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 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.
Whiteboard Inspect 0708 TsFile
Apache TsFile edition of Xense/whiteboard_inspect_0708, a
LeRobot v3.0 bimanual Flexiv Rizon 4 robotics dataset.
Source and attribution
- Original dataset: https://huggingface.co/datasets/Xense/whiteboard_inspect_0708
- Publishing organization: XenseRobotics (
Xense) - Repository contributor: fza (
fza1796262052) - License: Apache-2.0
- Task:
Pick up the inspection probe, press it on each red-marked spot on the whiteboard one by one, put down the probe, pick up the eraser, and wipe off all the red marks. - Robot:
bi_flexiv_rizon4_rt - Train split: 19 episodes, 67,684 frame rows, one task, 30 fps, 19 Parquet files
- Source frame layout:
data/chunk-{chunk_index:03d}/file-{file_index:03d}.parquet
The source dataset card does not provide a paper or BibTeX citation. Cite the original Hugging Face dataset, XenseRobotics, and contributor fza when using this data.
TsFile schema
Time = round(timestamp * 1000) as INT64 milliseconds and restarts at zero in
each episode. The source timestamp column is removed because it is exactly
represented by Time / 1000 seconds. index is renamed to sample_index, and
frame_index is retained.
| Columns | TsFile type | Role |
|---|---|---|
Time |
INT64/TIMESTAMP | TIME |
episode_index, task_index |
STRING device segments | TAG |
frame_index, sample_index |
INT64 | FIELD |
action_0 ... action_19 |
FLOAT | FIELD |
observation_state_0 ... observation_state_19 |
FLOAT | FIELD |
The 20 action and 20 state elements follow the source feature order. Each arm contains TCP x/y/z, six rotation representation values, r1 through r6, in the source-defined order, and a gripper position value. The left-arm values precede the right-arm values. Dots in source vector names are represented by the scalar field prefix and element index. No numeric rows, action dimensions, or state dimensions are omitted.
Storage uses GORILLA + LZ4 for FLOAT/DOUBLE, TS_2DIFF + LZ4 for INT32/INT64,
TS_2DIFF + LZ4 for Time, and RLE + LZ4 for BOOLEAN fields. TAG values use
the TsFile table/device mechanism.
Original videos
The 133 source MP4 files remain at videos/ and
are not included here. The path template is
videos/{video_key}/chunk-{chunk_index:03d}/file-{file_index:03d}.mp4
for these streams:
observation.images.head(640 x 480, H.264, 30 fps)observation.images.left_wrist(640 x 480, H.264, 30 fps)observation.images.right_wrist(640 x 480, H.264, 30 fps)observation.images.left_tactile_0(700 x 400, H.264, 30 fps)observation.images.left_tactile_1(700 x 400, H.264, 30 fps)observation.images.right_tactile_0(700 x 400, H.264, 30 fps)observation.images.right_tactile_1(700 x 400, H.264, 30 fps)
Use episode_index and frame_index to align numeric rows with the matching
frame in each original per-episode video.
Read example
from tsfile import TsFileReader
reader = TsFileReader("data/xense_whiteboard_inspect_0708.tsfile")
with reader.query_table(
"xense_whiteboard_inspect_0708",
["episode_index", "task_index", "Time", "frame_index", "action_0"],
batch_size=4096,
) as result:
print(result.read_arrow_batch().to_pandas().head())
reader.close()
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