Datasets:

jzpeng
/

aaronsu11_so100_instrument

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 Instrument TsFile

This dataset is an Apache TsFile conversion of aaronsu11/so100_instrument, a LeRobot v2.1 SO100 robot-manipulation dataset containing demonstrations for grabbing or picking up scissors and forceps.

Modalities: Time-series. The converted repository contains numeric robot state, actions, frame timing, and episode/task tags. The two camera streams remain in the original Hugging Face dataset and are linked below.

Source Dataset and Provenance

Original dataset: aaronsu11/so100_instrument
Pinned source revision: 32acf178fc1f70ba4649e36e083da6a91aa018b1
Original repository creator and uploader: Aaron Su (aaronsu11)
License: Apache-2.0
Robot type: so100
LeRobot codebase version: v2.1
Split: train
Sampling rate: 30 fps
Scale: 125 episodes, 25,882 frame rows, 4 tasks, 125 source Parquet files, 250 source videos
Source frame layout: data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet
Source video layout: videos/chunk-{episode_chunk:03d}/{video_key}/episode_{episode_index:06d}.mp4

The source README embeds an older 85-episode copy of meta/info.json. At the pinned revision, the actual meta/info.json, Parquet tree, and video tree all describe the current 125-episode dataset; those files are authoritative here.

Tasks and Scale

task_index	Task	Episodes	Rows
0	Grab the scissors	45	12,081
1	Grab the forceps	40	8,825
2	Pick up the scissors	20	2,783
3	Pick up the forceps	20	2,193

Converted Files

TsFile: data/so100_instrument_train.tsfile
Table: so100_instrument_train
Rows: 25,882
Episodes/devices: 125
TsFile size: 1.81 MiB
Time precision: milliseconds
Metadata: meta/ is mirrored from the source, with meta/info.json rewritten to describe the TsFile artifact and conversion mapping.

TsFile Schema

Time is an INT64 millisecond timestamp computed as round(timestamp * 1000) and restarts for each episode.

TAG columns (stored as TsFile STRING tags while preserving the original INT64 source dtype in metadata):

episode_index
task_index

FIELD columns:

frame_index
sample_index
action_0
action_1
action_2
action_3
action_4
action_5
observation_state_0
observation_state_1
observation_state_2
observation_state_3
observation_state_4
observation_state_5

Flattened vector groups:

action -> action_0 ... action_5 (6 FLOAT fields)
observation.state -> observation_state_0 ... observation_state_5 (6 FLOAT fields)

Conversion Notes

The dataset was converted with the shared config-driven LeRobot conversion workflow.
The train split is merged into one table-model TsFile. Filter by episode_index and task_index to select an episode or task.
action[6] and observation.state[6] are flattened to scalar FLOAT fields; the full source prefix is retained and . is replaced with _.
The source timestamp column is dropped after Time synthesis because it is redundant with Time / 1000 seconds.
The source index column is retained as sample_index; frame_index is retained unchanged.
All 25,882 source rows and all 12 action/state dimensions are retained.

Videos

Videos are not duplicated in this converted repository. The pinned source contains two frame-aligned camera streams, each with 125 per-episode MP4 files:

observation.images.front - 125 episode MP4 files
observation.images.wrist - 125 episode MP4 files

The numeric TsFile rows remain aligned with the original videos through episode_index, frame_index, and the source per-episode metadata.

Validation

The generated TsFile was checked for successful conversion, non-zero size, table schema consistency, source row-count equality, and query readback.

Minimal Read Example

from tsfile import TsFileReader

reader = TsFileReader("data/so100_instrument_train.tsfile")
table_name = "so100_instrument_train"
columns = [
    "episode_index",
    "task_index",
    "frame_index",
    "sample_index",
    "action_0",
    "observation_state_0",
]

with reader.query_table(table_name, columns, batch_size=65536) as result:
    batch = result.read_arrow_batch()
    print(batch.to_pandas().head())
reader.close()

Citation

The source dataset card provides no paper or completed citation. Cite the original Hugging Face dataset and Aaron Su (aaronsu11) when using this converted artifact.

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Total file size:

2.18 MB