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 68, 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.

MuJoCoPickAndPlace v1 TsFile

Apache TsFile representation of johnsutor/MuJoCoPickAndPlace-v1, a LeRobot v3.0 MuJoCo robotics dataset.

Source

  • Author and publisher: John Sutor (johnsutor)
  • License: Apache-2.0
  • Task: Pick up the red cube and place it on the blue circle.
  • Robot type: SO-101
  • Split: train (0:10)
  • Sampling rate: 30 fps
  • Episodes: 10; frame rows: 4,725; tasks: 1; source Parquet shards: 1
  • Source frame layout: data/chunk-{chunk_index:03d}/file-{file_index:03d}.parquet

The source card does not provide a paper or completed BibTeX citation.

TsFile layout

The numeric rows are stored in data/johnsutor_mujoco_pick_and_place_v1.tsfile as table johnsutor_mujoco_pick_and_place_v1. Source metadata JSON is retained under meta/; the task and episode metadata are represented as JSONL, and no source Parquet file is placed there.

Time = round(timestamp * 1000) is an INT64 millisecond timeline that restarts at zero for every episode. The source timestamp is omitted because it equals Time / 1000 seconds. index is renamed to sample_index, and frame_index is preserved.

Role Columns
TIME Time (INT64, milliseconds)
TAG/device episode_index, task_index
FIELD frame_index, sample_index (INT64)
FIELD action[6] -> action_0 ... action_5 (FLOAT)
FIELD observation.state[6] -> observation_state_0 ... observation_state_5 (FLOAT)
FIELD observation.environment_state[36] -> observation_environment_state_0 ... observation_environment_state_35 (FLOAT)
FIELD reward, success, done, and six reward_components_* values (FLOAT)

No numeric row, action dimension, state dimension, environment-state dimension, reward value, or frame index is dropped.

Videos

Videos remain in the original Hugging Face repository and are not included here:

The source layout is videos/{video_key}/chunk-{chunk_index:03d}/file-{file_index:03d}.mp4. Numeric rows align with both camera streams through episode_index, frame_index, and the offsets recorded in meta/episodes.jsonl.

Read example

from tsfile import TsFileReader

reader = TsFileReader("data/johnsutor_mujoco_pick_and_place_v1.tsfile")
columns = [
    "episode_index",
    "task_index",
    "frame_index",
    "sample_index",
    "action_0",
    "observation_state_0",
    "observation_environment_state_0",
    "reward",
]
with reader.query_table("johnsutor_mujoco_pick_and_place_v1", columns, batch_size=4096) as result:
    print(result.read_arrow_batch().to_pandas().head())
reader.close()
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