DevOps &amp; Cloud

NVDINOv2 for self-supervised visual representation learning. Trains vision transformers via self-distillation

tao-train-pointpillars

PointPillars for 3D object detection from LiDAR point clouds. Encodes point clouds into a pseudo-image via a

tao-train-depth-anything-v2

Monocular depth estimation using Metric Depth Anything v2 or Relative Depth Anything architectures. Predicts

tao-train-centerpose

CenterPose for keypoint / pose estimation. Detects object centers and regresses keypoint locations for 6-DoF

tao-train-bevfusion

BEVFusion for multi-sensor 3D object detection. Fuses LiDAR point clouds and camera images in bird's-eye-view

tao-train-ocdnet

OCDNet for scene text detection. Detects arbitrary-oriented text regions in natural images using a

tao-train-oneformer

OneFormer for universal image segmentation. Unifies panoptic, instance, and semantic segmentation with a

tao-train-segformer

SegFormer for semantic segmentation. Lightweight transformer-based architecture with hierarchical feature

tao-train-foundation-stereo

Stereo depth estimation using FoundationStereo. Predicts disparity maps from stereo image pairs for 3D

tao-train-deformable-detr

Deformable DETR for 2D object detection. Uses deformable attention for efficient multi-scale feature processing,

tao-train-fast-foundation-stereo

Real-time stereo depth estimation using FastFoundationStereo (FFS), the distilled bp2 commercial variant of

cloud

Create cloud provider architecture diagrams using PlantUML syntax with official AWS, Azure, GCP, and Alibaba Cloud service icons. Best for multi-service cloud topologies and migration blueprints.

network

Create network topology diagrams using PlantUML syntax with mxgraph device icons (Cisco, Citrix, etc.). Best for LAN/WAN layouts, datacenter interconnects, and physical/logical network design.

uml

Create UML diagrams using PlantUML syntax. Best for software modeling — Class, Sequence, Activity, State Machine, Component, Use Case, and Deployment diagrams with concise text-based notation and auto-layout.

architecture

Create layered system architecture diagrams using HTML/CSS templates with color-coded tiers and grid layouts. Best for technology stacks, microservices topology, and multi-tier application design.

tao-run-automl

Run AutoML / hyperparameter optimization (HPO) for NVIDIA TAO networks using AutoMLRunner. Handles algorithm

tao-train-image-classification

PyTorch-based TAO image classification. Supports a wide range of backbones (FAN, EfficientNet, ResNet, etc.)

tao-train-ocrnet

OCRNet for scene text recognition. Recognizes text content from cropped text-region images and supports CTC

tao-train-optical-inspection

Optical Inspection for defect detection using Siamese networks. Compares image pairs to detect manufacturing

Host setup for TAO GPU backends. Checks and, after user approval, installs NVIDIA driver branch 580, CUDA Toolkit 13.0, and NVIDIA Container Toolkit 1.19.0 for Docker/local-Docker and Kubernetes GPU worker hosts. The `--check-only` path works on any Linux distribution; `--install` automates debian-family (Ubuntu/Debian/Pop!_OS/Mint/Zorin/Raspbian), rhel-family (Fedora/RHEL/Rocky/AlmaLinux), and suse-family (openSUSE/SLES) hosts, and prints actionable manual-install steps for everything else. Use when the user asks to "set up an NVIDIA GPU host", "check TAO Docker GPU runtime", or prepare a Kubernetes GPU worker for TAO.