GR00T-X-Embodiment-Sim

# GR00T-X-Embodiment-Sim → FiftyOne (Native Multimodal MCAP)  A 42-episode subset of [nvidia/PhysicalAI-Robotics-GR00T-X-Embodiment-Sim](https://huggingface.co/datasets/nvidia/PhysicalAI-Robotics-GR00T-X-Embodiment-Sim), six episodes from each of seven embodiments, converted to native multimodal MCAP episodes. Each episode carries the camera streams as H.264 `foxglove.CompressedVideo`, per-part robot state and action telemetry with timeline plot channels, and the task instruction. ## Installation ```bash pip install fiftyone ``` ## Usage ```python import fiftyone as fo import fiftyone.utils.huggingface as fouh dataset = fouh.load_from_hub( "Voxel51/GR00T-X-Embodiment-Sim", name="GR00T-X-Embodiment-Sim", persistent=True, ) fo.launch_app(dataset) ``` ## What you get - 42 `.mcap` episodes across `single_panda_gripper`, `bimanual_panda_gripper`, `bimanual_panda_hand`, `gr1_arms_waist`, `gr1_full_upper_body`, `sim_behavior_r1_pro`, and `unitree_g1` - Telemetry segmented into named channels per the source `modality.json` (for example `/joint-position-state`, `/end-effector-position-absolute-state`, `/gripper-qpos-action`), each with a timeline plot channel - Per-episode fields: `embodiment`, `task`, `source_task`, `episode_index`, `num_frames`, `duration` - Camera streams transmuxed from the source H.264 without re-encoding ## License & attribution The source dataset is released by NVIDIA under [CC-BY-4.0](https://creativecommons.org/licenses/by/4.0/); this subset is distributed under the same license. Changes from the source: episode subsetting and conversion from LeRobot parquet/mp4 format to MCAP.