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Mastering iOS 14 Programming

You're reading from   Mastering iOS 14 Programming Build professional-grade iOS 14 applications with Swift 5.3 and Xcode 12.4

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Product type Paperback
Published in Mar 2021
Publisher Packt
ISBN-13 9781838822842
Length 558 pages
Edition 4th Edition
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Authors (3):
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Mario Eguiluz Alebicto Mario Eguiluz Alebicto
Author Profile Icon Mario Eguiluz Alebicto
Mario Eguiluz Alebicto
Chris Barker Chris Barker
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Chris Barker
Donny Wals Donny Wals
Author Profile Icon Donny Wals
Donny Wals
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Toc

Table of Contents (22) Chapters Close

Preface 1. Chapter 1: What's New in iOS 14? 2. Chapter 2: Working with Dark Mode FREE CHAPTER 3. Chapter 3: Using Lists and Tables 4. Chapter 4: Creating a Detail Page 5. Chapter 5: Immersing Your Users with Animation 6. Chapter 6: Understanding the Swift Type System 7. Chapter 7: Flexible Code with Protocols, Generics, and Extensions 8. Chapter 8: Adding Core Data to Your App 9. Chapter 9: Fetching and Displaying Data from the Network 10. Chapter 10: Making Smarter Apps with Core ML 11. Chapter 11: Adding Media to Your App 12. Chapter 12: Improving Apps with Location Services 13. Chapter 13: Working with the Combine Framework 14. Chapter 14: Creating an App Clip for Your App 15. Chapter 15: Recognition with Vision Framework 16. Chapter 16: Creating Your First Widget 17. Chapter 17: Using Augmented Reality 18. Chapter 18: Creating a macOS app with Catalyst 19. Chapter 19: Ensuring App Quality with Tests 20. Chapter 20: Submitting Your App to the App Store 21. Other Books You May Enjoy

Summary

We started this chapter by learning about the basic building blocks of every Vision feature: how to use a VNRequest instance, its corresponding VNRequestHandler instances, and the resulting VNObservation instances.

After learning the basics, we applied them to text recognition. We compared different recognition levels by using .fast and .accurate. We also learned about regions of interest and how they can affect the performance of Vision requests. Finally, we improved our results in text recognition by applying domain knowledge, fixing potential errors and misreads from Vision.

Finally, we learned about the new hand landmarks recognition capability. But this time, we also learned how to apply Vision requests to real-time video streams. We were able to detect hand landmarks in a video feed from a device's front camera and display an overlay to show the results. This chapter also provided a similar example that could be applied to body pose recognition.

In the...

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