Stable Cascade in ComfyUI with Updated Method and Custom Workflows
TLDRIn this informative video, the presenter introduces an updated method for utilizing Stable Cascade in ComfyUI, complete with custom workflows. The tutorial guides viewers through downloading specific checkpoints from the ComfyUI repository, explains the process of text-to-image and image-to-image workflows, and offers tips for improving the quality of generated images. The presenter also shares personal methods for refining the噪点 and achieving higher resolution images, providing a comprehensive guide for users to enhance their Stable Cascade experience in ComfyUI.
Takeaways
- 🔍 The video introduces an updated method for using Stable Cascade in Comfort UI with custom workflows.
- 📚 Download specific checkpoints for Comfort UI from the Stable Cascade examples page in the comfy UI repo.
- 📱 For users with the portable Windows version, checkpoints should be placed in the 'comy UI/models/checkpoints' folder.
- 🌟 The text-to-image workflow is explained, highlighting the process from text encoding to image generation through stages C, B, and A.
- 🎨 The image-to-image workflow is demonstrated, showing how to convert an image into latents and then enhance it using Stable Cascade.
- 💡 The video creator shares two custom methods to improve the quality of Stable Cascade images, addressing issues like noise and oversharpening.
- 🛠️ The first custom method is a high-resolution fix, which involves a two-pass Stable Cascade process with upscaling and denoising.
- 🔄 The second method combines Stable Cascade with an XD XL model, using a two-stage control net to maintain composition and improve image quality.
- 🔎 A third workflow is presented for creating high-quality widescreen wallpapers with a triple pass Stable Cascade at different resolutions.
- 🌐 The importance of maintaining aspect ratio and experimenting with compression and denoising values for optimal image quality is emphasized.
- 🎥 The video concludes with a recommendation to experiment with both custom methods to determine which works best for different scenarios.
Q & A
What is the main topic of the video?
-The main topic of the video is the updated method for using Stable Cascade in ComfyUI, including an overview of the workflows provided by Comfy Anonymous and the introduction of some custom workflows.
Where can the checkpoints for ComfyUI be downloaded from?
-The checkpoints for ComfyUI can be downloaded from the Stable Cascade examples page in the ComfyUI repo.
What are the two models that need to be downloaded for using Stable Cascade with ComfyUI?
-The specific models to be downloaded are not named in the script, but they can be found on the Hugging Face repo under the provided links at the top of the examples page.
How does one update ComfyUI to work with the new nodes?
-To update ComfyUI, one needs to have the ComfyUI manager installed. Then, they should go to the manager, click on 'update comy', wait for a few seconds, exit the command prompt, and restart ComfyUI.
What is the purpose of the new node for generating latent images in the Stable Cascade workflow?
-The new node for generating latent images is used specifically for the Stable Cascade models. It allows users to pick the width and height for the final image and set a compression factor to compress the latency for the first stage of the generation process.
What is the recommended compression factor for the Stage C of the Stable Cascade generation process?
-The recommended compression factor for Stage C is 42, which works well with a resolution of 1024 by 1024.
How does the text to image workflow function in the video?
-The text to image workflow starts by loading the Stage C model, creating a text encoding, feeding it into a sampler, and then running the latents through special Cascade conditioning into Stage B and Stage A, resulting in the final image.
What is the difference between the image to image workflow and the text to image workflow?
-The main difference is that the image to image workflow uses a node for converting images into latents specifically for the Stable Cascade models, whereas the text to image workflow starts with creating an empty latent.
What aesthetic issue does the video address with Stable Cascade images?
-The video addresses the overbaked or oversharpened look of Stable Cascade images, and the particular noise that appears in textures like grass and gravel, which the creator finds less appealing.
How does the highres fix method improve the quality of Stable Cascade images?
-The highres fix method improves the image quality by doing a two-pass Stable Cascade process. The first pass generates the initial image, which is then upscaled and denoised before being passed through Stable Cascade again. This helps reduce noise and the overbaked look.
What are the custom nodes used in the video for the Stable Cascade to XD XL workflow?
-The custom nodes used in the video for the Stable Cascade to XD XL workflow include the Control Net Ore Ox, which provides pre-processors and models for better image composition and detail.
Outlines
🖼️ Introduction to Stable Cascade and Comfy UI Workflows
The video begins by introducing the viewer to an updated method for using Stable Cascade in Comfy UI. The host plans to demonstrate workflows from the Comfy UI repository and share custom workflows. The first step involves downloading checkpoints from the Comfy UI repo, specifically those designed for the platform. The host provides instructions on where to find and download these models and where to store them, depending on the user's setup. The video then moves on to explain the text-to-image workflow, highlighting the process of creating a text encoding and feeding it into a sampler. The host also emphasizes the importance of updating Comfy UI to ensure compatibility with the new workflows.
🌐 Text-to-Image Workflow and Stable Cascade Execution
In this paragraph, the host runs a text-to-image workflow using the Stable Cascade method. They explain the process of generating an image based on a provided prompt, which includes loading checkpoints and going through various stages of the workflow. The host also discusses the resulting image, noting the unique characteristics of Stable Cascade models, such as their tendency to produce a particular noise in textures like grass and gravel. The paragraph concludes with the host suggesting two methods to address these issues and promising to share them in the video.
🔍 High-Res Fix Method for Stable Cascade
The host introduces a high-resolution fix method for Stable Cascade, which involves a two-pass process. The first pass is similar to the text-to-image workflow, but with the addition of upscaling the generated image by 1.5 times and converting it back into latents. The second pass involves denoising with a recommended value range of 0.2 to 0.6, depending on the image. The host demonstrates the effectiveness of this method by showing an improved text clarity and reduced noise in the final image, thus enhancing the overall quality.
🎨 Stable Cascade to SDXL Workflow and Custom Nodes
The host presents a workflow that transitions from Stable Cascade to SDXL, using custom nodes and models. The workflow aims to maintain the composition quality from Stable Cascade while improving the visual aesthetics. The host explains the process of converting the initial image into latents with a reduced compression factor and then running it through a two-stage control net. They also mention the installation of specific custom nodes and models required for this workflow. The video shows the results of this method, highlighting the improved image quality and adherence to the original prompt.
🌟 Triple Pass Workflow for Enhanced Image Quality
The final paragraph discusses an extension of the high-res fix method, involving a triple pass for even higher image quality. The host sets custom resolutions for each pass, emphasizing the importance of maintaining aspect ratios and using multiples of 64 for optimal results. The video demonstrates the process, showing how each pass refines the image and reduces noise. The host concludes by comparing the initial and final images, showcasing the significant improvements in detail and overall visual appeal. The paragraph ends with the host's personal preference for this method and a suggestion to use it for creating wallpapers.
Mindmap
Keywords
💡Stable Cascade
💡ComfyUI
💡Checkpoints
💡Workflows
💡Text-to-Image
💡Image-to-Image
💡Latent Images
💡Compression Factor
💡Denoising
💡Two-Stage Control Net
💡Highres Fix
Highlights
Updated method for using Stable Cascade in Comfort UI
Custom workflows for Stable Cascade in Comfort UI
Downloading checkpoints specifically made for Comfort UI
Explaining the workflow of Text to Image conversion
Using Stage C model for text encoding and sampler
The importance of updating Comfy UI for new features
Generating latent images for Stable Cascade models
Adjusting compression factor for different resolutions
Exploring Image to Image workflow for Stable Cascade
Converting images into latents for Stable Cascade models
Highres fix method for Stable Cascade to improve image quality
Two-pass Stable Cascade for enhanced text and composition
Using XD XL models for a specific aesthetic look
Cascade to SDXL workflow for maintaining composition
Installing custom nodes for Control Netore Ox
Triple pass Stable Cascade for detailed wallpapers
Adjusting denoising value for composition and detail balance
Upscaling and final pass for high-quality images