Datasets:

zjt24
/

svla_so100_task4_v3_clean

Tasks:

Robotics

Tags:

License:

Dataset card Files Files and versions

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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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SVLA SO100 Task4 V3 Clean TsFile

This dataset is converted from danaaubakirova/svla_so100_task4_v3_clean to Apache TsFile format.

Modalities: Time-series. The converted repository contains numeric SO100 robot state/action trajectories and LeRobot metadata. Camera videos are not included in this TsFile conversion; they remain in the original Hugging Face dataset under its videos/ tree.

Source Dataset

Original dataset: danaaubakirova/svla_so100_task4_v3_clean
License: apache-2.0
Robot type from source metadata: so100
Source codebase version from metadata: v2.1
Task: Put the red cube on top of the blue cube.
Sampling rate: 30 fps
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
Source card note: created using LeRobot.

At conversion time, the repository exposed 50 frame Parquet files, totaling 21,897 rows. The source meta/info.json declares 56 episodes and 22,956 frames, while the dataset card embeds an older 40-episode snapshot; this conversion follows the files actually present in the repository.

Converted Data

TsFile path: data/svla_so100_task4_v3_clean.tsfile
Table name: svla_so100_task4_v3_clean
Converted rows: 21,897
Episodes converted: 50
Episode indexes converted: 0-19, 21-36, and 40-53
Tasks: 1
Source frame Parquet files converted: 50
Output file size: 412,485 bytes
Time precision: milliseconds

Schema

Time: integer timestamp in milliseconds, computed as round(timestamp * 1000).
TAG columns: episode_index, task_index.
Integer FIELD columns: frame_index, sample_index.
FLOAT FIELD columns: action_0 through action_5.
FLOAT FIELD columns: observation_state_0 through observation_state_5.

The six action and observation-state dimensions follow the SO100 joint names from the source metadata:

main_shoulder_pan
main_shoulder_lift
main_elbow_flex
main_wrist_flex
main_wrist_roll
main_gripper

Conversion Notes

Vector columns are flattened while preserving source names: action becomes action_0..action_5, and observation.state becomes observation_state_0..observation_state_5.
The source timestamp column is dropped because it is represented by Time / 1000 seconds after conversion.
The source index column is renamed to sample_index.
Video features observation.images.top and observation.images.wrist are omitted from this repository. Use the original dataset videos at danaaubakirova/svla_so100_task4_v3_clean/videos.
Source meta/ files are mirrored, with meta/info.json updated to describe the converted TsFile path, converted schema, row count, and video policy.

Read Example

from pathlib import Path

tsfile_path = Path("data/svla_so100_task4_v3_clean.tsfile")
print(tsfile_path)

# Read this file with the Apache TsFile Java/Python SDK or TsFile tools.

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