Datasets:
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 β "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) β
round(timestamp * 1000); the sourcetimestampcolumn is dropped (it equals Time / 1000). - episode_index (TAG) β device dimension.
- task_index (TAG) β device dimension.
- episode_index (INT64) β measurement.
- task_index (INT64) β measurement.
- frame_index (INT64) β measurement.
- sample_index (INT64) β measurement.
- action_0 (FLOAT) β measurement.
- action_1 (FLOAT) β measurement.
- action_2 (FLOAT) β measurement.
- action_3 (FLOAT) β measurement.
- action_4 (FLOAT) β measurement.
- action_5 (FLOAT) β measurement.
- observation_state_0 (FLOAT) β measurement.
- observation_state_1 (FLOAT) β measurement.
- observation_state_2 (FLOAT) β measurement.
- observation_state_3 (FLOAT) β measurement.
- observation_state_4 (FLOAT) β measurement.
- observation_state_5 (FLOAT) β measurement.
The vector columns are flattened per joint:
action_*β commanded joints: main_shoulder_pan, main_shoulder_lift, main_elbow_flex, main_wrist_flex, main_wrist_roll, main_gripper.observation_state_*β 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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