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Machine Learning with Core ML

You're reading from   Machine Learning with Core ML An iOS developer's guide to implementing machine learning in mobile apps

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Product type Paperback
Published in Jun 2018
Publisher Packt
ISBN-13 9781788838290
Length 378 pages
Edition 1st Edition
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Author (1):
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Joshua Newnham Joshua Newnham
Author Profile Icon Joshua Newnham
Joshua Newnham
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Toc

Table of Contents (12) Chapters Close

Preface 1. Introduction to Machine Learning FREE CHAPTER 2. Introduction to Apple Core ML 3. Recognizing Objects in the World 4. Emotion Detection with CNNs 5. Locating Objects in the World 6. Creating Art with Style Transfer 7. Assisted Drawing with CNNs 8. Assisted Drawing with RNNs 9. Object Segmentation Using CNNs 10. An Introduction to Create ML 11. Other Books You May Enjoy

Performing inference 

This may come as a bit of an anticlimax for someone expecting some hardcore coding, but its simplicity definitely pays tribute to the effort of Apple's engineers in making this framework one of the most accessible ways to work with a ML model. Without further ado, let's put the final pieces together; we start by instantiating an instance of our model we had imported in the previous section.

Near the top, but within the body of the ViewController class, add the following line:

let model = Inceptionv3()

Our model is now ready; we return to the onFrameCaptured method, starting from where we previously left off, and add the following code snippet:

let prediction = try? self.model.prediction(image:scaledPixelBuffer)

// Update label
DispatchQueue.main.sync {
classifiedLabel.text = prediction?.classLabel ?? "Unknown"
}

In case you...

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