Easy Deepfake Tutorial: DeepFaceLab 2.0 Quick96
TLDRThis tutorial demonstrates how to create deepfake videos using DeepFaceLab 2.0 build 7182020 on a Windows PC with NVIDIA graphics. It guides through downloading and installing the software, extracting images from videos, processing them to extract faces, training the deepfake model, and merging the faces to generate the final video. The instructor emphasizes using default settings and provides tips for adjusting the model's accuracy and previewing results.
Takeaways
- 💻 Use DeepFaceLab 2.0 build 7182020 for creating deepfake videos.
- 🖥️ Requires a Windows PC with an NVIDIA graphics card.
- 🔧 Utilize the Quick96 preset trainer with default settings.
- 📥 Download DeepFaceLab from GitHub releases, no installation needed.
- 📁 Extract images from source and destination videos using default settings.
- 🔍 Extract facesets from the images for deepfake processing.
- 👀 View and optionally remove unwanted faces from the facesets.
- 🤖 Begin training the deepfake model using the Quick96 preset.
- 🔄 Monitor training accuracy and loss values to assess model performance.
- 🎞️ Merge the trained faces into the final deepfake video.
- 🖊️ Adjust erode and blur mask values for better deepfake results.
- 📹 Merge the deepfake frames with destination audio to complete the video.
- 🚀 Experiment with training and merger settings to enhance deepfake quality.
Q & A
What software is used in the tutorial to create deepfake videos?
-The tutorial uses DeepFaceLab 2.0 build 7 18 2020 to create deepfake videos.
What hardware is required to run DeepFaceLab as per the tutorial?
-A Windows PC with an NVIDIA graphics card is required to run DeepFaceLab.
How can one obtain DeepFaceLab for the tutorial?
-DeepFaceLab can be downloaded from the releases section on github.com/iperov/DeepFaceLab using either a torrent magnet link or 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.
What does the 'extract images from video' step involve?
-This step processes the video files to create a .png file for each frame, which will be used for deepfake creation.
How are faces extracted from the images in the tutorial?
-The tutorial uses the 'data src faceset extract' and 'data dst faceset extract' files to process images and extract faces for the deepfake.
What is the function of the 'view aligned result' files in the tutorial?
-These files allow users to view the source and destination facesets, and remove unwanted faces if necessary.
What does the training step in the tutorial entail?
-The training step involves using the 'train Quick96' file to load image files and run the first iteration of the deepfake model training.
How can one determine when to end the training in the tutorial?
-The tutorial suggests using the preview window to monitor loss values and image previews, and ending training when desired results are achieved.
What is the merging step in creating a deepfake video?
-The merging step involves using the 'merge Quick96' file to apply settings and process the frames to create the final deepfake video.
How is the final deepfake video created in the tutorial?
-After merging the faces, the tutorial instructs to use the 'merge to mp4' file to combine the deepfake frames with the destination audio into a video file.
Can the tutorial be applied to personal videos to create a deepfake?
-Yes, the tutorial can be followed with personal videos by renaming them and replacing the 'data_src.mp4' and 'data_dst.mp4' files.
Outlines
🎥 Introduction to Creating Deepfake Videos
The instructor introduces a tutorial on creating deepfake videos using DeepFaceLab 2.0. The process requires a Windows PC with an NVIDIA graphics card. The tutorial will utilize the software's Quick96 preset trainer with default settings. The first step involves downloading and installing DeepFaceLab from GitHub, extracting the files, and navigating to the 'DeepFaceLab NVIDIA' folder. The workspace contains folders for images and trained model files, with source and destination videos labeled 'data src' and 'data dst'. The tutorial will guide through extracting images from these videos, processing them to extract faces, and then training the deepfake model using default settings. The preview window during training provides visual feedback on the training process, with loss values indicating the accuracy of the model.
🔧 Finalizing and Viewing the Deepfake Video
After training the deepfake model, the tutorial proceeds to the merging step, where the faces are merged to create the final video. The instructor demonstrates how to use the merger settings to adjust the erode and blur mask values for a more convincing deepfake. Once the merging is complete, the new frames are combined with the destination audio to form the final video file. The tutorial concludes with viewing the deepfake video from the workspace folder and encourages experimentation with training and merger settings to achieve desired results. The instructor also suggests that users can create deepfakes from their own videos by following the same steps and replacing the source and destination video files.
Mindmap
Keywords
💡Deepfake
💡DeepFaceLab
💡NVIDIA graphics card
💡Quick96 preset trainer
💡Extract Images
💡Facesets
💡Training
💡Merge
💡Erode mask value
💡Blur mask value
💡Merge to mp4
Highlights
Tutorial on creating deepfake videos using DeepFaceLab 2.0 build 7 18 2020.
Requires a Windows PC with an NVIDIA graphics card.
Quick96 preset trainer used with default settings.
Download DeepFaceLab from GitHub releases.
No installation needed; extract files to use.
Workspace folder holds images and trained model files.
Extract images from source and destination videos.
Process images to extract faces for deepfake.
View and select facesets for the deepfake model.
Begin training the deepfake model using default settings.
Training accuracy and loss values are displayed.
Preview window updates with keyboard commands.
Save and exit training to create the deepfake model.
Merge faces to create the final deepfake video.
Adjust erode and blur mask values for better results.
Merge deepfake frames into a video with destination audio.
View the completed deepfake video in the workspace folder.
Restart training to improve deepfake quality.
Experiment with merger settings for desired results.
Create deepfakes from personal videos by following the tutorial.