Description |
1 online resource (192 p.) |
Contents |
Cover -- Preface -- Title Page -- Copyright -- Contributors -- Table of Contents -- Part 1: Understanding Deepfakes -- Chapter 1: Surveying Deepfakes -- Introducing deepfakes -- Exploring the uses of deepfakes -- Entertainment -- Parody -- Education -- Advertisements -- Discovering how deepfakes work -- Generative auto-encoders -- Assessing the limitations of generative AI -- Resolution -- Training required for each face pair -- Training data -- Looking at existing deepfake software -- Faceswap -- DeepFaceLab -- First Order Model -- Reface -- Summary |
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Chapter 2: Examining Deepfake Ethics and Dangers -- The unethical origin of deepfakes -- Being an ethical deepfaker -- Consent -- Respect -- Deception -- Putting it into practice -- The dangers of deepfakes -- Reputation -- Politics -- Avoiding consequences by claiming manipulation -- Preventing damage from deepfakes -- Starving the model of data -- Authenticating any genuine media -- Deepfake detection -- Public relations -- Public awareness -- Summary -- Chapter 3: Acquiring and Processing Data -- Why data is important -- Understanding the value of variety -- Pose -- Expression -- Lighting |
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Bringing this variety together -- Sourcing data -- Filming your own data -- Getting data from historical sources -- Improving your data -- Linear color -- Data matching -- Upscaling -- Summary -- Chapter 4: The Deepfake Workflow -- Technical requirements -- Identifying suitable candidates for a swap -- Preparing the training images -- Extracting faces from your source data -- Curating training images -- Training a model -- Setting up -- Launching and monitoring training -- Manual intervention -- Applying a trained model to perform a swap -- The alignments file -- Cleaning the alignments file |
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Fixing the alignments file -- Using the Preview tool -- Generating the swap -- Summary -- Part 2: Getting Hands-On with the Deepfake Process -- Chapter 5: Extracting Faces -- Technical requirements -- Getting image files from a video -- Running extract on frame images -- face_alignments.json -- face_bbox_{filename}_{face number}.png -- face_aligned_{filename}_{face number}.png -- face_mask_{filename}_{face number}.png -- Getting hands-on with the code -- Initialization -- Image preparation -- Face detection -- Face landmarking/aligning -- Summary -- Exercises |
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Chapter 6: Training a Deepfake Model -- Technical requirements -- Understanding convolutional layers -- Getting hands-on with AI -- Defining our upscaler -- Creating the encoder -- Building the decoders -- Exploring the training code -- Creating our models -- Looping over the training -- Teaching the network -- Saving results -- Summary -- Exercises -- Chapter 7: Swapping the Face Back into the Video -- Technical requirements -- Preparing to convert video -- Getting hands-on with the convert code -- Initialization -- Loading the AI -- Preparing data -- The conversion loop |
Note |
Creating the video from images |
Summary |
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. |
Subject |
Generative programming (Computer science)
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Deepfakes.
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Generative art.
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Programmation générative. |
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Art génératif. |
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generative art. |
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Deepfakes |
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Generative art |
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Generative programming (Computer science) |
Added Author |
Tora, Matt, author.
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Other Form: |
Print version: Lyon, Bryan Exploring Deepfakes Birmingham : Packt Publishing, Limited,c2023 |
ISBN |
9781801817844 electronic book |
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1801817847 electronic book |
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paperback |
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