Datasets:

smilegeng
/

train4

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
codebase_version: string
robot_type: string
total_episodes: int64
total_frames: int64
total_tasks: int64
total_videos: int64
total_chunks: int64
chunks_size: int64
fps: int64
splits: struct<train: string>
  child 0, train: string
data_path: string
video_path: string
features: struct<action: struct<dtype: string, shape: list<item: int64>, names: list<item: string>>, observati (... 1026 chars omitted)
  child 0, action: struct<dtype: string, shape: list<item: int64>, names: list<item: string>>
      child 0, dtype: string
      child 1, shape: list<item: int64>
          child 0, item: int64
      child 2, names: list<item: string>
          child 0, item: string
  child 1, observation.state: struct<dtype: string, shape: list<item: int64>, names: list<item: string>>
      child 0, dtype: string
      child 1, shape: list<item: int64>
          child 0, item: int64
      child 2, names: list<item: string>
          child 0, item: string
  child 2, observation.images.laptop: struct<dtype: string, shape: list<item: int64>, names: list<item: string>, info: struct<video.fps: d (... 158 chars omitted)
      child 0, dtype: string
      child 1, shape: list<item: int64>
          child 0, item: int64
      child 2, names: list<item: string>
          child 0, item: string
      child 3, info: struct<video.fps: double, video.height: int64, video.width: int64, video.channels: int64, video.code (... 76 chars omitted)
          child 0, video.fps: double
          child 1, video.height: i
...
4>
          child 0, item: int64
      child 2, names: null
  child 6, episode_index: struct<dtype: string, shape: list<item: int64>, names: null>
      child 0, dtype: string
      child 1, shape: list<item: int64>
          child 0, item: int64
      child 2, names: null
  child 7, index: struct<dtype: string, shape: list<item: int64>, names: null>
      child 0, dtype: string
      child 1, shape: list<item: int64>
          child 0, item: int64
      child 2, names: null
  child 8, task_index: struct<dtype: string, shape: list<item: int64>, names: null>
      child 0, dtype: string
      child 1, shape: list<item: int64>
          child 0, item: int64
      child 2, names: null
tsfile_conversion: struct<source_dataset: string, source_data_path: string, converted_data_path: string, table_name: st (... 240 chars omitted)
  child 0, source_dataset: string
  child 1, source_data_path: string
  child 2, converted_data_path: string
  child 3, table_name: string
  child 4, time_precision: string
  child 5, time_column: string
  child 6, tag_columns: list<item: string>
      child 0, item: string
  child 7, row_count: int64
  child 8, episode_files: int64
  child 9, vector_columns_flattened: struct<observation.state: string, action: string>
      child 0, observation.state: string
      child 1, action: string
  child 10, frame_alignment: string
  child 11, notes: string
source_data_path: string
tasks: list<item: string>
  child 0, item: string
length: int64
episode_index: int64
to
{'episode_index': Value('int64'), 'tasks': List(Value('string')), 'length': Value('int64')}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
                  return get_rows(
                      dataset=dataset,
                  ...<4 lines>...
                      column_names=column_names,
                  )
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                File "/src/services/worker/src/worker/utils.py", line 127, in get_rows
                  rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
                File "/src/services/worker/src/worker/utils.py", line 483, in safe_iter
                  yield from ds.decode(False) if ds.features else ds
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2840, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2373, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2398, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              codebase_version: string
              robot_type: string
              total_episodes: int64
              total_frames: int64
              total_tasks: int64
              total_videos: int64
              total_chunks: int64
              chunks_size: int64
              fps: int64
              splits: struct<train: string>
                child 0, train: string
              data_path: string
              video_path: string
              features: struct<action: struct<dtype: string, shape: list<item: int64>, names: list<item: string>>, observati (... 1026 chars omitted)
                child 0, action: struct<dtype: string, shape: list<item: int64>, names: list<item: string>>
                    child 0, dtype: string
                    child 1, shape: list<item: int64>
                        child 0, item: int64
                    child 2, names: list<item: string>
                        child 0, item: string
                child 1, observation.state: struct<dtype: string, shape: list<item: int64>, names: list<item: string>>
                    child 0, dtype: string
                    child 1, shape: list<item: int64>
                        child 0, item: int64
                    child 2, names: list<item: string>
                        child 0, item: string
                child 2, observation.images.laptop: struct<dtype: string, shape: list<item: int64>, names: list<item: string>, info: struct<video.fps: d (... 158 chars omitted)
                    child 0, dtype: string
                    child 1, shape: list<item: int64>
                        child 0, item: int64
                    child 2, names: list<item: string>
                        child 0, item: string
                    child 3, info: struct<video.fps: double, video.height: int64, video.width: int64, video.channels: int64, video.code (... 76 chars omitted)
                        child 0, video.fps: double
                        child 1, video.height: i
              ...
              4>
                        child 0, item: int64
                    child 2, names: null
                child 6, episode_index: struct<dtype: string, shape: list<item: int64>, names: null>
                    child 0, dtype: string
                    child 1, shape: list<item: int64>
                        child 0, item: int64
                    child 2, names: null
                child 7, index: struct<dtype: string, shape: list<item: int64>, names: null>
                    child 0, dtype: string
                    child 1, shape: list<item: int64>
                        child 0, item: int64
                    child 2, names: null
                child 8, task_index: struct<dtype: string, shape: list<item: int64>, names: null>
                    child 0, dtype: string
                    child 1, shape: list<item: int64>
                        child 0, item: int64
                    child 2, names: null
              tsfile_conversion: struct<source_dataset: string, source_data_path: string, converted_data_path: string, table_name: st (... 240 chars omitted)
                child 0, source_dataset: string
                child 1, source_data_path: string
                child 2, converted_data_path: string
                child 3, table_name: string
                child 4, time_precision: string
                child 5, time_column: string
                child 6, tag_columns: list<item: string>
                    child 0, item: string
                child 7, row_count: int64
                child 8, episode_files: int64
                child 9, vector_columns_flattened: struct<observation.state: string, action: string>
                    child 0, observation.state: string
                    child 1, action: string
                child 10, frame_alignment: string
                child 11, notes: string
              source_data_path: string
              tasks: list<item: string>
                child 0, item: string
              length: int64
              episode_index: int64
              to
              {'episode_index': Value('int64'), 'tasks': List(Value('string')), 'length': Value('int64')}
              because column names don't match

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Vacuame/train4 (LeRobot SO-100) - TsFile

This dataset converts the numeric time-series from Vacuame/train4 to Apache TsFile while preserving the LeRobot episode-level layout.

Repository Layout

README.md
data/chunk-000/episode_000000.tsfile
data/chunk-000/episode_000001.tsfile
meta/info.json
meta/tasks.jsonl
meta/episodes.jsonl
meta/stats.json
videos/chunk-000/observation.images.laptop/episode_000000.mp4
videos/chunk-000/observation.images.laptop/episode_000001.mp4
videos/chunk-000/observation.images.phone/episode_000000.mp4
videos/chunk-000/observation.images.phone/episode_000001.mp4

Source Dataset

Source: Vacuame/train4
LeRobot version: v2.0
Robot type: so100
Episodes: 2
Frames: 119
FPS: 30
Task: try
Video streams: observation.images.laptop, observation.images.phone

The original source data is one Parquet file per episode:

data/chunk-000/episode_000000.parquet
data/chunk-000/episode_000001.parquet

The converted data keeps the same episode granularity:

data/chunk-000/episode_000000.tsfile
data/chunk-000/episode_000001.tsfile

TsFile Mapping

Table name: vacuame_train4
TAG columns: episode_id, task_id
Time precision: milliseconds
Time definition: round(frame_index * 1000 / 30)
timestamp is preserved as episode_timestamp_s
index is renamed to sample_index
observation.state[6] is flattened to state_0 ... state_5
action[6] is flattened to action_0 ... action_5
Row count preserved: 119 source rows -> 119 TsFile rows across 2 files

Video Alignment

Videos are not stored inside TsFile. They are mirrored under videos/ and aligned by episode and frame:

data/chunk-000/episode_000000.tsfile
videos/chunk-000/observation.images.laptop/episode_000000.mp4
videos/chunk-000/observation.images.phone/episode_000000.mp4

Within an episode, frame_index aligns with the video frame index, and episode_timestamp_s aligns with video time in seconds.

Metadata

meta/info.json has been updated so:

"data_path": "data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.tsfile"

It also includes a tsfile_conversion object documenting the source path, converted path, TAG columns, time mapping, row count, and vector flattening.

Citation

@misc{vacuame_train4,
  title  = {train4 (LeRobot SO-100)},
  author = {Vacuame},
  url    = {https://huggingface.co/datasets/Vacuame/train4},
  publisher = {Hugging Face}
}

The source HuggingFace dataset does not declare an explicit license.

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