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

Product type Paperback

Published in Jan 2019

Publisher Packt

ISBN-13 9781789136678

Length 316 pages

Edition 1st Edition

Languages

Python

Tools

Keras

Concepts

Deep Learning

Author (1):

Kailash Ahirwar

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Table of Contents (11) Chapters

Preface

1. Introduction to Generative Adversarial Networks FREE CHAPTER

2. 3D-GAN - Generating Shapes Using GANs

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

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Downloading the CelebA dataset

For this chapter, we will use the large-scale CelebFaces Attributes (CelebA) dataset, which is available at http://mmlab.ie.cuhk.edu.hk/projects/CelebA.html. The dataset contains 202, 599 face images of celebrities.

The dataset is available for non-commercial research purposes only and can't be used for commercial purposes. If you intend to use the dataset for commercial purposes, seek permissions from the owners of the images.

We will use the CelebA dataset to train our SRGAN network. Perform the following steps to download and extract the dataset:

Download the dataset from the following link:

https://www.dropbox.com/sh/8oqt9vytwxb3s4r/AAB06FXaQRUNtjW9ntaoPGvCa?dl=0

Extract images from the downloaded img_align_celeba.zip by executing the following command:

unzip img_align_celeba.zip

We have now downloaded and extracted the dataset. We can...

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Authors (1)

Ahirwar

Kailash Ahirwar is a machine learning and deep learning enthusiast. He has worked in many areas of Artificial Intelligence (AI), ranging from natural language processing and computer vision to generative modeling using GANs. He is a co-founder and CTO of Mate Labs. He uses GANs to build different models, such as turning paintings into photos and controlling deep image synthesis with texture patches. He is super optimistic about AGI and believes that AI is going to be the workhorse of human evolution.

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