Datasets:

azithromycin
/

Beegbrain_so100_put_cube_cup

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.

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SO100 Put Cube in Cup TsFile

This Apache TsFile edition comes from Beegbrain/so100_put_cube_cup, a LeRobot v2.0 SO100 robot-manipulation dataset. It contains numeric robot trajectories, frame timing, and episode/task tags. Camera videos remain in the original repository.

Source Dataset and Attribution

Original dataset: Beegbrain/so100_put_cube_cup
Original author/uploader: Beegbrain
Authorship evidence: the repository shows Beegbrain as its owner, uploader, and sole contributor. The source card gives no separate author list.
License: Apache-2.0
Task: "Put the red cube in the red cup."
Robot: so100; LeRobot version: v2.0
Split: train; sampling rate: 15 fps
Scale: 50 episodes, 10,778 frames, 1 task
Source layout: 50 Parquet shards at data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet

TsFile Data

Path: data/beegbrain_so100_put_cube_cup.tsfile (293,817 bytes)
Table: beegbrain_so100_put_cube_cup
Rows: 10,778; episodes/devices: 50; tasks: 1
Time precision: milliseconds
TsFile/source-Parquet size ratio: 0.371
Source metadata remains under meta/, with meta/info.json describing the TsFile layout.

Schema

Time = round(timestamp * 1000) milliseconds. Time restarts at zero in every episode. Source timestamp is omitted afterward because it equals Time / 1000 seconds.

TAG columns, stored through the TsFile table/device mechanism:

episode_index
task_index

Scalar FIELD columns:

frame_index
sample_index (renamed from source index)

Flattened FLOAT FIELD groups:

action[6] -> action_0 ... action_5
observation.state[6] -> observation_state_0 ... observation_state_5

The six dimensions are main_shoulder_pan, main_shoulder_lift, main_elbow_flex, main_wrist_flex, main_wrist_roll, and main_gripper. Dots in source vector names become underscores. No numeric row, episode, task, or vector 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 storage

The physical table schema, Time codec, every FIELD codec, and all 10,778 rows were read back with the Apache TsFile Java API.

Videos

Videos are not included in this TsFile repository. The source has 100 frame-aligned AV1 MP4 files (155,224,490 bytes, about 148.0 MiB), 640x480, 15 fps, no audio, in two streams:

Each stream uses videos/chunk-000/{video_key}/episode_{episode_index:06d}.mp4. episode_index, frame_index, and meta/episodes.jsonl preserve alignment.

Usage

from tsfile import TsFileReader

reader = TsFileReader("data/beegbrain_so100_put_cube_cup.tsfile")
with reader.query_table(
    "beegbrain_so100_put_cube_cup",
    ["episode_index", "task_index", "frame_index", "sample_index",
     "action_0", "observation_state_0"],
    batch_size=65536,
) as result:
    print(result.read_arrow_batch().to_pandas().head())
reader.close()

Source Notes

The source card states that the dataset was created with LeRobot. It does not provide a paper or completed BibTeX citation.

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