Nvidia Skills

skills/skills/tao-train-depth-anything-v2

Monocular depth estimation using Metric Depth Anything v2 or Relative Depth Anything architectures. Predicts per-pixel depth from single RGB images. Use when…

skills/skills/tao-train-dino

DINO (DETR with Improved DeNoising Anchor Boxes) for 2D object detection. Transformer-based detector with denoising training, multi-scale features, and…

skills/skills/tao-train-fast-foundation-stereo

Real-time stereo depth estimation using FastFoundationStereo (FFS), the distilled bp2 commercial variant of FoundationStereo. Predicts disparity maps from…

skills/skills/tao-train-foundation-stereo

Stereo depth estimation using FoundationStereo. Predicts disparity maps from stereo image pairs for 3D reconstruction. Use when training, evaluating,…

skills/skills/tao-train-grounding-dino

Grounding DINO for open-set object detection. Combines DINO-style detection with a BERT text encoder for language-guided detection — detects objects described…

skills/skills/tao-train-image-classification

PyTorch-based TAO image classification. Supports a wide range of backbones (FAN, EfficientNet, ResNet, etc.) with distillation and quantization for deployment.…

skills/skills/tao-train-mask-auto-encoder

Masked Auto-Encoder (MAE) for self-supervised pretraining and fine-tuning. Masks random patches and reconstructs them to learn visual representations; supports…

skills/skills/tao-train-mask-auto-label

MAL (Mask Auto-Label) for weakly-supervised segmentation. Produces segmentation masks from minimal annotations (point or box annotations) using a ViT-MAE…

skills/skills/tao-train-mask-grounding-dino

Mask Grounding DINO for grounded instance segmentation. Extends Grounding DINO with a mask-prediction head for open-set segmentation guided by text prompts.…

skills/skills/tao-train-mask2former

Mask2Former for universal image segmentation (panoptic, instance, and semantic). Transformer-based with masked attention for high-quality segmentation results.…

skills/skills/tao-train-metric-learning-recognition

Metric-learning recognition (ml-recog) for fine-grained visual recognition. Learns embeddings for retrieval-based matching (e.g., retail product recognition)…

skills/skills/tao-train-nvdinov2

NVDINOv2 for self-supervised visual representation learning. Trains vision transformers via self-distillation (teacher-student) without labels and produces…

skills/skills/tao-train-nvpanoptix3d

NVPanoptix3D for panoptic 3D scene reconstruction from posed RGB images. Produces 3D panoptic segmentation (semantic, instance, and panoptic masks) with…

skills/skills/tao-train-ocdnet

OCDNet for scene text detection. Detects arbitrary-oriented text regions in natural images using a differentiable binarization approach. Use when training,…

skills/skills/tao-train-ocrnet

OCRNet for scene text recognition. Recognizes text content from cropped text-region images and supports CTC and attention-based decoders. Use when training,…

skills/skills/tao-train-oneformer

OneFormer for universal image segmentation. Unifies panoptic, instance, and semantic segmentation with a single architecture using task-conditioned queries.…

skills/skills/tao-train-optical-inspection

Optical Inspection for defect detection using Siamese networks. Compares image pairs to detect manufacturing defects, anomalies, or quality issues. Use when…

skills/skills/tao-train-pointpillars

PointPillars for 3D object detection from LiDAR point clouds. Encodes point clouds into a pseudo-image via a pillar-based representation, then applies 2D…

skills/skills/tao-train-pose-classification

Pose classification using ST-GCN (Spatial Temporal Graph Convolutional Network). Classifies skeleton sequences into action categories from pose-keypoint data.…

skills/skills/tao-train-reid

Person re-identification (ReID). Learns discriminative embeddings to match the same person across different camera views, based on metric learning. Use when…

skills/skills/tao-train-rtdetr

RT-DETR (Real-Time DEtection TRansformer) for 2D object detection. Designed for real-time inference with competitive accuracy and supports distillation and…

skills/skills/tao-train-segformer

SegFormer for semantic segmentation. Lightweight transformer-based architecture with hierarchical feature extraction, efficient for real-time segmentation…

skills/skills/tao-train-single-step

Standard single-step train/eval/export workflow for any TAO model. Use when training a TAO model on a dataset without iterative data augmentation, AutoML, or…

skills/skills/tao-train-sparse4d

Sparse4D for multi-camera temporal 3D object detection and tracking. Uses sparse queries with deformable attention across camera views and time for end-to-end…

skills/skills/tao-train-visual-changenet

Visual ChangeNet for binary image classification and segmentation in AOI defect detection. Use when training, evaluating, exporting, or running inference for…

skills/skills/tao-validate-dataset-format

Run `tao-daft validate` to check NVIDIA TAO DAFT datasets for structure, schema, and cross-reference errors. Do not use for non-DAFT formats. Use when the user…

skillspector/skills/terraform-deployer

Deploy infrastructure using Terraform

nemo-relay/.agents/skills/test-ffi-surface

Build and test the NeMo Relay FFI surface; use this for crates/ffi changes, header generation, or ABI-facing validation

nemo-relay/.agents/skills/test-go-binding

Build and test the NeMo Relay Go binding; use this for go/nemo_relay changes or Go-facing integration checks

nemo-relay/.agents/skills/test-node-binding

Build and test the NeMo Relay Node.js binding; use this for crates/node changes or Node-facing integration checks