Search icon CANCEL
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
Intelligent Mobile Projects with TensorFlow

You're reading from   Intelligent Mobile Projects with TensorFlow Build 10+ Artificial Intelligence apps using TensorFlow Mobile and Lite for iOS, Android, and Raspberry Pi

Arrow left icon
Product type Paperback
Published in May 2018
Publisher Packt
ISBN-13 9781788834544
Length 404 pages
Edition 1st Edition
Languages
Tools
Arrow right icon
Author (1):
Arrow left icon
Jeff Tang Jeff Tang
Author Profile Icon Jeff Tang
Jeff Tang
Arrow right icon
View More author details
Toc

Table of Contents (14) Chapters Close

Preface 1. Getting Started with Mobile TensorFlow FREE CHAPTER 2. Classifying Images with Transfer Learning 3. Detecting Objects and Their Locations 4. Transforming Pictures with Amazing Art Styles 5. Understanding Simple Speech Commands 6. Describing Images in Natural Language 7. Recognizing Drawing with CNN and LSTM 8. Predicting Stock Price with RNN 9. Generating and Enhancing Images with GAN 10. Building an AlphaZero-like Mobile Game App 11. Using TensorFlow Lite and Core ML on Mobile 12. Developing TensorFlow Apps on Raspberry Pi 13. Other Books You May Enjoy

Running the TensorFlow and Keras models on iOS

We won't bore you by repeating the project setup step - just follow what we did before to create a new Objective-C project named StockPrice that will use the manually built TensorFlow library (see the iOS section of Chapter 7, Recognizing Drawing with CNN and LSTM, if you need detailed info). Then add the two amzn_tf_frozen.pb and amzn_keras_frozen.pb model files to the project and you should have your StockPrice project in Xcode, as in Figure 8.3:

Figure 8.3 iOS app using the TensorFlow- and Keras-trained models in Xcode

In ViewController.mm, we'll first declare some variables and one constant:

unique_ptr<tensorflow::Session> tf_session;
UITextView *_tv;
UIButton *_btn;
NSMutableArray *_closeprices;
const int SEQ_LEN = 20;

Then create a button-tap handler to let the user choose either the TensorFlow or Keras model ...

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 €18.99/month. Cancel anytime