Book Image

Generative AI with Python and TensorFlow 2

By : Joseph Babcock, Raghav Bali
4 (1)
Book Image

Generative AI with Python and TensorFlow 2

4 (1)
By: Joseph Babcock, Raghav Bali

Overview of this book

Machines are excelling at creative human skills such as painting, writing, and composing music. Could you be more creative than generative AI? In this book, you’ll explore the evolution of generative models, from restricted Boltzmann machines and deep belief networks to VAEs and GANs. You’ll learn how to implement models yourself in TensorFlow and get to grips with the latest research on deep neural networks. There’s been an explosion in potential use cases for generative models. You’ll look at Open AI’s news generator, deepfakes, and training deep learning agents to navigate a simulated environment. Recreate the code that’s under the hood and uncover surprising links between text, image, and music generation.
Table of Contents (16 chapters)
14
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15
Index

Style transfer and image transformation

In addition to mapping artificial images to a space of random numbers, we can also use generative models to learn a mapping between one kind of image and a second. This kind of model can, for example, be used to convert an image of a horse into that of a zebra (Figure 1.7), create deep fake videos in which one actor's face has been replaced with another's, or transform a photo into a painting (Figures 1.2 and 1.4):21

Figure 1.7: CycleGANs apply stripes to horses to generate zebras22

Another fascinating example of applying generative modeling is a study in which lost masterpieces of the artist Pablo Picasso were discovered to have been painted over with another image. After X-ray imaging of The Old Guitarist and The Crouching Beggar indicated that earlier images of a woman and a landscape lay underneath (Figure 1.8), researchers used the other paintings from Picasso's blue period or other color photographs (Figure...