Datasets:

jzpeng
/

coop_multitask_dataset_10all

Tasks:

Robotics

Modalities:

Tags:

Dataset card Files Files and versions

xet

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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 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.

Coop Multitask Dataset 10-All (TsFile)

Converted from shivakanthsujit/coop_multitask_dataset_10all at pinned revision 6cb422f666597a34d84c689a3433d55e6a8a483a. Modalities: Time-series.

Dataset description

This pinned LeRobot v2.1 Panda dataset contains 140 manipulation episodes spanning ten task labels involving a pasta pan, pot, mugs, wine glasses, and a blue target area.

The ten source tasks cover placing the pasta pan or pot in the blue area; picking up the pasta pan or pot; picking up the leftmost/rightmost mug; placing the mug in the blue area; picking up the leftmost/“righmost” wine glass (source spelling); and placing the wine glass in the blue area.

Source repository owner/publisher: shivakanthsujit
License: not declared by the pinned source; no license is asserted here.
Paper/homepage/citation: no completed paper, homepage, or citation is documented in the pinned source card unless linked above.

Source metadata note: The pinned source revision has no README.md; source facts come from its meta/info.json, task metadata, data Parquets, and config. No source license, paper, homepage, citation, or author list was declared.

Dataset Scale

Split	Episodes	Tasks	Source trajectory Parquets	TsFile rows	Sampling rate	TsFile files/shards
`train`	140	10	140	15,286	10 Hz	1

The staged Parquet has 15,286 rows and 254 columns including Time; TsFile chunk metadata independently reports the same 15,286 rows.

TsFile schema

Column	Role	TsFile type	Observed/source range
`Time`	TIME	INT64	0–19,000 ms; restarts per episode
`episode_index`	TAG	STRING	source integer 0–139
`task_index`	TAG	STRING	source integer 0–9
`frame_index`	FIELD	INT64	0–190 within an episode
`sample_index`	FIELD	INT64	0–15,285 globally

Exact remaining FIELD names/ranges and imported types:

active_robot (INT64), gripper_states, gripper_commands (FLOAT)
state_0–state_6, delta_actions_0–delta_actions_6 (FLOAT)
env_state_0–env_state_155 (FLOAT)
tcp_states_0–tcp_states_11, joint_states_0–joint_states_7, joint_actions_0–joint_actions_7 (FLOAT)
qpos_0–qpos_6, absolute_actions_0–absolute_actions_6, absolute_commands_0–absolute_commands_5 (FLOAT)
commanded_actions_0–commanded_actions_11, transformation_matrices_0–transformation_matrices_15 (FLOAT)

Conversion

All source episodes in the train split are merged into data/coop_multitask_dataset_10all_train.tsfile; episode_index and task_index are TAG dimensions.
Time = round(timestamp * 1000) in milliseconds. The source timestamp column is omitted because it is redundant with Time / 1000 seconds.
frame_index is retained. Source index is retained as sample_index.
Every vector is fully flattened: the complete source name is kept, . becomes _, and element indices are appended. Float vectors are imported as single-precision FLOAT fields.
Other scalar source columns shown above are retained; no trajectory rows are intentionally dropped.
Source metadata is mirrored for publication, with copied meta/info.json rewritten to describe the converted data path and conversion semantics.

Video policy

The pinned metadata declares 560 source videos across image, wrist_image, left_ego_image, and right_ego_image. MP4 files were not downloaded or uploaded; they remain in the pinned source videos/ tree.

Minimal read example

from tsfile import TsFileReader

reader = TsFileReader("data/coop_multitask_dataset_10all_train.tsfile")
print(reader.get_all_table_schemas().keys())
reader.close()

Source and provenance

Source dataset: shivakanthsujit/coop_multitask_dataset_10all
Pinned source revision: 6cb422f666597a34d84c689a3433d55e6a8a483a
Converted artifact: data/coop_multitask_dataset_10all_train.tsfile

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Total file size:

15.8 MB