Change Image Style With Multi-ControlNet in ComfyUI 🔥
TLDRIn this tutorial, the speaker demonstrates how to change an image's style from realistic to anime using Multi-ControlNet in ComfyUI. They guide viewers through installing necessary components like ConFI Manager and custom notes, and explain the workflow for generating masks to control image details. The speaker also shares a trick for removing backgrounds using ControlNet, showcasing the process step-by-step and discussing the use of different control net models to achieve the desired outcome. The tutorial concludes with tips on creating videos using multiple control nets for a stable result without flickering.
Takeaways
- 🎨 Use Multi-ControlNet in ComfyUI for more control over image generation, especially for achieving better or professional results.
- 📚 Install Confu Manager for easy management and installation of custom nodes.
- 🌐 Download necessary models and notes from Hugging Face website for different control net models.
- 🖼️ Use a pre-processor to generate a mask from an image for the diffusion model to create the desired output.
- 🔍 Include all pre-processors for different control net models to analyze and choose the right mask.
- 🎭 Transform a realistic picture into an anime style by using specific control net models and adjusting their weights.
- 📐 Utilize the CR multicontrol net stack to control which control net models are used in the image generation process.
- 🖱️ Adjust the control net strength (weight) to balance the influence of each control net model on the final image.
- 🌄 Remove unwanted background elements by using depth maps and inverting masks with the invert mask preprocessor.
- 📦 Organize the workflow with packages like Sweet Kuui for visual clarity and better node connections.
- 📹 For video creation, use multiple control nets and techniques like anime diff or warp fusion for more stable outputs.
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 a trick for removing the background.
Why might someone choose to use Multi-ControlNet over automatic 1111 in ComfyUI?
-One might choose to use Multi-ControlNet over automatic 1111 in ComfyUI because it provides more control over the generated image, which can be useful for achieving better or more professional results.
How can viewers obtain the workflow and notes mentioned in the video?
-Viewers can obtain the workflow and notes by downloading them through the provided GI p page link, or by using Confu Manager and following the installation process described in the video.
What is the purpose of the ControlNet pre-processor in the workflow?
-The ControlNet pre-processor is used for generating different types of masks from the input image, which allows the diffusion model to create different characteristics in the output image.
What is the significance of the 'CR multicontrol net stack' in the workflow?
-The 'CR multicontrol net stack' is significant as it allows the user to control which ControlNet model is used in the image generation process, enabling fine-tuning of the image style.
How does the video demonstrate the process of removing a background from an image?
-The video demonstrates the process by using a depth map in combination with line art, inverting the mask to apply it to the person instead of the background, and then using the new mask to generate an image without the person in the background.
What website is recommended for finding free images and videos for testing purposes?
-The website recommended for finding free images and videos is Pexels.
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 process, such as the checkpoint name, variational out encoder, and other parameters.
How can one adjust the influence of a ControlNet model on the final image?
-One can adjust the influence of a ControlNet model by changing the 'control net strength' or 'control net weight', which determines how much weight is given to that particular model in the image generation process.
What is the purpose of the 'cas sampler' in the workflow?
-The 'cas sampler' is used to generate the final image based on the settings and conditions provided, such as the model, positive and negative prompts, and other parameters.
How can viewers ensure they have all the necessary components for the workflow?
-Viewers can ensure they have all necessary components by checking the list of packages mentioned in the video, installing any missing custom notes through Confu Manager, or by searching for and installing them manually.
Outlines
🎨 Introduction to Multicontrol Net in COMI
The speaker begins by addressing the audience and introducing the topic of Multicontrol Net within COMI. They acknowledge that while many find the automatic 111 interface more user-friendly, Multicontrol Net offers more control over the generated image, which can be beneficial for achieving better or more professional results. The speaker outlines their intention to demonstrate converting a realistic style image to an anime style using Multicontrol Net and also mentions a trick for background removal. They proceed to guide the audience through the process of installing necessary components such as the Confi Manager and custom notes, and setting up the workflow for image style transformation.
🖼️ Building the Workflow for Style Transformation
The paragraph delves into the specifics of constructing the workflow for changing the style of an image. It details the use of the load image note to upload the content model and the necessity of a preprocessor to generate a mask for the diffusion model. The speaker discusses the various types of masks and their impact on the final image, emphasizing the importance of selecting the right control net models. They introduce the CR Multicontrol Net Stack, explaining how it allows for the selection and combination of different control net models to achieve the desired style transformation. The speaker also touches on the process of adjusting the control net strength to balance the influence of each model on the output image.
🌟 Fine-Tuning the Control Net Models
This section focuses on fine-tuning the control net models to achieve the desired anime style transformation. The speaker describes the process of generating multiple masks to analyze and decide which ones to use. They discuss the possibility of using different control net models together to control various aspects of the image such as depth, color, and shape. The speaker also addresses an issue with an unwanted person appearing in the background of the generated image and provides solutions, such as using the depth map in combination with line art to remove the background or adjusting the control net weight of the open pose model.
📚 Finalizing the Workflow and Generating the Image
The speaker concludes the tutorial by finalizing the workflow and generating the transformed image. They detail the settings for the efficient loader and the cas sampler, including the choice of checkpoint name, variational out encoder, and prompt adjustments. The speaker also discusses the aspect ratio settings and the inclusion of a save image note for convenience. They demonstrate how to remove unwanted elements from the background by inverting the mask and using the depth map creatively. The paragraph ends with a brief mention of advanced techniques for video creation and a thank you note to the viewers, inviting them to watch the next video.
Mindmap
Keywords
💡Multi-ControlNet
💡ComfyUI
💡ControlNet
💡Anime Style
💡Background Removal
💡Confu Manager
💡Control Net Strength
💡Open Pose
💡Depth Map
💡Variational Out Encoder
💡Efficient Loader
Highlights
Introduction to Multi-ControlNet within ComfyUI for image style transformation.
Comparison between automatic and manual control for achieving better and more professional image results.
Demonstration of changing a realistic image style to an anime style using Multi-ControlNet.
Tutorial on removing the background of an image using ControlNet.
Explanation of the workflow for using ControlNet, including downloading and installing necessary components.
Use of Confu Manager for easy installation of custom notes.
Utilization of Pexels for sourcing free images for testing and experimenting with stable diffusion.
Importance of choosing the right pre-processor and control model for generating masks.
Technique for generating multiple masks to analyze and select the desired control net.
Adjusting the control net strength to balance the influence of the mask on the final image.
Combining different control net models to control image depth, color, and shape.
Inclusion of a preview feature to visualize the mask created by the pre-processor.
Strategy for avoiding unwanted elements in the background by manipulating control net models.
Use of depth maps in combination with line art to refine the image and remove the background.
Inversion of masks to selectively apply effects on the subject rather than the background.
Customization of the final image using various settings in the efficient loader and sampler.
Option to save the generated image and compare it with the original for assessment.
Discussion on using multiple control nets for creating videos and the advantages of advanced techniques.
Conclusion and invitation to the next video for further insights.