Datasets:

zjt24
/

pickup_single_cotton_v2

Tasks:

Robotics

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License:

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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 66, 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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Pickup Single Cotton V2 TsFile

This dataset is a TsFile conversion of konstantinZ/pickup-single-cotton-V2, a LeRobot v2.1 Panda follower robotics dataset.

Modalities: Time-series. The original camera videos are not uploaded here; they remain available in the source dataset under videos/.

Source Dataset

Source: konstantinZ/pickup-single-cotton-V2
License: apache-2.0
Created using: LeRobot
Codebase version: v2.1
Robot type: panda_follower
Split: train 0:50
Scale: 50 episodes, 24,994 frames, 1 task, 1 data chunk, 150 videos
Sampling rate: 30 fps
Task: "Pick and place sorting task of medical equipment with the Eranka Emika Panda robot and lerobot."

Converted Files

TsFile path: data/pickup_single_cotton_v2.tsfile
Table name: pickup_single_cotton_v2
Row count: 24,994
Time precision: milliseconds
Metadata: meta/ is mirrored from the source dataset, with meta/info.json updated to describe the converted TsFile artifact and video policy.

Schema

Time is generated as round(timestamp * 1000) in milliseconds. Time restarts within each episode, and episode_index plus task_index identify the series.

TAG columns:

episode_index
task_index

FIELD columns:

frame_index
sample_index converted from the source index
action_0 to action_8
observation_state_0 to observation_state_8

The action and observation vectors use these source element names in order:

panda_joint1.pos
panda_joint2.pos
panda_joint3.pos
panda_joint4.pos
panda_joint5.pos
panda_joint6.pos
panda_joint7.pos
panda_finger_joint1.pos
panda_finger_joint2.pos

Conversion Notes

All 50 train episodes are stored in a single TsFile using the TsFile table model, with episode_index and task_index as TAG columns.
The source timestamp column is not retained as a FIELD because it is the source for Time and equals Time / 1000 seconds after conversion.
The source index column is renamed to sample_index.
action[9] is flattened to scalar FLOAT fields action_0 to action_8.
observation.state[9] is flattened to scalar FLOAT fields observation_state_0 to observation_state_8.
Video features are omitted from this repository: observation.images.overhead, observation.images.front, and observation.images.wrist. Use the original dataset videos linked above for frame-aligned visual data.

Minimal Read Example

from tsfile import TsFileReader

path = "data/pickup_single_cotton_v2.tsfile"
reader = TsFileReader(path)

columns = [
    "episode_index",
    "task_index",
    "frame_index",
    "sample_index",
    "action_0",
    "observation_state_0",
]

with reader.query_table("pickup_single_cotton_v2", columns, batch_size=1024) as result:
    batch = result.read_arrow_batch()
    if batch is not None:
        df = batch.to_pandas()
        print(df.head())

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