Change Image Style With Multi-ControlNet in ComfyUI 🔥
TLDRThis tutorial demonstrates how to use Multi-ControlNet within ComfyUI to transform a realistic image into an anime style. It covers the installation of necessary components like Confu Manager and custom notes, and guides through the workflow of uploading an image, applying different control net models to generate masks, and adjusting their weights for desired effects. The presenter also shares a trick for removing backgrounds using control nets and provides a step-by-step guide on assembling the workflow, concluding with a comparison of the initial and final image results.
Takeaways
- 🎨 Use Multi-ControlNet within ComfyUI for more control over generated images and to achieve better or professional results.
- 📚 Install Confu Manager for easy management of custom notes, which can be found on the provided GitHub page.
- 🔍 Use different ControlNet pre-processors to generate various masks, allowing for different image characteristics.
- 🎭 Transform a realistic image into an anime style by using specific ControlNet models and adjusting their weights.
- 🖼️ Utilize the CR Multi-ControlNet Stack to control which ControlNet models are used in the image generation process.
- 🤖 The ControlNet strength (or weight) determines the influence of a particular ControlNet model on the output image.
- 📐 Use the CR Aspect Ratio to maintain the desired dimensions of the generated image.
- 🌳 For removing the background or changing it, use depth maps in combination with line art and other ControlNet models.
- 🧩 Clone the ControlNet stack to use more than one ControlNet model, which is useful for creating videos.
- 🎥 For video generation, besides using ControlNet models, consider advanced techniques like Anime Diff or Warp Fusion for more stable videos.
- 📝 Customize the prompt and settings in the efficient loader to align with the desired output, such as using a specific variational out encoder and adjusting the CFG scale.
Q & A
What is the main topic of the video?
-The main topic of the video is about using Multi-ControlNet within ComfyUI to change an image style from realistic to anime style and also to show a trick for removing the background using ControlNet.
Why is Multi-ControlNet considered more useful than automatic methods for image generation?
-Multi-ControlNet is considered more useful because it provides more control over the generated image, which can lead to better or more professional results tailored to the user's specific needs.
How can users install custom notes in ComfyUI?
-Users can install custom notes in ComfyUI by using Confu Manager, which can be found on the GI p page provided in the video. They can follow the simple installation process, which includes cloning the repository and installing the missing custom notes.
What is the purpose of the pre-processor in the context of image generation?
-The pre-processor is used to generate a mask from the input image, which the diffusion model can then use to generate the final image. Different types of pre-processors allow for the generation of different characteristics in the output image.
How does the CR Multi-ControlNet Stack help in the image generation process?
-The CR Multi-ControlNet Stack allows users to control which ControlNet model is used in the image generation process. It enables the selection and combination of different ControlNet models to control various aspects of the image, such as depth, color, or shape.
What is the significance of the 'control net strength' in the video?
-The 'control net strength' corresponds to the control net weight in the process, determining how much influence a particular ControlNet model has on the final image. A weight of one means full influence, while a reduced weight like 0.7 means the model's influence is lessened.
How does the presenter use the depth map to remove the background from an image?
-The presenter uses the depth map in combination with the line art ControlNet model. By inverting the mask and using the depth map, they can apply the mask to the person in the image rather than the background, effectively removing the background.
What is the role of the 'Efficient Loader' in the workflow?
-The 'Efficient Loader' is used to load the main settings for the image generation, such as the checkpoint name, variational out encoder, and other parameters. It helps streamline the process by organizing and loading these settings efficiently.
How can users create a video using different ControlNet models?
-Users can create a video by using image-to-image generation with different ControlNet models for each frame. This can be done in a simple manner by applying flickering effects using tools like D Vinci or Adobe for a quick video, or using more advanced techniques like Anime Diff or Warp Fusion for more stable videos.
What is the purpose of the 'Remove Background' section in the workflow?
-The 'Remove Background' section is used to create a mask that isolates the person or object in the image from the background. This is achieved by inverting the mask and using the depth map in combination with the line art ControlNet model.
How does the presenter ensure the final image matches their desired outcome?
-The presenter ensures the final image matches their desired outcome by carefully selecting and adjusting the ControlNet models and their respective weights. They also use the 'Remove Background' section to refine the image and remove unwanted elements.
Outlines
🎨 Introduction to Multi-Control Net for Image Style Conversion
The speaker introduces the topic of using Multi-Control Net within a specific software (referred to as 'comi') for image style conversion. They acknowledge the user-friendliness of 'automatic, 111' but emphasize that Multi-Control Net offers more control over the generated image, which is beneficial for achieving professional results. The workflow involves changing a realistic style image to an anime style and demonstrates a trick for background removal using Control Net. The speaker guides on installing necessary components like Confi Manager and downloading specific notes for the workflow.
🖼️ Building the Workflow for Image Style Transformation
The paragraph details the process of constructing a workflow for transforming an image into an anime style. It involves using various control net models to control different aspects of the image such as depth, color, and shape. The speaker explains how to use the CR Multi-Control Net Stack to select and control which control net models are used in the process. They also discuss adjusting the control net strength or weight to balance the influence of each model on the final output. The paragraph concludes with the speaker's intention to demonstrate the process using a realistic picture as an example.
🌟 Fine-Tuning the Control Net Models for Style Conversion
The speaker elaborates on the fine-tuning process of the control net models to achieve the desired style conversion. They discuss the inclusion of all pre-processors for different control net models to analyze and select the masks that will be used. The paragraph also covers the decision-making process regarding which control net models to use, such as line art and open pose, and how to connect them to the CR Multi-Control Net Stack. The speaker adjusts the control net strength for a more balanced output and connects the stack to the Efficient Loader, detailing the settings for the main model and the prompt used for the conversion.
📸 Addressing Background Issues and Finalizing the Image
The final paragraph addresses the issue of an unwanted person appearing in the background of the generated image. The speaker explores the use of depth maps and other control net models to manipulate the background and remove unwanted elements. They demonstrate how to invert masks to apply them to the subject rather than the background and how to connect the new masks to the control net stack. The paragraph concludes with the speaker showing the final result of the style-converted image without the unwanted background figure and briefly mentions techniques for creating videos using control net models.
Mindmap
Keywords
💡Multi-ControlNet
💡ComfyUI
💡Anime Style
💡Control Net Pre-Processor
💡CR Multi-Control Net Stack
💡Control Net Strength
💡Efficient Loader
💡Variational Out Encoder
💡CFG Scale
💡Remove Background
💡Invert Mask
Highlights
Multi-ControlNet is a tool within ComfyUI for changing image styles with more control than automatic options.
The tutorial focuses on changing a realistic style image to an anime style.
ControlNet allows for fine-tuning of image characteristics such as depth, color, and shape.
A trick for removing the background using ControlNet is demonstrated.
Confi Manager is used for installing and managing custom notes.
CR MultiControl Net Stack is used to control which ControlNet models are applied.
Different ControlNet models can be combined for more nuanced image generation.
The tutorial uses a realistic picture from Pexels for demonstration purposes.
ControlNet strength corresponds to the weight given to a particular model in the image generation process.
The use of a Variational Out Encoder is discussed for high-resolution fits.
The tutorial demonstrates how to connect the ControlNet stack to an Efficient Loader.
The process includes setting the aspect ratio and dimensions for the generated image.
A method for generating a mask to transform an image into an anime style is shown.
The tutorial explains how to avoid unwanted elements in the background by manipulating ControlNet masks.
Inversion of masks can be used to focus on specific elements of an image rather than the background.
The final output image can be compared to the initial image to assess the changes made.
The tutorial suggests using multiple ControlNets for creating videos, particularly for more stable outputs.
Advanced techniques like Anime Diff or Warp Fusion are mentioned for generating stable videos.