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Generative Adversarial Networks Projects

You're reading from  Generative Adversarial Networks Projects

Product type Book
Published in Jan 2019
Publisher Packt
ISBN-13 9781789136678
Pages 316 pages
Edition 1st Edition
Languages
Concepts
Author (1):
Kailash Ahirwar Kailash Ahirwar
Profile icon Kailash Ahirwar
LinkedIn
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.
See other products by Kailash Ahirwar

Table of Contents (11) Chapters

Preface 1. Introduction to Generative Adversarial Networks 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

Downloading the dataset

In this chapter, we will be working with the monet2photo dataset. This dataset is open source and is made available by the Berkeley AI Research (BAIR) laboratory, UC Berkeley. You can choose to download the dataset manually from the following link: https://people.eecs.berkeley.edu/~taesung_park/CycleGAN/datasets/monet2photo.zip.

After downloading it, unzip it in the root directory.

Alternatively, to automatically download the dataset, execute the following commands:

wget https://people.eecs.berkeley.edu/~taesung_park/CycleGAN/datasets/monet2photo.zip
upzip monet2photo.zip

These commands will download the dataset and unzip it in the project's root directory.

The monet2photo dataset is available for educational purposes only. To use it in commercial projects, you have to get permission from the BAIR laboratory, UC Berkeley. We don't hold the copyright...
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Authors (1)

Profile icon Kailash Ahirwar
LinkedIn
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.
See other products by Kailash Ahirwar

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