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
episode_index: int64
stats: struct<action: struct<min: list<item: double>, max: list<item: double>, mean: list<item: double>, st (... 1443 chars omitted)
child 0, action: struct<min: list<item: double>, max: list<item: double>, mean: list<item: double>, std: list<item: d (... 33 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 1, observation.state: struct<min: list<item: double>, max: list<item: double>, mean: list<item: double>, std: list<item: d (... 33 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 2, observation.images.laptop: struct<min: list<item: list<item: list<item: double>>>, max: list<item: list<item: list<item: double (... 129 chars omitted)
child 0, min: list<item: list<item: list<item: double>>>
child 0, item: list<item: list<item: double>>
child 0, item: list<item: double>
...
ax: list<item: int64>, mean: list<item: double>, std: list<item: dou (... 31 chars omitted)
child 0, min: list<item: int64>
child 0, item: int64
child 1, max: list<item: int64>
child 0, item: int64
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 7, index: struct<min: list<item: int64>, max: list<item: int64>, mean: list<item: double>, std: list<item: dou (... 31 chars omitted)
child 0, min: list<item: int64>
child 0, item: int64
child 1, max: list<item: int64>
child 0, item: int64
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 8, task_index: struct<min: list<item: int64>, max: list<item: int64>, mean: list<item: double>, std: list<item: dou (... 31 chars omitted)
child 0, min: list<item: int64>
child 0, item: int64
child 1, max: list<item: int64>
child 0, item: int64
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
tasks: list<item: string>
child 0, item: string
length: int64
to
{'episode_index': Value('int64'), 'tasks': List(Value('string')), 'length': 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
episode_index: int64
stats: struct<action: struct<min: list<item: double>, max: list<item: double>, mean: list<item: double>, st (... 1443 chars omitted)
child 0, action: struct<min: list<item: double>, max: list<item: double>, mean: list<item: double>, std: list<item: d (... 33 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 1, observation.state: struct<min: list<item: double>, max: list<item: double>, mean: list<item: double>, std: list<item: d (... 33 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 2, observation.images.laptop: struct<min: list<item: list<item: list<item: double>>>, max: list<item: list<item: list<item: double (... 129 chars omitted)
child 0, min: list<item: list<item: list<item: double>>>
child 0, item: list<item: list<item: double>>
child 0, item: list<item: double>
...
ax: list<item: int64>, mean: list<item: double>, std: list<item: dou (... 31 chars omitted)
child 0, min: list<item: int64>
child 0, item: int64
child 1, max: list<item: int64>
child 0, item: int64
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 7, index: struct<min: list<item: int64>, max: list<item: int64>, mean: list<item: double>, std: list<item: dou (... 31 chars omitted)
child 0, min: list<item: int64>
child 0, item: int64
child 1, max: list<item: int64>
child 0, item: int64
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 8, task_index: struct<min: list<item: int64>, max: list<item: int64>, mean: list<item: double>, std: list<item: dou (... 31 chars omitted)
child 0, min: list<item: int64>
child 0, item: int64
child 1, max: list<item: int64>
child 0, item: int64
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
tasks: list<item: string>
child 0, item: string
length: int64
to
{'episode_index': Value('int64'), 'tasks': List(Value('string')), 'length': 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.
so100_playx (TsFile)
Apache TsFile version of baptiste-04/so100_playX.
Overview
A LeRobot robot dataset recorded on a so100 arm. Task(s): Move box red to zone 1; Move box red to zone 2; Move box red to home; Move box blue to zone 1; Move box blue to zone 2; Move box blue to home; Move box yellow to zone 1; Move box yellow to zone 2; Move box yellow to home. Each frame holds the commanded action and observed observation.state joint positions, plus camera views stored as videos in the original dataset.
- Episodes: 85
- Frames: 52,317
- Sampling rate: 30 fps
- Tasks: 9 — "Move box red to zone 1; Move box red to zone 2; Move box red to home; Move box blue to zone 1; Move box blue to zone 2; Move box blue to home; Move box yellow to zone 1; Move box yellow to zone 2; Move box yellow to home"
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.
- episode_index (INT64) — measurement.
- task_index (INT64) — measurement.
- frame_index (INT64) — measurement.
- sample_index (INT64) — measurement.
- action_0 (FLOAT) — measurement.
- action_1 (FLOAT) — measurement.
- action_2 (FLOAT) — measurement.
- action_3 (FLOAT) — measurement.
- action_4 (FLOAT) — measurement.
- action_5 (FLOAT) — measurement.
- observation_state_0 (FLOAT) — measurement.
- observation_state_1 (FLOAT) — measurement.
- observation_state_2 (FLOAT) — measurement.
- observation_state_3 (FLOAT) — measurement.
- observation_state_4 (FLOAT) — measurement.
- observation_state_5 (FLOAT) — measurement.
The vector columns are flattened per joint:
action_*— commanded joints: main_shoulder_pan, main_shoulder_lift, main_elbow_flex, main_wrist_flex, main_wrist_roll, main_gripper.observation_state_*— observed joints: main_shoulder_pan, main_shoulder_lift, main_elbow_flex, main_wrist_flex, main_wrist_roll, main_gripper.
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/so100_playx.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/baptiste-04/so100_playX
- Author / publisher: baptiste-04
- License: apache-2.0
- Note: camera videos are NOT included; see the original dataset.
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