63 lines
2.7 KiB
Markdown
63 lines
2.7 KiB
Markdown
# ComfyUI Background Removal
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Custom ComfyUI node for background removal in images. Built on top of **rembg** (with ONNX models) and Pillow (PIL)
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It takes an image as input and produces an image (IMAGE) and an alpha mask (MASK) as output.
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## Quickstart
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1. Install [ComfyUI](https://docs.comfy.org/get_started).
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2. Activate ComfyUI virual environment. For example:
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``
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source venv/bin/activate
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``
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3. Install node in `custom_nodes` folder:
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```
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cd ComfyUI/custom_nodes
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git clone https://github.com/d3cker/comfyui_remove_background
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```
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4. Install requirements
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```
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cd comfyui_remove_background
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pip3 install -r requirements.txt
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```
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# Features
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- For all features please read [rembg](https://github.com/danielgatis/rembg) documentation.
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- Muli-GPU / CPU support
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- Preload dlls for Windows
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- Alpha matting (CPU)
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# Options
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- model: Choose prefered model.
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- device: auto/cpu/cuda:1/cuda:2, etc.
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- allow_cpu_fallback: Fallback to CPU if GPU not available.
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- alpha_matting: Enables alpha matting to refine the alpha channel and improve edge separation (e.g., hair, fur, semi-transparent edges).
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- alpha_matting_background_threshold: Mask value at or below this is treated as sure background when building the trimap (lower = less aggressive background)
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- alpha_matting_foreground_threshold: Mask value at or above this is treated as sure foreground when building the trimap (higher = stricter foreground).
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- alpha_matting_erode_size: Erosion size used to shrink sure foreground/background regions, increasing the “unknown” band for matting (larger = wider refinement zone, slower/more smoothing).
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# Supported models
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List from **rembg** repository:
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```
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- u2net - A pre-trained model for general use cases.
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- u2netp - A lightweight version of u2net model.
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- u2net_human_seg : A pre-trained model for human segmentation.
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- u2net_cloth_seg - A pre-trained model for Cloths Parsing from human portrait. Here clothes are parsed into 3 category: Upper body, Lower body and Full body.
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- silueta - Same as u2net but the size is reduced to 43Mb.
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- isnet-general-use - A new pre-trained model for general use cases.
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- isnet-anime - A high-accuracy segmentation for anime character.
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- sam - A pre-trained model for any use cases.
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- birefnet-general - A pre-trained model for general use cases.
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- birefnet-general-lite - A light pre-trained model for general use cases.
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- birefnet-portrait - A pre-trained model for human portraits.
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- birefnet-dis - A pre-trained model for dichotomous image segmentation (DIS).
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- birefnet-hrsod - A pre-trained model for high-resolution salient object detection (HRSOD).
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- birefnet-cod - A pre-trained model for concealed object detection (COD).
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- birefnet-massive - A pre-trained model with massive dataset.
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``` |