Object Detection Workshop with Red Hat OpenShift AI
Introduction
Welcome!
In this workshop, you’ll learn an easy way to incorporate data science and AI/ML into an OpenShift development workflow. As an example, you’ll use an object detection model in several different ways.
You will:
-
use Jupyter Notebooks to explore a pre-trained object detection model,
-
deploy the model using OpenShift AI model serving,
-
integrate the model into a real-time object detection app,
-
run offline scoring object detection pipelines,
-
refine and train the model,
-
and finally update the object detection app using the trained model.
And all of this without having to install anything on your own computer, thanks to Red Hat OpenShift AI.
Environment
If you haven’t already got an instance of Red Hat OpenShift AI, find out more on the developer page. There, you can spin up your own account on the free OpenShift AI Sandbox or learn about installing on your own OpenShift cluster.
Videos
If you’d like to follow along with the accompanying videos of this workshop, you can find them in the article on the Red Hat Developer website or watch on YouTube
Start!
If you’re ready, let’s start!