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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

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Product type Paperback
Published in May 2018
Publisher Packt
ISBN-13 9781788834544
Length 404 pages
Edition 1st Edition
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Author (1):
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Jeff Tang Jeff Tang
Author Profile Icon Jeff Tang
Jeff Tang
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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

Using the GAN models in Android

It turns out we don't need to use the custom TensorFlow Android library, as we did in Chapter 7, Recognizing Drawing with CNN and LSTM, to run the GAN models in Android. Simply create a new Android Studio app called GAN with all the defaults, add compile 'org.tensorflow:tensorflow-android:+' to the app's build.gradle file, create a new assets folder and copy the two GAN model files and a test blurry image there.

Your project in Android Studio should now look like Figure 9.5:

Figure 9.5: Android Studio GAN app overview, showing constant definitions

Notice that for simplicity, we set BATCH_SIZE to 1. You can easily set it to any number and get that many outputs back as we did in iOS. Other than the constants defined in Figure 9.5, we'll create a few instance variables:

private Button mButtonMNIST;
private Button mButtonPix2Pix...
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