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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 image captioning model in iOS

As the CNN part of the model is based on Inception v3, the same model we used in Chapter 2, Classifying Images with Transfer Learning, we can and will use the simpler TensorFlow pod to create our Objective-C iOS app. Follow the steps here to see how to use both the image2text_frozen_transformed.pb and image2text_frozen_transformed_memmapped.pb model files in a new iOS app:

  1. Similar to the first four steps in Chapter 2, Classifying Images with Transfer Learning, in the Adding TensorFlow to your Objective-C iOS app section, create a new iOS project named Image2Text, add a new file named Podfile with the following content:
target 'Image2Text'
pod 'TensorFlow-experimental'

Then run pod install on a Terminal and open the Image2Text.xcworkspace file. Drag and drop ios_image_load.h, ios_image_load.mm, tensorflow_utils...

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