Create high-quality deepfake videos with Stable Diffusion (Mov2Mov & ReActor)

AI Lab Tutorial
14 Jan 202406:49

TLDRUTA Akiyama introduces a method for creating high-quality deepfake videos using Stable Diffusion with the help of two expansion functions: Mov2Mov and ReActor. The tutorial begins with downloading and installing these functions, guiding viewers on how to use the Stable Diffusion platform. Akiyama selects the 'beautiful realistic' model for creating Asian-style visuals and explains the process of uploading the original video, adjusting settings, and using ReActor for face swapping without altering the video's original characteristics. The video concludes with a demonstration of the successful deepfake creation and instructions on how to download the final product. Akiyama encourages viewers to explore Stable Diffusion's capabilities for generating images and offers assistance for any questions or comments.

Takeaways

  • 📚 **Introduction to Stable Diffusion**: UTA akiyama introduces the process of creating high-quality deepfake videos using Stable Diffusion, focusing on the expansion functions Mov2Mov and ReActor.
  • 🔍 **Loop Technique and Expansion Functions**: Previously, the face swap technique called Loop was introduced, but this time, the focus is on using the improved version, the expansion function called ReActor.
  • 📥 **Downloading Expansion Functions**: To get started, download the Mov2Mov and ReActor expansion functions from the provided links in the summary column.
  • 🔄 **Installing and Restarting Stable Diffusion**: After downloading, install the expansion functions and restart Stable Diffusion to complete the installation process.
  • 🎨 **Choosing the Model**: For creating Asian style visuals, the 'beautiful realistic' model is selected, which is adept at generating realistic images.
  • 📼 **Uploading the Original Video**: Upload the original video that will be used for face replacement and set the sampling method to DPM Plus+ 2m, Crow.
  • 📏 **Adjusting Video Dimensions**: Modify the width and height to match the original video's size for consistency.
  • 🔧 **Denoiising Strength**: Set the denoising strength to zero to reproduce the original video faithfully without altering its appearance.
  • 🖼️ **Reactor for Face Replacement**: Use the ReActor to upload the desired face image and enable the reactor for gender detection and face swap features.
  • 🔄 **Code Fore and GFP Gun**: Utilize the Code Fore restoration model for correcting blurred faces and the GFP Gun model for fixing broken faces, adjusting their weights as needed.
  • ⏱️ **Processing and Progress**: Monitor the progress of the video processing in Google collaboration and wait for it to reach 100% completion.
  • 📁 **Downloading the Video**: Once the processing is done, download the high-quality deepfake video from the Stable Diffusion web UI outputs section.
  • 🌟 **Final Thoughts**: The video concludes by emphasizing the ease of creating high-quality deepfake videos with the help of ReActor and Mov2Mov, and encourages viewers to explore text-to-image generation as well.

Q & A

  • What is the main topic of the video?

    -The main topic of the video is how to create high-quality deepfake videos using Stable Diffusion with the expansion functions Move2Move and ReActor.

  • Who is the presenter of the video?

    -The presenter of the video is UTA Akiyama.

  • What is the first step in creating a deepfake video as described in the video?

    -The first step is to download and install the Move2Move and ReActor expansion functions in Stable Diffusion.

  • How can viewers find the link to download the expansion functions?

    -Viewers can find the link to download the expansion functions in the summary column of the video.

  • What is the purpose of the Move2Move expansion function?

    -The Move2Move expansion function converts each frame of the original video into an image and creates a new video by connecting these images.

  • What is the role of the ReActor expansion function in the process?

    -The ReActor expansion function is used for face swapping, allowing the modification of faces in the video to create a deepfake.

  • Which model does UTA Akiyama use for creating Asian style visuals?

    -UTA Akiyama uses the 'Beautiful Realistic' model for creating Asian style visuals.

  • What sampling method does UTA Akiyama choose for the video creation process?

    -UTA Akiyama chooses the default DPM Plus+ 2m Crow sampling method for the video creation process.

  • How does the 'denoising strength' setting affect the video?

    -The 'denoising strength' setting determines how faithfully the original video is reproduced. A setting closer to zero results in a more faithful reproduction, while a higher value introduces more differences.

  • What is the 'code forer' feature in ReActor?

    -The 'code forer' is a restoration model in ReActor that keeps the structure of the image and cleanses a blurry image.

  • How can viewers check the progress of the video processing?

    -Viewers can check the progress of the video processing in Google Collaboration.

  • What should viewers do if they find the video useful?

    -If viewers find the video useful, they are encouraged to like and subscribe, and to leave any questions or comments in the comments section.

Outlines

00:00

😀 Introduction to High-Quality Deepfake Video Creation

UTA Akiyama introduces the audience to the process of creating high-quality deepfake videos using Stable Diffusion, a tool for AI image creation. The tutorial covers downloading and installing two expansion functions: 'move to move' for video conversion and 'reactor' for face swapping. The speaker guides viewers on how to use these tools, emphasizing the importance of selecting the right model and settings for realistic results. The video concludes with a demonstration of the face-swapping process using an AI-generated image and the reactor function.

05:02

🎬 Deepfake Video Processing and Results

After setting up the necessary tools, UTA Akiyama demonstrates the creation of a deepfake video. The process involves selecting a model that specializes in Asian visuals, uploading the original video, and adjusting settings such as sampling method and noising strength. The face-swapping is done using the reactor function, where the user can upload a desired face image and enable features like gender detection and image restoration. The video shows the successful replacement of the original face with the AI-generated one, resulting in a high-quality deepfake video without any face collapse. The speaker also explains how to download the processed video and encourages viewers to experiment with generating images as well as videos.

Mindmap

Keywords

💡Deepfake

Deepfake refers to the use of artificial intelligence and machine learning techniques to create convincing fake videos or images of people appearing to say or do something they did not. In the video, the term is central as it describes the process of creating high-quality deepfake videos using Stable Diffusion, a technology that allows for the manipulation and generation of visual content.

💡Stable Diffusion

Stable Diffusion is a term used to describe a system or software capable of generating or manipulating images and videos in a stable and high-quality manner. In the context of the video, it is the platform on which the deepfake creation process is based, utilizing expansion functions to enhance its capabilities.

💡Loop

In the video, Loop refers to a face swap technique previously introduced by the speaker. It is a method used in the creation of deepfake videos where the faces of individuals in a video are swapped with others. The mention of Loop sets the stage for the introduction of more advanced techniques using expansion functions.

💡Reactor

Reactor is an expansion function used within the Stable Diffusion system to improve the face swap process in deepfake videos. It is described as an improved version of the Loop technique and is used to change faces in a more natural and accurate way. The video demonstrates how to use Reactor to achieve high-quality results.

💡Move to Move

Move to Move is another expansion function for Stable Diffusion that is used to convert videos into a series of images and then generate a new video by reconnecting these images. It is likened to creating an AI image by attaching text to an image for each frame of the video. This function is crucial for the video's theme of generating high-quality deepfake videos.

💡Extensions

In the context of the video, extensions refer to additional functionalities or plugins that can be added to the Stable Diffusion platform to enhance its capabilities. Both Move to Move and Reactor are installed as extensions to achieve the desired video manipulation effects.

💡Sampling Method

The sampling method is a technical term related to the process of generating images or videos using AI. In the video, the speaker chooses a sampling method called DPM Plus+ 2m, Crow, which influences the quality and style of the generated deepfake video.

💡Noising Strength

Noising strength is a parameter that determines the level of noise or distortion introduced into the generated video during the AI image creation process. A lower value, such as zero, results in a more faithful reproduction of the original video, while higher values can lead to a more stylized or different outcome.

💡Gender Detection

Gender Detection is a feature within the Reactor function that identifies the gender of the faces in the video and adjusts the face swap process accordingly. This feature is important for maintaining the realism of the deepfake video by ensuring that the swapped faces match the original subjects' genders.

💡Code Fore

Code Fore is a restoration model mentioned in the video used to correct and improve the quality of the generated image after the face swap process. It is particularly useful for dealing with blurred faces, ensuring that the final deepfake video appears natural and undistorted.

💡Google Collaboration

Google Collaboration is a tool or platform that allows for the tracking of progress on tasks or projects. In the video, it is used to monitor the progress of the deepfake video creation process, indicating when the processing is complete.

Highlights

UTA Akiyama introduces how to create high-quality deepfake videos with Stable Diffusion using the expansion functions Mov2Mov and ReActor.

The face swap technique called Loop is improved with the Reactor expansion function.

The video uses the Mov2Mov expansion function to convert each frame into an image and create a new video.

The process includes downloading the Mov2Mov and Reactor expansion functions from provided URLs.

Stable Diffusion is launched, and the extensions tab is used to install the expansion functions.

After installation, the software is restarted to complete the setup.

The SD Web Reactor is installed for advanced face swap functionalities.

The 'beautiful realistic' model is chosen for creating Asian style visuals.

The original video is uploaded for face generation, using the default sampling method DPM Plus+ 2m, Crow.

The width and height are adjusted to match the size of the original video for consistency.

The denoising strength is set to zero to maintain the original video's fidelity during face replacement.

The Reactor is used to upload the face image for the desired change.

Gender detection and face restoration features are available within the Reactor for natural-looking results.

The 'code forer' model is selected to correct blurred faces during the face swap process.

The settings are finalized, and the video processing begins with progress tracked in Google Collaboration.

The processed deepfake video is highly accurate with no face collapse, showcasing the effectiveness of the technique.

The final video can be downloaded from the Stable Diffusion Web UI under the 'outputs' section.

ReActor and Mov2Mov make it easy to create high-quality deepfake videos, with potential for text-to-image generation as well.

The video concludes with an invitation for viewers to like, subscribe, and engage with questions or comments.

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