Easy DeepFake Tutorial using DeepFaceLab | Part 1 [2023]

The speaker welcomes viewers to a tutorial on how to create deepfake footage using AI technology. They emphasize the importance of subscribing and liking the video to support their content. The tutorial focuses on using DeepFaceLab, a tool that utilizes AI to swap faces in videos. The speaker promises to clarify how this technology works and guide viewers through the process, starting with the installation of DeepFaceLab from deepfacelab.com. They mention different versions of the software tailored to various graphics card capabilities and suggest using the last version for most users, except those with high-end graphics cards who might opt for the RDX 3000 Series version. The speaker reassures viewers that the tutorial will be useful for beginners and aims to clear confusion about AI's role in face swapping.

The tutorial continues with instructions on setting up DeepFaceLab, including downloading and extracting the software. The speaker discusses the file structure, highlighting the importance of understanding the difference between data source and data destination files. They explain that the data source file contains the original face, while the data destination file is where the face will be applied. The speaker advises using high-resolution video clips, preferably interview footage, for the best results. They also touch on the process of extracting images from the data source and mention that future videos will cover advanced techniques and manual pack creation.

The speaker dives into more advanced setup procedures, including the use of pre-trained models and face packs for DeepFaceLab. They guide viewers on how to install face packs and use them in the software, emphasizing the importance of aligning and extracting face data correctly. The speaker uses a custom face set as an example and explains the options available in the software for extracting and aligning faces. They also mention the use of a question mark key to get help within the software and the option to use different resolutions for face extraction, with a recommendation for 512 resolution for this tutorial.

This section covers the model training process in DeepFaceLab, including the use of pre-trained models to speed up training. The speaker guides viewers on how to select and load a pre-trained model, adjust settings, and start the training process. They explain various settings such as auto backup, preview history, target iteration, and others, providing insights on what each setting does and how it affects the training. The speaker also demonstrates how to update frames and interpret the training results, including source loss and destination loss values, to evaluate the model's performance.

The speaker wraps up the tutorial by discussing the final steps of creating a deepfake video. They cover the process of merging frames, adjusting the mask and blower settings for better blending, and applying these settings to all frames. The speaker also demonstrates how to save the model, create backups, and export the final video in various formats. They acknowledge the limitations of the tutorial due to time constraints and the low resolution of the example, but they assure viewers that with longer training times and higher resolutions, the results will be significantly improved. The speaker promises to create more advanced tutorials in the future.

In the final part of the tutorial, the speaker concludes by showing the before and after results of the deepfake process. They compare the original video with the deepfake output, highlighting the improvements and areas that need more training for better quality. The speaker expresses their excitement about the potential of AI in video editing and reassures viewers that they will be creating more tutorials to cover advanced techniques, including how to work with higher resolutions and refine the deepfake process. They thank viewers for watching, encourage them to share the video, and look forward to addressing questions and feedback in future videos.