Datasets:
The dataset viewer is not available for this subset.
Exception: SplitsNotFoundError
Message: The split names could not be parsed from the dataset config.
Traceback: Traceback (most recent call last):
File "tsfile/tsfile_py_cpp.pyx", line 567, in tsfile.tsfile_py_cpp.tsfile_reader_new_c
tsfile.exceptions.FileOpenError: 28:
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 286, in get_dataset_config_info
for split_generator in builder._split_generators(
~~~~~~~~~~~~~~~~~~~~~~~~~^
StreamingDownloadManager(base_path=builder.base_path, download_config=download_config)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/tsfile/tsfile.py", line 271, in _split_generators
scan = self._scan_metadata(all_files)
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/tsfile/tsfile.py", line 318, in _scan_metadata
with self._open_reader(file) as reader:
~~~~~~~~~~~~~~~~~^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/tsfile/tsfile.py", line 742, in _open_reader
return TsFileReader(file)
File "tsfile/tsfile_reader.pyx", line 323, in tsfile.tsfile_reader.TsFileReaderPy.__init__
SystemError: <class '_weakrefset.WeakSet'> returned a result with an exception set
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 68, in compute_split_names_from_streaming_response
for split in get_dataset_split_names(
~~~~~~~~~~~~~~~~~~~~~~~^
path=dataset,
^^^^^^^^^^^^^
config_name=config,
^^^^^^^^^^^^^^^^^^^
token=hf_token,
^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
info = get_dataset_config_info(
path,
...<6 lines>...
**config_kwargs,
)
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 291, in get_dataset_config_info
raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
G1 06 11 TsFile
Apache TsFile edition of Jiangeng/G1_06_11, a LeRobot v2.1 Unitree G1 whole-body dataset for the task: Put the teddy bear in the bag. Numeric trajectories are stored in one table-model TsFile.
Source and attribution
- Original repository owner, publisher, uploader, and sole listed contributor: Jiangeng. No separate personal name is provided.
- License: the source repository does not declare one.
- Paper, homepage, and citation: the source repository does not provide them.
- Split:
train; 51 episodes; 79,948 frame rows; one task; 50 Hz; 51 source Parquet episode shards. - Task
0:Put the teddy bear in the bag.
Data layout
The table is jiangeng_g1_06_11 and contains 79,948 rows across 51 TAG devices. The source Parquet shards total 67,782,033 bytes; the TsFile is 31,817,362 bytes (46.9% of the source Parquet size).
| Column or group | TsFile role | Type | Meaning |
|---|---|---|---|
Time |
TIME | INT64 milliseconds | round(timestamp * 1000), restarting at zero for each episode |
episode_index |
TAG | STRING from source INT64 | Source episode identity, values 0 through 50 |
task_index |
TAG | STRING from source INT64 | Source task identity, value 0 |
frame_index |
FIELD | INT64 | Frame position within the episode |
sample_index |
FIELD | INT64 | Source index, renamed for clarity |
teleop_delta_heading |
FIELD | DOUBLE | Source heading delta |
teleop_smpl_frame_index |
FIELD | INT64 | Source SMPL frame index |
teleop_stream_mode, teleop_planner_mode |
FIELD | INT32 | Teleoperation and locomotion planner modes |
teleop_planner_speed, teleop_planner_height |
FIELD | FLOAT | Planner speed and height |
observation_state_0 ... observation_state_42 |
FIELD | FLOAT | G1 joint state; 43 elements |
observation_eef_state_0 ... observation_eef_state_13 |
FIELD | FLOAT | left/right wrist position and quaternion state; 14 elements |
action_wbc_0 ... action_wbc_42 |
FIELD | FLOAT | whole-body controller action; 43 elements |
observation_root_orientation_0 ... observation_root_orientation_3 |
FIELD | FLOAT | flattened source observation.root_orientation vector; 4 elements |
observation_projected_gravity_0 ... observation_projected_gravity_2 |
FIELD | FLOAT | flattened source observation.projected_gravity vector; 3 elements |
observation_cpp_rotation_offset_0 ... observation_cpp_rotation_offset_3 |
FIELD | FLOAT | flattened source observation.cpp_rotation_offset vector; 4 elements |
observation_init_base_quat_0 ... observation_init_base_quat_3 |
FIELD | FLOAT | flattened source observation.init_base_quat vector; 4 elements |
action_motion_token_0 ... action_motion_token_63 |
FIELD | FLOAT | motion token; 64 elements |
teleop_smpl_joints_0 ... teleop_smpl_joints_71 |
FIELD | FLOAT | SMPL joint values; 72 elements |
teleop_smpl_pose_0 ... teleop_smpl_pose_62 |
FIELD | FLOAT | SMPL pose values; 63 elements |
teleop_body_quat_w_0 ... teleop_body_quat_w_3 |
FIELD | FLOAT | flattened source teleop.body_quat_w vector; 4 elements |
teleop_target_body_orientation_0 ... teleop_target_body_orientation_5 |
FIELD | FLOAT | flattened source teleop.target_body_orientation vector; 6 elements |
teleop_left_hand_joints_0 ... teleop_left_hand_joints_6 |
FIELD | FLOAT | flattened source teleop.left_hand_joints vector; 7 elements |
teleop_right_hand_joints_0 ... teleop_right_hand_joints_6 |
FIELD | FLOAT | flattened source teleop.right_hand_joints vector; 7 elements |
teleop_left_wrist_joints_0 ... teleop_left_wrist_joints_2 |
FIELD | FLOAT | flattened source teleop.left_wrist_joints vector; 3 elements |
teleop_right_wrist_joints_0 ... teleop_right_wrist_joints_2 |
FIELD | FLOAT | flattened source teleop.right_wrist_joints vector; 3 elements |
teleop_planner_movement_0 ... teleop_planner_movement_2 |
FIELD | FLOAT | flattened source teleop.planner_movement vector; 3 elements |
teleop_planner_facing_0 ... teleop_planner_facing_2 |
FIELD | FLOAT | flattened source teleop.planner_facing vector; 3 elements |
teleop_vr_3pt_position_0 ... teleop_vr_3pt_position_8 |
FIELD | FLOAT | flattened source teleop.vr_3pt_position vector; 9 elements |
teleop_vr_3pt_orientation_0 ... teleop_vr_3pt_orientation_17 |
FIELD | FLOAT | three-point VR orientation; 18 elements |
The source timestamp column is not stored separately because it is represented by Time / 1000 seconds. All 79,948 numeric rows, every episode and task identity, frame_index, and every numeric vector element are retained. Source vector prefixes are preserved with dots replaced by underscores.
Encoding and compression
- TIME, INT32, and INT64:
TS_2DIFF + LZ4 - FLOAT and DOUBLE:
GORILLA + LZ4 - BOOLEAN, when present:
RLE + LZ4 - TAG values: TsFile table-model device/tag storage
Videos and alignment
The 51 source ego-view MP4 files are not included here. They remain in the original repository at videos/chunk-000/observation.images.ego_view, named episode_000000.mp4 through episode_000050.mp4. The source directory is displayed as 257 MB on Hugging Face.
The source template is videos/chunk-{episode_chunk:03d}/{video_key}/episode_{episode_index:06d}.mp4. Use episode_index and frame_index to align a numeric row with its 50 FPS video frame.
Read example
from tsfile import TsFileReader
reader = TsFileReader("data/jiangeng_g1_06_11.tsfile")
with reader.query_table(
"jiangeng_g1_06_11",
[
"episode_index",
"task_index",
"frame_index",
"sample_index",
"observation_state_0",
"action_wbc_0",
],
batch_size=1024,
) as result:
batch = result.read_arrow_batch()
print(batch.to_pandas().head())
reader.close()
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