Datasets:

THUgewu
/

humanoid_pick_and_place

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:  (... 1722 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.images.cam_front: 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 8, 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 9, 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:  (... 1722 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.images.cam_front: 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 8, 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 9, 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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Humanoid Pick and Place (TsFile)

Apache TsFile version of axiboai/humanoid_pick_and_place.

Overview

Teleoperated demonstrations of a humanoid upper body performing a single pick-and-place task: "pick up cube and place in bin". Each episode records the synchronized joint states and motor action targets of a two-armed humanoid (14 arm/wrist joints plus a pinch-distance value per hand) sampled at 30 Hz.

Robot: humanoid_upper_body (dual arm, 16-DoF state/action vector).
Scale: 50 episodes, 40,477 frames, 1 task.
Sampling rate: 30 fps.
Cameras: 3 RGB streams (cam_front, cam_left_wrist, cam_right_wrist), 480×640 — provided as video in the original dataset, see note below.

Schema (TsFile structure)

All 50 episodes are stored in a single .tsfile table. Episodes are addressed as TsFile devices via the TAG columns.

Time (INT64, milliseconds) — round(timestamp * 1000); restarts at 0 each episode (33 ms steps at 30 fps).
episode_index (TAG) — source episode id (0–49). Query one episode with WHERE episode_index=0.
task_index (TAG) — source task id (always 0; the single pick-and-place task).
frame_index (FIELD, INT64) — frame number within the episode.
sample_index (FIELD, INT64) — global sample index (source index).
observation_state_0 … observation_state_15 (FIELD, FLOAT) — measured joint positions: left/right shoulder pitch·roll·yaw, elbow, wrist roll·pitch·yaw, and left/right hand pinch distance.
action_0 … action_15 (FIELD, FLOAT) — commanded targets, same 16-element layout as the state vector.

The 16-element observation.state and action vectors are flattened to <name>_0..<name>_15 (single-precision FLOAT). The source timestamp column is dropped because it equals Time / 1000 seconds.

Usage

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

Source & license

Original dataset: https://huggingface.co/datasets/axiboai/humanoid_pick_and_place
Author / publisher: axiboai
Camera videos (cam_front, cam_left_wrist, cam_right_wrist) are not included in this repository; see the original dataset videos/ directory.
License: not declared by the original dataset; please defer to the original.

Downloads last month: 51

Total file size:

3.15 MB