Nurec Skills

Use to drive NVIDIA Omniverse NuRec / Neural Reconstruction Engine (NRE) via the public NGC containers nvcr.io/nvidia/nre/nre and nvcr.io/nvidia/nre/nre-tools (NGC_API_KEY required) — train 3DGUT Gaussian reconstructions from NCore clips, generate aux data, adapt an existing USDZ to an augmented target-vehicle rig (carline adaptation), render frames or LiDAR sweeps (local or warm `serve-grpc`), export PLY/depth/mesh/USDZ, edit actors, and evaluate metrics. Do NOT use for per-object asset capture (use `asset-harvester`) or sensor-to-NCore conversion (use `ncore`).

Use when converting any sensor dataset into NVIDIA NCore V4 format (and feeding it to NuRec or a robotics-to-sim "r2s" pipeline). Covers ingesting raw cameras, LiDARs, radars, IMUs, depth or stereo into V4 sequences; authoring a new converter from the template; adapting PAI / Waymo / PandaSet / NuScenes to V4; handling non-AV rigs (mono+depth, mono+lidar, stereo, multi-stereo, RGB-D, COLMAP / SfM, ROS2 bag); and diagnosing a broken converter against `validate.py`. Do NOT use to train reconstructions (use `nre`) or to extract per-object 3D assets (use `asset-harvester`). Trigger keywords: ncore, ncore v4, convert, ingest, zarr, itar, nurec, waymo, pandaset, nuscenes, pai, hyperion, colmap, scannetpp, stereo, multi-stereo, mono+depth, mono+lidar, kitti, sfm, camera, lidar, radar, imu, cuboid, poses, intrinsics, ego mask, ros2, rosbag, mcap, realsense, zed, rgb-d, r2s, robotics, sam2.

Use to run NVIDIA DiffusionHarmonizer (public successor to the older Fixer recipes) to enhance, harmonize, evaluate, or fine-tune novel-view frames from NRE / NuRec / 3DGS / NeRF reconstructions. Do NOT use for training the 3D reconstruction itself (use `nre`) or for sensor-to-NCore conversion (use `ncore`).

Router for NVIDIA NuRec / NRE / 3DGUT / USDZ / NCore V4 / asset harvest / frame cleanup tasks — picks the right sibling (nre, ncore, asset-harvester, nurec-fixer, physical-ai-datasets). Use when the sub-skill is unclear or a multi-stage pipeline is needed; do NOT use for non-NuRec tasks or to run any pipeline itself.

Use to install and run NVIDIA Asset Harvester (Apache-2.0) to extract per-object 3D Gaussian Splat assets (`gaussians.ply`) from AV NCore V4 clips or masked single images via SparseViewDiT + TokenGS, optionally producing `metadata.yaml` for NuRec object insertion. Do NOT use for full-scene reconstruction (use `nre`) or for inputs without per-object masks.

Use when the user wants to find, download, or pick a NVIDIA Physical AI dataset on Hugging Face for autonomous-vehicle, robotics, spatial intelligence, manipulation, or neural-reconstruction workflows. Catalog of every dataset under huggingface.co/nvidia with the `PhysicalAI-` prefix, organised by domain (AV, Robotics-Manipulation, Robotics-GR00T, Robotics-mindmap, Robotics-NuRec, Spatial Intelligence, Grasping, Healthcare, Sim-Ready, Material properties), with per-dataset size, format, gating, license, and the downstream sibling skill (`ncore`, `nre`, `asset-harvester`, `nurec-fixer`) or upstream tool (Isaac Sim, CARLA, Isaac-GR00T, Cosmos-*) that consumes it. Do NOT use as a runtime — it routes you elsewhere. Trigger keywords: nvidia physical ai dataset, PhysicalAI- dataset, hf nvidia dataset, NCore dataset, NuRec dataset, GR00T dataset, GraspGen, SimReady, Cosmos-Drive-Dreams, Lyra SDG, Open-H-Embodiment, huggingface-cli download, physical_ai_av, dataset gated, RDS-HQ.