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Tao Toolkit

Tao Toolkit - Home

Tao Toolkit

Table of Contents

Introduction

  • Overview
  • TAO Launcher
  • Migration Guides
    • Migrating to TAO 5.5
    • Migrating from TAO 4.0.x to TAO 5.0.0
    • Migrating from TAO 3.x to TAO 4.0
    • Migrating from Legacy TLT to TAO
    • Migrating to the TAO API from TAO 5.3.0
  • Working With the Containers

Getting Started

  • Getting Started
  • Beginners
  • Intermediate Users
  • Advanced Users

Model Zoo

  • Overview

Running TAO in the Cloud

  • Running TAO in the Cloud
  • Running TAO on an AWS VM
  • Running TAO on Google Cloud Platform
  • Running TAO on an Azure VM
  • Running TAO on Google Colab
  • Running TAO on an EKS
  • Running TAO on an AKS

TAO API

  • Overview
  • Setup
  • Deployment
  • Train, Adapt, Optimize (TAO) REST API
  • Remote Client
  • API Reference

AutoML

  • AutoML

CV Fine-tuning

  • Optimizing the Training Pipeline
  • Visualizing Training
  • Data Annotation Format
  • Computer Vision Finetuning
    • PyTorch
      • Metric Learning Recognition
        • Metric Learning Recognition
      • Instance Segmentation
        • Data Input for Instance Segmentation
        • mask2former
        • Mask Auto Labeler
        • Mask Grounding DINO
      • CenterPose
        • CenterPose
      • Character Recognition
        • OCRNet
      • VisualChangeNet
        • Visual ChangeNet-Segmentation
        • Visual ChangeNet-Classification
      • 3D Object Detection
        • PointPillars
      • ReIdentificationNet Transformer
        • ReIdentificationNet Transformer
      • Optical Inspection
        • SiameseOI
      • Pose Classification
        • PoseClassificationNet
      • Object Detection
        • Grounding DINO
        • DINO
        • OCDNet
        • Deformable DETR
      • ReIdentificationNet
        • ReIdentificationNet
      • ActionRecognitionNet
      • BEVFusion
      • Image Classification PyT
      • SegFormer
    • TensorFlow 2.x
      • Image Classification (TF2)
      • EfficientDet (TF2)
    • TensorFlow 1.x [Deprecated]
      • Body Pose Estimation
        • Body Pose Estimation
      • Character Recognition
        • LPRNet
      • Emotion Classification
      • Facial Landmarks Estimation
        • Facial Landmarks Estimation
      • Gaze Estimation
      • Gesture Recognition
      • HeartRate Estimation
      • Instance Segmentation
        • Data Input for Instance Segmentation
        • MaskRCNN
      • Image Classification (TF1)
      • Multitask Image Classification
      • Object Detection
        • DetectNet_v2
        • FasterRCNN
        • YOLOv3
        • YOLOv4
        • YOLOv4-tiny
        • SSD
        • DSSD
        • RetinaNet
        • EfficientDet (TF1)
      • Semantic Segmentation
        • UNET
  • Foundation Models

MLOPS integration

  • TAO MLOPS Integration
  • TAO WandB Integration
  • TAO Clearml Integration

Deploying to Inference SDKs

  • Integrating TAO CV Models with Triton Inference Server
  • TAO Converter
    • TAO Converter with Classification TF1/TF2
    • TAO Converter with Deformable DETR
    • TAO Converter with Detectnet_v2
    • TAO Converter with DSSD
    • TAO Converter with EfficientDet
    • TAO Converter with FasterRCNN
    • TAO Converter with MaskRCNN
    • TAO Converter with Multitask Classification
    • TAO Converter with Retinanet
    • TAO Converter with SSD
    • TAO Converter with UNET
    • TAO Converter with YOLOv3
    • TAO Converter with YOLOv4
    • TAO Converter with YOLOv4-tiny
  • Optimizing and Profiling with TensorRT
    • TRTEXEC with ActionRecognitionNet
    • TRTEXEC with BodyPoseNet
    • TRTEXEC with CenterPose
    • TRTEXEC with Classification TF1/TF2/PyT
    • TRTEXEC with Deformable-DETR
    • TRTEXEC with DetectNet-v2
    • TRTEXEC with DINO
    • TRTEXEC with DSSD
    • TRTEXEC with EfficientDet TF1/TF2
    • TRTEXEC with Facial Landmarks Estimation
    • TRTEXEC with Faster RCNN
    • TRTEXEC with Grounding DINO
    • TRTEXEC with LPRNet
    • TRTEXEC with Metric Learning Recognition
    • TRTEXEC with Mask RCNN
    • TRTEXEC with Multitask Classification
    • TRTEXEC with OCDNet
    • TRTEXEC with OCRNet
    • TRTEXEC with PointPillars
    • TRTEXEC with PoseClassificationNet
    • TRTEXEC with ReIdentificationNet
    • TRTEXEC with ReIdentificationNet Transformer
    • TRTEXEC with RetinaNet
    • TRTEXEC with Segformer
    • TRTEXEC with SiameseOI
    • TRTEXEC with SSD
    • TRTEXEC with UNet
    • TRTEXEC with YOLO_v3
    • TRTEXEC with YOLO_v4
    • TRTEXEC with YOLO_v4_tiny
    • TRTEXEC with VisualChangeNet
    • TRTEXEC with Mask2former
    • TRTEXEC with Mask Grounding DINO
  • Integrating TAO Models into DeepStream
    • Deploying to DeepStream for Classification TF1/TF2/PyTorch
    • Deploying to DeepStream for Multitask Classification
    • Deploying to DeepStream for DetectNet_v2
    • Deploying to DeepStream for Deformable DETR
    • Deploying to DeepStream for DINO
    • Deploying to DeepStream for DSSD
    • Deploying to DeepStream for EfficientDet
    • Deploying to DeepStream for FasterRCNN
    • Deploying to DeepStream for RetinaNet
    • Deploying to DeepStream for SSD
    • Deploying to DeepStream for YOLOv3
    • Deploying to DeepStream for YOLOv4
    • Deploying to DeepStream for YOLOv4-tiny
    • Deploying to DeepStream for MaskRCNN
    • Deploying to Deepstream for UNet
    • Deploying to Deepstream for Segformer
    • Deploying nvOCDR to DeepStream

Deploying with TAO Deploy

  • TAO Deploy Overview
  • TAO Deploy Installation
  • CenterPose with TAO Deploy
  • Classification (PyTorch) with TAO Deploy
  • Classification (TF1) with TAO Deploy
  • Classification (TF2) with TAO Deploy
  • Deformable DETR with TAO Deploy
  • DINO with TAO Deploy
  • Grounding DINO with TAO Deploy
  • DetectNet_v2 with TAO Deploy
  • DSSD with TAO Deploy
  • EfficientDet (TF1) with TAO Deploy
  • EfficientDet (TF2) with TAO Deploy
  • Faster RCNN with TAO Deploy
  • LPRNet with TAO Deploy
  • Mask RCNN with TAO Deploy
  • Mask2former with TAO Deploy
  • MLRecogNet with TAO Deploy
  • Multitask Image Classification with TAO Deploy
  • OCDNet with TAO Deploy
  • RetinaNet with TAO Deploy
  • SSD with TAO Deploy
  • Segformer with TAO Deploy
  • UNet with TAO Deploy
  • YOLOv3 with TAO Deploy
  • YOLOv4 with TAO Deploy
  • YOLOv4-tiny with TAO Deploy
  • OCRNet with TAO Deploy
  • SiameseOI with TAO Deploy
  • VisualChangeNet-Classification with TAO Deploy
  • VisualChangeNet-Segmentation with TAO Deploy
  • Mask Grounding DINO with TAO Deploy

Bring Your Own Model (BYOM)

  • Bring Your Own Model (BYOM)
    • BYOM Converter
    • BYOM Image Classification

Data Services

  • Annotations
  • Offline Data Augmentation
  • Auto-Label
  • Data Analytics

More Information

  • Release Notes
  • Frequently Asked Questions
  • Troubleshooting Guide
  • Tutorial Videos
    • Getting started with NVIDIA TAO
    • Create Custom Multi-Modal Fusion Models
    • Use Visual Prompt for In-Context Segmentation with NVIDIA TAO
    • Estimate and Track Object Poses with the NVIDIA TAO FoundationPose Model
    • Open Vocabulary Object Detection with NVIDIA Grounding-DINO
    • Use Text Prompts for Auto-Labeling with NVIDIA TAO
    • Visualize Model Training with TensorBoard
  • Support Information
  • Acknowledgements
  • Tutorial Videos

Tutorial Videos#

TAO Toolkit provides the following tutorial videos to cover popular use cases:

  • Getting started with NVIDIA TAO
  • Create Custom Multi-Modal Fusion Models
  • Use Visual Prompt for In-Context Segmentation with NVIDIA TAO
  • Estimate and Track Object Poses with the NVIDIA TAO FoundationPose Model
  • Open Vocabulary Object Detection with NVIDIA Grounding-DINO
  • Use Text Prompts for Auto-Labeling with NVIDIA TAO
  • Visualize Model Training with TensorBoard

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Getting started with NVIDIA TAO
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Last updated on Jun 25, 2025.