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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:    ReadError
Message:      unexpected end of data
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 90, in get_rows_or_raise
                  return get_rows(
                File "/src/libs/libcommon/src/libcommon/utils.py", line 197, in decorator
                  return func(*args, **kwargs)
                File "/src/services/worker/src/worker/utils.py", line 68, in get_rows
                  rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2012, in __iter__
                  for key, example in ex_iterable:
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 188, in __iter__
                  for key_example in islice(self.generate_examples_fn(**gen_kwags), shard_example_idx_start, None):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 113, in _generate_examples
                  for example_idx, example in enumerate(self._get_pipeline_from_tar(tar_path, tar_iterator)):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 40, in _get_pipeline_from_tar
                  current_example[field_name.lower()] = f.read()
                File "/usr/local/lib/python3.9/tarfile.py", line 690, in read
                  raise ReadError("unexpected end of data")
              tarfile.ReadError: unexpected end of data

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Dataset Card

This is the fine-tuning dataset used in the paper RDT-1B: a Diffusion Foundation Model for Bimanual Manipulation.

Source

Uses

Download all archive files and use the following command to extract:

cat rdt_data.tar.gz.* | tar -xzvf -

In the resulting rdt_data folder, each sub-folder is a task. In each task sub-folder, we have HDF5 files and the instruction JSON file, as illustrated below:

rdt_data/---task_1/---episode_1.hdf5
          |         |
          |-task_2/ |-episode_2.hdf5
          |         |
          |-task_3/ |-...
          |         |
          |-...     |-expanded_instruction_gpt-4-turbo.json

Each HDF5 file corresponds to a trajectory/episode of the task, which has the following keys:

  • observations:
    • qpos: joint positions of the two robot arms, (TRAJ_LEN, 14); the seventh and fourteenth joints are gripper joint angles
    • images:
      • cam_high: RGB images from the exterior camera at each time step, (TRAJ_LEN, 480, 640, 3)
      • cam_left_wrist: RGB images from the left-wrist camera at each time step, (TRAJ_LEN, 480, 640, 3)
      • cam_right_wrist: RGB images from the right-wrist camera at each time step, (TRAJ_LEN, 480, 640, 3)
  • action: desired joint positions of the two robot arms at the next time step, (TRAJ_LEN, 14); Note that this is slightly different from the actual joint positions at the next time step

Note: The number in episode_<NUMBER>.hdf5 is not necessarily consecutive. TRAJ_LEN may vary from episode to episode.

Each JSON file corresponds to the annotated language instructions of the task, which has the following keys:

  • instruction: original human-annotated instructions; its value is a string
  • expanded_instruction: instructions generated by GPT-4-Turbo by expanding the original one; its value is a list of strings
  • simplified_instruction: instructions generated by GPT-4-Turbo by simplifying the original one; its value is a list of strings

Citation

If you find our work helpful, please cite us:

@article{liu2024rdt,
  title={RDT-1B: a Diffusion Foundation Model for Bimanual Manipulation},
  author={Liu, Songming and Wu, Lingxuan and Li, Bangguo and Tan, Hengkai and Chen, Huayu and Wang, Zhengyi and Xu, Ke and Su, Hang and Zhu, Jun},
  journal={arXiv preprint arXiv:2410.07864},
  year={2024}
}

Thank you!

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