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 71, 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.
LeKiwi PickCube Test TsFile
This dataset is an Apache TsFile conversion of oumeanin/lekiwi-pickcube-test, a LeRobot v3.0 LeKiwi mobile-manipulator dataset.
The converted artifact contains tabular time-series robot state, action, frame, episode, and task data. Camera videos remain in the original Hugging Face dataset and are not duplicated here.
Source Dataset and Author
- Original dataset: oumeanin/lekiwi-pickcube-test
- Pinned source revision: d904800f111d7f6724cc7ab21ab5bc4a3ad60ddf
- Original repository owner and uploader: oumeanin
- License: Apache-2.0
- Robot type:
lekiwi_soarm - LeRobot codebase version:
v3.0 - Task: LeKiwi pick-cube test demonstrations
- Split:
train - Sampling rate: 30 fps
- Scale: 50 episodes, 185,664 frame rows, 1 task, 1 Parquet data shard
- Source data layout:
data/chunk-{chunk_index:03d}/file-{file_index:03d}.parquet - Source video layout:
videos/{video_key}/chunk-{chunk_index:03d}/file-{file_index:03d}.mp4
The source card does not provide a paper, completed citation, or a separate
formal author list. Repository ownership and commit history identify
oumeanin as the source publisher.
Converted Files
- TsFile:
data/oumeanin_lekiwi_pickcube_test_train.tsfile(975,363 bytes) - Table:
oumeanin_lekiwi_pickcube_test_train - Rows: 185,664
- Episode/task devices: 50
- Time precision: milliseconds
- Metadata:
meta/is mirrored from the source, withmeta/info.jsonupdated for the TsFile artifact
TsFile Schema
Time is INT64 milliseconds computed as
round(timestamp * 1000). It restarts at zero for each episode.
TAG columns, stored through the TsFile table device/TAG mechanism:
episode_indextask_index
Scalar INT64 FIELD columns:
frame_indexsample_index, renamed from sourceindex
Flattened FLOAT FIELD groups:
action[9]->action_0...action_8observation.state[9]->observation_state_0...observation_state_8
The nine dimensions in both groups are: shoulder_pan.pos, shoulder_lift.pos, elbow_flex.pos, wrist_flex.pos, wrist_roll.pos, gripper.pos, base_vx_mps, base_vy_mps, base_theta_degps.
Encoding and Conversion Notes
- FLOAT/DOUBLE fields use GORILLA + LZ4.
- INT32/INT64 fields and Time use TS_2DIFF + LZ4.
- BOOLEAN fields use RLE + LZ4 when present; this source has no BOOLEAN field.
- Source
episode_indexandtask_indexare TsFile TAGs. - All source rows are merged into one train TsFile and sorted by TAGs then Time.
- Vector columns are flattened to scalar fields; dots become underscores.
- Source
timestampis dropped after Time synthesis because it equalsTime / 1000seconds. - Source
indexbecomessample_index;frame_indexis kept. - No numeric row or state/action dimension is dropped.
- The TsFile is 0.3252 times the source Parquet size.
Videos
Videos are not included in this TsFile repository. The source contains two frame-aligned AV1, 640x480, 30 fps streams without audio, each with ten MP4 shards:
- observation.images.base -
file-000.mp4throughfile-009.mp4 - observation.images.wrist -
file-000.mp4throughfile-009.mp4
The source path template is videos/{video_key}/chunk-{chunk_index:03d}/file-{file_index:03d}.mp4.
episode_index, frame_index, and meta/episodes/
preserve alignment between numeric rows and the original video frames.
Validation
Apache TsFile Java 2.2.1 performed a full query readback of all 185,664 rows. The validator also checked the table schema, TAG columns, per-column physical encoding/compression, Time encoding/compression, unique TAG+Time keys, vector widths, and monotonic Time within every episode. Reports remain local and are not part of this upload-ready directory.
Minimal Read Example
from tsfile import TsFileReader
reader = TsFileReader("data/oumeanin_lekiwi_pickcube_test_train.tsfile")
table_name = "oumeanin_lekiwi_pickcube_test_train"
columns = [
"episode_index",
"task_index",
"frame_index",
"sample_index",
"action_0",
"observation_state_0",
]
with reader.query_table(table_name, columns, batch_size=65536) as result:
batch = result.read_arrow_batch()
print(batch.to_pandas().head())
reader.close()
Citation
The source card provides no paper or completed BibTeX entry. Cite the original
Hugging Face dataset and its publisher, oumeanin, when using this
converted artifact.
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