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# ComfyUI-RMBG
A sophisticated ComfyUI custom node engineered for advanced image background removal and precise segmentation of objects, faces, clothing, and fashion elements. This tool leverages a diverse array of models, including RMBG-2.0, INSPYRENET, BEN, BEN2, BiRefNet, Lucida, SDMatte, SAM, SAM2, SAM3, Florence-2, YOLOv8, Big-Lama, and GroundingDINO, while also incorporating real-time background replacement, instant VRAM unloading, and enhanced edge detection for improved accuracy.
A sophisticated ComfyUI custom node engineered for advanced image background removal and precise segmentation of objects, faces, clothing, and fashion elements. This tool leverages a diverse array of models, including RMBG-2.0, VRMBG-3.0, FeyNoBg, Finegrain Box Segmenter, INSPYRENET, BEN, BEN2, BiRefNet, Lucida, SDMatte, SAM, SAM2, SAM3, Florence-2, YOLOv8/YOLO11, Big-Lama, and GroundingDINO, while also incorporating real-time background replacement, instant VRAM unloading, and enhanced edge detection for improved accuracy.
## News & Updates
- **2026/10/20**: Update ComfyUI-RMBG to **v3.3.0** ( [update.md](https://github.com/1038lab/ComfyUI-RMBG/blob/main/update.md#v330-20261020) )
![V3 3 0_nodes](https://github.com/user-attachments/assets/97138882-e084-43cf-a6d2-8745981109f3)
- Added Canvas (RMBG) interactive multi-layer compositing studio with aspect-locked transform gizmos and dynamic layer slots.
- Added VRMBG (Video Background Removal) node for flicker-free sequential video matting.
- Added FeyNoBg (Ultra-Fine Matting) node with deepened Swin-L architecture for fine hairs and semi-transparent subjects.
- Added Finegrain Box Segmenter node for 1024px box-promptable matting compatible with Florence-2 and YOLO bounding boxes.
- Overhauled YOLO Segmentation with YOLO26-seg & YOLO11-seg, native RGBA cutout, and collapsible advanced options drawer.
- Rebuilt Florence-2 on a native local PyTorch architecture (100% offline, zero remote code vulnerabilities, removed matplotlib).
- Native FP16 acceleration for RMBG-2.0 and BiRefNet with automatic intermediate VRAM clearing.
- **2026/09/30**: Update ComfyUI-RMBG to **v3.2.0** ( [update.md](https://github.com/1038lab/ComfyUI-RMBG/blob/main/update.md#v320-20260930) )
![v2.9.4_sam3](https://github.com/user-attachments/assets/9b165789-a291-4df0-a147-67cca8011262)
![v3 2 0_sam3](https://github.com/user-attachments/assets/9b165789-a291-4df0-a147-67cca8011262)
- Upgraded to new `SAM3 Multiplex` segmentation node with native `safetensors` support (`sam3.safetensors`, `sam3.1_multiplex_fp16.safetensors`)
- Added `unload_model` toggle across all nodes for instant GPU VRAM release
- Added New `Resolution Selector` & `Image Compare` nodes
@@ -243,8 +252,11 @@ install requirment.txt in the ComfyUI-RMBG folder
```
### 4. Manually download the models:
- The model will be automatically downloaded to `ComfyUI/models/RMBG/` when first time using the custom node.
- Most models can be automatically downloaded to `ComfyUI/models/RMBG/` on first use. VRMBG-3.0 requires manual download due to official BRIA license terms.
- 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.
- Manually download the VRMBG-3.0 model by visiting official [briaai/VRMBG-3.0](https://huggingface.co/briaai/VRMBG-3.0), then download the files (`config.json`, `model.safetensors`, `model.py`, `vrmbg3_config.py`) and place them in the `/ComfyUI/models/RMBG/VRMBG-3.0` folder.
- Manually download the FeyNoBg model by visiting this [link](https://huggingface.co/1038lab/FeyNobg), then download the files (`config.json`, `FeyNobg.safetensors`, `preprocessor_config.json`) and place them in the `/ComfyUI/models/RMBG/FeyNoBg` folder.
- Manually download the Finegrain Box Segmenter model by visiting this [link](https://huggingface.co/1038lab/finegrain-box-segmenter), then download the files (`finegrain-box-segmenter.safetensors`) and place them in the `/ComfyUI/models/RMBG/finegrain-box-segmenter` folder.
- 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.
- 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.
- 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.
@@ -338,6 +350,25 @@ BEN2 is a more advanced version of BEN, offering:
- Support for more image types
- Suitable for batch processing
## VRMBG-3.0
VRMBG-3.0 is a dedicated temporal video and image sequence background matting model by BRIA AI:
- Temporal consistency: Autoregressive state tracking conditioned on prior frame foreground features to eliminate boundary jitter.
- Chunked video processing: Supports batch-by-batch execution on long sequences without memory fragmentation.
- Native 1024x1024 resolution inference.
- Manual model placement: Requires manual download of files from [briaai/VRMBG-3.0](https://huggingface.co/briaai/VRMBG-3.0) into `ComfyUI/models/RMBG/VRMBG-3.0/`.
## FeyNoBg
FeyNoBg is an ultra-fine dichotomous matting model featuring a deepened Swin-L backbone (263M parameters):
- Boundary reconstruction: Excels at complex dichotomous image segmentation.
- Wispy & transparent subjects: Exceptional accuracy on wispy hair strands, animal fur, transparent glassware, lace, and motion-blurred edges with zero trimap required.
- Sub-pixel foreground edge refinement: Built-in boundary optimizer ensuring crisp, halo-free results.
## Finegrain Box Segmenter
Finegrain Box Segmenter provides 1024px high-definition prompt-guided object matting:
- Swin-B MVANet architecture: High-resolution salient object matting optimized for 1024px images.
- Florence-2 & YOLO integration: Seamlessly connects to detection `BBOX` outputs for automated, targeted segmentation.
- Robust boundary definition: Preserves fine details, hard edges, and object textures.
## BIREFNET MODELS
BIREFNET is a powerful model for image segmentation, offering:
- BiRefNet-general purpose model (balanced performance)
@@ -437,6 +468,9 @@ GroundingDINO is a model for text-prompted object detection and segmentation, of
## Credits
- RMBG-2.0: https://huggingface.co/briaai/RMBG-2.0
- VRMBG-3.0: https://huggingface.co/briaai/VRMBG-3.0
- FeyNoBg: https://huggingface.co/1038lab/FeyNobg
- Finegrain Box Segmenter: https://huggingface.co/1038lab/finegrain-box-segmenter
- INSPYRENET: https://github.com/plemeri/InSPyReNet
- BEN: https://huggingface.co/PramaLLC/BEN
- BEN2: https://huggingface.co/PramaLLC/BEN2
@@ -464,4 +498,4 @@ GroundingDINO is a model for text-prompted object detection and segmentation, of
If this custom node helps you or you like my work, please give me ⭐ on this repo! It's a great encouragement for my efforts!
## License
GPL-3.0 License
GPL-3.0 License<img width="1527" height="1121" alt="2026-10-20-00-12-39" src="https://github.com/user-attachments/assets/7c6da7e5-d324-48e8-b655-5c567360fff6" />