (INT64, milliseconds) —
round(timestamp * 1000); the sourcetimestampcolumn is dropped (it equals Time / 1000). - episode_index (TAG) — device dimension.
- task_index (TAG) — device dimension.
- frame_index (INT64) — measurement.
- sample_index (INT64) — measurement.
- action_0..N (FLOAT) — commanded joints.
- action.radian_urdf0_0..N (FLOAT) — measurement.
- gripper_binary_0..N (FLOAT) — measurement.
- radian_urdf0_0..N (FLOAT) — measurement.
- robot_xyzrpy_0..N (FLOAT) — measurement.
- skill.goal_position.gripper_0..N (FLOAT) — measurement.
- skill.goal_position.joint_0..N (FLOAT) — measurement.
- skill.goal_position.robot_xyzrpy_0..N (FLOAT) — measurement.
- skill.natural_language_0..N (FLOAT) — measurement.
- skill.progress_0..N (FLOAT) — measurement.
- skill.type_0..N (FLOAT) — measurement.
- skill.verification_question_0..N (FLOAT) — measurement.
- state_0..N (FLOAT) — measurement.
- subtask.natural_language_0..N (FLOAT) — measurement.
- subtask.object_name_0..N (FLOAT) — measurement.
- subtask.target_position_0..N (FLOAT) — measurement.
Vector columns are flattened element-wise with an index suffix.
Usage
Install the Apache TsFile Python SDK (pip install tsfile) and read a converted file:
from pathlib import Path
from tsfile import TsFileReader
path = Path("data/phase1_pick_place_A1_10fps.tsfile")
with TsFileReader(str(path)) as reader:
schemas = reader.get_all_table_schemas()
print("tables:", list(schemas))
table_name = next(iter(schemas))
table = schemas[table_name]
columns = [column.get_column_name() for column in table.get_columns()]
print("columns:", columns)
field_names = [
column.get_column_name()
for column in table.get_columns()
if column.get_column_name() not in {"Time", "time"}
]
if field_names:
with reader.query_table(table_name, field_names[:3], batch_size=1024) as result:
batch = result.read_arrow_batch()
if batch is not None:
print(batch.to_pandas().head())
Source & license
- Original dataset: https://huggingface.co/datasets/HyeonseokE/phase1_pick_place_A1_10fps
- Author / publisher: HyeonseokE
- License: not declared by the original dataset; please defer to the original.
- Note: camera videos are NOT included; see the original dataset for them.
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