Need step by step instructions for TAO


my env is a jetson xavier with 5 ip cameras streaming via rtsp. A graph made by graph compser is running on the jetson with a people, car and traffic sign detectionmodel. So far it is working.

My goal is to increase the people detection by using TAO. I want to use use an amazon ec2 g3 instance, therefor is an howto description in the nvidia quick start. But here I am quite irritated in going forward.

Pleasre give me simple step by step instructions, how to use TAO.

Which data (pictures or videos) do I have to prepare for upload into TAO?

Is TAO usage guided, so that I will follow a line of bread crumbs to the final result?

What should I have in mind when generating a custom model for my jetson with the graph using five different video scenes in live mode?


You can refer to yolov4_tiny network, YOLOv4-tiny - NVIDIA Docs

Quick start : TAO Toolkit Quick Start Guide - NVIDIA Docs
Notebook: TAO Toolkit Quick Start Guide - NVIDIA Docs

Thank you!
Please let me ask some further questions:
I have collected several jpeg pictures from the cameras, triggerd by motion detection. On each picture are one or more objects (persons and or animals).

  1. Is the next task to group the pictures in folders (person and animal)?
  2. How do I group the pictures, that inherit both types of objects?
    Please take care of my “simple” type of question:
  3. Do I have to manually create a label file for each image?


Which kind of task are you going to train, classification or object-detection or segmentation?

Good question! :-)
On the one hand, I want to classify animals (i.e. dogs).
On the other hand detecting objects (people and animals).

So, i have to build a classifcation of dogs at first?

For classification task, yes, it is needed to split the training dataset into different folders.
One folder for one class. You can download classification notebook for reference.

Can you please give me an appropriate url? Much thanks!

Notebook: TAO Toolkit Quick Start Guide - NVIDIA Docs

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