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real-stanford
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universal_manipulation_interface

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The dataset viewer is not available for this split.
Cannot extract the features (columns) for the split 'train' of the config 'default' of the dataset.
Error code:   FeaturesError
Exception:    UnicodeDecodeError
Message:      'utf-8' codec can't decode byte 0xff in position 0: invalid start byte
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 244, in compute_first_rows_from_streaming_response
                  iterable_dataset = iterable_dataset._resolve_features()
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 4523, in _resolve_features
                  features = _infer_features_from_batch(self.with_format(None)._head())
                                                        ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2768, in _head
                  return next(iter(self.iter(batch_size=n)))
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2972, in iter
                  for key, pa_table in ex_iterable.iter_arrow():
                                       ~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2483, in _iter_arrow
                  yield from self.ex_iterable._iter_arrow()
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 547, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 430, 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/text/text.py", line 98, in _generate_tables
                  batch = f.read(self.config.chunksize)
                File "/usr/local/lib/python3.14/site-packages/datasets/utils/file_utils.py", line 839, in read_with_retries
                  out = read(*args, **kwargs)
                File "<frozen codecs>", line 325, in decode
              UnicodeDecodeError: 'utf-8' codec can't decode byte 0xff in position 0: invalid start byte

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UMI (Universal Manipulation Interface) data

Demonstration data of UMI, collected by the authors: the raw GoPro recordings and the UMI SLAM pipeline session workspaces of the paper's tasks, plus the processed zarr datasets. Deduplicated: the authors' *_mp4s.zip packagings and the colleague-made transcodes are not repeated (see Layout).

Layout

<task>/<name>.zarr.zip: the processed UMI replay buffer of each task, the format the UMI training code reads (data/camera0_rgb 224x224 JPEG-XL frames, data/robot0_eef_pos, data/robot0_eef_rot_axis_angle, data/robot0_gripper_width, meta/episode_ends; the bimanual tasks also carry camera1_* / robot1_*). cup_in_the_wild.zarr.zip is the file published at https://real.stanford.edu/umi/data/zarr_datasets/. cup_in_the_wild/mp4s/<location>/, cup_in_lab/mp4s/<date>/, dynamic_tossing/mp4s/<date>/: the raw GoPro recordings (demo_*.mp4, mapping*.mp4, gripper_calibration_*.mp4), i.e. the raw_videos/ input of the UMI SLAM pipeline. bimanual_cloth_folding/sessions/<session>/ and bimanual_dish_washing/sessions/<session>/: the UMI SLAM pipeline workspace of each bimanual recording session: demos/<demo>/ with raw_video.mp4, imu_data.json, tag_detection.pkl, slam_mask.png, camera_trajectory.csv (when SLAM succeeded) and the stage logs, demos/mapping*/ with map_atlas.osa and tx_slam_tag.json, demos/gripper_calibration_*/ with gripper_range.json, calibration/ (some sessions) and dataset_plan.pkl. The pipeline's raw_videos/ directory is omitted: it held only symlinks to demos/*/raw_video.mp4. bimanual_cloth_folding/open_source_slam_reruns/<session>_480/: the SLAM re-runs of sessions 20231228_cheng and 20231228_zhenjia made for the open-source release (same videos, omitted here; different camera_trajectory.csv, map_atlas.osa, dataset_plan.pkl). The authors' open-source packagings bimanual_cloth_folding_mp4s.zip (sessions 20231228_cheng + 20240103_zhenjia) and bimanual_dish_washing_mp4s.zip (session 20240109_zhenjia) were byte copies of those sessions' demos/*/raw_video.mp4 and are not repeated. Every zarr store is one *.zarr.zip: an uncompressed zip of the store's files, readable in place with zarr.open(zarr.storage.ZipStore(path, mode="r")) or unpacked with unzip -d <name>.zarr <name>.zarr.zip.

Contents

path files GB
bimanual_cloth_folding 1 14.71
bimanual_cloth_folding/open_source_slam_reruns 2225 1.08
bimanual_cloth_folding/sessions 11164 185.84
bimanual_dish_washing 1 22.84
bimanual_dish_washing/sessions 9591 218.99
cup_in_lab 1 4.49
cup_in_lab/mp4s 350 30.23
cup_in_the_wild 1 17.99
cup_in_the_wild/mp4s 2932 221.43
dynamic_tossing 1 8.78
dynamic_tossing/mp4s 298 47.39
total 26565 773.8

License

MIT, the license of the project's GitHub repository (https://github.com/real-stanford/universal_manipulation_interface).
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