Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardware
Paper • 2304.13705 • Published • 7
The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
task_index: int64
__index_level_0__: string
-- schema metadata --
pandas: '{"index_columns": ["__index_level_0__"], "column_indexes": [{"na' + 449
to
{'episode_index': Value('int64'), 'data/chunk_index': Value('int64'), 'data/file_index': Value('int64'), 'dataset_from_index': Value('int64'), 'dataset_to_index': Value('int64'), 'videos/observation.images.top/chunk_index': Value('int64'), 'videos/observation.images.top/file_index': Value('int64'), 'videos/observation.images.top/from_timestamp': Value('float64'), 'videos/observation.images.top/to_timestamp': Value('float64'), 'tasks': List(Value('string')), 'length': Value('int64'), 'stats/observation.images.top/min': List(List(List(Value('float64')))), 'stats/observation.images.top/max': List(List(List(Value('float64')))), 'stats/observation.images.top/mean': List(List(List(Value('float64')))), 'stats/observation.images.top/std': List(List(List(Value('float64')))), 'stats/observation.images.top/count': List(Value('int64')), 'stats/observation.state/min': List(Value('float64')), 'stats/observation.state/max': List(Value('float64')), 'stats/observation.state/mean': List(Value('float64')), 'stats/observation.state/std': List(Value('float64')), 'stats/observation.state/count': List(Value('int64')), 'stats/action/min': List(Value('float64')), 'stats/action/max': List(Value('float64')), 'stats/action/mean': List(Value('float64')), 'stats/action/std': List(Value('float64')), 'stats/action/count': List(Value('int64')), 'stats/episode_index/min': List(Value('int64')), 'stats/episode_index/max': List(Value('int64')), 'stats/episode_index/mean': List(Value('float64')), 'stats/episode_index/std': List(Value('float64')), 'stats/episode_index/count': List(Value('int64')), 'stats/frame_index/min': List(Value('int64')), 'stats/frame_index/max': List(Value('int64')), 'stats/frame_index/mean': List(Value('float64')), 'stats/frame_index/std': List(Value('float64')), 'stats/frame_index/count': List(Value('int64')), 'stats/timestamp/min': List(Value('float64')), 'stats/timestamp/max': List(Value('float64')), 'stats/timestamp/mean': List(Value('float64')), 'stats/timestamp/std': List(Value('float64')), 'stats/timestamp/count': List(Value('int64')), 'stats/next.done/min': List(Value('bool')), 'stats/next.done/max': List(Value('bool')), 'stats/next.done/mean': List(Value('float64')), 'stats/next.done/std': List(Value('float64')), 'stats/next.done/count': List(Value('int64')), 'stats/index/min': List(Value('int64')), 'stats/index/max': List(Value('int64')), 'stats/index/mean': List(Value('float64')), 'stats/index/std': List(Value('float64')), 'stats/index/count': List(Value('int64')), 'stats/task_index/min': List(Value('int64')), 'stats/task_index/max': List(Value('int64')), 'stats/task_index/mean': List(Value('float64')), 'stats/task_index/std': List(Value('float64')), 'stats/task_index/count': List(Value('int64')), 'meta/episodes/chunk_index': Value('int64'), 'meta/episodes/file_index': 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(
^^^^^^^^^
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/python3.12/site-packages/datasets/iterable_dataset.py", line 2815, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2352, in __iter__
for key, pa_table in self._iter_arrow():
^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2377, in _iter_arrow
for key, pa_table in self.ex_iterable._iter_arrow():
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.12/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/python3.12/site-packages/datasets/packaged_modules/parquet/parquet.py", line 220, in _generate_tables
yield Key(file_idx, batch_idx), self._cast_table(pa_table)
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/parquet/parquet.py", line 156, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2369, in table_cast
return cast_table_to_schema(table, schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
task_index: int64
__index_level_0__: string
-- schema metadata --
pandas: '{"index_columns": ["__index_level_0__"], "column_indexes": [{"na' + 449
to
{'episode_index': Value('int64'), 'data/chunk_index': Value('int64'), 'data/file_index': Value('int64'), 'dataset_from_index': Value('int64'), 'dataset_to_index': Value('int64'), 'videos/observation.images.top/chunk_index': Value('int64'), 'videos/observation.images.top/file_index': Value('int64'), 'videos/observation.images.top/from_timestamp': Value('float64'), 'videos/observation.images.top/to_timestamp': Value('float64'), 'tasks': List(Value('string')), 'length': Value('int64'), 'stats/observation.images.top/min': List(List(List(Value('float64')))), 'stats/observation.images.top/max': List(List(List(Value('float64')))), 'stats/observation.images.top/mean': List(List(List(Value('float64')))), 'stats/observation.images.top/std': List(List(List(Value('float64')))), 'stats/observation.images.top/count': List(Value('int64')), 'stats/observation.state/min': List(Value('float64')), 'stats/observation.state/max': List(Value('float64')), 'stats/observation.state/mean': List(Value('float64')), 'stats/observation.state/std': List(Value('float64')), 'stats/observation.state/count': List(Value('int64')), 'stats/action/min': List(Value('float64')), 'stats/action/max': List(Value('float64')), 'stats/action/mean': List(Value('float64')), 'stats/action/std': List(Value('float64')), 'stats/action/count': List(Value('int64')), 'stats/episode_index/min': List(Value('int64')), 'stats/episode_index/max': List(Value('int64')), 'stats/episode_index/mean': List(Value('float64')), 'stats/episode_index/std': List(Value('float64')), 'stats/episode_index/count': List(Value('int64')), 'stats/frame_index/min': List(Value('int64')), 'stats/frame_index/max': List(Value('int64')), 'stats/frame_index/mean': List(Value('float64')), 'stats/frame_index/std': List(Value('float64')), 'stats/frame_index/count': List(Value('int64')), 'stats/timestamp/min': List(Value('float64')), 'stats/timestamp/max': List(Value('float64')), 'stats/timestamp/mean': List(Value('float64')), 'stats/timestamp/std': List(Value('float64')), 'stats/timestamp/count': List(Value('int64')), 'stats/next.done/min': List(Value('bool')), 'stats/next.done/max': List(Value('bool')), 'stats/next.done/mean': List(Value('float64')), 'stats/next.done/std': List(Value('float64')), 'stats/next.done/count': List(Value('int64')), 'stats/index/min': List(Value('int64')), 'stats/index/max': List(Value('int64')), 'stats/index/mean': List(Value('float64')), 'stats/index/std': List(Value('float64')), 'stats/index/count': List(Value('int64')), 'stats/task_index/min': List(Value('int64')), 'stats/task_index/max': List(Value('int64')), 'stats/task_index/mean': List(Value('float64')), 'stats/task_index/std': List(Value('float64')), 'stats/task_index/count': List(Value('int64')), 'meta/episodes/chunk_index': Value('int64'), 'meta/episodes/file_index': Value('int64')}
because column names don't matchNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
aloha_sim_transfer_cube_human (TsFile)
Apache TsFile version of the LeRobot dataset
lerobot/aloha_sim_transfer_cube_human.
Overview
ALOHA simulated bimanual transfer-cube manipulation demonstrations.
- Robot: ALOHA (simulated)
- Episodes: 50
- Frames: 20,000
- Sampling rate: 50 fps
- Tasks: 1
Schema (TsFile structure)
- Time (INT64, milliseconds) —
round(timestamp * 1000), restarting per episode. - episode_index / task_index (TAG) — the device dimension. Query a single episode with
WHERE episode_index=N. - FIELD —
frame_index,sample_index, and the flattened state/action vectors (observation_state_0..13,action_0..13) as single-precision FLOAT.
The robot's camera video streams are time-series-irrelevant and not uploaded to this repository;
get them from the original dataset (its videos/ directory). The source meta/ is mirrored here.
Usage
Read the .tsfile files with the Apache TsFile Java or Python SDK.
Source & license
- Original dataset:
lerobot/aloha_sim_transfer_cube_human - Author / publisher: LeRobot team / ALOHA
- Paper: arXiv:2304.13705
- License: mit
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