Build an Image Segmentation Deep Learning Model with Python from Unreal Engine 5 Generated Images

Learn how to snag the most in demand role in the tech field today!

Train a neural network in Google Colaboratory! Use images procedurally generated in Unreal Engine 5.


Do you want to build machine learning models? Sign up for this course. You’ll learn the fundamentals of Python, the #1 language for machine learning, data science and artificial intelligence.


You’ll use images generated by the Unreal game engine to train a segmentation neural network. Start your AI journey today and boost your career prospects!

  • Code in Python
  • Clean data for machine learning
  • Build a neural network model
  • Use Unreal images for machine learning



Procedural generation can be used to create randomized versions of data. This is useful for when you need to generate large datasets quickly.

In this project, we use Unreal blueprints to generate 3D scenes in the Unreal Engine. The generated 3D scenes include grass, rocks and bushes in varying positions. We used blueprints to enabled a segmented view of the scene, where different objects like grass, a rock, a bush are painted in a unique colour.

The purpose is to have a realistic 3D scene and a segmented 3D scene, so that we can train a neural network to take a 3D scene and create a segmented 3D scene. Image segmentation is one type of computer vision, used for object detection, image recognition and more. We use another blueprint to take screenshots of the scene and its segmented version. This is the basis of the dataset we are creating. We can move around in the scene and capture many screenshots of a 3D world from multiple angles.

The power of scripting allows us to generate tons of image data that mimics the real world. The result is a dataset of images of a 3D world. We build a supervised neural network and train the model on the image data. The model learns how to take an image of a 3D world and generate a segmented version of that image.

Your Instructor


Alexandra Kropf
Alexandra Kropf

Alexandra Kropf is Mammoth Interactive's CLO and a software developer with extensive experience in full-stack web development, app development and game development. She has helped produce courses for Mammoth Interactive since 2016, including the Coding Interview series in Java, JavaScript, C++, C#, Python and Swift.

Mammoth Interactive is a leading online course provider in everything from learning to code to becoming a YouTube star. Mammoth Interactive courses have been featured on Harvard’s edX, Business Insider and more.

Over 12 years, Mammoth Interactive has built a global student community with 4 million courses sold. Mammoth Interactive has released over 350 courses and 3,500 hours of video content.

Founder and CEO John Bura has been programming since 1997 and teaching since 2002. John has created top-selling applications for iOS, Xbox and more. John also runs SaaS company Devonian Apps, building efficiency-minded software for technology workers like you.


Course Curriculum


  Course Overview
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  Deep Learning Introduction
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