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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 drawing classification model in iOS

To fix the previous RefSwitch error, which will occur no matter whether you use the TensorFlow Pod as we did in Chapter 2, Classifying Images with Transfer Learning, and Chapter 6, Describing Images in Natural Language, or the manually built TensorFlow library, as in the other chapters, we have to use some new trick. The error occurs because the INT64 data type is required for a RefSwitch operation, but it's not one of the registered data types built into the TensorFlow library because, by default, to make the library as small as possible, only common data types for each operation are included. We may fix this from the model building end in Python, but here we'll just show you how to fix this from the iOS end, which can be useful when you don't have access to the source code to build a model.

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