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

Next Tech and AI
21 Dec 202310:30

TLDRThis video tutorial demonstrates how to perform face-swapping using Stable Diffusion with Automatic1111 WebUI and ControlNet. It guides viewers through the process of installing necessary models and checkpoints, including the IP adapter from H94 and the SD15-OpenPose.pth file. The video showcases face-swapping techniques on various examples, including challenging ones like side profile images and real photos. It details the steps to prepare images, set parameters like sampling method and noising strength, and use control net units for better results. The tutorial also touches on improving the swap by adjusting control steps and weights, and concludes with a creative example of swapping faces with an alien character. The video is a comprehensive guide for those interested in experimenting with face-swapping technology.

Takeaways

  • 🚀 Use Automatic1111 WebUI with ControlNet and the Plus-Face-IP-adapter for a simple and flexible face-swapping solution without proprietary development environments.
  • 📚 If ControlNet is not installed, refer to the upscaling video for instructions.
  • 🔍 Two additional models are needed: IP adapter from H94 on hugging face and SD15-OpenPose.pth from lllyasviel.
  • 📁 Place the IP adapter in the Stable Diffusion WebUI directory and OpenPose in the extensions folder.
  • 🔄 Check for updates in the extensions tab of the WebUI, particularly for ControlNet, and apply them.
  • 🖼️ Use the EPICrealism model to prepare target images for the face swap.
  • 🔍 In the image-to-image tab, place the target image and enable ControlNet unit 0 with the source face image.
  • 🎭 No prompt is needed; the required information is contained within the two images.
  • 🔢 Set the sampling method to DPM-2M-SDE-KARRAS, keep the resize at 1, and adjust noising strength and control step for best results.
  • 🖌️ After generating the initial face swap, use the inpaint tab to refine the mask and improve the result.
  • 👓 For face swaps involving glasses or beards, adjust the starting control step and control weight to match the target image.
  • 👽 Experiment with different control net units and models, such as open pose, for more realistic swaps.
  • 🎨 The IP adapter can also be used in text-to-image applications, allowing for creative and detailed generation.

Q & A

  • What is the main topic of the video?

    -The video is about how to perform a face swap using Stable Diffusion with Automatic1111 WebUI and ControlNet.

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

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

  • 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 role of the EPICrealism model in the face swap process?

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

  • How does one select the source image for the face swap?

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

  • What sampling method is recommended for the face swap process?

    -The recommended sampling method is DPM-2M-SDE-KARRAS.

  • Why is the starting control step not set to 0 in this process?

    -Setting the starting control step to 0 may cause the inserted face not to match the size of the original picture; hence, it is set to a value between 0.2 and 0.5.

  • How can one correct the orientation of the swapped face, such as the chin direction?

    -To correct the orientation, another control net unit can be enabled and the OpenPose model can be selected, which includes the full model for better control.

  • What is the significance of increasing the number of steps in the face swap process?

    -Increasing the number of steps improves the quality of the generated image, making it look more natural and less 'ugly'.

  • How can the face swap be improved when using a real photo?

    -The face swap can be improved by adjusting the starting control step and the control weight to better match the target image's features.

  • What is the potential application of the IP adapter for face swapping in text-to-image generation?

    -The IP adapter can be used to include facial details from a portrait into a generated image, enhancing the realism of the text-to-image output.

  • What is the recommended control weight when using a female robot picture with the IP-adapter-plus-face?

    -The control weight should be increased to 1.2 to ensure that several details from the portrait are included in the generated picture.

Outlines

00:00

😀 Introduction to Face Swapping with Automatic1111 WebUI

The video introduces a method for face swapping without the need for proprietary development environments using Automatic1111 WebUI and ControlNet with the Plus-Face-IP-adapter. It guides viewers through installing ControlNet checkpoints and demonstrates the face swap process with various examples. The video covers the use of Stable Diffusion, downloading necessary models from H94 on hugging face and lllyasviel, and placing them in the correct directories. It also explains how to prepare images for the face swap, enabling ControlNet units, selecting the correct IP-adapter and model, adjusting parameters like sampling method, noising strength, and control step. The video highlights the challenges of swapping faces in different orientations and the importance of increasing the number of steps for better results. It concludes with a demonstration of the process and a reminder to subscribe for more content.

05:05

🔍 Enhancing Face Swap Quality with Control Net Units

This paragraph focuses on improving the quality of face swaps by using additional control net units and the open pose model. It discusses the preference for the full open pose model to ensure all elements are included. The video demonstrates how to generate a better result by adjusting the starting control step and control weight, and how to make quick corrections in the inpaint section for more accurate results. It also explores using a real photo for the face swap, addressing challenges like missing glasses and imperfections in the beard and hair. The video then moves on to more creative applications, such as swapping faces with an alien and a female robot, and shows how the IP adapter can be used in text-to-image scenarios. It concludes with an encouragement to try the process and a call to action for likes or comments.

10:13

🎨 Advanced Techniques for Text-to-Image with IP Adapter

The final paragraph showcases advanced techniques for text-to-image using the IP adapter, building on the previous demonstrations of face swapping. It discusses the process of generating a suitable image with specific sampling methods and steps, and setting the height for the checkpoint. The video then illustrates how to use the control net with a different picture, in this case, a female robot created with SDXL, and how to adjust the control weight to achieve a desired level of detail from the portrait in the generated image. It concludes by encouraging viewers to try the process themselves.

Mindmap

Keywords

💡Face-Swap

Face-swap refers to the process of replacing one person's face with another's in a digital image or video. In the context of the video, it involves using specific software and models to achieve a realistic and seamless facial replacement. The video demonstrates how to perform a face-swap using the Stable Diffusion WebUI and ControlNet, which are tools for image manipulation.

💡Stable Diffusion

Stable Diffusion is a term used to describe a type of technology that can generate images from textual descriptions. In the video, it is mentioned as a foundational tool used in conjunction with the Automatic1111 WebUI to facilitate the face-swapping process. It is an essential component as it provides the base for the images into which faces are swapped.

💡ControlNet

ControlNet is a neural network architecture used for controlling image generation processes, such as face-swapping. The video explains how to integrate ControlNet with the Stable Diffusion WebUI to perform face-swapping. It is a critical tool for guiding the face-swapping process to ensure that the inserted face matches the orientation and lighting of the target image.

💡IP Adapter

An IP adapter, in the context of this video, refers to a specific model or tool used to enhance the face-swapping process. The script mentions downloading an 'IP adapter from H94 on hugging face' and another file from lllyasviel, which are used to improve the accuracy and quality of the face-swapped images. The IP adapter is crucial for the integration of different facial features in the final output.

💡EPICrealism

EPICrealism is a model mentioned in the video that is used to prepare images for the face-swapping process. It is likely a tool or algorithm designed to enhance the realism of images, making them more suitable for the face-swapping procedure. The video suggests that using EPICrealism can help in creating more challenging and realistic face-swapping scenarios.

💡Control Image

A control image is the source image containing the face that will be swapped onto the target image. The video script describes placing the control image with the source face into the independent control image section of the interface. This image is essential as it dictates the facial features that will be transferred to the target image during the face-swapping process.

💡Sampling Method

The sampling method refers to the technique used to generate the final image from the input data. In the video, 'DPM-2M-SDE-KARRAS' is set as the sampling method, which is a specific algorithm used for generating images in a way that reduces noise and artifacts, leading to a more refined and realistic output.

💡Noising Strength

Noising strength is a parameter that determines the level of noise or randomness introduced into the image generation process. The video mentions setting the noising strength to 1 to heavily modify the target image. This parameter is important as it affects the final quality and appearance of the face-swapped image.

💡Control Step

The control step is a parameter that determines the starting point of the control process in the face-swapping algorithm. The video suggests setting it between 0.2 and 0.5 to ensure the inserted face matches the size of the original picture. This parameter is crucial for the alignment and integration of the swapped face with the target image.

💡Inpaint Section

The inpaint section is a feature within the software that allows for the manual correction or editing of specific parts of the image. The video describes using the inpaint section to make quick corrections to the face-swapped image, such as adjusting the hairline, beard, and glasses. This tool is important for fine-tuning the final output and addressing any imperfections in the face swap.

💡Text-to-Image

Text-to-image refers to the process of generating images based on textual descriptions. The video mentions using the IP adapter in a text-to-image scenario, which suggests that the technology can be used to create images from textual prompts in addition to face-swapping. This showcases the versatility of the tools discussed in the video for various image generation tasks.

Highlights

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

To perform a face swap, you will need to install additional ControlNet checkpoints.

Two models are essential 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.

The OpenPose model should be installed in the Stable Diffusion WebUI extensions as a ControlNet model.

Updates for ControlNet can be checked and applied in the extensions tab of the WebUI.

The EPICrealism model can be used to prepare pictures for the face swap.

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

The sampling method DPM-2M-SDE-KARRAS is recommended for the face swap process.

No resizing is needed, so the 'resize by' parameter should remain at 1.

The noising strength should be set to 1 for heavy modification of the target image.

Select the downloaded IP-adapter and the model IP-adapter plus-face for the face swap.

The starting control step should be set between 0.2 and 0.5 to ensure the face matches the original picture size.

Inpainting can be used to correct any imperfections in the face swap result.

Another control net unit with the open pose model can be used to improve facial direction and alignment.

Higher denoising strength can fix minor imperfections in the face swap result.

Face swapping with real photos can be done, although it may require adjustments to the starting control step and control weight.

The IP adapter plus-face can be used for creative applications, such as swapping faces with fictional characters like aliens.

The IP adapter for face swapping can also be utilized in text-to-image applications.

Increasing the control weight can help incorporate more details from the source image into the generated picture.

The video provides a step-by-step guide on how to perform a face swap using the Automatic1111 WebUI and ControlNet.