Book Image

Exploring Deepfakes

By : Bryan Lyon, Matt Tora
Book Image

Exploring Deepfakes

By: Bryan Lyon, Matt Tora

Overview of this book

Applying Deepfakes will allow you to tackle a wide range of scenarios creatively. Learning from experienced authors will help you to intuitively understand what is going on inside the model. You’ll learn what deepfakes are and what makes them different from other machine learning techniques, and understand the entire process from beginning to end, from finding faces to preparing them, training the model, and performing the final swap. We’ll discuss various uses for face replacement before we begin building our own pipeline. Spending some extra time thinking about how you collect your input data can make a huge difference to the quality of the final video. We look at the importance of this data and guide you with simple concepts to understand what your data needs to really be successful. No discussion of deepfakes can avoid discussing the controversial, unethical uses for which the technology initially became known. We’ll go over some potential issues, and talk about the value that deepfakes can bring to a variety of educational and artistic use cases, from video game avatars to filmmaking. By the end of the book, you’ll understand what deepfakes are, how they work at a fundamental level, and how to apply those techniques to your own needs.
Table of Contents (15 chapters)
1
Part 1: Understanding Deepfakes
6
Part 2: Getting Hands-On with the Deepfake Process
10
Part 3: Where to Now?

Summary

In this chapter, we learned the workflow required to create a deepfake using the open source Faceswap software. The importance of data variety was discussed and the steps required to acquire, curate and generate face sets were demonstrated. We learned how to train a model within Faceswap, and how to gauge when a model has been fully trained, as well as learned some tricks to improve the quality of the model. Finally, we learned how to take our trained model and apply it to a source video to swap the faces within the video.

In the next chapter, we will begin to take a hands-on look at the neural networks available to build a deepfake pipeline from scratch using the PyTorch ML toolkit, starting with the models available for detecting and extracting faces from source images.