DeepFaceLab 2.0 Easy Tutorial | Part 1 [ 2023 ]
TLDRThis tutorial guides viewers through using DeepFaceLab 2.0, a deepfaking software that swaps faces in videos. It covers downloading the software from various sources, selecting the appropriate build based on GPU, and extracting images from source and destination folders. The video also explains the face extraction process, training a new model, and merging frames into an MP4. Despite using a basic model and short training time, the tutorial successfully demonstrates creating a deepfake, encouraging viewers to experiment with more advanced settings for better results.
Takeaways
- 😀 DeepFaceLab is a deepfake software used for face swapping in videos.
- 🔧 The software can be downloaded from GitHub, torrent, or mega, with specific builds for different GPU types.
- 💾 Users need to extract the software to a location on their PC and set up a workspace with 'source' and 'destination' folders.
- 🖼️ The 'source' folder contains the face to be swapped, while the 'destination' folder will have the face after the swap.
- 🚀 Pre-trained models can be downloaded from facevfx.com to speed up the deepfaking process.
- 🧐 The tutorial covers basic steps like clearing the workspace, extracting images from source and destination, and face detection.
- 💻 The performance of the software depends on the user's GPU and CPU capabilities, with better hardware leading to faster processing.
- 🎥 FPS (frames per second) can be adjusted during image extraction, with zero FPS meaning every frame is used.
- 🤖 The software includes options for different face extraction methods, such as 'whole face' or 'face', affecting the quality and GPU usage.
- 📈 Training a new model from scratch is time-consuming and not recommended for beginners; using pre-trained models is advised.
- 🎬 The final steps involve merging the extracted faces into a video format, with the ability to adjust settings for better results.
Q & A
What is DeepFaceLab?
-DeepFaceLab is a deepfaking software that can convert any face from a source to a destination, creating realistic face replacements in videos.
Where can I find the official website for DeepFaceLab?
-The official website for DeepFaceLab is deepfakevfx.com.
How many ways are mentioned in the script to download DeepFaceLab?
-Three ways are mentioned: GitHub repo, torrent, and mega.
What does the script recommend downloading DeepFaceLab based on?
-The script recommends downloading DeepFaceLab based on the user's GPU, with specific builds for different series like the RTX 3000 Series.
What is the purpose of the 'Clear Workspace' button in DeepFaceLab?
-The 'Clear Workspace' button is used to delete the model, destination, and source folders, essentially resetting the workspace.
What does the script suggest for setting FPS when extracting images from the source?
-For extracting images from the source, the script suggests setting the FPS to zero to extract every single frame.
What is the difference between 'Whole Face' and 'Hit' when extracting faces from images?
-The 'Whole Face' option extracts from the forehead to the chin, while 'Hit' extracts from the hair to the neck, making it a more comprehensive and GPU-intensive process.
What is the recommended image resolution when extracting faces according to the script?
-The recommended image resolution for extracting faces is 500x500, but the script changes this to 1000x1000 to improve quality.
Why is it not recommended to create a new model from scratch in DeepFaceLab as per the tutorial?
-Creating a new model from scratch is not recommended because it takes a very long time to train compared to using a pre-trained model, which can provide better and faster results.
What is the significance of the 'P' button during the training process in DeepFaceLab?
-The 'P' button is used to preview the updated face during the training process, allowing users to see the progress of the deepfaking in real-time.
How long did the tutorial run the training process for the demonstration?
-The tutorial ran the training process for approximately five minutes for demonstration purposes.
Outlines
😀 Introduction to DeepFaceLab
The speaker introduces the video tutorial on how to use DeepFaceLab, a deepfaking software. They explain that DeepFaceLab is available for download from their official website, deepfakevfx.com, and can be accessed through various methods including GitHub, torrent, and MEGA. The tutorial focuses on downloading the software using MEGA and selecting the appropriate build based on the user's GPU. The speaker also mentions that they will provide links in the video description for further assistance. They briefly touch on the software's capability to convert any face from a source to a destination and plan to cover advanced topics in a future video.
🔧 Setting Up DeepFaceLab
The tutorial proceeds with setting up DeepFaceLab by extracting the downloaded files to a chosen location. The speaker guides viewers through the initial setup, explaining the roles of 'data destination' and 'data source' folders. They also discuss the importance of selecting the right model file, which can be downloaded from the face VFX website to speed up the deepfaking process. The video covers the steps of clearing the workspace, extracting images from the source, and setting the FPS and image format. The speaker emphasizes the impact of a powerful GPU on the speed of the extraction process and provides guidance on how to handle different frame rates and image resolutions.
🎭 Extracting and Training Faces
The speaker continues the tutorial by explaining how to extract images from the destination folder, which is crucial for ensuring smooth deepfake results. They then guide viewers through the process of using the 'data source facer extract' feature to detect and extract faces from the source data. The tutorial covers various options for face extraction, including whole face and head options, and the speaker provides tips on optimizing settings based on the user's GPU capabilities. They also discuss the importance of image resolution in the extraction process and how it affects the quality of the final deepfake. The segment ends with the speaker demonstrating the face extraction process and providing real-time feedback on the progress.
🤖 Training the DeepFake Model
The speaker introduces the training phase of creating a deepfake, where they explain the process of training a model from scratch versus using a pre-trained model. They warn that training a model from scratch is time-consuming but provide a step-by-step guide on how to do so, including naming the model and setting various training parameters. The tutorial covers the importance of choosing the right batch size, resolution, and model architecture for optimal training results. The speaker also discusses the use of the 'DF' model for better results and provides insights on other settings like encoder dimensions and optimizers. They conclude this segment by demonstrating the training preview and explaining the significance of various metrics displayed during the training process.
🚀 Finalizing the DeepFake Video
The final segment of the tutorial focuses on the last steps of creating a deepfake video. The speaker demonstrates how to merge the extracted faces with the source video and convert the result into an MP4 file. They explain the importance of selecting the right model and settings for the merging process and provide a quick overview of the default options. The tutorial concludes with the speaker showcasing the initial results of the deepfake, emphasizing that the quality can be significantly improved with more training time and better hardware. They also tease upcoming videos that will cover advanced topics and techniques for creating high-quality deepfakes.
Mindmap
Keywords
💡DeepFaceLab
💡Deepfaking
💡GPU
💡Source
💡Destination
💡Model
💡FPS
💡Training
💡Resolution
💡Batch Size
Highlights
Introduction to DeepFaceLab, a deep faking software.
DeepFaceLab's ability to convert any face from source to destination.
Downloading DeepFaceLab through GitHub, torrent, or MEGA.
Selecting the appropriate DeepFaceLab build based on GPU.
Extracting DeepFaceLab to a chosen location.
Understanding the roles of 'destination' and 'source' folders.
Downloading pre-trained models from FaceVFX for faster processing.
Clearing the workspace and its implications.
Extracting images from the source at zero FPS.
Choosing image format and starting the extraction process.
Extracting images from the destination folder.
Data source face extraction for detecting faces in the source.
Options for whole face vs. head and shoulders extraction.
Adjusting image resolution for face extraction quality.
Extracting faces from the destination using similar settings.
Starting the training process with a new model.
Importance of GPU in training time and model quality.
Settings for training, including batch size and resolution.
Choosing the DF model for better results at the cost of GPU power.
Options for optimizer, belief, and sample during training.
Saving the training process and creating backups.
Merging the SE HD for finalizing the deep fake.
Adjusting settings for merging and previewing the deep fake.
Final step of merging to MP4 and completing the deep fake process.
Final results and considerations for training time and quality.
Encouragement for viewers to practice and improve their deep faking skills.