metadata
license: apache-2.0
task_categories:
- robotics
tags:
- LeRobot
- tsfile
- timeseries
- format:tsfile
pretty_name: G1_Dex1_PickPlaceRedBlock_Dataset_Sim
modality: timeseries
configs:
- config_name: default
data_files:
- split: train
path: data/g1_dex1_pickplaceredblock_dataset_sim.tsfile
G1_Dex1_PickPlaceRedBlock_Dataset_Sim (TsFile)
Apache TsFile version of unitreerobotics/G1_Dex1_PickPlaceRedBlock_Dataset_Sim.
Overview
A LeRobot robot-manipulation dataset. The source card is auto-generated ("This dataset was created using LeRobot") and does not add a free-text description; the facts below are taken from the source meta/info.json.
- Robot: Unitree_G1_Gripper
- Episodes: 216
- Frames: 163330
- Sampling rate: 30.0 fps
- Splits: a single
trainsplit
Schema (TsFile structure)
- Time (INT64, milliseconds) —
round(timestamp * 1000); the sourcetimestampcolumn (seconds) is dropped because it equalsTime / 1000. - episode_index (TAG), task_index (TAG) — device dimensions; query one episode with
WHERE episode_index = <n>. - frame_index (FIELD, INT64), sample_index (FIELD, INT64, from the source
index) — per-frame bookkeeping. - Vector columns (single-precision FLOAT, source name with
.→_and an element index appended):- observation.state →
observation_state_0..observation_state_15(FLOAT) - action →
action_0..action_15(FLOAT)
- observation.state →
Camera video streams are not included in this repository; see the original dataset for the videos: https://huggingface.co/datasets/unitreerobotics/G1_Dex1_PickPlaceRedBlock_Dataset_Sim (videos/ directory).
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/g1_dex1_pickplaceredblock_dataset_sim.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/unitreerobotics/G1_Dex1_PickPlaceRedBlock_Dataset_Sim
- Author / publisher: unitreerobotics
- License: apache-2.0