Practical Simulations for Machine Learning

Chapter 13. Creating More Advanced Synthesized Data

In this chapter, we’ll return to synthesis and build upon the introduction to synthesizing data using Unity’s Perception that we worked through back in Chapter 3.

Specifically, we’ll use randomizers to add a random element to the images generated from our dice, and learn how to explore the data we’re synthesizing, making use of the labels we added earlier.

Adding Random Elements to the Scene

To generate useful synthetic data, we need to add random elements to the scene. The random elements we’re going to add are:

• A random floor color

• A random camera position

By randomly changing the color of the floor and the position of the camera, we’ll be able to generate a variety of random images of dice, which can then be used to train an image recognition system outside of Unity to recognize dice in a huge range of situations.

We’re going to be working with the same project we ended up with way back at the end of Chapter 3, so either duplicate it or re-create it from scratch before continuing. We duplicated it and renamed it “SimpleDiceWithRandomizers.”

Tip

Don’t forget that it needs to be a 3D URP project, which is different from the projects you’ve been making throughout Part II for simulations. Refer back to “Creating the Unity Project” if you need a reminder.

Randomizing the Floor Color

To randomize the floor color, we first need a randomizer. To add a randomizer, open the Unity scene and do the following:

1. Find the Scenario ...