ComfyUI Mask Area Condition

A simple custom node for ComfyUI that analyzes the size (area) of a mask relative to the total image area. Its primary purpose is to enable conditional workflows, allowing you to run face detailing only when needed based on the size of the detected face.

Why Measure Mask Size?

Image generation models often struggle with rendering small details, especially faces. While nodes like Face Detailer (part of the popular Impact Pack) or ADetailer (After Detailer) can fix this using inpainting, running them unconditionally adds significant processing time, even if the face is already large and well-rendered.

While it's possible to achieve similar conditional logic by combining existing nodes (e.g., getting mask properties and using math/comparison nodes), this dedicated MaskAreaCondition node provides a streamlined, single-node solution specifically for this common optimization task, keeping your workflow cleaner and easier to manage.

This node helps optimize such workflows by checking the mask size first.

Features

• Mask Area Condition node:
  • Calculates the percentage of the mask area compared to the total tensor area.
  • Outputs a boolean (is_below_threshold) indicating if the mask percentage is less than the provided threshold.
  • Outputs the calculated mask size percentage (mask_area_percent).
  • Passes the original mask through (mask_passthrough) for easy chaining.
• Helper Node for Conditional Workflows:
  • Select Data based on Condition: Takes two data inputs (data_if_true, data_if_false) of any type and a boolean condition. It outputs either data_if_true or data_if_false based on the condition. This is useful for dynamically selecting workflow parameters (like KSampler steps) or routing final data (like images) based on the mask area condition.

Installation

Via ComfyUI Manager (Recommended)

1. Ensure you have ComfyUI Manager installed
2. Open ComfyUI and click the "Manager" button
3. Navigate to "Install Custom Nodes" tab
4. Search for "Mask Area Condition"
5. Click "Install"
6. Restart ComfyUI and reload the browser tab

Manual Installation

1. Navigate to your ComfyUI custom_nodes directory:

   cd /path/to/ComfyUI/custom_nodes/
   

2. Clone this repository:

   git clone https://github.com/a-und-b/ComfyUI_MaskAreaCondition.git
   

3. Restart ComfyUI

Usage

1. Add the Mask Area Condition node to your workflow (Category: mask/conditional).
2. Connect a MASK output from another node to the mask input.
3. Set the desired threshold_percent value (0-100).
4. Implement Conditional Logic using Select Data:
   • Identify the parameter you want to control based on the mask size (e.g., the steps input of a KSampler for inpainting).
   • Create two Primitive nodes holding the different values for that parameter (e.g., one Integer node with 28 for full processing, one with 1 for minimal processing/bypass).
   • Add the Select Data based on Condition node.
   • Connect the is_below_threshold output from Mask Area Condition to the condition input of Select Data.
   • Connect the Primitive node for the "condition is true" case (e.g., 28 steps) to the data_if_true input.
   • Connect the Primitive node for the "condition is false" case (e.g., 1 step) to the data_if_false input.
   • Connect the selected_data output of Select Data to the target parameter input (e.g., the KSampler's steps input).
5. Handle Output Image Routing (Optional but common): If your conditional process generates a different final image (e.g., an inpainted image vs. the original), you might still need a way to select the correct final image.
   • One common approach is to use a second Select Data based on Condition node.
   • Feed the original image (or bypassed image) into data_if_false.
   • Feed the processed image (e.g., inpainted image) into data_if_true.
   • Use the same is_below_threshold boolean as the condition.
   • The selected_data output will be the correct image to send to Save Image.
6. Optionally, use mask_area_percent for display or other logic, and mask_passthrough for the actual processing step.

Example Use Cases

• Optimize Face Detailing: Automatically skip computationally expensive face detailing (like Face Detailer or After Detailer) if the detected face mask is already large enough (i.e., when is_below_threshold is False).
• Conditional Image Processing: Apply different effects or processing steps based on the size of a masked object.
• Workflow Routing: Direct the workflow down different paths depending on whether a detected object meets a size criterion.
• Quality Control: Filter out or handle masks differently if they are too small or too large for subsequent reliable processing.

Acknowledgements

• Georg Neumann from KI Marketing Bootcamp for the initial code and concept
• The ComfyUI team and contributors for creating an amazing platform
• The vibrant ComfyUI community and all the custom node creators who continue to push the boundaries of what's possible
• Claude by Anthropic for assistance in code refactoring, optimization, and documentation

License

This project is licensed under the MIT License - see the LICENSE file for details.

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Created with ❤️ for the ComfyUI community.