Master the innovative world of deepfakes and generative AI for face replacement with this full-color guide

Purchase of the print or Kindle book includes a free PDF eBook

Key Features:

• Understand what deepfakes are, their history, and how to use the technology ethically
• Get well-versed with the workflow and processes involved to create your own deepfakes
• Learn how to apply the lessons and techniques of deepfakes to your own problems

Book Description:

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.

What You Will Learn:

• Gain a clear understanding of deepfakes and their creation
• Understand the risks of deepfakes and how to mitigate them
• Collect efficient data to create successful deepfakes
• Get familiar with the deepfakes workflow and its steps
• Explore the application of deepfakes methods to your own generative needs
• Improve results by augmenting data and avoiding overtraining
• Examine the future of deepfakes and other generative AIs
• Use generative AIs to increase video content resolution

Who this book is for:

This book is for AI developers, data scientists, and anyone looking to learn more about deepfakes or techniques and technologies from Deepfakes to help them generate new image data. Working knowledge of Python programming language and basic familiarity with OpenCV, Pillow, Pytorch, or Tensorflow is recommended to get the most out of the book.