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# ComfyUI-RMBG
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A ComfyUI custom node designed for advanced image background removal and object, face, clothes, and fashion segmentation, utilizing multiple models including RMBG-2.0, INSPYRENET, BEN, BEN2, SAM, and GroundingDINO.
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A ComfyUI custom node designed for advanced image background removal and object, face, clothes, and fashion segmentation, utilizing multiple models including RMBG-2.0, INSPYRENET, BEN, BEN2, BiRefNet-HR, SAM, and GroundingDINO.
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$${\color{red}If\ this\ custom\ node\ helps\ you\ or\ you\ like\ my\ work,\ please\ give\ me⭐on\ this\ repo!}$$
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$${\color{red}It's\ a\ greatest\ encouragement\ for\ my\ efforts!}$$
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$$\textcolor{red}{\Huge \text{If this custom node helps you or you like my work, please give me ⭐ on this repo!}}$$
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$$\textcolor{red}{\Huge \text{It's a great encouragement for my efforts!}}$$
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## News & Updates
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- 2025/02/07: Update ComfyUI-RMBG to v1.8.0 with new BiRefNet-HR model ( [update.md](https://github.com/1038lab/ComfyUI-RMBG/blob/main/update.md#v180-20250207) )
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- Added a new custom node for BiRefNet-HR model.
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- Support high resolution image processing (up to 2048x2048)
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- 2025/02/04: Update ComfyUI-RMBG to v1.7.0 with new BEN2 model ( [update.md](https://github.com/1038lab/ComfyUI-RMBG/blob/main/update.md#v170-20250204) )
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- Added a new custom node for BEN2 model.
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- 2025/01/22: Update ComfyUI-RMBG to v1.6.0 with new Face Segment custom node ( [update.md](https://github.com/1038lab/ComfyUI-RMBG/blob/main/update.md#v160-20250122) )
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## Features
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- Background Removal (RMBG Node)
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- Multiple models: RMBG-2.0, INSPYRENET, BEN
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- Multiple models: RMBG-2.0, INSPYRENET, BEN, BEN2
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- Various background options
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- Batch processing support
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@@ -92,12 +101,12 @@ install requirment.txt in the ComfyUI-RMBG folder
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### 3. Manually download the models:
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- The model will be automatically downloaded to `ComfyUI/models/RMBG/` when first time using the custom node.
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- Manually download the RMBG-2.0 model by visiting this [link](https://huggingface.co/briaai/RMBG-2.0/tree/main), then download the files and place them in the `/ComfyUI/models/RMBG/RMBG-2.0` folder.
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- Manually download the RMBG-2.0 model by visiting this [link](https://huggingface.co/1038lab/RMBG-2.0), then download the files and place them in the `/ComfyUI/models/RMBG/RMBG-2.0` folder.
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- Manually download the INSPYRENET models by visiting the [link](https://huggingface.co/1038lab/inspyrenet), then download the files and place them in the `/ComfyUI/models/RMBG/INSPYRENET` folder.
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- Manually download the BEN model by visiting the [link](https://huggingface.co/1038lab/BEN), then download the files and place them in the `/ComfyUI/models/RMBG/BEN` folder.
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- Manually download the BEN2 model by visiting the [link](https://huggingface.co/1038lab/BEN2), then download the files and place them in the `/ComfyUI/models/RMBG/BEN2` folder.
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- Manually download the BiRefNet-HR by visiting the [link](https://huggingface.co/1038lab/BiRefNet_HR), then download the files and place them in the `/ComfyUI/models/RMBG/BiRefNet-HR` folder.
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- Manually download the SAM models by visiting the [link](https://huggingface.co/1038lab/sam), then download the files and place them in the `/ComfyUI/models/SAM` folder.
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- Manually download the GroundingDINO models by visiting the [link](https://huggingface.co/1038lab/GroundingDINO), then download the files and place them in the `/ComfyUI/models/grounding-dino` folder.
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- Manually download the Clothes Segment model by visiting the [link](https://huggingface.co/1038lab/segformer_clothes), then download the files and place them in the `/ComfyUI/models/RMBG/segformer_clothes` folder.
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- Manually download the Fashion Segment model by visiting the [link](https://huggingface.co/1038lab/segformer_fashion), then download the files and place them in the `/ComfyUI/models/RMBG/segformer_fashion` folder.
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@@ -174,12 +183,27 @@ BEN is robust on various image types, offering:
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- Effective on both simple and complex scenes
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- Suitable for batch processing
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## BEN2
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BEN2 is a more advanced version of BEN, offering:
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- Improved accuracy and speed
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- Better handling of complex scenes
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- Support for more image types
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- Suitable for batch processing
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## BIREFNET-HR
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BIREFNET-HR is a powerful model for image segmentation, offering:
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- High accuracy in complex environments
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- Precise edge detection and preservation
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- Excellent handling of fine details
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- Support for multiple objects in a single image
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## SAM
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SAM is a powerful model for object detection and segmentation, offering:
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- High accuracy in complex environments
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- Precise edge detection and preservation
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- Excellent handling of fine details
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- Support for multiple objects in a single image
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- Output Comparison
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- Output with background
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- Batch output for video
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@@ -213,10 +237,13 @@ GroundingDINO is a model for text-prompted object detection and segmentation, of
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- RMBG-2.0: https://huggingface.co/briaai/RMBG-2.0
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- INSPYRENET: https://github.com/plemeri/InSPyReNet
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- BEN: https://huggingface.co/PramaLLC/BEN
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- BEN2: https://huggingface.co/PramaLLC/BEN2
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- BiRefNet-HR: https://huggingface.co/ZhengPeng7/BiRefNet_HR
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- SAM: https://huggingface.co/facebook/sam-vit-base
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- GroundingDINO: https://github.com/IDEA-Research/GroundingDINO
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- Clothes Segment: https://huggingface.co/mattmdjaga/segformer_b2_clothes
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- Created by: [1038 Lab](https://github.com/1038lab)
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## License
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GPL-3.0 License
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GPL-3.0 License
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# ComfyUI-RMBG Update Log
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## v1.8.0 (2025/02/07)
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### New Model Added: BiRefNet-HR
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- Added support for BiRefNet High Resolution model
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- Trained with 2048x2048 resolution images
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- Superior performance metrics (maxFm: 0.925, MAE: 0.026)
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- Better edge detection and detail preservation
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- FP16 optimization for faster processing
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- MIT License for commercial use
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### Technical Improvements
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- Added FP16 (half-precision) support for better performance
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- Optimized for high-resolution image processing
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- Enhanced memory efficiency
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- Maintained compatibility with existing workflows
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- Simplified model loading through Transformers pipeline
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### Performance Comparison
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- BiRefNet-HR vs other models:
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- Higher resolution support (up to 2048x2048)
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- Better edge detection accuracy
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- Improved detail preservation
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- Optimized for high-resolution images
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- More efficient memory usage with FP16 support
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## v1.7.0 (2025/02/05)
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### New Model Added: BEN2
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