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.

First Task Short TsFile

This dataset is an Apache TsFile conversion of pietroom/first_task_short, a LeRobot v2.1 SO100 robot-manipulation dataset for passing a marker.

Source Dataset and Attribution

  • Original dataset: pietroom/first_task_short
  • Original author, repository owner, uploader, and video contributor: pietroom
  • License: Apache-2.0
  • Task: "Pass the marker."
  • Robot: so100; LeRobot version: v2.1
  • Split: train; sampling rate: 30 fps
  • Scale: 90 episodes, 53,830 frames, 1 task
  • Source shards: 90 Parquet files totaling 2,911,374 bytes
  • Source layout: data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet
  • The source card provides no paper, external homepage, or completed citation.

Data Summary

  • Path: data/pietroom_first_task_short.tsfile
  • Table: pietroom_first_task_short
  • Rows: 53,830; episodes/devices: 90; tasks: 1
  • Time precision: milliseconds
  • TsFile/source-Parquet size ratio: 0.366

Schema and Mapping

Time = round(timestamp * 1000) milliseconds. Time starts at zero and is strictly increasing in every episode. The source timestamp is omitted after conversion because it is recoverable as Time / 1000 seconds.

TsFile column Role Type Source mapping
Time TIME TIMESTAMP round(timestamp * 1000) ms
episode_index TAG STRING Original INT64 episode index
task_index TAG STRING Original INT64 task index
frame_index FIELD INT64 Preserved
sample_index FIELD INT64 Renamed from index
action_0 ... action_5 FIELD FLOAT Flattened from action[6]
observation_state_0 ... observation_state_5 FIELD FLOAT Flattened from observation.state[6]

The six vector dimensions are main_shoulder_pan, main_shoulder_lift, main_elbow_flex, main_wrist_flex, main_wrist_roll, and main_gripper. Dots in source names are replaced by underscores. No numeric row, episode, task, action dimension, or state dimension is dropped.

Encodings and Compression

  • FLOAT/DOUBLE: GORILLA + LZ4
  • INT32/INT64: TS_2DIFF + LZ4
  • Time: TS_2DIFF + LZ4
  • BOOLEAN: RLE + LZ4 (the source has no BOOLEAN field)
  • TAG: TsFile table/device TAG storage

Videos

Videos are not included in this TsFile dataset. The 180 original AV1 MP4 files remain in the source repository, 640x480 at 30 fps with no audio, in two streams with 90 episode files each:

The source layout is videos/chunk-{episode_chunk:03d}/{video_key}/episode_{episode_index:06d}.mp4. Use episode_index and frame_index to align numeric rows with video frames.

Minimal Read Example

from tsfile import TsFileReader

reader = TsFileReader("data/pietroom_first_task_short.tsfile")
with reader.query_table(
    "pietroom_first_task_short",
    ["episode_index", "task_index", "frame_index", "sample_index",
     "action_0", "observation_state_0"],
    batch_size=65536,
) as result:
    batch = result.read_arrow_batch()
    print(batch.to_pandas().head())
reader.close()

Citation

The source card supplies no paper or completed citation. Cite the original Hugging Face dataset and its publisher, pietroom, when using this conversion.

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