Hugging Face's logo

Datasets:
chrisvoncsefalvay
/
openembodiment-dvrk-subset

ArXiv:
License:
Dataset card Files
xet
 Community
Dataset Viewer
Duplicate
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:    CastError
Message:      Couldn't cast
action_dim: int64
exclude_reason: string
fps: double
image_keys: list<item: string>
  child 0, item: string
include: bool
robot_type: string
root: string
state_dim: int64
tasks: list<item: null>
  child 0, item: null
total_episodes: int64
total_frames: int64
metadata: string
to
{'metadata': Value('string')}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
                  return get_rows(
                         ^^^^^^^^^
                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 77, in get_rows
                  rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
                                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2815, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2352, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2377, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.12/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/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 310, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 130, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2369, in table_cast
                  return cast_table_to_schema(table, schema)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              action_dim: int64
              exclude_reason: string
              fps: double
              image_keys: list<item: string>
                child 0, item: string
              include: bool
              robot_type: string
              root: string
              state_dim: int64
              tasks: list<item: null>
                child 0, item: null
              total_episodes: int64
              total_frames: int64
              metadata: string
              to
              {'metadata': Value('string')}
              because column names don't match

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.

Open-H dVRK convenience subset

This dataset is a convenience subset of nvidia/PhysicalAI-Robotics-Open-H-Embodiment, curated for dVRK/da Vinci surgical robotics experiments and staged so training runs can stream from one place instead of rehydrating the upstream corpus file-by-file.

The NVIDIA dataset is the canonical source: a CC-BY-4.0, LeRobot v2.1 corpus of paired healthcare robotics video and kinematics, with video stored as MP4 and kinematics stored as Parquet. All substantive credit for the source data belongs with NVIDIA and the Open-H Embodiment contributors. Please cite and review the upstream dataset card, licence and terms before using this snapshot. This repository exists to make reproducible dVRK-domain Cosmos post-training less theatrical.

Media and tensors are stored under data/openh_snapshot/; manifests and snapshot metadata are under metadata/.

Intended use

  • Domain-specific post-training of action-conditioned video models.
  • dVRK action-space validation and short-horizon surgical world-model research.
  • Streaming/restart-friendly training on ephemeral GPU instances.

This snapshot is not a clinical dataset release, a new annotation layer or a replacement for the upstream Open-H Embodiment corpus.

Streaming the manifest 

from datasets import load_dataset

repo_id = "chrisvoncsefalvay/openembodiment-dvrk-subset"
manifest = load_dataset(
    "json",
    data_files=f"hf://datasets/{repo_id}/metadata/openh_dvrk_manifest.train.jsonl",
    split="train",
    streaming=True,
)
first = next(iter(manifest))

Rehydrating the curated snapshot 

from huggingface_hub import snapshot_download

local_dir = snapshot_download(
    repo_id="chrisvoncsefalvay/openembodiment-dvrk-subset",
    repo_type="dataset",
    allow_patterns=["data/openh_snapshot/**", "metadata/**"],
)

The upload path uses Hugging Face Hub Xet storage when available, so resumed uploads/downloads avoid the upstream API-rate-limit bottleneck.

Citation

If you use this convenience subset, cite both this dataset repository and the upstream Open-H Embodiment source corpus. This subset mirrors selected dVRK/da Vinci roots from nvidia/PhysicalAI-Robotics-Open-H-Embodiment; all source data credit remains with Open-H and the original contributors.

@misc{voncsefalvay2026openembodimentdvrksubset,
  title = {Open-H dVRK convenience subset},
  author = {von Csefalvay, Chris},
  year = {2026},
  publisher = {Hugging Face},
  url = {https://huggingface.co/datasets/chrisvoncsefalvay/openembodiment-dvrk-subset},
  note = {Convenience dVRK/da Vinci subset of nvidia/PhysicalAI-Robotics-Open-H-Embodiment}
}

@misc{nvidia2026physicalairoboticsopenh,
  title = {PhysicalAI-Robotics-Open-H-Embodiment},
  author = {{NVIDIA Corporation} and {Open-H Embodiment community}},
  year = {2026},
  publisher = {Hugging Face},
  url = {https://huggingface.co/datasets/nvidia/PhysicalAI-Robotics-Open-H-Embodiment},
  note = {CC-BY-4.0 Open-H Embodiment LeRobot v2.1 source corpus}
}

@misc{openh2026medicalrobotics,
  title = {Open-H-Embodiment: A Large-Scale Dataset for Enabling Foundation Models in Medical Robotics},
  author = {{Open-H-Embodiment Consortium}},
  year = {2026},
  eprint = {2604.21017},
  archivePrefix = {arXiv},
  primaryClass = {cs.RO},
  url = {https://arxiv.org/abs/2604.21017}
}
Downloads last month
4,332
Total file size:
98.4 GB

Models trained or fine-tuned on chrisvoncsefalvay/openembodiment-dvrk-subset

Paper for chrisvoncsefalvay/openembodiment-dvrk-subset