How to make AI Faces. ControlNet Faces Tutorial.

Sebastian Kamph
28 Apr 202314:42

TLDRThis tutorial guides viewers on how to use ControlNet to manipulate faces within Stable Fusion. The video begins by demonstrating the potential output when using ControlNet and offers tips to ensure successful results. The presenter explains the difference between 'face' and 'face only' in the preprocessor and how these settings affect the body's pose in the final image. Various techniques are discussed, including using negative styles to improve image quality, prompting the AI for specific actions, and adjusting the control step for variations. The tutorial also covers using different ControlNet models and the Mediapipe face option for additional detail. The presenter emphasizes the importance of testing different settings to achieve the desired outcome and concludes by encouraging viewers to explore further with workflow tutorials for more advanced techniques.

Takeaways

  • 🎨 Use ControlNet in Stable Fusion to manipulate faces and poses in generated images.
  • 📌 Select the appropriate preprocessor for faces, such as 'Face' or 'Face Only', to control the pose and direction.
  • 🔍 The 'Face Only' option allows the body to take any shape, while 'Face' restricts the body to match the pose.
  • 📈 Start with ControlNet version 1.1 for portrait images and use Stable Fusion 1.5 models.
  • 🔧 Adjust the control steps from 0 to 1 to fine-tune the level of control over the generated images.
  • 🚫 Negative styles can be used to correct issues like teeth misalignment in the generated faces.
  • ✅ Prompting the AI with specific actions (e.g., 'woman shouting') can help achieve the desired output even if not visible in the control image.
  • 🔄 Combining prompts with styles like 'digital oil painting' can enhance the quality and style of the generated images.
  • 🧩 Changing the ending control step can introduce variations while maintaining a base style for the generated images.
  • 👽 For full character images, use 'Open Pose Full' to control the entire character's pose, including hands.
  • ✍️ If faces are not generated correctly, use the inpainting tool to manually correct them for better results.
  • 🤖 Mediapipe Face is an alternative to ControlNet 1.1, offering more detailed control around the eyes and mouth.

Q & A

  • What is the main topic of the tutorial?

    -The main topic of the tutorial is how to control faces inside of stable Fusion using ControlNet.

  • What are the two preprocessor options available for faces in ControlNet?

    -The two preprocessor options available for faces in ControlNet are 'face' and 'face only'.

  • What happens when you use the 'face only' preprocessor option?

    -When you use the 'face only' preprocessor option, the body can take any shape around the face, whereas with the 'face' option, the body is restricted to having the same pose as indicated by the lines in the preprocessor.

  • What is the purpose of using negative styles in the generation process?

    -Negative styles are used to fix issues encountered in the generated images, such as incorrect facial features, by providing the AI with additional information to guide the image generation.

  • How can you prompt the AI to generate images with specific facial expressions?

    -You can prompt the AI to generate images with specific facial expressions by including descriptive text in the prompt, such as 'woman shouting', which tells the AI to generate images with the woman's mouth open.

  • What is the difference between using the 'full' and 'face only' models in ControlNet?

    -The 'full' model generates a full body with the face, while the 'face only' model focuses solely on the face, allowing the body to take any shape around it. The choice depends on whether you want the body's pose to be controlled or not.

  • What is the role of the 'control weighted' parameter in the ControlNet?

    -The 'control weighted' parameter determines the influence of the ControlNet on the image generation. Starting the control at 0 and ending at 1 means that the AI will gradually increase the control from no influence to full influence over the course of the render.

  • How can you introduce variations into the generated images?

    -You can introduce variations into the generated images by changing the ending control step, which alters the degree of control exerted by the ControlNet, allowing for more randomness or 'chaos' in the final output.

  • What is the significance of using the 'open pose' model in ControlNet?

    -The 'open pose' model in ControlNet is particularly useful when you want to change the style of the generated images, as it allows for more flexibility in the body's pose and can handle different styles effectively.

  • How can you fix facial features that are not generated correctly?

    -You can fix facial features that are not generated correctly by using the 'between painting' feature, which allows you to manually edit the face and instructs the AI to fill in the rest of the image with new material while keeping the original content intact.

  • What is the Mediapipe face model, and how does it differ from the ControlNet 1.1 face models?

    -The Mediapipe face model is a separate face detection model that provides more detailed information around the eyes, eyebrows, and mouth compared to the ControlNet 1.1 face models. It offers an alternative option for users to achieve better results based on their specific needs.

Outlines

00:00

😀 Introduction to Controlling Faces in Stable Fusion

The speaker begins by introducing the audience to the process of controlling faces within Stable Fusion, a tool that allows for the manipulation of facial features in images. They demonstrate how an input image can be transformed into various output results with the help of a control net. The tutorial also suggests installing necessary components if not already done, and provides a link to a previous video for guidance. A practical demonstration is given where an image of a woman shouting is used to explain the use of the face-only preprocessor option in Control Net, which allows for the control of facial features such as the mouth, nose, and eyes. The difference between 'face' and 'face only' preprocessor options is explained, highlighting how they affect the body's pose in the final image. The speaker also mentions the use of Control Version 1.1 with Stable Fusion 1.5 models and provides troubleshooting tips for common issues encountered with the face preprocessor.

05:02

🎨 Advanced Techniques for Control Net Image Generation

The paragraph delves into advanced techniques for generating images using Control Net. The speaker discusses the use of 'negative styles' to improve image quality and correct common issues like distorted teeth. They also explain how to prompt the AI for specific poses or actions not captured in the control image by adding descriptive text, as demonstrated with the example of a woman shouting. The paragraph further explores the use of different models and settings within Stable Fusion to achieve desired outcomes, such as using the 'open pose face only' model to allow for more variation in the body's pose while maintaining the face's pose. The speaker also touches on the process of generating images with variations by adjusting the control step settings, providing examples of how this can introduce a degree of randomness to the image generation process.

10:03

🚀 Exploring Open Pose and Media Pipe Face Models in Control Net

The final paragraph focuses on the use of the Open Pose model for full character images and the Media Pipe Face model as alternative options within Control Net. The speaker explains that Open Pose is particularly effective for changing styles and maintaining the integrity of the character's pose, even when faces are not clearly visible in the original image. They also demonstrate how to correct facial features that do not render well by using the 'digital painting' feature to manually adjust the face. The Media Pipe Face model is introduced as an alternative to Control Net's face models, offering more detailed control around the eyes, eyebrows, and mouth. The speaker encourages viewers to test different options to find the best fit for their specific needs and concludes with a reminder to subscribe for more content.

Mindmap

Keywords

💡ControlNet

ControlNet is a tool used for generating and manipulating AI-generated faces within the Stable Fusion software. It allows users to input specific facial features or poses and receive output images that reflect those inputs. In the video, the presenter demonstrates how to use ControlNet to control the facial features and poses of generated faces, such as a woman shouting, to achieve desired results.

💡Stable Fusion

Stable Fusion is a software platform that is used for creating and editing AI-generated images. It is mentioned in the video as the environment where ControlNet is being utilized. The presenter uses Stable Fusion to demonstrate the process of generating faces with ControlNet, highlighting its capabilities in producing detailed and controlled facial expressions and poses.

💡Face Preprocessor

The face preprocessor is a feature within ControlNet that allows users to preview and adjust the facial features and pose before generating the final image. It is used to ensure that the generated faces align with the desired input, such as the direction of the head and upper torso. The video shows how the face preprocessor can be manipulated to control the outline of the face, mouth, nose, and eyes.

💡Control Version

The control version refers to the specific model or version of ControlNet being used. In the video, the presenter mentions using Control version 1.1 and also references the existence of 2.1 models. The control version affects the level of detail and the options available for manipulating the AI-generated faces.

💡Open Pose

Open Pose is a model within ControlNet that is used for generating full body poses, including the face, body, and hands. It is highlighted in the video for its ability to capture detailed poses and is particularly useful when the presenter wants to change the style of the generated character, such as transforming a man walking into an astronaut on the moon.

💡Negative Styles

Negative styles are specific prompts or styles that are added to the generation process to avoid undesired outcomes. The video script mentions using negative styles to fix issues with the generated images, such as teeth appearing messed up. By including negative styles, the presenter is able to generate better and more accurate facial features in the output images.

💡Digital Oil Painting

Digital oil painting is a style option that can be applied to the generated images to give them a painterly, artistic appearance. In the context of the video, the presenter uses the digital oil painting style to enhance the visual appeal of the generated faces, making them look more like traditional oil paintings.

💡Image Upscaling

Image upscaling is a process that involves increasing the resolution of an image while maintaining or improving its quality. The video mentions image upscaling as a step that can be taken to further enhance the quality of the generated faces after they have been created with ControlNet and Stable Fusion.

💡In-Painting

In-painting is a technique used to fill in or correct parts of an image. In the video, the presenter discusses using in-painting to fix facial features that did not generate correctly, such as messy faces on a character that was supposed to be a Viking Warrior.

💡Media Pipe Face

Media Pipe Face is an alternative face model within ControlNet that offers more detailed control over facial features, particularly around the eyes, eyebrows, and mouth. The video compares Media Pipe Face with the standard ControlNet 1.1 face models, suggesting that it provides additional detail and could be a better option depending on the user's needs.

💡Ending Control Step

The ending control step is a parameter in ControlNet that determines the level of control exerted over the generation process. By adjusting the ending control step, the presenter in the video is able to introduce variations into the generated images, creating a mix of controlled and random elements to achieve a more diverse set of outputs.

Highlights

Learn how to control faces in stable Fusion using ControlNet.

Input an image and output various results while maintaining facial expressions and poses.

Utilize different preprocessor options for the face to achieve desired outcomes.

Control the direction of the head and upper torso for more natural-looking results.

Experiment with 'face only' and 'full' models to adjust the level of control over the generation.

Use Control Version 1.1 for optimal results with stable Fusion 1.5 models.

Adjust control weights and steps to fine-tune the facial features and pose.

Employ negative styles to improve image quality and correct common issues.

Prompt the AI with specific descriptions to achieve better facial expressions in the output.

Combine facial controls with various styles for enhanced image generation.

Explore the open pose face only model for greater flexibility in body positioning.

Vary the ending control step to introduce randomness and variation into the facial pose.

Utilize ControlNet and stable Fusion to create images with consistent facial poses and varied body positions.

Improve character generation by using open pose full for detailed facial and body control.

Incorporate MediaPipe Face for additional facial control options and more detailed facial features.

Apply image-to-image upscaling and inpainting for enhanced facial details and corrections.