Dataset Viewer
The dataset viewer is not available for this subset.
Cannot get the split names for the config 'default' of the dataset.
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.

SO100 413 TsFile

This dataset is an Apache TsFile representation of Jiangeng/so100_413, a LeRobot v2.1 SO-100 dataset for the task "Pick the cube."

The numeric trajectories, episode and task identifiers, frame timing, and source metadata are included. Camera videos remain in the original Hugging Face repository.

Source Dataset

  • Source: Jiangeng/so100_413
  • Author and publisher: Jiangeng, the repository owner and sole listed contributor
  • License: Apache-2.0
  • Robot: SO-100
  • LeRobot codebase version: v2.1
  • Task: Pick the cube
  • Split: train, episodes 0 through 49
  • Scale: 50 episodes, 17,851 frames, 1 task, 30 fps
  • Source layout: 50 Parquet episode shards in data/chunk-000/
  • Source numeric size: 1,114,470 bytes
  • TsFile table: jiangeng_so100_413
  • TsFile rows: 17,851

The original card does not identify a separate personal author name, paper, homepage, or complete citation. Attribution therefore follows the facts published by the source repository.

Schema

Column TsFile role Type Source
Time TIME millisecond timestamp round(timestamp * 1000)
episode_index TAG string device segment source scalar
task_index TAG string device segment source scalar
frame_index FIELD INT64 source scalar
sample_index FIELD INT64 source index
action_0 ... action_5 FIELD FLOAT flattened action[6]
observation_state_0 ... observation_state_5 FIELD FLOAT flattened observation.state[6]

The six action and state dimensions are, in source order: left_shoulder_pan, left_shoulder_lift, left_elbow_flex, left_wrist_flex, left_wrist_roll, and left_gripper.

Time And Episode Mapping

Time is round(timestamp * 1000) in milliseconds. It restarts at zero for each episode and remains monotonic within each (episode_index, task_index) device. The original timestamp field is not repeated because it equals Time / 1000 seconds. frame_index is retained, and source index is renamed to sample_index.

All 50 source episode shards are merged into one table-model TsFile. No numeric rows, episodes, tasks, action dimensions, or state dimensions are omitted.

Videos

The source contains 100 AV1 MP4 files at 30 fps, split across two camera streams with 50 episode files each:

Videos are not included here. Use episode_index and frame_index to align numeric rows with the corresponding source video frames.

Usage

from tsfile import ColumnCategory, TsFileReader

path = "data/jiangeng_so100_413.tsfile"
reader = TsFileReader(path)
table_name = "jiangeng_so100_413"
schema = reader.get_all_table_schemas()[table_name]
columns = [
    column.get_column_name()
    for column in schema.get_columns()
    if column.get_category() in (ColumnCategory.FIELD, ColumnCategory.TAG)
]

with reader.query_table(table_name, columns, batch_size=65536) as result:
    first_batch = result.read_arrow_batch()

Citation

The source repository does not provide a complete BibTeX citation. Please cite the original dataset URL and credit Jiangeng when using this data.

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