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ComfyDeploy: How ComfyUI-RMBG works in ComfyUI?

What is ComfyUI-RMBG?

A ComfyUI node for removing image backgrounds using RMBG-2.0

How to install it in ComfyDeploy?

Head over to the machine page

  1. Click on the "Create a new machine" button
  2. Select the Edit build steps
  3. Add a new step -> Custom Node
  4. Search for ComfyUI-RMBG and select it
  5. Close the build step dialig and then click on the "Save" button to rebuild the machine

ComfyUI-RMBG

A ComfyUI node for removing image backgrounds using RMBG-2.0.

RMBG_3

Features

RMBG-2.0 is built on the innovative BiRefNet (Bilateral Reference Network) architecture, offering:

  • High accuracy in complex environments
  • Precise edge detection and preservation
  • Excellent handling of fine details
  • Support for multiple objects in a single image

Installation

  1. Clone this repository to your ComfyUI custom_nodes folder:
cd ComfyUI/custom_nodes
git clone https://github.com/1038lab/ComfyUI-RMBG
  1. RMBG Model Download:
  • The model will be automatically downloaded to ComfyUI/models/RMBG/ when first time using the custom node.

Usage

RMBG

Optional Settings :bulb: Tips

| Optional Settings | :memo: Description | :bulb: Tips | |----------------------|-----------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------| | Sensitivity | Adjusts the strength of mask detection. Higher values result in stricter detection. | Default value is 0.5. Adjust based on image complexity; more complex images may require higher sensitivity. | | Processing Resolution | Controls the processing resolution of the input image, affecting detail and memory usage. | Choose a value between 256 and 2048, with a default of 1024. Higher resolutions provide better detail but increase memory consumption. | | Mask Blur | Controls the amount of blur applied to the mask edges, reducing jaggedness. | Default value is 0. Try setting it between 1 and 5 for smoother edge effects. | | Mask Offset | Allows for expanding or shrinking the mask boundary. Positive values expand the boundary, while negative values shrink it. | Default value is 0. Adjust based on the specific image, typically fine-tuning between -10 and 10. | | Performance Optimization | Properly setting options can enhance performance when processing multiple images. | If memory allows, consider increasing process_res and mask_blur values for better results, but be mindful of memory usage. |

Basic Usage

  1. Load RMBG (Remove Background) node from the 🧪AILab/🧽RMBG category
  2. Connect an image to the input
  3. Get two outputs:
    • IMAGE: Processed image with transparent background
    • MASK: Binary mask of the foreground

Parameters

  • sensitivity: Controls the background removal sensitivity (0.0-1.0)
  • process_res: Processing resolution (512-2048, step 128)
  • mask_blur: Blur amount for the mask (0-64)
  • mask_offset: Adjust mask edges (-20 to 20)

About RMBG-2.0

RMBG-2.0 is developed by BRIA AI and uses the BiRefNet architecture which includes:

  • Localization Module (LM): Generates semantic maps for primary image areas
  • Restoration Module (RM): Performs precise boundary restoration using:
    • Original Reference: Provides general background context
    • Gradient Reference: Focuses on edges and fine details

The model is trained on a diverse dataset of over 15,000 high-quality images, ensuring:

  • Balanced representation across different image types
  • High accuracy in various scenarios
  • Robust performance with complex backgrounds

Requirements

  • ComfyUI
  • Python 3.10+
  • Required packages (automatically installed):
    • torch>=2.0.0
    • torchvision>=0.15.0
    • Pillow>=9.0.0
    • numpy>=1.22.0
    • transformers>=4.30.0
    • safetensors>=0.3.0

Credits

License

MIT License