Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Swift Cookbook

You're reading from   Swift Cookbook Over 60 proven recipes for developing better iOS applications with Swift 5.3

Arrow left icon
Product type Paperback
Published in Feb 2021
Publisher Packt
ISBN-13 9781839211195
Length 500 pages
Edition 2nd Edition
Languages
Tools
Arrow right icon
Authors (3):
Arrow left icon
Chris Barker Chris Barker
Author Profile Icon Chris Barker
Chris Barker
Keith D. Moon Keith D. Moon
Author Profile Icon Keith D. Moon
Keith D. Moon
Keith Moon Keith Moon
Author Profile Icon Keith Moon
Keith Moon
Arrow right icon
View More author details
Toc

Table of Contents (14) Chapters Close

Preface 1. Swift Building Blocks 2. Mastering the Building Blocks FREE CHAPTER 3. Data Wrangling with Swift Control Flow 4. Generics, Operators, and Nested Types 5. Beyond the Standard Library 6. Building iOS Apps with Swift 7. Swift Playgrounds 8. Server-Side Swift 9. Performance and Responsiveness in Swift 10. SwiftUI and Combine Framework 11. Using CoreML and Vision in Swift 12. About Packt 13. Other Books You May Enjoy

Using CoreML models to detect objects in images

In this recipe, we'll take the app we just built and incorporate the CoreML framework in order to detect objects in our images.

We'll also take a look at the generated CoreML models available for us to use and download directly from Apple's Developer portal.

Getting ready

For this recipe, you'll need the latest version of Xcode available from the Mac App Store.

Next, head on over to the Apple Developer portal at the following address: https://developer.apple.com/machine-learning/models/.

Here, you will find out a little bit more about the models available for us to download and use in our Xcode project.

You'll notice there are options for image models and text models. For this recipe, we're going to be using image models, specifically one called Resnet50, which uses a residual neural network that attempts to identify and classify what it perceives to be the dominant object in an image.

For more information...
lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime
Banner background image