Practical Artificial Intelligence with Swift

Chapter 4. Vision

This chapter explores the practical side of implementing vision-related artificial intelligence (AI) features in your Swift apps. Taking a top-down approach, we explore seven vision tasks, and how to implement them by using Swift and various AI tools.

Practical AI and Vision

Here are the seven practical AI tasks related to vision that we explore in this chapter:

Face detection

This uses image analysis techniques to count faces in an image and perform various actions with that information, such as applying other images on top of the face, with the correct rotation.

Barcode detection

This uses Apple’s frameworks to find barcodes in images.

Saliency detection

This task finds the most salient area of an image using Apple’s frameworks.

Image similarity

How similar are two images? We build an app that lets the user pick two images and determine how similar they are.

Image classification

Classification is a classic AI problem. We build a classification app than can tell us what we’ve taken a photo of.

Drawing recognition

Recognition is basically classification, no matter what you’re classifying, but in the interest of exploring a breadth of practical AI topics with you, here we build an app that lets you take a photo of a line-drawing and identify the drawing.

Style classification

We update our Image Classification app to support identifying the style of a supplied image by converting a model built with another set of tools into Apple’s CoreML format. ...