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Generative Adversarial Networks Projects

You're reading from   Generative Adversarial Networks Projects Build next-generation generative models using TensorFlow and Keras

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Product type Paperback
Published in Jan 2019
Publisher Packt
ISBN-13 9781789136678
Length 316 pages
Edition 1st Edition
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Author (1):
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Kailash Ahirwar Kailash Ahirwar
Author Profile Icon Kailash Ahirwar
Kailash Ahirwar
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Table of Contents (11) Chapters Close

Preface 1. Introduction to Generative Adversarial Networks 2. 3D-GAN - Generating Shapes Using GANs FREE CHAPTER 3. Face Aging Using Conditional GAN 4. Generating Anime Characters Using DCGANs 5. Using SRGANs to Generate Photo-Realistic Images 6. StackGAN - Text to Photo-Realistic Image Synthesis 7. CycleGAN - Turn Paintings into Photos 8. Conditional GAN - Image-to-Image Translation Using Conditional Adversarial Networks 9. Predicting the Future of GANs 10. Other Books You May Enjoy

Preparing the data

In this chapter, we will be working with the Facades dataset, which is available at the following link:

http://efrosgans.eecs.berkeley.edu/pix2pix/datasets/facades.tar.gz.

This dataset contains facade labels and ground truth facade images. A facade is generally the front side of a building, and facade labels are architectural labels of a facade image. We will learn more about facades after we download the dataset. Perform the following commands to download and extract the dataset:

  1. Download the dataset by executing the following commands:
# Before downloading the dataset navigate to data directory
cd data

# Download the dataset
wget http://efrosgans.eecs.berkeley.edu/pix2pix/datasets/facades.tar.gz
  1. After downloading the dataset, extract the dataset using the following command:
tar -xvzf facades.tar.gz

The file structure of the downloaded dataset is as follows...

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