Fix Faces with ADetailer in Stable Diffusion Automatic1111

FoxtonAI
12 Jul 202405:57

TLDRThis tutorial video demonstrates how to enhance and fix facial features in AI-generated images using the Stable Diffusion ADetailer extension in Automatic1111. The presenter guides viewers through generating a base image, applying ADetailer with YOLO face models, and refining prompts for detailed facial features. The video concludes with an image upscale to improve sharpness and clarity, showcasing a significant visual improvement over the original.

Takeaways

  • 🖼️ The video tutorial focuses on enhancing faces in AI-generated images using the Stable Diffusion ADetailer extension.
  • 🔧 Viewers are instructed to have ADetailer and the best face models installed for optimal results.
  • 💻 The demonstration is conducted on a Windows 11 PC using a local install of Automatic 1111.
  • 📝 A base image is generated without ADetailer to establish a comparison for the improvement process.
  • 📸 The tutorial highlights common AI-generated face distortions, such as lack of clarity when the face is distant from the camera.
  • 🔄 ADetailer is enabled in Automatic 1111, and settings are adjusted to refine the facial features of the generated image.
  • 📈 The use of YOLO face models within ADetailer is discussed, with a preference for the YOLO 8S model demonstrated.
  • 📑 Positive and negative prompt boxes are utilized to guide the facial detail enhancement process.
  • 🔍 The tutorial suggests using specific prompts like 'photo realistic extremely detailed face' for better results.
  • 🖌️ After generating the image with ADetailer, the video suggests upscaling to improve sharpness and clarity.
  • 🌐 Links to resources such as the Open Model Database and specific upscalers are provided for further enhancement tools.

Q & A

  • What is the main focus of the video?

    -The main focus of the video is to demonstrate how to fix and improve faces using the Stable Diffusion ADetailer extension in Automatic1111.

  • What are the prerequisites for following the tutorial?

    -To follow the tutorial, you need to have ADetailer and the best face models installed. If not, the video suggests watching an ADetailer installation video linked in the description.

  • Which operating system and software version is used in the video?

    -The video uses a Windows 11 PC with a standard local install of Automatic1111.

  • What is the first step in generating an image without using ADetailer?

    -The first step is to open Automatic1111, go to the text to image tab, and use a previously generated image as a base by dragging it into the text prompt box.

  • What checkpoint is used in the video for image generation?

    -The video uses the 'absolute reality SD 1.5' checkpoint for image generation.

  • What are the typical issues with AI-generated faces at a distance?

    -Typical issues include distortions and a lack of clarity in the face when it is at a distance from the camera.

  • How does the video suggest improving the face in the generated image?

    -The video suggests using ADetailer with the YOLO models, specifically the YOLO 8S model, to improve the face in the generated image.

  • What positive and negative prompts are recommended for the face in ADetailer?

    -For positive prompts, 'photo realistic extremely detailed face' is recommended, and for negative prompts, 'easy negative deformed face deformed eyes' is suggested.

  • What additional setting is adjusted to improve the final image's sharpness and clarity?

    -The video suggests doing a quick upscale using the '4 times NM KD super scale' as the upscaler to improve the sharpness and clarity of the final image.

  • Where can one find the best resource for upscalers?

    -The Open Model Database is mentioned as the best resource for upscalers.

  • What is the final result of using ADetailer and upscaling in the video?

    -The final result is a significant improvement in the face's detail and the overall sharpness and clarity of the image compared to the original base image.

Outlines

00:00

🖼️ Fixing and Improving Faces with Stable Diffusion

The video tutorial begins by introducing the process of enhancing facial features in AI-generated images using the Stable Diffusion and Detailer extension. The presenter instructs viewers to ensure they have the necessary software installed, specifically mentioning 'Ad Detailer' and the 'Best Face Models'. A link to an installation guide is promised in the video description. The tutorial continues on a Windows 11 PC, using a local installation of 'Automatic 1111'. The presenter demonstrates generating a base image without Detailer to establish a starting point. They then guide viewers through the process of generating an image with facial enhancements using the Detailer extension, selecting the 'Face YOLO 8s' model for better results. The tutorial also covers the use of positive and negative prompts to refine the facial details, and concludes with a suggestion to upscale the image for improved sharpness and clarity, recommending the '4x NMKD Super Scale' upscaler from the Open Model Database.

05:01

📈 Comparing Results and Final Touches

In the second paragraph, the video script describes the comparison between the original base image and the final image after applying the facial enhancements and upscaling. The presenter highlights the significant improvement in sharpness and clarity of the final image. They also provide a direct comparison between the original and the final result, emphasizing the effectiveness of the techniques used. The video concludes with a prompt for viewers to explore additional settings within the Detailer extension to further refine their results. The presenter expresses hope that the tutorial was helpful and teases the next video, inviting viewers to join them for more content.

Mindmap

Keywords

💡Stable Diffusion

Stable Diffusion is a type of AI model that generates images from textual descriptions. It is part of a broader category of AI technologies known as 'diffusion models'. In the context of the video, Stable Diffusion is used to create images, and the tutorial focuses on enhancing the quality of generated faces using an extension called 'ADetailer'.

💡ADetailer

ADetailer is an extension for the Stable Diffusion model that is designed to improve the detail and quality of specific parts of an image, particularly faces. The video script describes how to use ADetailer to fix and enhance the facial features in images generated by Stable Diffusion.

💡Automatic1111

Automatic1111 is a user interface for the Stable Diffusion model, allowing users to generate images through a more accessible and graphical interface. The video script walks through the process of using ADetailer within the Automatic1111 interface to improve the quality of generated faces.

💡YOLO

YOLO stands for 'You Only Look Once' and refers to a family of AI models that are used for object detection in images. In the video, YOLO models are used as face models within ADetailer to detect and enhance faces in the generated images.

💡Face Model

A face model in the context of the video is a specific type of AI model used by ADetailer to recognize and enhance facial features in images. The script mentions different YOLO face models, such as the 'YOLO 8S model', which is chosen for its effectiveness in improving the quality of faces.

💡Text Prompt

A text prompt is a textual description that users provide to the AI model to guide the generation of an image. In the video, the text prompt is used to generate a base image, and then ADetailer is applied to enhance the face within that image.

💡Positive Prompt

A positive prompt is a type of text prompt that includes desired attributes or qualities to be emphasized in the generated image. In the video, 'photo realistic extremely detailed face' is used as a positive prompt to guide ADetailer in enhancing the facial details.

💡Negative Prompt

A negative prompt is used to exclude certain attributes or qualities from the generated image. The video mentions 'easy negative deformed face deformed eyes' as a negative prompt to avoid facial distortions in the AI-generated image.

💡Upscale

Upscaling in the context of image generation refers to the process of increasing the resolution or clarity of an image. The video describes using an 'upscale' feature in Automatic1111 to improve the sharpness and clarity of the final image after facial enhancements have been made.

💡ESRGAN

ESRGAN stands for Enhanced Super-Resolution Generative Adversarial Networks. It is a type of AI model used for upscaling images while maintaining or improving their quality. In the video, '4 times NM KD super scale' is mentioned as an ESRGAN upscaler used to enhance the image's sharpness and clarity.

Highlights

Introduction to using Stable Diffusion with ADetailer extension to enhance faces in images.

Necessity of having ADetailer and the best face models installed for the process.

Link to ADetailer installation video provided for viewers.

Demonstration on a Windows 11 PC using a local install of Automatic 1111.

Generating a base image without ADetailer to compare improvements.

Using the 'absolute reality SD 1.5' checkpoint for image generation.

Observation of typical AI-generated facial distortions and lack of clarity.

Enabling ADetailer in Automatic 1111 to fix the face in the generated image.

Preference for YOLO models in ADetailer for better facial detail.

Comparison of different YOLO face models and selection of the 8S model.

Adding specific face-related prompts to the ADetailer prompt boxes for better results.

Use of 'photo realistic extremely detailed face' as a positive prompt.

Utilization of 'easy negative' prompt embedding to avoid common AI facial issues.

Leaving other ADetailer settings at default to evaluate base performance.

Significant improvement in facial detail observed after ADetailer application.

Exploration of additional ADetailer settings for further image enhancement.

Upscaling the final image to improve sharpness and clarity using NMKD super scaler.

Recommendation of Open Model Database for accessing various upscalers.

Final comparison showcasing the dramatic improvement from the original base image.

Encouragement for viewers to experiment with ADetailer settings for personalized results.