You're reading from Generative Adversarial Networks Projects

Product typeBook

Published inJan 2019

Reading LevelIntermediate

PublisherPackt

ISBN-139781789136678

Edition1st Edition

Languages

Python

Tools

TensorFlow Keras

Concepts

Deep Learning

Author (1)

Kailash Ahirwar

Preparing the data

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

ht tp://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:

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

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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Generative Adversarial Networks Projects

Published in: Jan 2019Publisher: PacktISBN-13: 9781789136678

Author (1)

Kailash 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.
Read more about Kailash Ahirwar

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Author (1)

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