Datasets:

THUgewu
/

train4

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 66, 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.

Vacuame/train4 (LeRobot SO-100) - TsFile

This dataset converts the numeric frame time-series from Vacuame/train4 to Apache TsFile format.

Modalities: Time-series. The original camera videos are not included in this converted repository; they remain in the source Hugging Face dataset.

Source Dataset

Original dataset: Vacuame/train4
LeRobot version: v2.0
Robot type: so100
Scale: 2 episodes, 119 frames, 1 task (try)
Sampling rate: 30 fps
Source frame data: data/chunk-000/episode_000000.parquet and data/chunk-000/episode_000001.parquet
Source videos: 2 camera streams, observation.images.laptop and observation.images.phone, available in the source dataset videos/ tree
License: the source dataset does not declare an explicit license

Converted Layout

README.md
data/vacuame_train4.tsfile
meta/info.json
meta/tasks.jsonl
meta/episodes.jsonl
meta/stats.json

The converted TsFile contains all 119 numeric frame rows in one table named vacuame_train4.

Schema

Role	Column(s)	Type	Notes
Time	`Time`	INT64 ms	`round(timestamp * 1000)`
TAG	`episode_index`, `task_index`	INT64	Source columns used as TsFile device tags
FIELD	`frame_index`, `sample_index`	INT64	`index` is renamed to `sample_index`
FIELD	`action_0` ... `action_5`	FLOAT	Flattened from `action[6]`
FIELD	`observation_state_0` ... `observation_state_5`	FLOAT	Flattened from `observation.state[6]`

Conversion Notes

The generic lerobot converter was used.
timestamp is dropped because it is redundant with Time / 1000 seconds.
frame_index is kept so rows can be aligned back to source video frames.
Vector columns preserve the source feature name with . replaced by _: observation.state becomes observation_state_0..observation_state_5, and action becomes action_0..action_5.
Video features are omitted from the converted repository. Use the original dataset's videos/ tree for camera data.
Source meta/ files are mirrored; meta/info.json is updated with a tsfile_conversion object documenting the converted path, schema roles, flattened features, dropped features, omitted videos, and row count.

Usage

from tsfile import TsFileReader

reader = TsFileReader("data/vacuame_train4.tsfile")
schemas = reader.get_all_table_schemas()
table_name = next(iter(schemas))

columns = [
    "episode_index",
    "task_index",
    "frame_index",
    "observation_state_0",
    "action_0",
]

with reader.query_table(table_name, columns, batch_size=65536) as result:
    while (batch := result.read_arrow_batch()) is not None:
        df = batch.to_pandas()
        # Process rows here.

reader.close()

Citation

@misc{vacuame_train4,
  title     = {train4 (LeRobot SO-100)},
  author    = {Vacuame},
  url       = {https://huggingface.co/datasets/Vacuame/train4},
  publisher = {Hugging Face}
}

Downloads last month: 56

Total file size:

20.8 kB