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Datasets:
smilegeng
/
piperx_flatten_success_rollouts

Tasks:
Robotics
Size:
100K<n<1M
Tags:
robotics
LeRobot
tsfile
modality:timeseries
License:
Dataset card Files
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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
episode_index: int64
tasks: list<item: string>
  child 0, item: string
length: int64
skip_counts: struct<non_success: int64>
  child 0, non_success: int64
script: string
raw_dir: string
repo_id: string
processed_sources: list<item: string>
  child 0, item: string
version: int64
max_episodes: null
to
{'version': Value('int64'), 'script': Value('string'), 'raw_dir': Value('string'), 'repo_id': Value('string'), 'max_episodes': Value('null'), 'processed_sources': List(Value('string')), 'skip_counts': {'non_success': 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 2815, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2352, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/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/python3.14/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
              tasks: list<item: string>
                child 0, item: string
              length: int64
              skip_counts: struct<non_success: int64>
                child 0, non_success: int64
              script: string
              raw_dir: string
              repo_id: string
              processed_sources: list<item: string>
                child 0, item: string
              version: int64
              max_episodes: null
              to
              {'version': Value('int64'), 'script': Value('string'), 'raw_dir': Value('string'), 'repo_id': Value('string'), 'max_episodes': Value('null'), 'processed_sources': List(Value('string')), 'skip_counts': {'non_success': Value('int64')}}
              because column names don't match

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piperx_flatten_success_rollouts (TsFile)

Apache TsFile version of the LeRobot dataset Ishan-Axibo/piperx_flatten_success_rollouts.

Overview

Successful dual-arm rollouts of the task "pick towel from pile, fold and stack".

  • Robot: piperx_bimanual (dual-arm PiperX)
  • Episodes: 53
  • Frames: 181,264
  • Sampling rate: 30 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 three camera streams (cam_front / cam_left_wrist / cam_right_wrist) 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

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