Face Swapping in ComfyUI with LoRA (ADetailer/FaceDetailer Guide)

My AI Force
25 Apr 202409:08

TLDRIn this tutorial, viewers are guided through the process of face swapping in ComfyUI using LoRA (ADetailer/FaceDetailer). The presenter explains how to install necessary tools, set up a workflow with nodes for image generation and face detection, and fine-tune settings for seamless face swapping. The video also demonstrates how to preview and compare the before-and-after results, ensuring a high-quality output. Tips for adjusting settings to fix common issues are provided, making it an informative watch for AI photography enthusiasts.

Takeaways

  • 😀 The video provides a tutorial on face swapping in ComfyUI using LoRA (ADetailer/FaceDetailer).
  • 🔧 To begin, you need a LoRA model trained specifically on headshots of the person whose face you want to use.
  • 💻 After training, use this model to create a face that closely resembles your subject, enhancing AI photography.
  • 🛠️ Install necessary tools in ComfyUI, including 'Efficiency' nodes and 'Impact Pack' to set up the workflow.
  • 🔍 Use 'E.fficient loader XXL' to load checkpoints, prompts, and set image size in one step.
  • 🖼️ For image generation, connect 'E.fficient loader XXL' with 'P.Sampler Sdxl' and set up checkpoint, prompt, and other settings.
  • 👤 Implement 'Alteristic Detector Provider' with 'B box slace yolow v8m' for effective face detection using bounding boxes.
  • 🎭 Use 'SamLoader' for image segmentation to separate detected faces from the bounding box.
  • 🔄 Set up 'Face Detailer' as the key node for face swapping, ensuring it can use different checkpoints and LoRA models.
  • 📸 Compare the original and swapped faces visually using 'Preview Image' nodes to assess the effectiveness of the swap.
  • 🛡️ Adjust settings like 'feather', 'bbox crop factor', and 'bbox dilation' in 'Face Detailer' to refine the face swapping results.

Q & A

  • What is the main topic of the video?

    -The main topic of the video is how to perform face swapping in ComfyUI using LoRA (ADetailer/FaceDetailer Guide).

  • What is LoRA and how is it used in the video?

    -LoRA is a custom-trained model used to swap faces in images. In the video, it is used to create a face that looks like the model, which can then be swapped onto any person.

  • What are the necessary tools mentioned for setting up the workflow in ComfyUI?

    -The necessary tools mentioned are the installation of the 'Efficiency' nodes and the 'ComfyUI Impact Pack', followed by a restart of ComfyUI.

  • How does the video guide the user to generate images using Sdxl?

    -The video guides the user to generate images using Sdxl by using the 'E dot loader XXL' node, which combines loading checkpoints, prompts, and setting the image size.

  • What is the purpose of the 'Alteristic Detector Provider' module in the workflow?

    -The 'Alteristic Detector Provider' module is used to detect faces and human bodies within images, with 'B box slace yolow v8m' being the recommended model for face detection.

  • What does the 'Sam loader' node do in the workflow?

    -The 'Sam loader' node is used for image segmentation, separating the detected faces from the bounding box using a model developed by Meta.

  • How is the 'Face Detailer' node utilized in the face swapping process?

    -The 'Face Detailer' node is used to swap faces smoothly by connecting it with the image output from the 'Key Sampler' and the model output from the 'Efficient Loader'.

  • What additional settings can be adjusted in 'Face Detailer' to improve the face swap result?

    -Settings such as 'feather', 'bbox crop factor', 'bbox dilation', and 's bbox expansion' can be adjusted to improve the face swap result and reduce visible seams.

  • How does the video help the user compare the before and after effects of the face swap?

    -The video instructs the user to drag out 'prev image' nodes from both the 'Key Sampler' in Sdxl and the 'Face Detailer' to visually compare the effects before and after the face swap.

  • What is the final step shown in the video for completing the face swap?

    -The final step shown is clicking the 'Q prompt' button to generate the preview image of the mask used for the face swap and comparing it to the original.

Outlines

00:00

🎥 Getting Started with Face Swapping in Confy UI

This paragraph introduces the tutorial on using Confy UI to swap faces in images, similar to the previous tutorial on using the 'a detail' extension. The focus is on creating a face that resembles the model using a custom train, 'Laura,' and then applying this face to any subject to enhance AI photography. The tutorial begins by guiding viewers to install necessary tools in Confy UI, specifically the 'Efficiency Nodes' and the 'Impact Pack.' It then demonstrates setting up a workflow by installing and connecting nodes such as 'E dot loader XXL' and 'P sampler' to generate images. The paragraph concludes with a successful image generation, setting the stage for the face swapping process.

05:04

🔍 Advanced Face Swapping with Custom Nodes and Settings

The second paragraph delves into the intricacies of setting up the face swapping process using specific nodes and configurations within Confy UI. It starts by explaining the need for additional 'Efficient Loaders' that support different models and the importance of using 'train Laura' for face swapping. The tutorial then guides viewers through connecting nodes for face detection, segmentation, and swapping, emphasizing the use of 'alteristic detector provider' and 'Sam loader' for effective detection and segmentation. The paragraph also covers fine-tuning the process by setting up checkpoint prompts and adjusting settings like 'feather' and 'bbox crop factor' for a seamless face swap. The tutorial concludes with a visual comparison of the before and after face swap images, demonstrating the effectiveness of the process and offering tips for troubleshooting common issues.

Mindmap

Keywords

💡Face Swapping

Face swapping is a technique used in digital image editing where faces from different images are exchanged. In the context of the video, face swapping is achieved using AI tools within ComfyUI, allowing users to replace a person's face in an image with another, creating a realistic composite. The script describes a step-by-step process for setting up a workflow in ComfyUI to perform face swapping using a custom-trained model called LoRA.

💡LoRA

LoRA, short for 'Low-Rank Adaptation', is a technique used in machine learning to fine-tune pre-trained models with fewer parameters. In the video, LoRA is used to train a model specifically on headshots of a person, aiming to create a face that looks just like the model. This trained model is then utilized for face swapping in images, enhancing the quality and realism of the AI-generated photography.

💡ComfyUI

ComfyUI is a user interface for AI image generation tools. The video provides a tutorial on how to use ComfyUI to set up a workflow for face swapping. It is mentioned as a platform where users can install custom nodes and utilize various AI models to generate and manipulate images, taking their AI photography to the next level.

💡Custom Nodes

Custom nodes refer to additional modules or tools that can be installed to enhance the functionality of a software platform. In the script, the presenter instructs viewers to install custom nodes like 'Efficiency' and 'Impact Pack' in ComfyUI to facilitate the face swapping process. These nodes provide specialized functions that are not available in the base software, thus expanding its capabilities.

💡E.fficient Loader

The E.fficient Loader is a custom node mentioned in the video that simplifies the process of loading checkpoints, setting prompts, and defining image sizes in one go. It is used to streamline the workflow in ComfyUI, making it easier for users to generate images with specific characteristics for face swapping.

💡Key Sampler

Key Sampler is a term used in the video to describe a node that generates images based on the settings and checkpoints provided. It is connected to the Efficient Loader and is responsible for producing the initial image that will undergo face swapping. The script guides viewers on how to set up the Key Sampler within the ComfyUI workflow.

💡Alteristic Detector

Alteristic Detector is a module in ComfyUI that offers various models for detecting faces and human bodies. The video specifically mentions using 'B box slice yolow v8m' as a model for face detection. This model uses a bounding box to identify the face area, which is crucial for the face swapping process. The script emphasizes the effectiveness of this model for first detection.

💡Image Segmentation

Image segmentation is the process of partitioning an image into multiple segments or regions. In the context of the video, image segmentation is used to separate the detected faces from the bounding box. The Sam Loader, which stands for 'Segment anything', is the tool mentioned for this purpose. It is used to create a mask that isolates the face, preparing it for the face swapping process.

💡Face Detailer

Face Detailer is a node in ComfyUI that is used to perform the actual face swapping. It is likened to the ADetailer in Automatic 1111 and is responsible for smoothly swapping the faces using the trained LoRA model. The video explains how to connect the Face Detailer to other nodes and set up the necessary checkpoints and prompts to ensure a seamless face swap.

💡Feather Option

The Feather Option is a setting within the Face Detailer node that helps to soften the edges of the face mask, similar to feathering a mask in Photoshop. The video suggests using this option to reduce visible seams around the face after the face swap, thereby improving the naturalness of the final image.

Highlights

Introduction to face swapping in ComfyUI using LoRA (ADetailer/FaceDetailer Guide).

Requirement of having a LoRA model trained specifically on headshots of the person for face swapping.

Installation of custom nodes in ComfyUI for efficient workflow setup.

Use of E-Dot Loader XXL for combining checkpoint loading, prompts, and image size settings.

Integration of P Sampler Sdxl for image generation.

Setting up checkpoint, prompt, and other settings for image generation.

Utilization of Alteristic Detector Provider for face detection.

Selection of B-Box Slice YOLOv8m model for effective face detection.

Explanation of B-Box as an abbreviation for bounding box.

Application of Sam Loader for image segmentation to separate detected faces.

Importance of choosing the Sam model that includes 'L' for better segmentation.

Introduction to Face Detailer as the A-Detailer equivalent in ComfyUI.

Connecting nodes for face swapping using the generated image from the Sdxl model.

Adjusting settings in Face Detailer for optimal face swapping results.

Previewing the face swap result and comparing it to the original image.

Troubleshooting face swap issues by adjusting settings like feather, bbox crop factor, and bbox dilation.

Conclusion and call to action for viewers to like and follow for more tutorials.

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