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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

Retraining using the Inception v3 model

In the TensorFlow source that we set up in the previous chapter, there's a Python script, tensorflow/examples/image_retraining/retrain.py, that you can use to retrain the Inception v3 or MobileNet models. Before we run the script to retrain the Inception v3 model for our dog breed recognition, we need to first download the Stanford Dogs Dataset (http://vision.stanford.edu/aditya86/ImageNetDogs), which contains images of 120 dog breeds (you only need to download the Images in the link, not the Annotations).

Untar the downloaded dog images.tar file in ~/Downloads, and you should see a list of folders in ~/Downloads/Images, as shown in the following screenshot. Each folder corresponds to one dog breed and contains about 150 images (you don't need to supply explicit labels for images as the folder names are used to label the images...

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