How to FACE-SWAP with Stable Diffusion and ControlNet. Simple and flexible.

Next Tech and AI
21 Dec 202310:30

TLDRThe video tutorial provides a step-by-step guide on how to perform face-swapping using Stable Diffusion with Automatic1111 WebUI and ControlNet. It covers the installation of necessary models, including the IP adapter from H94 and SD15-OpenPose.pth, and their placement in the appropriate directories. The process involves setting up ControlNet units, selecting the correct models and adapters, and adjusting parameters such as the sampling method, noising strength, and control step for optimal results. The video also demonstrates how to address challenges like incorrect facial direction and mismatched facial features by using additional control net units and adjusting control weights. It concludes with examples of face-swapping with real photos and even an alien, showcasing the flexibility and potential of the technique. The tutorial is an excellent resource for those interested in exploring face-swapping technology without proprietary development environments.

Takeaways

  • 🚀 Use Automatic1111 WebUI with ControlNet and the Plus-Face-IP-adapter for a simple and flexible face-swapping solution without proprietary development environments.
  • 📚 Install additional ControlNet checkpoints and follow instructions provided in the upscaling video for setup.
  • 🔍 Two models are needed: IP adapter from H94 on hugging face and SD15-OpenPose.pth from lllyasviel.
  • 📂 Place the downloaded models in the respective directories of the Stable Diffusion WebUI for ControlNet and extensions.
  • 🔄 Check for updates in the WebUI extensions tab, especially for ControlNet, and apply them if necessary.
  • 🖼️ Use the EPICrealism model to prepare images for the face swap, which can be installed via the upscale video.
  • 🔧 Enable ControlNet unit 0 and use an image with the source face as the control image for the face swap.
  • ⚙️ Set the sampling method to DPM-2M-SDE-KARRAS, keep the resize at 1, and adjust noising strength and control step for best results.
  • 🎭 Select the appropriate IP-adapter and model for the face swap, and adjust the starting control step for a good fit.
  • 🖌️ Use the inpaint tab to create a mask for the face area and refine the face swap result.
  • 👓 Improve the face swap by adjusting the starting control step and control weight, especially for elements like glasses and hair.
  • 👽 For fun, experiment with swapping faces with unconventional images like aliens, and adjust control settings to fit the new context.
  • 📝 The IP adapter can also be used in text-to-image applications, offering further creative possibilities.

Q & A

  • What is the main topic of the video?

    -The main topic of the video is how to perform face-swapping using Stable Diffusion with Automatic1111 WebUI and ControlNet.

  • Which additional models are required for the face swap process?

    -Two additional models are required: an IP adapter from H94 on hugging face and a file named SD15-OpenPose.pth from lllyasviel.

  • Where should the downloaded models be placed within the Stable Diffusion WebUI directory?

    -The IP adapter-Plus-Face should be placed in the 'models ControlNet' directory, and OpenPose should go into 'extensions' as part of the WebUI ControlNet models.

  • What is the purpose of the EPICrealism model in the face swap process?

    -The EPICrealism model is used to prepare some pictures for the face swap, enhancing the quality of the images used in the process.

  • How is the source image for the face swap placed in the WebUI?

    -The source image with the face to be swapped is placed in the 'independent control image' section with ControlNet unit 0 enabled.

  • What sampling method should be set for the face swap process?

    -The sampling method to be set is DPM-2M-SDE-KARRAS.

  • Why is the starting control step not set to 0 during the face swap?

    -The starting control step should be set between 0.2 and 0.5 to ensure the inserted face matches the size of the original picture; otherwise, it might not fit correctly.

  • What is the role of the inpaint tab in the face swap process?

    -The inpaint tab is used to copy the image and draw a mask around the area where the face will be swapped, allowing for more precise editing.

  • How can the face swap result be improved if the facial features do not match perfectly?

    -The face swap result can be improved by adjusting the starting control step, increasing the control weight, or making quick corrections in the inpaint section.

  • What is the significance of using a higher denoising strength in upscaling?

    -Using a higher denoising strength in upscaling can help fix minor imperfections in the face swap, such as inconsistencies in hair or facial features.

  • How can the IP adapter for face swapping be used in text to image generation?

    -The IP adapter for face swapping can be utilized in text to image generation to include facial features, clothing, and skin details into the generated images.

  • What is the recommended control weight when using a different picture for text to image generation?

    -The recommended control weight to be increased to 1.2 when using a different picture for text to image generation to ensure the inclusion of several details from the portrait.

Outlines

00:00

😀 Introduction to Face Swapping with Automatic1111 WebUI

The video begins with an introduction to face swapping using the Automatic1111 WebUI and ControlNet with the Plus-Face-IP-adapter. The host explains that this method avoids the need for proprietary development environments and is a straightforward solution. The audience is guided through the process of installing ControlNet checkpoints and performing face swaps with various examples. Key components include using Stable Diffusion, downloading necessary models from H94 and lllyasviel, and placing them in the correct directories. The video also covers the use of the EPICrealism model for preparing images, and detailed steps for performing the face swap, including setting up ControlNet units, choosing the correct models and adapters, and adjusting parameters such as sampling method, noising strength, and control steps.

05:05

🎨 Enhancing Face Swaps with Control Net Units

The second paragraph focuses on improving the face swap process by utilizing additional control net units and the open pose model. The host demonstrates how to correct issues like the direction of the chin by enabling another control net unit and selecting the open pose model. The importance of painting the hairline and the potential for upscaling with higher denoising strength to fix imperfections is discussed. The video then transitions to a face swap with a real photo, addressing challenges such as the transparency of the background and the accuracy of the glasses and beard in the result. The host also suggests increasing the control weight and starting control step to refine the face swap. The paragraph concludes with a creative example of swapping a human face with an alien's, demonstrating the flexibility of the tool.

10:13

👽 Exploring Advanced Uses of IP Adapter for Face Swapping

The final paragraph explores advanced uses of the IP adapter for face swapping, including its application in text-to-image scenarios. The host shares a personal test where details from a portrait were successfully included in the generated image, covering face, cloth, and skin. The video encourages viewers to try the process for themselves, emphasizing the potential for creative and detailed results.

Mindmap

Keywords

💡Face-Swap

Face-swap is the process of replacing one person's face with another in a digital image or video. In the video, it is a central theme where the host demonstrates how to use specific software and models to swap faces in images, creating a new visual output.

💡Stable Diffusion

Stable Diffusion is a term that refers to a type of machine learning model used for generating images from textual descriptions. In the context of the video, it is the foundational technology used in conjunction with other tools to perform the face-swapping process.

💡ControlNet

ControlNet is a neural network architecture designed to control and manipulate image generation tasks such as face-swapping. The video explains how to integrate ControlNet with Stable Diffusion to achieve more precise and flexible face-swapping results.

💡IP Adapter

An IP (Intermediate Representation) adapter is a tool used to adapt and translate the input data for the face-swapping models. The video mentions downloading an IP adapter specifically designed for face-swapping tasks to enhance the process.

💡Hugging Face

Hugging Face is a company that provides a platform for developers to share and use machine learning models. In the video, it is mentioned as the source for obtaining the IP adapter model necessary for the face-swapping process.

💡EPICrealism

EPICrealism is a model used for generating highly realistic images. The video's host uses this model to prepare pictures for the face-swapping process, emphasizing the importance of realistic source material for the face swap.

💡Control Image

A control image is a specific input used by the face-swapping software to guide the transformation process. In the video, the host uses an image with a source face as the control image to direct how the face-swap should look.

💡Sampling Method

The sampling method refers to the technique used by the AI to generate the final image. DPM-2M-SDE-KARRAS, mentioned in the video, is a specific sampling method chosen for its effectiveness in creating high-quality face-swapped images.

💡Noising Strength

Noising strength is a parameter that determines the level of noise or randomness introduced into the image generation process. The video explains setting this parameter to achieve the desired level of modification in the target image during face-swapping.

💡Inpaint Tab

The inpaint tab is a feature within the software that allows for manual editing or 'painting' of specific areas of the image. The host uses this feature to make corrections and refinements to the face-swapped image, such as adjusting the hairline.

💡Control Step

The control step is a parameter that determines the influence of the control image on the final output. The video demonstrates adjusting the control step to ensure the swapped face matches the orientation and features of the original image.

💡Text to Image

Text to image is a process where a machine learning model generates an image based on a textual description. The video shows an additional application of the IP adapter in generating images from text, showcasing the versatility of the tool.

Highlights

Automatic1111 WebUI with ControlNet and the Plus-Face-IP-adapter offers a simple and flexible solution for face-swapping without installing proprietary development environments.

The video provides a detailed guide on installing additional ControlNet checkpoints for face-swapping.

Two models are necessary for the face swap: an IP adapter from H94 on hugging face and a file from lllyasviel.

The IP adapter-Plus-Face-SD15 SaveTensors should be placed in the Stable Diffusion WebUI directory under models ControlNet.

The OpenPose file should be placed in the Stable Diffusion WebUI extensions as the WebUI ControlNet models.

In the extensions tab of the WebUI, users can check for updates of ControlNet and apply them.

The EPICrealism model can be used to prepare images for the face swap, with instructions available in an upscale video.

ControlNet unit 0 should be enabled, and the source face image should be placed in the independent control image section.

No prompt is needed for the face swap as all required information is contained within the two images.

The sampling method should be set to DPM-2M-SDE-KARRAS, and the noising strength should be set to 1 for heavy modification.

The downloaded IP-adapter and model IP-adapter-plus-face should be selected, and the starting control step should be between 0.2 and 0.5.

To swap the face, copy the image to the inpaint tab and apply a mask with a small brush before finishing with a larger brush.

Increasing the number of steps between 50 and 60 can improve the face swap result.

Using another control net unit with the open pose model can help correct facial features like the chin direction.

The face swap can be further improved by adjusting the starting control step or increasing the control weight.

Inpaint section can be used for quick corrections to improve facial features such as beard, hair, and glasses.

The face swap can be performed with real photos, avoiding copyright issues by using personal images.

The IP adapter for face swapping can also be used in text-to-image applications, offering a wide range of creative possibilities.

The video demonstrates the use of the IP adapter in text-to-image with a female robot example, showcasing the inclusion of various details.