Datasets:
The dataset viewer is not available for this subset.
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.
SO101 Pompom Orange TsFile
This dataset is an Apache TsFile conversion of ptizzza/so101_pompom_orange, a LeRobot v2.1 SO101 robot-manipulation dataset created and uploaded by Olga Perepelkina (ptizzza).
Modalities: Time-series, Tabular.
The source task metadata states: Grasp a yellow pompom and put it in the yellow bowl. The repository name uses orange; this README preserves both the repository name and the authoritative task text.
Source Dataset
- Pinned source revision: 44ff81db8252a189b4f1fbc481dc54f1d6a74661
- Author/uploader: Olga Perepelkina (ptizzza)
- License: Apache-2.0
- Robot type: so101; LeRobot codebase version: v2.1
- Split: train
- Scale: 50 episodes, 22,400 frame rows, 1 task, 50 source Parquet files, 30 fps
- 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 card does not provide a paper or completed citation.
Converted Files
- TsFile: data/ptizzza_so101_pompom_orange_train.tsfile
- Table: ptizzza_so101_pompom_orange_train
- Rows: 22,400
- Devices/episodes: 50
- TsFile size: 308,144 bytes
- Metadata: meta/ mirrors the source metadata; meta/info.json records the TsFile path, conversion mapping, source revision, and video policy.
TsFile Schema
Time is an INT64 millisecond timestamp computed as round(timestamp * 1000); it restarts at 0 for each episode. The redundant source timestamp field is dropped.
TAG columns (TsFile table device/tag mechanism):
- episode_index
- task_index
FIELD columns:
- frame_index
- sample_index (renamed from source index)
- action_0 ... action_5 (flattened from action[6])
- observation_state_0 ... observation_state_5 (flattened from observation.state[6]; dot becomes underscore)
No numeric rows or action/state dimensions were dropped. Source camera pixels are omitted from TsFile.
Encoding and Compression
The final file was rewritten with the explicit compact policy from EncodedLeRobotTsFileImporter.java:
- FLOAT/DOUBLE fields: GORILLA + LZ4
- INT32/INT64 fields: TS_2DIFF + LZ4
- Time: TS_2DIFF + LZ4
- BOOLEAN fields: RLE + LZ4
- TAG columns: TsFile table device/tag mechanism
This replaces the importer default of PLAIN/uncompressed encoding and substantially reduces the converted file size.
Videos
Videos are not duplicated in this converted repository. The source contains 50 frame-aligned AV1 MP4 files (640x480, 30 fps, no audio; 163,684,674 bytes) under videos/chunk-000/observation.images.webcam/. Numeric rows align with the original videos through episode_index, frame_index, and meta/episodes.jsonl.
Validation
Local validation passed: 50 source Parquet shards, 22,400 staged rows, 22,400 TsFile metadata rows, 50 devices, 2 TAG columns, 14 FIELD columns, non-empty SDK query readback, and a non-zero TsFile. VALIDATION.md and validation_report.json are kept locally and are not part of the uploaded dataset.
Usage
from tsfile import TsFileReader
reader = TsFileReader("data/ptizzza_so101_pompom_orange_train.tsfile")
with reader.query_table(
"ptizzza_so101_pompom_orange_train",
["episode_index", "task_index", "frame_index", "action_0", "observation_state_0"],
batch_size=65536,
) as result:
batch = result.read_arrow_batch()
print(batch.to_pandas().head())
reader.close()
- Downloads last month
- 32