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.
Fabric Winding 4-Camera TsFile
Apache TsFile conversion of axiboai/fabric_winding_4cam, a LeRobot v2.1 humanoid upper-body dataset for the task “wind the motors”.
Source and attribution
- Publishing organization/uploader: AXIBO (axiboai)
- Individual author: not named in the source card or metadata
- License: Apache-2.0
- Paper/citation: not supplied by the source card
- Split: train; 115 episodes, 188,387 frames, 1 task, 30 fps
- Robot type: humanoid_upper_body; LeRobot codebase v2.1
- Task index 0: “wind the motors”
Source Parquet and videos
The source has 115 Parquet files at data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet.
The four streams cam_front, cam_top, cam_left_wrist, and cam_right_wrist contain 115 MP4 files each at videos/chunk-{episode_chunk:03d}/{video_key}/episode_{episode_index:06d}.mp4. Videos are not duplicated in this repository; use the original videos directory. Numeric rows remain aligned through episode_index and frame_index.
Converted artifacts
| Train shard | Episodes | Rows | Bytes |
|---|---|---|---|
| fabric_winding_4cam_train-00000-of-00016.tsfile | 0-3 (4) | 10,452 | 611,105 |
| fabric_winding_4cam_train-00001-of-00016.tsfile | 4-7 (4) | 10,239 | 598,373 |
| fabric_winding_4cam_train-00002-of-00016.tsfile | 8-12 (5) | 10,364 | 596,870 |
| fabric_winding_4cam_train-00003-of-00016.tsfile | 13-19 (7) | 11,738 | 697,783 |
| fabric_winding_4cam_train-00004-of-00016.tsfile | 20-26 (7) | 11,224 | 664,163 |
| fabric_winding_4cam_train-00005-of-00016.tsfile | 27-32 (6) | 11,102 | 661,674 |
| fabric_winding_4cam_train-00006-of-00016.tsfile | 33-39 (7) | 10,957 | 644,272 |
| fabric_winding_4cam_train-00007-of-00016.tsfile | 40-47 (8) | 11,745 | 692,285 |
| fabric_winding_4cam_train-00008-of-00016.tsfile | 48-55 (8) | 10,970 | 650,735 |
| fabric_winding_4cam_train-00009-of-00016.tsfile | 56-63 (8) | 11,418 | 673,418 |
| fabric_winding_4cam_train-00010-of-00016.tsfile | 64-71 (8) | 11,551 | 702,371 |
| fabric_winding_4cam_train-00011-of-00016.tsfile | 72-78 (7) | 11,659 | 682,245 |
| fabric_winding_4cam_train-00012-of-00016.tsfile | 79-85 (7) | 11,004 | 667,851 |
| fabric_winding_4cam_train-00013-of-00016.tsfile | 86-92 (7) | 11,354 | 689,056 |
| fabric_winding_4cam_train-00014-of-00016.tsfile | 93-100 (8) | 11,565 | 705,864 |
| fabric_winding_4cam_train-00015-of-00016.tsfile | 101-114 (14) | 21,045 | 1,275,193 |
| Total | 115 | 188,387 | 11,213,258 |
All shards use the table fabric_winding_4cam_train. The source Parquet files total 17,851,827 bytes; the merged staging Parquet is 12,015,759 bytes.
TsFile schema
Time = round(timestamp * 1000) milliseconds and restarts at zero for each episode. The source timestamp in seconds is dropped because it is redundant with Time / 1000.
TAG columns use the TsFile table device/tag mechanism: episode_index, task_index.
FIELD columns are frame_index, sample_index (renamed from source index), and 36 flattened FLOAT fields:
| Index | Source dimension | State FIELD | Action FIELD |
|---|---|---|---|
| 0 | left_shoulder_pitch | observation_state_0 | action_0 |
| 1 | left_shoulder_roll | observation_state_1 | action_1 |
| 2 | left_shoulder_yaw | observation_state_2 | action_2 |
| 3 | left_elbow | observation_state_3 | action_3 |
| 4 | left_wrist_roll | observation_state_4 | action_4 |
| 5 | left_wrist_pitch | observation_state_5 | action_5 |
| 6 | left_wrist_yaw | observation_state_6 | action_6 |
| 7 | right_shoulder_pitch | observation_state_7 | action_7 |
| 8 | right_shoulder_roll | observation_state_8 | action_8 |
| 9 | right_shoulder_yaw | observation_state_9 | action_9 |
| 10 | right_elbow | observation_state_10 | action_10 |
| 11 | right_wrist_roll | observation_state_11 | action_11 |
| 12 | right_wrist_pitch | observation_state_12 | action_12 |
| 13 | right_wrist_yaw | observation_state_13 | action_13 |
| 14 | left_hand_lift | observation_state_14 | action_14 |
| 15 | left_hand_push | observation_state_15 | action_15 |
| 16 | right_hand_lift | observation_state_16 | action_16 |
| 17 | right_hand_push | observation_state_17 | action_17 |
Physical codec policy:
- Time: TS_2DIFF + LZ4
- INT32/INT64: TS_2DIFF + LZ4
- FLOAT/DOUBLE: GORILLA + LZ4
- BOOLEAN: RLE + LZ4
- TAG: TsFile table device/tag storage
Only redundant timestamp is dropped. Camera columns are video references in the source metadata and remain available in the original repository.
Validation
All shards passed exact Python SDK readback against their staging Parquet data and Java schema/codec inspection. Together they contain 188,387 rows and 115 TAG devices with no duplicate TAG/Time rows. Local JSON and Markdown validation reports and the conversion script are intentionally excluded from this repository.
Usage
from tsfile import TsFileReader
reader = TsFileReader("data/fabric_winding_4cam_train-00000-of-00016.tsfile")
columns = [
"episode_index", "task_index", "frame_index", "sample_index",
"observation_state_0", "action_0",
]
with reader.query_table("fabric_winding_4cam_train", columns, batch_size=65536) as result:
print(result.read_arrow_batch().to_pandas().head())
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