Datasets:

jzpeng
/

Dangvi_soarm100_data2

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.

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SOARM100 Data2 TsFile

Apache TsFile edition of Dangvi/soarm100_data2, a LeRobot v2.1 SO100 dataset with demonstrations for lifting orange or green 2x4 blocks above an 8x8 blue block.

Source and attribution

Original author, repository owner, and uploader: DANBI KIM (Dangvi).
License: Apache-2.0.
The source card provides no homepage, paper, or completed BibTeX citation.
Split: train; 75 episodes; 33,440 frame rows; 2 tasks; 30 FPS; 75 source Parquet shards.
The source card's embedded metadata example says 25 episodes, but the current meta/info.json, episode metadata, and repository file tree consistently contain 75 episodes.
Task 0: Pick up the 2x4 orange block and go up the 8x8 blue block.
Task 1: Pick up the 2x4 green block and go up the 8x8 blue block.

Data layout

The table is dangvi_soarm100_data2 and contains 33,440 rows across 75 episode/task devices.

Column	TsFile role	Type	Meaning
`Time`	TIME	INT64 milliseconds	`round(timestamp * 1000)`, restarting at zero per episode
`episode_index`	TAG	STRING from source INT64	Source episode identity
`task_index`	TAG	STRING from source INT64	Source task identity
`frame_index`	FIELD	INT64	Frame position within the episode
`sample_index`	FIELD	INT64	Source `index`, renamed for clarity
`action_0` ... `action_5`	FIELD	FLOAT	Flattened `action[6]`
`observation_state_0` ... `observation_state_5`	FIELD	FLOAT	Flattened `observation.state[6]`

timestamp is not retained as a separate FIELD because it is represented by Time / 1000 seconds. Vector names preserve their source prefixes, with dots changed to underscores. No trajectory row, episode, task, action dimension, or state dimension is removed.

Videos and alignment

The 150 source AV1 videos remain in the original repository under videos/chunk-000:

observation.images.webcam: 75 MP4 files, 256,529,229 bytes
observation.images.wristcam: 75 MP4 files, 133,437,099 bytes

The source template is videos/chunk-{episode_chunk:03d}/{video_key}/episode_{episode_index:06d}.mp4. Use episode_index and frame_index to align each numeric row with both 30 FPS video streams. The videos are not included in this TsFile dataset.

Read example

from tsfile import TsFileReader

reader = TsFileReader("data/dangvi_soarm100_data2.tsfile")
with reader.query_table(
    "dangvi_soarm100_data2",
    ["episode_index", "task_index", "frame_index", "sample_index", "action_0", "observation_state_0"],
    batch_size=1024,
) as result:
    batch = result.read_arrow_batch()
    print(batch.to_pandas().head())
reader.close()

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Total file size:

716 kB