Datasets:

zjt24
/

sam_frames5

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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SAM Frames5 (TsFile)

This dataset is an Apache TsFile conversion of the Hugging Face dataset 1g0rrr/sam_frames5. The source was created with LeRobot and contains sam_double robot demonstrations for peeling the protective layer from adhesive tape.

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

Source Dataset

Original dataset: 1g0rrr/sam_frames5
License: apache-2.0
LeRobot codebase version: v2.1
Robot type: sam_double
Task: Peel off the protective layer from the adhesive tape.
Split: train (0:51)
Scale: 51 episodes, 32,369 frames, 1 task
Sampling rate: 30 fps
Source frame files: 51 Parquet files
Source videos: 153 MP4 files across 3 camera streams
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 camera streams are observation.images.laptop, observation.images.phone, and observation.images.side. Each stream contains 51 videos at 30 fps. Source video frames are 480 x 640 RGB, encoded with AV1, and contain no audio.

Converted File

TsFile: data/sam_frames5_train.tsfile
TsFile table: sam_frames5_train
Converted rows: 32,369
Episodes: 51
Time precision: milliseconds
TAG columns: episode_index, task_index
File size: 537,440 bytes
SHA-256: 7415819c4cfe7786f3fe18ff489fe58e8c22abb1c7128c51ebc324c47c4bc788

All train episodes are merged into one TsFile. The source episode_index and task_index columns are retained as TAG columns, so queries can select an episode without synthetic aliases.

Schema

Time is computed as Time = round(timestamp * 1000) in milliseconds and restarts in each episode. At 30 fps, consecutive frames are approximately 33.333 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_6 (FLOAT)
observation_state_0 through observation_state_6 (FLOAT)

The seven vector elements use this source order for both action and observation.state:

main_shoulder_pan
main_shoulder_lift
main_elbow_flex
main_wrist_flex
main_wrist_side
main_wrist_roll
main_gripper

Vector column names preserve the complete source feature name: . is replaced with _, then 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: 1g0rrr/sam_frames5/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/sam_frames5_train.tsfile. Its tsfile_conversion object records the source and converted file counts, table name, Time formula, TAG columns, row count, feature mappings, and frame/video alignment. The converted total_videos is 0; the source count of 153 is preserved as tsfile_conversion.source_video_count.

Validation

The converted file was compared with all 51 source Parquet files and read back with the TsFile Python SDK:

source and staged rows: 32,369
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

Usage

from tsfile import TsFileReader

path = "data/sam_frames5_train.tsfile"
with TsFileReader(path) as reader:
    schemas = reader.get_all_table_schemas()
    table = schemas["sam_frames5_train"]
    print([(column.get_column_name(), column.get_category())
           for column in table.get_columns()])

Source & License

The source dataset is maintained at 1g0rrr/sam_frames5 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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