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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

Image recognition and text to speech

There are two TensorFlow Raspberry Pi example apps (https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/pi_examples) located in tensorflow/contrib/pi_examples: label_image and camera. We'll modify the camera example app to integrate text to speech so the app can speak out its recognized images when moving around. Before we build and test the two apps, we need to install some libraries and download the prebuilt TensorFlow Inception model file:

sudo apt-get install -y libjpeg-dev
sudo apt-get install libv4l-dev

curl https://storage.googleapis.com/download.tensorflow.org/models/inception_dec_2015_stripped.zip -o /tmp/inception_dec_2015_stripped.zip

cd ~/tensorflow-1.6.0
unzip /tmp/inception_dec_2015_stripped.zip -d tensorflow/contrib/pi_examples/label_image/data/

To build the label_image and camera apps, run:

make -f tensorflow...
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