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 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.

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.

Unitree H1 Warehouse TsFile

Apache TsFile form of lerobot/unitreeh1_warehouse, a LeRobot robotics dataset containing Unitree H1 warehouse demonstrations.

Source and Attribution

  • Original repository: lerobot/unitreeh1_warehouse
  • Publishing organization: LeRobot
  • Repository history: initially created by cadene, with later maintenance by aliberts and aractingi
  • Formal data-collection authors: not specified by the original dataset card
  • License: Apache-2.0
  • Paper/citation: the original dataset card does not provide one
  • Robot type: unknown in the source metadata; the repository name identifies Unitree H1
  • Task: "Grab the spray paint on the shelf and place it in the bin on top of the robot dog."
  • Split: train, episodes 0 through 23
  • Scale: 24 episodes, 11,275 rows, one task, one source frame Parquet shard, 50 fps

Data and Videos

Videos are not included in this TsFile repository. Use episode_index and frame_index together with the source meta/episodes offsets to align numeric rows with both camera streams in the original Hugging Face repository.

Schema

Column TsFile role Type Description
Time TIME INT64 round(timestamp * 1000) milliseconds; restarts at 0 per episode
episode_index TAG STRING/device segment Original episode index
task_index TAG STRING/device segment Original task index; only task 0 is present
frame_index FIELD INT64 Frame number within the episode
sample_index FIELD INT64 Source index, renamed to avoid ambiguity
next_done FIELD BOOLEAN Source next.done terminal marker
observation_state_0 ... observation_state_18 FIELD FLOAT Flattened observation.state[19]
action_0 ... action_39 FIELD FLOAT Flattened action[40]

Conversion

  • The single source frame Parquet shard is written as one TsFile table.
  • Rows are sorted by episode_index, task_index, then Time.
  • episode_index and task_index use the TsFile table-model TAG/device mechanism.
  • Vector names retain their source prefixes with dots replaced by underscores.
  • Source timestamp is dropped after Time synthesis because it is exactly represented by Time / 1000 seconds.
  • Source index is retained as sample_index, and next.done is retained as next_done.
  • The two video features are omitted from TsFile because their payloads live in separate MP4 files, not in the frame Parquet shard.
  • No numeric frame rows, state dimensions, action dimensions, episodes, or tasks are dropped.
  • Only JSON metadata is included under meta/; source Parquet metadata files remain in the original repository and are not copied.

Read Example

from tsfile import TsFileReader

path = "data/lerobot_unitreeh1_warehouse.tsfile"
table_name = "lerobot_unitreeh1_warehouse"
reader = TsFileReader(path)
with reader.query_table(
    table_name,
    ["episode_index", "task_index", "Time", "frame_index", "action_0"],
    batch_size=4096,
) as result:
    batch = result.read_arrow_batch()
reader.close()
Downloads last month
18