Object Detection Workshop

Red Hat OpenShift Data Science Logo


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 and TensorFlow to explore a pre-trained object detection model

  • Serve the model in a REST API as a Flask App

  • Use source-to-image (s2i) to build and deploy the Flask App

  • Explore Kafka streams from notebooks

  • Deploy a Kafka consumer with the same object detection model

And all of this without having to install anything on your own computer, thanks to Red Hat OpenShift Data Science on the Developer Sandbox for Red Hat OpenShift and Red Hat OpenShift Streams for Apache Kafka.

What is Red Hat OpenShift Data Science?

Red Hat OpenShift Data Science is a managed service that provides a complete data science platform on Red Hat OpenShift. It includes Jupyter Notebooks, JupyterLab, and a variety of data science libraries and frameworks. It also includes a catalog of pre-built models and templates to help you get started quickly.

Red Hat OpenShift Data Science Notebook


Firstly, provision and login to your Developer Sandbox for Red Hat OpenShift. Here, you’ll find a pre-installed instance of Red Hat OpenShift Data Science, and will be able to follow along with the workshop.

Video Guide

Feel free to check out the blog post that accompanies this workshop: Build and deploy an object detection model using OpenShift Data Science. 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.