Datasets:

zjt24
/

move_objects_multitask

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.

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.

Move Objects Multitask (TsFile)

This dataset is an Apache TsFile conversion of the Hugging Face dataset villekuosmanen/move_objects_multitask. The source was created with LeRobot and contains ARX5 robot demonstrations for 58 object-manipulation tasks.

Modalities: Time-series. The source repository also contains three synchronized camera streams; videos are not included in this converted repository.

Source Dataset

Original dataset: villekuosmanen/move_objects_multitask
License: apache-2.0
Current LeRobot metadata version: v2.1
Robot type: arx5
Split: train (0:140)
Scale: 140 episodes, 100,760 frames, 58 tasks
Sampling rate: 50 fps
Source frame files: 140 Parquet files
Source video files present in the repository: 420
Camera streams: 3, each with 140 MP4 files
Source data 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 tasks include picking up or sliding household objects, moving objects to a shelf, placing objects in an oven dish or cardboard box, and several composed object interactions. The complete mapping from task_index 0 through 57 is preserved in meta/tasks.jsonl.

The camera streams are observation.images.front, observation.images.left_wrist, and observation.images.right_wrist. Source videos are 480 x 640 RGB AV1 at 50 fps and contain no audio.

Source metadata discrepancy

The current source meta/info.json declares total_videos: 432, while the repository file tree contains 420 MP4 files: 140 episodes multiplied by three camera streams. The converted metadata preserves both facts as source_metadata_video_count: 432 and source_video_count: 420. The source README also embeds an older v2.0 snapshot with 103,021 frames; this card uses the current v2.1 meta/info.json and the 100,760 rows measured across all 140 source Parquet files.

Converted File

TsFile: data/move_objects_multitask_train.tsfile
TsFile table: move_objects_multitask_train
Converted rows: 100,760
Episodes: 140
Tasks: 58
Time precision: milliseconds
TAG columns: episode_index, task_index
File size: 3,355,749 bytes
SHA-256: 9cb91a8cb77dd54c49590433765f0d52dff3cbf22638cc888ac40d378e91ae7a

All train episodes are merged into one TsFile. The original episode_index and task_index columns are retained as TAG columns, allowing queries by episode, task, or both without synthetic aliases.

Schema

Time is computed as Time = round(timestamp * 1000) in milliseconds and restarts in each episode. At 50 fps, consecutive frames are approximately 20 ms apart. The source timestamp column is not retained because it is redundant with Time / 1000 seconds. No source rows are dropped.

TAG columns:

episode_index
task_index

FIELD columns:

frame_index
sample_index (renamed from source index)
action_0 through action_13 (FLOAT)
observation_state_0 through observation_state_13 (FLOAT)

Both source vector features have 14 float32 elements. The source metadata does not provide element names, so this conversion preserves their original order without inventing semantic labels. Dots in source feature names are replaced with underscores before the zero-based element index is appended.

Video Policy

The three source video features are not converted or uploaded. Use the original dataset for synchronized videos: villekuosmanen/move_objects_multitask/videos.

Each numeric row retains episode_index, frame_index, task_index, and sample_index, preserving alignment with the original per-episode videos.

Metadata

The source meta/ files are mirrored in this repository. meta/info.json is updated so data_path points to data/move_objects_multitask_train.tsfile. Its tsfile_conversion object records the source and converted file counts, declared and observed video counts, table name, Time formula, TAG columns, row count, feature mappings, and frame/video alignment. The converted total_videos value is 0.

Validation

The converted file was compared with all 140 source Parquet files:

source and staged rows: 100,760
source tasks represented: 58
duplicate (episode_index, task_index, Time) rows: 0
maximum action-vector difference: 0
maximum observation-state-vector difference: 0
source index to converted sample_index mismatches: 0

The TsFile is also validated with the project pipeline and read back with the TsFile Python SDK before publication.

Usage

from tsfile import TsFileReader

path = "data/move_objects_multitask_train.tsfile"
with TsFileReader(path) as reader:
    schemas = reader.get_all_table_schemas()
    table = schemas["move_objects_multitask_train"]
    print([(column.get_column_name(), column.get_category())
           for column in table.get_columns()])

Source & License

The source dataset is maintained at villekuosmanen/move_objects_multitask and is distributed under the Apache License 2.0. The source card does not provide a paper, author list, or citation entry.

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