Datasets:

THULab
/

aloha_static_candy

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
observation.images.cam_low: 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>
              child 0, item: double
  child 1, max: list<item: list<item: list<item: double>>>
      child 0, item: list<item: list<item: double>>
          child 0, item: list<item: double>
              child 0, item: double
  child 2, mean: list<item: list<item: list<item: double>>>
      child 0, item: list<item: list<item: double>>
          child 0, item: list<item: double>
              child 0, item: double
  child 3, std: list<item: list<item: list<item: double>>>
      child 0, item: list<item: list<item: double>>
          child 0, item: list<item: double>
              child 0, item: double
  child 4, count: list<item: int64>
      child 0, item: int64
observation.images.cam_high: 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>
              child 0, item: double
  child 1, max: list<item: list<item: list<item: double>>>
      child 0, item: list<item: list<item: double>>
          child 0, item: list<item: double>
              child
...

      child 2, shape: list<item: int64>
          child 0, item: int64
  child 28, action_8: struct<dtype: string, role: string, shape: list<item: int64>>
      child 0, dtype: string
      child 1, role: string
      child 2, shape: list<item: int64>
          child 0, item: int64
  child 29, action_9: struct<dtype: string, role: string, shape: list<item: int64>>
      child 0, dtype: string
      child 1, role: string
      child 2, shape: list<item: int64>
          child 0, item: int64
  child 30, action_10: struct<dtype: string, role: string, shape: list<item: int64>>
      child 0, dtype: string
      child 1, role: string
      child 2, shape: list<item: int64>
          child 0, item: int64
  child 31, action_11: struct<dtype: string, role: string, shape: list<item: int64>>
      child 0, dtype: string
      child 1, role: string
      child 2, shape: list<item: int64>
          child 0, item: int64
  child 32, action_12: struct<dtype: string, role: string, shape: list<item: int64>>
      child 0, dtype: string
      child 1, role: string
      child 2, shape: list<item: int64>
          child 0, item: int64
  child 33, action_13: struct<dtype: string, role: string, shape: list<item: int64>>
      child 0, dtype: string
      child 1, role: string
      child 2, shape: list<item: int64>
          child 0, item: int64
total_tasks: int64
video_files_size_in_mb: int64
total_frames: int64
codebase_version: string
fps: int64
video_path: string
data_files_size_in_mb: int64
to
{'codebase_version': Value('string'), 'robot_type': Value('string'), 'total_episodes': Value('int64'), 'total_frames': Value('int64'), 'total_tasks': Value('int64'), 'chunks_size': Value('int64'), 'fps': Value('int64'), 'splits': {'train': Value('string')}, 'data_path': Value('string'), 'video_path': Value('string'), 'features': {'Time': {'dtype': Value('string'), 'role': Value('string'), 'shape': List(Value('int64'))}, 'episode_index': {'dtype': Value('string'), 'role': Value('string'), 'shape': List(Value('int64'))}, 'task_index': {'dtype': Value('string'), 'role': Value('string'), 'shape': List(Value('int64'))}, 'frame_index': {'dtype': Value('string'), 'role': Value('string'), 'shape': List(Value('int64'))}, 'sample_index': {'dtype': Value('string'), 'role': Value('string'), 'shape': List(Value('int64'))}, 'next_done': {'dtype': Value('string'), 'role': Value('string'), 'shape': List(Value('int64'))}, 'observation_state_0': {'dtype': Value('string'), 'role': Value('string'), 'shape': List(Value('int64'))}, 'observation_state_1': {'dtype': Value('string'), 'role': Value('string'), 'shape': List(Value('int64'))}, 'observation_state_2': {'dtype': Value('string'), 'role': Value('string'), 'shape': List(Value('int64'))}, 'observation_state_3': {'dtype': Value('string'), 'role': Value('string'), 'shape': List(Value('int64'))}, 'observation_state_4': {'dtype': Value('string'), 'role': Value('string'), 'shape': List(Value('int64'))}, 'observation_state_5': {'dtype': Value('string
...
deo_info': {'video.fps': Value('float64'), 'video.codec': Value('string'), 'video.pix_fmt': Value('string'), 'video.is_depth_map': Value('bool'), 'has_audio': Value('bool')}}, 'observation.images.cam_right_wrist': {'dtype': Value('string'), 'shape': List(Value('int64')), 'names': List(Value('string')), 'video_info': {'video.fps': Value('float64'), 'video.codec': Value('string'), 'video.pix_fmt': Value('string'), 'video.is_depth_map': Value('bool'), 'has_audio': Value('bool')}}, 'observation.state': {'dtype': Value('string'), 'shape': List(Value('int64')), 'names': {'motors': List(Value('string'))}, 'fps': Value('float64')}, 'action': {'dtype': Value('string'), 'shape': List(Value('int64')), 'names': {'motors': List(Value('string'))}, 'fps': Value('float64')}, 'episode_index': {'dtype': Value('string'), 'shape': List(Value('int64')), 'names': Value('null'), 'fps': Value('float64')}, 'frame_index': {'dtype': Value('string'), 'shape': List(Value('int64')), 'names': Value('null'), 'fps': Value('float64')}, 'timestamp': {'dtype': Value('string'), 'shape': List(Value('int64')), 'names': Value('null'), 'fps': Value('float64')}, 'next.done': {'dtype': Value('string'), 'shape': List(Value('int64')), 'names': Value('null'), 'fps': Value('float64')}, 'index': {'dtype': Value('string'), 'shape': List(Value('int64')), 'names': Value('null'), 'fps': Value('float64')}, 'task_index': {'dtype': Value('string'), 'shape': List(Value('int64')), 'names': Value('null'), 'fps': Value('float64')}}}}
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
              observation.images.cam_low: 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>
                            child 0, item: double
                child 1, max: list<item: list<item: list<item: double>>>
                    child 0, item: list<item: list<item: double>>
                        child 0, item: list<item: double>
                            child 0, item: double
                child 2, mean: list<item: list<item: list<item: double>>>
                    child 0, item: list<item: list<item: double>>
                        child 0, item: list<item: double>
                            child 0, item: double
                child 3, std: list<item: list<item: list<item: double>>>
                    child 0, item: list<item: list<item: double>>
                        child 0, item: list<item: double>
                            child 0, item: double
                child 4, count: list<item: int64>
                    child 0, item: int64
              observation.images.cam_high: 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>
                            child 0, item: double
                child 1, max: list<item: list<item: list<item: double>>>
                    child 0, item: list<item: list<item: double>>
                        child 0, item: list<item: double>
                            child
              ...
              
                    child 2, shape: list<item: int64>
                        child 0, item: int64
                child 28, action_8: struct<dtype: string, role: string, shape: list<item: int64>>
                    child 0, dtype: string
                    child 1, role: string
                    child 2, shape: list<item: int64>
                        child 0, item: int64
                child 29, action_9: struct<dtype: string, role: string, shape: list<item: int64>>
                    child 0, dtype: string
                    child 1, role: string
                    child 2, shape: list<item: int64>
                        child 0, item: int64
                child 30, action_10: struct<dtype: string, role: string, shape: list<item: int64>>
                    child 0, dtype: string
                    child 1, role: string
                    child 2, shape: list<item: int64>
                        child 0, item: int64
                child 31, action_11: struct<dtype: string, role: string, shape: list<item: int64>>
                    child 0, dtype: string
                    child 1, role: string
                    child 2, shape: list<item: int64>
                        child 0, item: int64
                child 32, action_12: struct<dtype: string, role: string, shape: list<item: int64>>
                    child 0, dtype: string
                    child 1, role: string
                    child 2, shape: list<item: int64>
                        child 0, item: int64
                child 33, action_13: struct<dtype: string, role: string, shape: list<item: int64>>
                    child 0, dtype: string
                    child 1, role: string
                    child 2, shape: list<item: int64>
                        child 0, item: int64
              total_tasks: int64
              video_files_size_in_mb: int64
              total_frames: int64
              codebase_version: string
              fps: int64
              video_path: string
              data_files_size_in_mb: int64
              to
              {'codebase_version': Value('string'), 'robot_type': Value('string'), 'total_episodes': Value('int64'), 'total_frames': Value('int64'), 'total_tasks': Value('int64'), 'chunks_size': Value('int64'), 'fps': Value('int64'), 'splits': {'train': Value('string')}, 'data_path': Value('string'), 'video_path': Value('string'), 'features': {'Time': {'dtype': Value('string'), 'role': Value('string'), 'shape': List(Value('int64'))}, 'episode_index': {'dtype': Value('string'), 'role': Value('string'), 'shape': List(Value('int64'))}, 'task_index': {'dtype': Value('string'), 'role': Value('string'), 'shape': List(Value('int64'))}, 'frame_index': {'dtype': Value('string'), 'role': Value('string'), 'shape': List(Value('int64'))}, 'sample_index': {'dtype': Value('string'), 'role': Value('string'), 'shape': List(Value('int64'))}, 'next_done': {'dtype': Value('string'), 'role': Value('string'), 'shape': List(Value('int64'))}, 'observation_state_0': {'dtype': Value('string'), 'role': Value('string'), 'shape': List(Value('int64'))}, 'observation_state_1': {'dtype': Value('string'), 'role': Value('string'), 'shape': List(Value('int64'))}, 'observation_state_2': {'dtype': Value('string'), 'role': Value('string'), 'shape': List(Value('int64'))}, 'observation_state_3': {'dtype': Value('string'), 'role': Value('string'), 'shape': List(Value('int64'))}, 'observation_state_4': {'dtype': Value('string'), 'role': Value('string'), 'shape': List(Value('int64'))}, 'observation_state_5': {'dtype': Value('string
              ...
              deo_info': {'video.fps': Value('float64'), 'video.codec': Value('string'), 'video.pix_fmt': Value('string'), 'video.is_depth_map': Value('bool'), 'has_audio': Value('bool')}}, 'observation.images.cam_right_wrist': {'dtype': Value('string'), 'shape': List(Value('int64')), 'names': List(Value('string')), 'video_info': {'video.fps': Value('float64'), 'video.codec': Value('string'), 'video.pix_fmt': Value('string'), 'video.is_depth_map': Value('bool'), 'has_audio': Value('bool')}}, 'observation.state': {'dtype': Value('string'), 'shape': List(Value('int64')), 'names': {'motors': List(Value('string'))}, 'fps': Value('float64')}, 'action': {'dtype': Value('string'), 'shape': List(Value('int64')), 'names': {'motors': List(Value('string'))}, 'fps': Value('float64')}, 'episode_index': {'dtype': Value('string'), 'shape': List(Value('int64')), 'names': Value('null'), 'fps': Value('float64')}, 'frame_index': {'dtype': Value('string'), 'shape': List(Value('int64')), 'names': Value('null'), 'fps': Value('float64')}, 'timestamp': {'dtype': Value('string'), 'shape': List(Value('int64')), 'names': Value('null'), 'fps': Value('float64')}, 'next.done': {'dtype': Value('string'), 'shape': List(Value('int64')), 'names': Value('null'), 'fps': Value('float64')}, 'index': {'dtype': Value('string'), 'shape': List(Value('int64')), 'names': Value('null'), 'fps': Value('float64')}, 'task_index': {'dtype': Value('string'), 'shape': List(Value('int64')), 'names': Value('null'), 'fps': Value('float64')}}}}
              because column names don't match

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aloha_static_candy

This dataset converts the numeric time-series from lerobot/aloha_static_candy to Apache TsFile format.

Dataset Description

The source dataset was created using LeRobot. It is an ALOHA robot dataset published by the LeRobot team.

Source dataset: lerobot/aloha_static_candy
Project: ALOHA
Paper: https://arxiv.org/abs/2304.13705
License: MIT

Converted Data

50 episodes, 35,000 frames, 50 fps
One TsFile: aloha_static_candy.tsfile
Table name: aloha_static_candy
TAG columns: episode_index, task_index
Time: round(timestamp * 1000) milliseconds
Source timestamp is used to synthesize Time and is not retained as a separate field
observation.state[14] is flattened to observation_state_0..observation_state_13
action[14] is flattened to action_0..action_13
Aside from the redundant source timestamp column noted above, no source time-series columns or rows are dropped

Videos

Video files are not included in this converted TsFile repository. The original camera streams remain in the source HuggingFace dataset:

https://huggingface.co/datasets/lerobot/aloha_static_candy/tree/main/videos

Use episode_index, frame_index, and Time to align TsFile rows with the original videos.

Downloads last month: 69

Total file size:

1.76 MB

Paper for THULab/aloha_static_candy

Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardware

Paper • 2304.13705 • Published Apr 23, 2023 • 7