AI and Machine Learning for Coders

Chapter 14. Using TensorFlow Lite in iOS Apps

Chapter 12 introduced you to TensorFlow Lite and how you can use it to convert your TensorFlow models into a power-efficient, compact format that can be used on mobile devices. In Chapter 13 you then explored creating Android apps that use TensorFlow Lite models. In this chapter you’ll do the same thing but with iOS, creating a couple of simple apps, and seeing how you can do inference on a TensorFlow Lite model using the Swift programming language.

You’ll need a Mac if you want to follow along with the examples in this chapter, as the development tool to use is Xcode, which is only available on Mac. If you don’t have it already, you can install it from the App Store. It will give you everything you need, including an iOS Simulator on which you can run iPhone and iPod apps without a physical device.

Creating Your First TensorFlow Lite App with Xcode

Once you have Xcode up and running, you can follow the steps outlined in this section to create a simple iOS app that incorporates the Y = 2X – 1 model from Chapter 12. While it’s an extremely simple scenario, and definite overkill for a machine learning app, the skeleton structure is the same as that used for more complex apps, and I’ve found it a useful way of demonstrating how to use models in an app.

Step 1. Create a Basic iOS App

Open Xcode and select File → New Project. You’ll be asked to pick the template for your new project. Choose Single View App, which is the simplest template ...