Datasets:

VGalaxies666
/

v21_apple_storage

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
episode_index: int64
stats: struct<observation.state: struct<min: list<item: double>, max: list<item: double>, mean: list<item:  (... 1178 chars omitted)
  child 0, observation.state: struct<min: list<item: double>, max: list<item: double>, mean: list<item: double>, std: list<item: d (... 33 chars omitted)
      child 0, min: list<item: double>
          child 0, item: double
      child 1, max: list<item: double>
          child 0, item: double
      child 2, mean: list<item: double>
          child 0, item: double
      child 3, std: list<item: double>
          child 0, item: double
      child 4, count: list<item: int64>
          child 0, item: int64
  child 1, action: struct<min: list<item: double>, max: list<item: double>, mean: list<item: double>, std: list<item: d (... 33 chars omitted)
      child 0, min: list<item: double>
          child 0, item: double
      child 1, max: list<item: double>
          child 0, item: double
      child 2, mean: list<item: double>
          child 0, item: double
      child 3, std: list<item: double>
          child 0, item: double
      child 4, count: list<item: int64>
          child 0, item: int64
  child 2, observation.image: struct<min: list<item: list<item: list<item: double>>>, max: list<item: list<item: list<item: double (... 129 chars omitted)
      child 0, min: list<item: list<item: list<item: double>>>
          child 0, item: list<item: list<item: double>>
              child 0, item: list<item: double>
               
...
ax: list<item: int64>, mean: list<item: double>, std: list<item: dou (... 31 chars omitted)
      child 0, min: list<item: int64>
          child 0, item: int64
      child 1, max: list<item: int64>
          child 0, item: int64
      child 2, mean: list<item: double>
          child 0, item: double
      child 3, std: list<item: double>
          child 0, item: double
      child 4, count: list<item: int64>
          child 0, item: int64
  child 6, index: struct<min: list<item: int64>, max: list<item: int64>, mean: list<item: double>, std: list<item: dou (... 31 chars omitted)
      child 0, min: list<item: int64>
          child 0, item: int64
      child 1, max: list<item: int64>
          child 0, item: int64
      child 2, mean: list<item: double>
          child 0, item: double
      child 3, std: list<item: double>
          child 0, item: double
      child 4, count: list<item: int64>
          child 0, item: int64
  child 7, task_index: struct<min: list<item: int64>, max: list<item: int64>, mean: list<item: double>, std: list<item: dou (... 31 chars omitted)
      child 0, min: list<item: int64>
          child 0, item: int64
      child 1, max: list<item: int64>
          child 0, item: int64
      child 2, mean: list<item: double>
          child 0, item: double
      child 3, std: list<item: double>
          child 0, item: double
      child 4, count: list<item: int64>
          child 0, item: int64
tasks: list<item: string>
  child 0, item: string
length: 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 478, 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 2818, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2355, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2380, 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 2369, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              episode_index: int64
              stats: struct<observation.state: struct<min: list<item: double>, max: list<item: double>, mean: list<item:  (... 1178 chars omitted)
                child 0, observation.state: struct<min: list<item: double>, max: list<item: double>, mean: list<item: double>, std: list<item: d (... 33 chars omitted)
                    child 0, min: list<item: double>
                        child 0, item: double
                    child 1, max: list<item: double>
                        child 0, item: double
                    child 2, mean: list<item: double>
                        child 0, item: double
                    child 3, std: list<item: double>
                        child 0, item: double
                    child 4, count: list<item: int64>
                        child 0, item: int64
                child 1, action: struct<min: list<item: double>, max: list<item: double>, mean: list<item: double>, std: list<item: d (... 33 chars omitted)
                    child 0, min: list<item: double>
                        child 0, item: double
                    child 1, max: list<item: double>
                        child 0, item: double
                    child 2, mean: list<item: double>
                        child 0, item: double
                    child 3, std: list<item: double>
                        child 0, item: double
                    child 4, count: list<item: int64>
                        child 0, item: int64
                child 2, observation.image: struct<min: list<item: list<item: list<item: double>>>, max: list<item: list<item: list<item: double (... 129 chars omitted)
                    child 0, min: list<item: list<item: list<item: double>>>
                        child 0, item: list<item: list<item: double>>
                            child 0, item: list<item: double>
                             
              ...
              ax: list<item: int64>, mean: list<item: double>, std: list<item: dou (... 31 chars omitted)
                    child 0, min: list<item: int64>
                        child 0, item: int64
                    child 1, max: list<item: int64>
                        child 0, item: int64
                    child 2, mean: list<item: double>
                        child 0, item: double
                    child 3, std: list<item: double>
                        child 0, item: double
                    child 4, count: list<item: int64>
                        child 0, item: int64
                child 6, index: struct<min: list<item: int64>, max: list<item: int64>, mean: list<item: double>, std: list<item: dou (... 31 chars omitted)
                    child 0, min: list<item: int64>
                        child 0, item: int64
                    child 1, max: list<item: int64>
                        child 0, item: int64
                    child 2, mean: list<item: double>
                        child 0, item: double
                    child 3, std: list<item: double>
                        child 0, item: double
                    child 4, count: list<item: int64>
                        child 0, item: int64
                child 7, task_index: struct<min: list<item: int64>, max: list<item: int64>, mean: list<item: double>, std: list<item: dou (... 31 chars omitted)
                    child 0, min: list<item: int64>
                        child 0, item: int64
                    child 1, max: list<item: int64>
                        child 0, item: int64
                    child 2, mean: list<item: double>
                        child 0, item: double
                    child 3, std: list<item: double>
                        child 0, item: double
                    child 4, count: list<item: int64>
                        child 0, item: int64
              tasks: list<item: string>
                child 0, item: string
              length: int64
              to
              {'episode_index': Value('int64'), 'tasks': List(Value('string')), 'length': Value('int64')}
              because column names don't match

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Apple Storage v2.1 (TsFile)

Apache TsFile version of rerun/v21_apple_storage.

Overview

A small LeRobot (v2.1) sample dataset of an apple-storage manipulation task on a Reachy 2 humanoid robot, recorded at 30 fps. It contains the first three episodes of the pollen-robotics/apple_storage dataset and is used to test the LeRobot dataloader in Rerun. Each episode is a trajectory for the single task "place the apple in the plate", with synchronized joint state and action commands.

Robot: reachy2, 19-DoF.
Episodes: 3 (episode_index 0–2; lengths 299 / 300 / 300).
Frames: 899 time-series rows.
Task: 1 — place the apple in the plate.
Sampling rate: 30 fps (from meta/info.json).

Note: the source meta/info.json records total_frames: 14983 (a value carried over from the full upstream dataset). The actual frame data in this sample is 899 rows, matching meta/episodes.jsonl (299 + 300 + 300).

Schema (TsFile structure)

All 3 episodes are stored in a single TsFile table; episode_index and task_index are TAG columns (the TsFile device dimension), so one episode is selected with WHERE episode_index=0.

Time (INT64, milliseconds) — round(timestamp * 1000); restarts at 0 for each episode, stepping by ~33 ms (30 fps).
episode_index (TAG) — source episode id, 0–2.
task_index (TAG) — source task id (0).
frame_index (FIELD, INT64) — frame number within the episode.
sample_index (FIELD, INT64) — the source global index column, renamed.
observation_state_0 … _18 (FIELD, FLOAT) — robot joint state, flattened from the 19-element observation.state vector.
action_0 … _18 (FIELD, FLOAT) — joint action command, flattened from the 19-element action vector.

The source timestamp column is dropped because it equals Time / 1000 seconds. No other columns or rows are dropped.

Videos

The camera video stream of the original dataset (observation.image) is NOT included in this repository. Obtain it from the original dataset: https://huggingface.co/datasets/rerun/v21_apple_storage (the videos/ directory).

Usage

Read the .tsfile file with the Apache TsFile Java or Python SDK.

Source & license

Original dataset: https://huggingface.co/datasets/rerun/v21_apple_storage
Upstream (full) dataset: https://huggingface.co/datasets/pollen-robotics/apple_storage
Author / publisher: rerun
Created with: LeRobot
License: Apache-2.0 (as declared by the original dataset).

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