Easy Deepfake tutorial for beginners Xseg
TLDRIn this tutorial, the creator shares an advanced deepfake technique using Nvidia's DeepFaceLab. The video guides viewers through setting up data sources, extracting images from videos, and refining face masks for better results. It emphasizes the importance of varied facial expressions and consistent lighting for creating realistic deepfakes. The tutorial also covers the training process, including mask editing and applying color transfer, culminating in a merged, high-quality deepfake video.
Takeaways
- 😀 This tutorial is an advanced deepfake guide for beginners, focusing on the Xseg method.
- 🎥 The presenter has been experimenting with deepfakes for about two weeks and acknowledges ongoing learning.
- 👨🏫 The tutorial references '10 Deep Fakery' as a helpful resource and data source for the presenter's learning process.
- 🏆 There's a call to action for viewers to vote for the presenter's CGI animated short film on My Road Reel 2020.
- 🎁 A promise is made to give back to subscribers if the presenter wins a competition.
- 💻 The tutorial uses Nvidia Deep Face Lab software for creating deepfakes.
- 📸 It's crucial to have a good data source with varied facial expressions and even lighting for better deepfake results.
- 🖼️ The process involves extracting images from video, aligning faces, and creating masks to refine the deepfake.
- 🎨 Manual editing of masks is emphasized for better results, including the use of the egg sag editor.
- 🤖 The tutorial covers training the deepfake model with GPU acceleration and discusses the importance of iterations.
- 🔧 Post-processing and color correction are part of finalizing the deepfake, with tips on merging and adjusting the fake video.
Q & A
What is the main topic of the video?
-The main topic of the video is a tutorial on creating deepfakes using a method called Xseg, which is more advanced than the previous tutorial the speaker did.
Who is the speaker acknowledging for their help?
-The speaker acknowledges '10 deep fakery' for providing tips and data sources that have been helpful in learning deep faking.
What is the speaker's current project in the tutorial?
-The speaker's current project involves using Nvidia Deep Face Lab to create a deepfake with a data source from the Dune trailer and another data source of themselves talking for variations.
Why is it important to have different facial variations when creating a data source?
-Having different facial variations ensures that the lighting is even and that there are diverse expressions, which improves the quality of the final deepfake footage.
What file formats are recommended for extracting images from the video in Deep Face Lab?
-The recommended file formats for extracting images from the video are PNG for better quality and JPEG.
What does the speaker suggest doing with images that have issues like blurriness or obstructions?
-The speaker suggests deleting images that have issues like blurriness, obstructions, or hands in front of the face to ensure better quality in the deepfake.
What is the purpose of the egg sag editor mentioned in the tutorial?
-The egg sag editor is used for manual masking around the faces in the video frames to help Deep Face Lab learn where to paste the faces accurately.
How does the speaker suggest improving the results of the deepfake?
-The speaker suggests improving the results by creating more masks around different facial looks and variations, and then training the masks using the '5 x segtrain bat' process.
What is the significance of the number of iterations in the deepfake training process?
-The number of iterations is significant as it determines how well the deepfake model learns the masks and facial features; more iterations can lead to better results.
What is the final step in the tutorial for creating the deepfake?
-The final step in the tutorial is merging the trained deepfake model with the video using the 'merge s aehd' process and then exporting the result as an MP4 file.
Outlines
🎥 Introduction to Advanced Deepfake Tutorial
The speaker introduces an advanced deepfake tutorial, acknowledging their relative newness to the technique. They mention a previous quick tutorial and give a shoutout to '10 deep fakery' for assistance. The speaker encourages viewers to vote for their CGI animated short film and shares plans to submit a live-action short film. They begin the tutorial by setting up a project with NVIDIA Deep Face Lab and discuss the importance of having varied facial expressions and even lighting for creating data sources.
📸 Extracting Images and Preparing Data Sources
The tutorial continues with instructions on extracting images from video data sources at a specified frame rate, choosing PNG format for quality. The process involves waiting for the extraction to complete and then repeating the steps for the data destination video. The speaker emphasizes checking the extracted images for quality and consistency, such as ensuring no blurriness or obstructions are present. They also touch on the use of histograms for sorting the data set and the importance of aligning the faces correctly.
🖼️ Masking and Manual Adjustments for Deepfaking
The speaker delves into the manual aspect of deepfaking, focusing on the use of the egg sag editor for masking. They describe the process of masking different facial looks and variations, emphasizing the importance of consistency and detail. The tutorial includes steps for masking both the data source and data destination, with a focus on improving the deepfake result by training the masks. The speaker also mentions the need for patience and attention to detail during the rotoscoping process.
🤖 Training the Deepfake Model
The tutorial moves on to training the deepfake model using the masks created in the previous steps. The speaker provides a detailed walkthrough of the settings and options, including GPU selection, batch size, and resolution. They discuss the importance of training iterations and the impact on video quality. The speaker also shares their experience with training times and the visual improvements observed as the model learns from the masks.
🎞️ Merging and Finalizing the Deepfake Video
The final part of the tutorial covers the merging process to create the final deepfake video. The speaker demonstrates how to apply the trained masks and adjust settings for optimal results. They address common issues like skin tone mismatch and provide solutions like color transfer adjustments. The tutorial concludes with exporting the deepfake video, and the speaker teases a follow-up tutorial on compositing in post-production software.
Mindmap
Keywords
💡Deepfake
💡NVIDIA Deep Face Lab
💡Data Source
💡Data Destination
💡Face Extraction
💡Training Masks
💡Iterations
💡Mask Editing
💡Color Transfer
💡Merging
Highlights
Advanced deepfake tutorial for beginners using Nvidia DeepFaceLab.
Creator has been learning deepfaking for about two weeks and shares current methods.
Acknowledgment of '10 Deep Fakery' for providing tips and data sources.
Encouragement to vote for the creator's CGI animated short film on My Road Reel 2020.
Mention of a live-action short film being submitted to My Road Reel.
Explanation of the need for even lighting and varied facial expressions in data sources.
Demonstration of extracting images from video using DeepFaceLab.
Importance of using PNG format for better image quality over JPEG.
Process of extracting faces from the source file using automatic face detection.
Manual inspection and cleaning of extracted faces to ensure quality.
Technique of using histogram similarities to sort the aligned face data.
Guidance on how to handle and correct misaligned faces in the data destination.
Introduction to the egg sag editor for manual mask creation.
Emphasis on the significance of masking variations in facial expressions.
Training the masks using the GPU for better deepfake results.
Applying the trained masks to the data source and destination.
Training the actual deepfake model using the prepared masks.
Discussion on the importance of iteration count in achieving a convincing deepfake.
Merging the deepfake model into a single video file.
Techniques for color transfer and mask blurring to enhance the final deepfake video.
Final result presentation and预告 of part two focusing on compositing in Davinci Resolve and After Effects.