ComfyUI 35 Grouped Nodes - Free Workflow - Stable Diffusion
TLDRThe video demonstrates an updated feature in ComfyUI's Stable Diffusion workflow, which allows users to group multiple nodes into a single, more manageable node. This new functionality enables customization of visible inputs, outputs, and widgets within the grouped node, streamlining the workflow. The tutorial shows how to convert nodes into a 'Group Loader', manage group settings, and rearrange nodes for a cleaner interface. The presenter also explains their workflow process, starting with a loader group, followed by sampling, latent upscaling, and post-processing steps, ending with saving the final image as a JPEG. The video concludes with a demonstration of the workflow in action.
Takeaways
- 😀 ComfyUI has a function to combine multiple nodes into a single grouped node, enhancing workflow organization.
- 🛠️ The grouping function has been improved to allow users to customize which inputs, outputs, and widgets are visible within the grouped node.
- 📋 The default ComfyUI workflow can be made neater by converting several nodes into a grouped node, simplifying the interface.
- 🔍 Users can manage the visibility of widgets within a grouped node through a management window, allowing for a cleaner and more focused workflow.
- 📝 The script demonstrates how to convert nodes into a 'group loader' to streamline the workflow and make it easier to follow.
- 🎨 The updated workflow organizes steps from left to right, making it logical and less cluttered, with the option to hide rarely used widgets.
- 🖼️ The workflow includes stages for loading, sampling, latent upscaling, detail enhancement, image upscaling, post-processing, and saving the final image.
- 🔄 The process starts with a loader group for prompts, checkpoint, and image size, followed by a sampler for initial image creation.
- 🔍 Further processing may involve a latent upscaler and a face detailer, depending on the needs of the image refinement.
- 🌟 Post-processing includes color, sharpening, vignette, and film grain adjustments before the final image is saved as a JPEG.
- 🔗 The video provides a link to download additional workflows and demonstrates the practical use of the grouping function in the default workflow.
Q & A
What is the main feature discussed in the video script about ComfyUI 35?
-The main feature discussed is the function to combine several different nodes into one new grouped node, which has been improved to allow users to decide which inputs, outputs, and widgets they want to see inside the new node.
How does the new function of grouping nodes in ComfyUI 35 make the workflow more user-friendly?
-The new function allows users to manage the visibility of widgets within the grouped node, rearrange the nodes, and customize the workflow to focus on the elements they frequently use, making the workflow neater and more tailored to individual needs.
What is the default workflow in the ComfyUI 35 video?
-The default workflow in the video is a stable diffusion workflow that has been rearranged for neatness and tidiness, which includes a loader group, pipe sampler, latent upscaler, phase detailer, image upscaling, post-processing, and saving the image as a JPEG.
How can users customize the visibility of widgets within a grouped node in ComfyUI 35?
-Users can right-click the grouped node, select it, and then manage the group node to choose which widgets should be visible or not, by checking or unchecking the visibility options.
What is the purpose of the 'Group Loader' in the ComfyUI 35 workflow?
-The 'Group Loader' is used to combine multiple nodes into a single node for easier management and to streamline the workflow, focusing on the checkpoint loader's function.
How does the video script describe the process of rearranging nodes within a grouped node?
-The script describes the process as selecting the grouped node, right-clicking to manage it, and then using the six dots to rearrange the internal nodes to the desired order.
What is the initial step in the ComfyUI 35 workflow when trying out a new prompt?
-The initial step is to use the loader group with prompts, checkpoint, and image size, and then activate the first sampler to quickly generate multiple images to select the ones for further processing.
How long does it take to generate one image in the ComfyUI 35 workflow with the turbo checkpoint?
-It takes close to six or seven seconds to generate one image with the turbo checkpoint on the user's system.
What is the final step in the ComfyUI 35 workflow after image upscaling?
-The final step is to save the image as a JPEG, which includes the workflow information generated at the first step.
How can users access the updated default workflow mentioned in the video script?
-Users can access the updated default workflow through the link provided in the text description of the video, which leads to a folder containing all the workflows.
Outlines
🛠️ Customizing Group Nodes in COMI Workflow
The video script discusses an updated feature in COMI that allows users to group different nodes into a single, more manageable node. This feature has been overhauled to provide greater flexibility, enabling users to choose which inputs, outputs, and widgets to display within the grouped node. The narrator demonstrates this by rearranging notes in the default COMI workflow, converting them into a group node named 'group loader'. They then manage the group node's visibility of widgets, making some visible and others invisible based on their usage. The narrator emphasizes the improved workflow organization and focus on essential parameters, showcasing a cleaner and more efficient interface.
🖼️ Streamlining Image Generation with COMI's Group Nodes
In the second paragraph, the script continues to explore the use of group nodes in COMI for streamlined image generation. The narrator explains their general workflow, starting with a loader group for prompts, checkpoints, and image size, followed by a sampler for initial image creation. They describe how they activate only the loader and sampler initially when testing new prompts, generating multiple images to select the most promising ones. Once an image is chosen, they proceed with latent upscaling, potentially followed by a face detailer if needed, and then image upscaling with optional post-processing steps. The narrator also mentions the inclusion of an adapter or control net in the workflow and provides a download link for additional resources. The paragraph concludes with a demonstration of the streamlined workflow in action, resulting in an upscaled image, and an invitation for viewers to enjoy the process.
Mindmap
Keywords
💡ComfyUI
💡Grouped Nodes
💡Workflow
💡Convert to Group
💡Widgets
💡Checkpoint
💡Sampler
💡Latent Upscale
💡Post Processing
💡JPEG
💡Turbo Checkpoint
Highlights
ComfyUI 35 introduces a new function to combine multiple nodes into a single grouped node.
The function has been improved to allow customization of inputs, outputs, and visible widgets within the grouped node.
Users can now manage the group node to select which widgets to display or hide.
The checkpoint name widget is an example of a commonly visible widget in the group node.
Widgets like batch size and D noise can be set to invisible if not frequently changed.
Nodes within a group can be rearranged for a cleaner workflow.
The updated workflow simplifies the process by removing unnecessary widgets.
The default workflow operates from left to right, making it easy to follow.
Grouping nodes helps declutter the workflow and focus on essential parameters.
Workflow steps include a loader group, pipe sampler, latent upscale, phase detailer, image upscaling, and post-processing.
The workflow starts with a loader group containing prompts, checkpoint, image size, and styler.
The pipe sampler is crucial for the initial creation and selection of images.
Further processing may involve a latent upscale followed by a phase detailer if needed.
Image upscaling and post-processing steps can be enabled or disabled based on user preference.
The final step is saving the image as a JPEG, which includes the workflow from the first step.
When testing new prompts, only the loader and first sampler are initially active for quick image generation.
The workflow allows for the quick selection of preferred images for further processing.
Optional steps like the latent upscaler and face detailer can be added based on user satisfaction with the image.
The workflow efficiency is demonstrated with the ability to upscale images and adjust post-processing settings.
The video concludes with a demonstration of the final image produced using the updated workflow.
