Book Image

Mastering iOS 14 Programming - Fourth Edition

By : Mario Eguiluz Alebicto, Chris Barker, Donny Wals
Book Image

Mastering iOS 14 Programming - Fourth Edition

By: Mario Eguiluz Alebicto, Chris Barker, Donny Wals

Overview of this book

Mastering iOS 14 development isn’t a straightforward task, but this book can help you do just that. With the help of Swift 5.3, you’ll not only learn how to program for iOS 14 but also be able to write efficient, readable, and maintainable Swift code that reflects industry best practices. This updated fourth edition of the iOS 14 book will help you to build apps and get to grips with real-world app development flow. You’ll find detailed background information and practical examples that will help you get hands-on with using iOS 14's new features. The book also contains examples that highlight the language changes in Swift 5.3. As you advance through the chapters, you'll see how to apply Dark Mode to your app, understand lists and tables, and use animations effectively. You’ll then create your code using generics, protocols, and extensions and focus on using Core Data, before progressing to perform network calls and update your storage and UI with the help of sample projects. Toward the end, you'll make your apps smarter using machine learning, streamline the flow of your code with the Combine framework, and amaze users by using Vision framework and ARKit 4.0 features. By the end of this iOS development book, you’ll be able to build apps that harness advanced techniques and make the best use of iOS 14’s features.
Table of Contents (22 chapters)

Recognizing text in images

The Vision framework has been improving its detection of text in images since its first iteration. In this section, we are going to learn some state-of-the-art techniques to obtain the best results on iOS 14.

We saw in the previous section that text detection in Vision can happen in two different ways, as defined by the value of recognitionLevel that we specify in the request: .fast and .accurate. Let's see the differences:

  • Fast recognition: This uses character recognition to detect text character by character within a bounding box. It is optimized for real-time recognition and uses a smaller memory footprint than .accurate. It doesn't handle rotated text or different fonts as well as the .accurate method.
  • Accurate recognition: This uses a neural network to detect strings and full lines, and then recognizes the words and sentences. By using a neural network and identifying words, the framework can detect or correct observations for...