tao▌

Cosmos3-Nano video QA supervised fine-tuning with FSDP parallelism. Use when training or evaluating video

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

Pose classification using ST-GCN (Spatial Temporal Graph Convolutional Network). Classifies skeleton sequences

Sparse4D for multi-camera temporal 3D object detection and tracking. Uses sparse queries with deformable

Run `tao-daft validate` to check NVIDIA TAO DAFT datasets for structure, schema, and cross-reference errors. Do

Standard single-step train/eval/export workflow for any TAO model. Use when training a TAO model on a dataset

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

Visual ChangeNet for binary image classification and segmentation in AOI defect detection. Use when training,

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

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