AI Agent Skills

Machine Learning Containers for NVIDIA Jetson and JetPack-L4T

Use when measuring Jetson Video Codec SDK or PyNvVideoCodec encode/decode throughput, comparing presets or surfaces, testing codec-worker capacity with authenti

Use when Jetson codec, profile, chroma, bit-depth, dimension, engine-count, or operational support must be reconciled using live SDK APIs, authenticated NVIDIA

Use when executing and verifying Jetson Video Codec SDK or PyNvVideoCodec encode/decode, transcode, segmentation, container decode, AV1, or acceptance workflows

Use when turning a Jetson encoder use case into one validated surface-neutral recipe with native and PyNvVideoCodec projections for codec, preset, rate control,

Use when installing, repairing, probing, or verifying native NVIDIA Video Codec SDK or PyNvVideoCodec on Jetson with official encode-to-decode samples, includin

NVIDIA-accelerated 3D scene reconstruction and Nav2 local costmap provider using nvblox

Deep learned, NVIDIA-accelerated 3D object pose estimation

NVIDIA-accelerated packages for arm motion planning and control

NVIDIA Isaac Transport for ROS package for hardware-acceleration friendly movement of messages

Hello AI World guide to deploying deep-learning inference networks and deep vision primitives with TensorRT and NVIDIA Jetson.

NVIDIA-accelerated, deep learned model support for image space object detection

NVIDIA-accelerated Apriltag detection and pose estimation.

GPU-ready Dockerfile to run Stability.AI stable-diffusion model v2 with a simple web interface. Includes multi-GPUs support.

Run agents like Hermes and OpenClaw more securely inside NVIDIA OpenShell with managed inference

PyTorch/TorchScript/FX compiler for NVIDIA GPUs using TensorRT