Datasets:

bx6d
/

r2s2r-data

Tasks:

Robotics

Tags:

License:

Dataset card Data Studio Files Files and versions

xet

Community

Dataset Preview

Duplicate

Split (2)

train

The full dataset viewer is not available (click to read why). Only showing a preview of the rows.

The dataset generation failed

Error code:   DatasetGenerationError
Exception:    TypeError
Message:      int() argument must be a string, a bytes-like object or a real number, not 'NoneType'
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1531, in _prepare_split_single
                  for key, record in generator:
                                     ^^^^^^^^^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 613, in wrapped
                  for item in generator(*args, **kwargs):
                              ~~~~~~~~~^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 127, in _generate_examples
                  for example_idx, example in enumerate(self._get_pipeline_from_tar(tar_path, tar_iterator)):
                                              ~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 32, in _get_pipeline_from_tar
                  for filename, f in tar_iterator:
                                     ^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/utils/track.py", line 49, in __iter__
                  for x in self.generator(*self.args):
                           ~~~~~~~~~~~~~~^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/utils/file_utils.py", line 1405, in _iter_from_urlpath
                  with xopen(urlpath, "rb", download_config=download_config, block_size=0) as f:
                       ~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/utils/file_utils.py", line 982, in xopen
                  file_obj = fs.open(paths[0], mode)
                File "<string>", line 3, in open
                File "/usr/local/lib/python3.14/unittest/mock.py", line 1176, in __call__
                  return self._mock_call(*args, **kwargs)
                         ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/unittest/mock.py", line 1180, in _mock_call
                  return self._execute_mock_call(*args, **kwargs)
                         ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/unittest/mock.py", line 1247, in _execute_mock_call
                  result = effect(*args, **kwargs)
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 786, in wrapped
                  tracker.files[urlpath] = {"read": 0, "size": int(f.size)}
                                                               ~~~^^^^^^^^
              TypeError: int() argument must be a string, a bytes-like object or a real number, not 'NoneType'
              
              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 1393, 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 1571, 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

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

stl unknown	__key__ string	__url__ string
null	train300_lerobot_rgb256_v1/meta/tasks	hf://datasets/bx6d/r2s2r-data@37ec686e340cca80e64cb7b561c36e088829ff57/r2s2r-train300-lerobot.tar.zst
null	train300_lerobot_rgb256_v1/meta/stats	hf://datasets/bx6d/r2s2r-data@37ec686e340cca80e64cb7b561c36e088829ff57/r2s2r-train300-lerobot.tar.zst
null	train300_lerobot_rgb256_v1/meta/episodes/chunk-000/file-000	hf://datasets/bx6d/r2s2r-data@37ec686e340cca80e64cb7b561c36e088829ff57/r2s2r-train300-lerobot.tar.zst
null	train300_lerobot_rgb256_v1/meta/info	hf://datasets/bx6d/r2s2r-data@37ec686e340cca80e64cb7b561c36e088829ff57/r2s2r-train300-lerobot.tar.zst
null	train300_lerobot_rgb256_v1/r2s2r_stage3_merge	hf://datasets/bx6d/r2s2r-data@37ec686e340cca80e64cb7b561c36e088829ff57/r2s2r-train300-lerobot.tar.zst
null	train300_lerobot_rgb256_v1/data/chunk-000/file-019	hf://datasets/bx6d/r2s2r-data@37ec686e340cca80e64cb7b561c36e088829ff57/r2s2r-train300-lerobot.tar.zst
null	train300_lerobot_rgb256_v1/data/chunk-000/file-014	hf://datasets/bx6d/r2s2r-data@37ec686e340cca80e64cb7b561c36e088829ff57/r2s2r-train300-lerobot.tar.zst
null	train300_lerobot_rgb256_v1/data/chunk-000/file-016	hf://datasets/bx6d/r2s2r-data@37ec686e340cca80e64cb7b561c36e088829ff57/r2s2r-train300-lerobot.tar.zst
null	train300_lerobot_rgb256_v1/data/chunk-000/file-005	hf://datasets/bx6d/r2s2r-data@37ec686e340cca80e64cb7b561c36e088829ff57/r2s2r-train300-lerobot.tar.zst
null	train300_lerobot_rgb256_v1/data/chunk-000/file-010	hf://datasets/bx6d/r2s2r-data@37ec686e340cca80e64cb7b561c36e088829ff57/r2s2r-train300-lerobot.tar.zst
null	train300_lerobot_rgb256_v1/data/chunk-000/file-023	hf://datasets/bx6d/r2s2r-data@37ec686e340cca80e64cb7b561c36e088829ff57/r2s2r-train300-lerobot.tar.zst
null	train300_lerobot_rgb256_v1/data/chunk-000/file-000	hf://datasets/bx6d/r2s2r-data@37ec686e340cca80e64cb7b561c36e088829ff57/r2s2r-train300-lerobot.tar.zst
null	train300_lerobot_rgb256_v1/data/chunk-000/file-007	hf://datasets/bx6d/r2s2r-data@37ec686e340cca80e64cb7b561c36e088829ff57/r2s2r-train300-lerobot.tar.zst
null	train300_lerobot_rgb256_v1/data/chunk-000/file-022	hf://datasets/bx6d/r2s2r-data@37ec686e340cca80e64cb7b561c36e088829ff57/r2s2r-train300-lerobot.tar.zst
null	train300_lerobot_rgb256_v1/data/chunk-000/file-020	hf://datasets/bx6d/r2s2r-data@37ec686e340cca80e64cb7b561c36e088829ff57/r2s2r-train300-lerobot.tar.zst
null	train300_lerobot_rgb256_v1/data/chunk-000/file-006	hf://datasets/bx6d/r2s2r-data@37ec686e340cca80e64cb7b561c36e088829ff57/r2s2r-train300-lerobot.tar.zst
null	train300_lerobot_rgb256_v1/data/chunk-000/file-003	hf://datasets/bx6d/r2s2r-data@37ec686e340cca80e64cb7b561c36e088829ff57/r2s2r-train300-lerobot.tar.zst
null	train300_lerobot_rgb256_v1/data/chunk-000/file-018	hf://datasets/bx6d/r2s2r-data@37ec686e340cca80e64cb7b561c36e088829ff57/r2s2r-train300-lerobot.tar.zst
null	train300_lerobot_rgb256_v1/data/chunk-000/file-009	hf://datasets/bx6d/r2s2r-data@37ec686e340cca80e64cb7b561c36e088829ff57/r2s2r-train300-lerobot.tar.zst
null	train300_lerobot_rgb256_v1/data/chunk-000/file-017	hf://datasets/bx6d/r2s2r-data@37ec686e340cca80e64cb7b561c36e088829ff57/r2s2r-train300-lerobot.tar.zst
null	train300_lerobot_rgb256_v1/data/chunk-000/file-004	hf://datasets/bx6d/r2s2r-data@37ec686e340cca80e64cb7b561c36e088829ff57/r2s2r-train300-lerobot.tar.zst
null	train300_lerobot_rgb256_v1/data/chunk-000/file-002	hf://datasets/bx6d/r2s2r-data@37ec686e340cca80e64cb7b561c36e088829ff57/r2s2r-train300-lerobot.tar.zst
null	train300_lerobot_rgb256_v1/data/chunk-000/file-012	hf://datasets/bx6d/r2s2r-data@37ec686e340cca80e64cb7b561c36e088829ff57/r2s2r-train300-lerobot.tar.zst
null	train300_lerobot_rgb256_v1/data/chunk-000/file-001	hf://datasets/bx6d/r2s2r-data@37ec686e340cca80e64cb7b561c36e088829ff57/r2s2r-train300-lerobot.tar.zst
null	train300_lerobot_rgb256_v1/data/chunk-000/file-013	hf://datasets/bx6d/r2s2r-data@37ec686e340cca80e64cb7b561c36e088829ff57/r2s2r-train300-lerobot.tar.zst
null	train300_lerobot_rgb256_v1/data/chunk-000/file-008	hf://datasets/bx6d/r2s2r-data@37ec686e340cca80e64cb7b561c36e088829ff57/r2s2r-train300-lerobot.tar.zst
null	train300_lerobot_rgb256_v1/data/chunk-000/file-021	hf://datasets/bx6d/r2s2r-data@37ec686e340cca80e64cb7b561c36e088829ff57/r2s2r-train300-lerobot.tar.zst
null	train300_lerobot_rgb256_v1/data/chunk-000/file-015	hf://datasets/bx6d/r2s2r-data@37ec686e340cca80e64cb7b561c36e088829ff57/r2s2r-train300-lerobot.tar.zst
null	train300_lerobot_rgb256_v1/data/chunk-000/file-011	hf://datasets/bx6d/r2s2r-data@37ec686e340cca80e64cb7b561c36e088829ff57/r2s2r-train300-lerobot.tar.zst

YAML Metadata Warning:The task_categories "imitation-learning" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, audio-text-to-text, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-ranking, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, image-text-to-image, image-text-to-video, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, visual-document-retrieval, any-to-any, video-to-video, other

R2S2R data

This repository preserves the focused data needed to train and evaluate the R2S2R (Scan-to-Sim-to-Real) project:

r2s2r-train300-lerobot.tar.zst: 300 qualified MuJoCo demonstration episodes exported in LeRobot v3 format (100,456 frames, 30 tasks, 20 Hz).
r2s2r-frozen-evaluation.tar.zst: frozen Seen-150 and Unseen-150 manifests and their evaluation packages. Evaluation packages intentionally contain no demonstration trajectories.
r2s2r-original-scans-v1.tar.zst: seven original Scaniverse GLB inputs and their provenance/hash manifest.
SHA256SUMS: archive integrity hashes.

The training observations contain two 256x256 RGB cameras and a seven-element xArm6-plus-gripper state. Actions contain six arm joints plus the gripper. Privileged MuJoCo state, contact, predicate, and object-pose fields were excluded from the policy dataset.

Source project

The code, generation recipes, scene specifications, frozen task definitions, and reproducibility documentation are maintained in the R2S2R source repository. These archives preserve data; they are not a standalone executable environment.

Extraction

sha256sum -c SHA256SUMS
tar --zstd -xf r2s2r-original-scans-v1.tar.zst
tar --zstd -xf r2s2r-train300-lerobot.tar.zst
tar --zstd -xf r2s2r-frozen-evaluation.tar.zst

Licensing and provenance

No single blanket license is asserted for the complete collection. The evaluation packages carry their component license and provenance records, and the scan archive carries the original-scan identity and SHA-256 manifest. Consumers must preserve and follow those embedded terms and verify that their use and redistribution of scan-derived material is authorized.

Downloads last month: 34

Total file size:

3.51 GB