Easy Deepfake Tutorial: DeepFaceLab 2.0 Quick96

Deepfakery
27 Jul 202006:39

TLDRThis tutorial guides viewers through creating deepfake videos using DeepFaceLab 2.0. It requires a Windows PC with an NVIDIA graphics card. The process involves downloading and installing DeepFaceLab, extracting images from source and destination videos, processing these images to extract faces, training the deepfake model with default settings, and finally merging the faces to produce the deepfake video. The instructor emphasizes the ability to restart training for improved quality and encourages experimenting with settings for desired results.

Takeaways

  • 😀 This tutorial teaches how to create deepfake videos using DeepFaceLab 2.0 build 7182020.
  • 💻 A Windows PC with an NVIDIA graphics card is required for the process.
  • 📂 The software is downloaded from GitHub and does not require installation, just extraction of files.
  • 📁 The 'workspace' folder contains subfolders for storing images and trained model files.
  • 📸 The process begins by extracting images from the source and destination videos using default settings.
  • 🔍 Faces are then extracted from these images to be used in creating the deepfake.
  • 👀 Viewers can inspect and potentially remove unwanted faces from the source and destination facesets.
  • 🤖 Training of the deepfake model is initiated with default settings, and the progress can be monitored through a preview window.
  • 🎭 The 'merge' step combines the trained model with the video to create the final deepfake video.
  • 🔧 Users can adjust erode and blur mask values to refine the deepfake video quality.
  • 🎞️ The final step is to merge the deepfake frames into a video file with the destination audio.
  • 🚀 The tutorial encourages experimentation with training and merger settings to achieve desired results.

Q & A

  • What is the tutorial about?

    -The tutorial is about creating deepfake videos using DeepFaceLab 2.0 build 7182020.

  • What software and hardware are required for this tutorial?

    -For this tutorial, you need a Windows PC with an NVIDIA graphics card and DeepFaceLab 2.0.

  • How can you obtain DeepFaceLab 2.0?

    -You can download DeepFaceLab 2.0 from the releases section on GitHub by iperov, using either a torrent magnet link or a download from Mega.nz.

  • What is the purpose of the 'workspace' folder in DeepFaceLab?

    -The 'workspace' folder in DeepFaceLab holds folders for images and trained model files, including source and destination video files.

  • How do you extract images from a video in the tutorial?

    -You extract images from a video by double-clicking the '2) extract images from video data src' file and using the default values.

  • What does 'Extract Facesets' involve in the tutorial?

    -Extracting facesets involves processing the images to extract faces that will be used in the deepfake.

  • How can you view the source and destination facesets?

    -You can view the facesets using the '4.1) data src view aligned result' and '5.1) data dst view aligned results' files.

  • What happens during the 'Training' step?

    -During the training step, the software loads all image files and attempts the first iteration of training to create the deepfake model.

  • What keyboard commands are available in the training preview window?

    -In the training preview window, you can use the P key to update the preview, and the Enter key to save the model and exit.

  • How do you merge the faces to create the final deepfake video?

    -You merge the faces by running the '7) merge Quick96' file, adjusting settings with keyboard commands, and then processing the remaining frames.

  • What is the final step to complete the deepfake video creation?

    -The final step is to merge the new deepfake frames into a video file with the destination audio using the '8) merge to mp4' file.

  • Can you use your own videos to create a deepfake?

    -Yes, you can create a deepfake from your own videos by renaming them and replacing the 'data_src.mp4' and 'data_dst.mp4' files.

Outlines

00:00

🎥 Deepfake Video Creation Tutorial

This paragraph introduces a tutorial on creating deepfake videos using DeepFaceLab 2.0. The process requires a Windows PC with an NVIDIA graphics card. The tutorial involves downloading and installing DeepFaceLab from GitHub, setting up the workspace, and using specific batch files for the deepfake creation. It outlines the steps for extracting images from videos, processing these images to extract faces, viewing the facesets, and beginning the training of the deepfake model with default settings. The training process is monitored through a preview window that shows accuracy and loss values, indicating the quality of the training. The paragraph concludes with instructions on when to end the training and save the model.

05:03

🔧 Finalizing the Deepfake Video

The second paragraph details the final steps in creating a deepfake video. It starts with merging the trained model to create the final video, adjusting erode and blur mask values for a better result, and applying these settings to all frames. The process continues with merging the new deepfake frames into a video file that includes the destination audio. The tutorial concludes with viewing the final deepfake video and offers advice on how to improve the quality by restarting the training or experimenting with different merger settings. It also suggests that users can create deepfakes from their own videos by following the same steps and replacing the source files.

Mindmap

Keywords

💡Deepfake

A deepfake refers to a synthetic media in which a person's face or voice is replaced with someone else's using artificial intelligence. In the context of the video, deepfakes are created by manipulating video footage to make it appear as if one person is doing or saying something they never did. The video tutorial demonstrates how to create a deepfake video using DeepFaceLab 2.0 software.

💡DeepFaceLab

DeepFaceLab is an open-source tool that uses deep learning to create deepfakes. It is the primary software used in the tutorial to demonstrate the process of generating a deepfake video. The video mentions using DeepFaceLab 2.0 build 7182020, indicating a specific version of the software.

💡Quick96 preset trainer

The Quick96 preset trainer is a feature within DeepFaceLab that allows users to train their deepfake models with default settings, which are optimized for speed and quality. The video instructs viewers to use this preset by pressing enter when prompted, streamlining the training process.

💡NVIDIA graphics card

An NVIDIA graphics card is a type of hardware required for running DeepFaceLab effectively. Graphics cards are essential for the processing power needed to create deepfakes, as they accelerate the complex computations involved in deep learning. The video specifies that a Windows PC with an NVIDIA graphics card is necessary.

💡Extract Images

Extracting images from a video is the first step in creating a deepfake, as mentioned in the video. This process involves taking individual frames from a video and converting them into still images, which are then used to train the deepfake model. The script mentions using a batch file to automate this extraction for both the source and destination videos.

💡Facesets

A faceset is a collection of images that contain faces extracted from the video frames. In the tutorial, facesets are created for both the source and destination videos. These sets are crucial for training the deepfake model to accurately swap faces in the final video.

💡Training

Training in the context of the video refers to the process of teaching the deepfake model to recognize and replicate facial features. This is done by feeding the model images from the facesets. The video describes using the 'train Quick96' batch file to start this process, which involves iterative learning to improve the model's accuracy.

💡Preview Window

The preview window is a feature in DeepFaceLab that allows users to see a real-time demonstration of the deepfake model's progress. It displays the model's output and includes loss values, which are indicators of the model's performance. The video explains how to use keyboard commands to interact with the preview window and assess the training.

💡Merging

Merging is the final step in creating a deepfake video, where the trained model's output is combined with the original video frames. The video script describes using the 'merge Quick96' batch file to apply the deepfake faces onto the destination video, resulting in the final fake video.

💡Erode mask value

The erode mask value is a setting used during the merging process to refine the edges of the face in the deepfake. In the video, adjusting this value with the W and S keys helps to contract the border around the face, ensuring a more seamless integration of the fake face onto the original video.

💡Blur mask value

The blur mask value is another setting used in the merging process to smooth out the transition between the fake face and the original video background. The video instructs viewers to increase this value with the E and D keys to achieve a more natural-looking deepfake.

Highlights

Tutorial on creating deepfake videos using DeepFaceLab 2.0 build 7182020.

Requires a Windows PC with an NVIDIA graphics card.

DeepFaceLab's Quick96 preset trainer is used with default settings.

Download DeepFaceLab from GitHub releases or Mega.nz.

No setup is needed for DeepFaceLab; just extract the files.

Workspace folder contains subfolders for images and trained model files.

Extract images from source and destination videos using default settings.

Process images to extract faces for the deepfake.

View and potentially remove unwanted faces from the facesets.

Begin training the deepfake model with default settings.

Training accuracy and loss values are displayed in the preview window.

Use keyboard commands to navigate and adjust the training preview.

End training and save the model when desired results are achieved.

Merge the trained faces to create the final deepfake video.

Adjust erode and blur mask values for better face merging.

Apply settings to all frames and process the remaining frames.

Merge deepfake frames into a video file with destination audio.

View the completed deepfake video and assess the quality.

Restart training to improve deepfake quality or experiment with merger settings.

Create deepfakes from personal videos by following the same tutorial.

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