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

AI Lab Tutorial
14 Jan 202406:49

TLDRUTA Akiyama introduces viewers to the creation of high-quality deepfake videos using Stable Diffusion with the expansion functions Move2Move and Reactor. Akiyama demonstrates the process of downloading and installing these functions, then guides through setting up the Stable Diffusion interface with a focus on the 'beautiful realistic' model for Asian-style visuals. The tutorial covers uploading the original video, adjusting sampling methods, and modifying video dimensions and noising strength. Akiyama also explains the Reactor's features, including gender detection and face restoration, before generating a deepfake video with a replaced face. The video concludes with instructions on how to download the processed video, encouraging viewers to explore further with Reactor and Move2Move for creating not just videos, but also text-to-image creations.

Takeaways

  • 🎥 **Introduction to Stable Diffusion**: UTA akiyama introduces a method to create high-quality deepfake videos using Stable Diffusion with the expansion functions Mov2Mov and ReActor.
  • 🔍 **Loop Technique**: Previously, the face swap technique called Loop was introduced, but now the focus is on the improved version called ReActor.
  • 📚 **Downloading Expansion Functions**: The video demonstrates how to download the Mov2Mov and ReActor expansion functions, with links provided in the summary column.
  • 🔧 **Installing Expansions**: After downloading, the user is guided through the installation process by copying and pasting the URL into the Stable Diffusion interface.
  • 🔄 **Restarting Stable Diffusion**: To complete the installation, the user is instructed to restart Stable Diffusion and check for the new tabs indicating successful installation.
  • 🌟 **Choosing the Model**: For creating Asian style visuals, the 'beautiful realistic' model is chosen, which is suitable for high-quality image generation.
  • 📺 **Video Processing**: The original video is uploaded and processed using the chosen model and sampling method, with options to adjust width, height, and noising strength.
  • 🧏‍♀️ **Face Replacement with ReActor**: The ReActor function is used to replace faces in the video, offering features like gender detection and face restoration.
  • ⚙️ **Adjusting Settings**: The user can adjust the settings for face replacement, including the use of a restoration model to correct blurred faces.
  • 📈 **Monitoring Progress**: The progress of video processing can be monitored in Google collaboration, and the user is advised to wait for 100% completion.
  • 📁 **Downloading the Video**: Once processing is complete, the user can download the deepfake video from the Stable Diffusion web UI.
  • 🌐 **Text-to-Image Generation**: In addition to video, the user is encouraged to explore generating images from text, expanding the capabilities of Stable Diffusion.

Q & A

  • What is the main topic of the video?

    -The video is about creating high-quality deepfake videos using Stable Diffusion with the expansion functions Move to Move 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 per the video?

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

  • How can one download the expansion functions?

    -One can download the expansion functions by clicking on the 'Extensions' tab in Stable Diffusion and using the provided links in the summary column to install them from URL.

  • What is the purpose of the Move to Move expansion function?

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

  • What is the role of the Reactor expansion function?

    -The Reactor expansion function is used for face swapping in the video, allowing the user to change the face in the video to a different one.

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

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

  • How does one set the sampling method in the Move to Move tab?

    -To set the sampling method, one should scroll down to the bottom of the Move to Move tab and select their preferred sampling method.

  • What is the effect of changing the denoising strength?

    -Changing the denoising strength affects the fidelity of the original video reproduction. A value closer to zero allows for a more faithful reproduction, while a higher value results in a more stylized output.

  • How does one upload the face image for the Reactor function?

    -To upload the face image, one should click on the Reactor, then upload the desired face image to the 'Single Source Image' field.

  • What is the purpose of the 'Code Fore' feature in the Reactor settings?

    -The 'Code Fore' feature is a restoration model that maintains the structure of the image and cleans up blurry images, particularly useful when the face in the video is blurred.

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

    -Viewers can check the progress of the video processing in Google Collaboration and wait until the process reaches 100% completion.

Outlines

00:00

😀 Introduction to High-Quality Deepfake Video Creation with Stable Diffusion

UTA Akiyama introduces viewers to creating high-quality deepfake videos using Stable Diffusion, an AI model. The video script details the process of downloading and installing two expansion functions, 'move to move' and 'reactor', which are used to manipulate videos and perform face swaps. Akiyama explains how to use these tools, including setting up the 'move to move' model and adjusting parameters such as sampling method, width, height, and denoisng strength. The script also covers how to upload an original video, modify faces using the 'reactor' function, and download the final deepfake video.

05:02

🎬 Demonstrating the Deepfake Video Creation Process with Reactor and Move to Move

The second paragraph demonstrates the actual creation of a deepfake video using the 'reactor' and 'move to move' functions. Akiyama guides viewers through the process of uploading a face image, enabling the reactor for gender detection and face swap, and using a restoration model to correct blurred faces. The script emphasizes the importance of adjusting settings like the code form of weight and provides a step-by-step guide to generating the video. Once the video is processed, Akiyama shows how to download it and encourages viewers to experiment with creating not just videos but also text-to-image creations. The video concludes with a call to action for likes, subscriptions, and viewer engagement.

Mindmap

Keywords

💡Deepfake Video

A deepfake video is a synthetic media in which a person's likeness is swapped with another's using artificial intelligence. It's a technique that has gained notoriety for its potential misuse but also has legitimate applications in entertainment and media. In the video, the creation of a high-quality deepfake video is the main theme, showcasing how it can be done using Stable Diffusion with the help of the 'Move to Move' and 'ReActor' expansion functions.

💡Stable Diffusion

Stable Diffusion is a term that refers to a type of AI model used for generating images and videos from textual descriptions. It is known for its ability to create stable and coherent outputs. In the context of the video, Stable Diffusion serves as the base platform for creating the deepfake video, with additional functionalities provided by expansion functions.

💡Loop

In the context of the video, Loop refers to a face swap technique previously introduced by the speaker. It is a method used to replace faces in videos with AI-generated faces, which is a precursor to the more advanced techniques discussed in the video.

💡ReActor

ReActor is an expansion function for Stable Diffusion that is used for face swapping in videos. It is an improved version of the Loop technique and is used in the video to change the face of a person in the original video to an AI-generated face without causing face collapse or other artifacts.

💡Move to Move

Move to Move is another expansion function for Stable Diffusion that is used to convert videos into a series of images (frames) and then back into a video. It is akin to creating an AI image by attaching text to the image created for each frame of the video, which is essential for generating deepfake videos.

💡Expansion Function

An expansion function in the context of Stable Diffusion refers to additional tools or features that extend the core capabilities of the AI model. Both 'Move to Move' and 'ReActor' are examples of expansion functions that enable more complex and specific manipulations of video content.

💡Face Swap

Face swap is a technique where the faces of individuals in a video or image are exchanged with others, often using AI. It is a core concept in the video, as the entire process revolves around swapping the original face in a video with an AI-generated one using the ReActor expansion function.

💡Sampling Method

The sampling method in AI refers to the technique used to generate outputs from a model. In the video, the speaker chooses a specific sampling method called DPM Plus+ 2m, Crow, which is a method for generating images that balances quality and speed.

💡Noising Strength

Noising strength is a parameter that determines the level of noise or variation introduced into the generated image or video. A lower value results in a more faithful reproduction of the original, while higher values can introduce more variation. In the video, the speaker sets the noising strength to zero to maintain the original video's quality.

💡Gender Detection

Gender detection is a feature within the ReActor function that identifies the gender of the face being swapped and adjusts the AI-generated face accordingly. It is mentioned in the video as a setting that can be used to ensure the swapped face matches the original's gender.

💡Code Fore

Code Fore is a restoration model mentioned in the video used to correct and improve the quality of the generated image, particularly when the face appears blurred. It helps maintain the structural integrity of the image while enhancing clarity.

Highlights

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

The face swap technique Loop is mentioned, which will be improved with the Reactor function.

Mov2Mov is an expansion function that converts videos into images and creates a new video by connecting these images.

The installation process for both Mov2Mov and SD Web Reactor is explained in detail.

The model 'Beautiful Realistic' is used for creating Asian style visuals.

The video demonstrates setting the prompt run to blank and uploading the original video for face generation.

Sampling method DPM Plus+ 2m Crow is chosen for the video creation process.

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

Denoiising strength is set to zero to accurately reproduce the original video.

Reactor is used to change the face in the video without causing face collapse.

Gender detection and Lister face features are explained as part of the Reactor function.

Code Fore is used for restoring the structure of the image and cleaning up blurriness.

The video shows how to monitor the processing progress and download the final deepfake video.

The final deepfake video is shown to be of high quality with an accurate face replacement.

The video concludes with an invitation to try generating text-to-image images and other creative uses of Stable Diffusion.

The viewer is encouraged to like, subscribe, and leave comments for further questions or feedback.

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