Datasets:

THUgewu
/

2000_delta_ee_oxe_gr00t

Error code:   DatasetGenerationError
Exception:    ArrowNotImplementedError
Message:      Cannot write struct type 'original_video_features' with no child field to Parquet. Consider adding a dummy child field.
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1869, in _prepare_split_single
                  num_examples, num_bytes = writer.finalize()
                                            ~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 781, in finalize
                  self.write_rows_on_file()
                  ~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 663, in write_rows_on_file
                  self._write_table(table)
                  ~~~~~~~~~~~~~~~~~^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 771, in _write_table
                  self._build_writer(inferred_schema=pa_table.schema)
                  ~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 812, in _build_writer
                  self.pa_writer = pq.ParquetWriter(
                                   ~~~~~~~~~~~~~~~~^
                      self.stream,
                      ^^^^^^^^^^^^
                  ...<9 lines>...
                      },
                      ^^
                  )
                  ^
                File "/usr/local/lib/python3.14/site-packages/pyarrow/parquet/core.py", line 1070, in __init__
                  self.writer = _parquet.ParquetWriter(
                                ~~~~~~~~~~~~~~~~~~~~~~^
                      sink, schema,
                      ^^^^^^^^^^^^^
                  ...<18 lines>...
                      store_decimal_as_integer=store_decimal_as_integer,
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                      **options)
                      ^^^^^^^^^^
                File "pyarrow/_parquet.pyx", line 2363, in pyarrow._parquet.ParquetWriter.__cinit__
                File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
                  return check_status(status)
                File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
                  raise convert_status(status)
              pyarrow.lib.ArrowNotImplementedError: Cannot write struct type 'original_video_features' with no child field to Parquet. Consider adding a dummy child field.
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1369, in compute_config_parquet_and_info_response
                  parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
                                                                        ~~~~~~~~~~~~~~~~~~~~~~~~~^
                      builder, max_dataset_size_bytes=max_dataset_size_bytes
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
                  builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
                  ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1694, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ~~~~~~~~~~~~~~~~~~~~~~~~~~^
                      gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  ):
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1880, in _prepare_split_single
                  raise DatasetGenerationError("An error occurred while generating the dataset") from e
              datasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset

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total_episodes int64	total_frames int64	fps int64	robot_type string	embodiment_tag string	data_path string	features dict	tsfile_conversion dict
2,007	423,477	20	franka	OXE_DROID	data/delta_ee_oxe_gr00t_2000.tsfile	{ "Time": { "dtype": "int64", "shape": [ 1 ], "tsfile_role": "TIME", "unit": "ms" }, "episode_index": { "dtype": "int64", "shape": [ 1 ], "tsfile_role": "TAG" }, "task_index": { "dtype": "int64", "shape": [ 1 ], "tsfile_role": "TAG" }, ...	{ "source_dataset": "kaveh-kamali/2000_delta_ee_oxe_gr00t", "source_data_path": null, "converted_data_path": "data/delta_ee_oxe_gr00t_2000.tsfile", "table_name": "delta_ee_oxe_gr00t_2000", "granularity": "merged", "time_precision": "ms", "time_mapping": { "source": "timestamp", "fps": 20, "uni...

2000_delta_ee_oxe_gr00t TsFile Conversion

This dataset is a TsFile conversion of kaveh-kamali/2000_delta_ee_oxe_gr00t, a LeRobot/GR00T-style Franka robot dataset with OXE_DROID embodiment metadata.

Modalities: Time-series. Camera videos, if present in the original dataset, are not included in this converted repository.

Source Dataset Facts

From the downloaded source metadata:

Source dataset: kaveh-kamali/2000_delta_ee_oxe_gr00t
Robot type: franka
Embodiment tag: OXE_DROID
Episodes: 2,007
Frames / converted rows: 423,477
Sampling rate: 20 fps
Tasks metadata:
- task_index=0: lift the red cube
- task_index=1: valid

Converted Files

data/delta_ee_oxe_gr00t_2000.tsfile — one merged TsFile containing all 2,007 episodes.
meta/ — mirrored source metadata with meta/info.json updated to describe the TsFile artifact.

The generated TsFile size is 16,323,311 bytes.

TsFile Schema

Table name: delta_ee_oxe_gr00t_2000
Time precision: milliseconds (ms)
Time: synthesized as round(timestamp * 1000). Time restarts per episode.
TAG columns: episode_index, task_index
FIELD columns:
- sample_index — source index renamed for clarity.
- annotation_human_action_task_description
- annotation_human_validity
- next_reward
- next_done
- observation_state_0 … observation_state_7 — flattened from observation.state as FLOAT fields.
- action_0 … action_6 — flattened from action as FLOAT fields.

Per the source meta/modality.json, the action vector represents 3 end-effector position deltas, 3 end-effector RPY rotation deltas, and 1 absolute gripper-position value. The modality metadata declares state segments for joint positions and gripper position; the converted schema reflects the actual Parquet vector width observed during conversion (observation_state_0 … observation_state_7).

Conversion Notes

Converter: generic scripts/converters/lerobot.py.
Source timestamp is dropped after creating Time, because it equals Time / 1000 seconds.
Source index is renamed to sample_index.
Vector columns preserve source names by replacing . with _ and appending the element index.
Videos are not uploaded; use the original Hugging Face dataset for source videos if needed.
Aside from the redundant timestamp column, no numeric time-series rows are intentionally dropped.

Minimal Read Example

# Use Apache TsFile tooling to read:
# data/delta_ee_oxe_gr00t_2000.tsfile
# Query one episode with a predicate such as WHERE episode_index = 0.

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Total file size:

16.3 MB