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.

Clear Square Orig TsFile

Apache TsFile representation of lirislab/clear_square_orig, a LeRobot v2.1 so100 robot dataset.

Source

  • Publisher/author: lirislab
  • License: Apache-2.0
  • Task: Remove everything from the square.
  • Split: train (0:50)
  • Sampling rate: 30 fps
  • Episodes: 50; frame rows: 19,189; tasks: 1; source Parquet shards: 50
  • Source frame layout: data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet

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

TsFile layout

The numeric rows are stored in data/lirislab_clear_square_orig.tsfile as table lirislab_clear_square_orig. The meta/ directory contains the JSON/JSONL metadata needed to describe the source; source Parquet files are not copied into meta/.

Time = round(timestamp * 1000) is an INT64 millisecond timeline that restarts at zero for each episode. The redundant source timestamp is dropped. index is renamed to sample_index; 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)

Storage profile: Time TS_2DIFF + LZ4; FLOAT/DOUBLE GORILLA + LZ4; INT32/INT64 TS_2DIFF + LZ4; BOOLEAN RLE + LZ4 (no BOOLEAN source columns). TAGs use native TsFile table-model device/tag storage.

Dropped source column: timestamp, because it is represented exactly by Time / 1000 seconds. No rows or numeric action/state dimensions are dropped.

Videos

The original repository stores 100 MP4 files (50 episodes x 2 streams, approximately 277 MB) under videos/:

  • videos/chunk-000/observation.images.realsense_top/episode_XXXXXX.mp4
  • videos/chunk-000/observation.images.realsense_side/episode_XXXXXX.mp4

Videos are not copied into this TsFile dataset. Numeric rows stay frame-aligned with the original videos through episode_index and frame_index.

Read example

from tsfile import TsFileReader

reader = TsFileReader("data/lirislab_clear_square_orig.tsfile")
with reader.query_table("lirislab_clear_square_orig", ["episode_index", "task_index", "Time", "frame_index", "action_0"], batch_size=4096) as result:
    print(result.read_arrow_batch().to_pandas().head())
reader.close()
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