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 ran the convert process on a folder full of images, replacing the faces using a trained model. We also turned the images back into a video, including changes to account for frame rate and copying audio.

We started by going over how to prepare a video for conversion. The convert process requires data created by the extract process from Chapter 5, Extracting Faces, and a trained AI model from Chapter 6, Training a Deepfake Model. With all the parts from the previous chapters, we were ready to convert.

We then walked through the code for the conversion process. This involved looking at the initialization, where we covered getting the Python script ready to operate. We then loaded the AI models and got them set up to work on a GPU if we have one. Next, we got the data ready for us to convert the faces in each frame. Finally, we ran two nested loops, which processed every face in every frame, swapping them to the other face. This part gave us a folder filled...