RemBG v1.4

rembg is the old reliable of background removal - the MIT-licensed tool that's been cutting subjects out of images since 2020, when a single r/StableDiffusion PSA about the A1111 extension was enough to take the operation mainstream. This node is the classic rembg v1.4 engine running as a hosted Runware endpoint: feed it an image, get a cutout back, and never download a u2net weight or load a model into VRAM.

If you already run local background removal - BiRefNet in ComfyUI core, or the Inspyrenet nodes - you don't need this; it's strictly slower to pay per image for what your GPU does free. But if you're on a laptop with no VRAM, or you want a background cutout in a cloud workflow where everything else already runs on Runware, this is the drop-in. It's also a nice second opinion node: when the local model mangles hair, rembg's u2net path sometimes disagrees usefully.

How it works

Your image (IMAGE tensor) is encoded to a PNG and sent to runware:109@1 with taskType: removeBackground. The result comes back as a native image output - the cutout on a transparent background when outputFormat is PNG, or composited onto whatever the format supports.

The inputs that make it interesting are the matting controls:

• settings.alphaMatting - toggle on to refine edges instead of a hard cut. On for hair, fur, and anything with soft edges; off for clean, flat subjects where it only adds time.
• settings.alphaMattingForegroundThreshold (default 240) and settings.alphaMattingBackgroundThreshold (default 10) - where the matting decides foreground ends and background begins. Higher background threshold removes more background but takes longer.
• settings.alphaMattingErodeSize (default 10) - how much the edge is eroded to smooth the silhouette.
• settings.postProcessMask - extra mask cleanup pass when the first cut is noisy.
• settings.returnOnlyMask - output the mask instead of the composited cutout, which is handy when you want to feed a mask into an inpaint or a compositing step.

Output: image (IMAGE). The advanced_json field takes settings.rgba if you want to control alpha handling precisely.

Installing

Pack-wide, one install: ComfyUI Manager → search Runware → install → restart, or:

cd ComfyUI/custom_nodes
git clone https://github.com/Runware/ComfyUI-Runware
pip install -r ComfyUI-Runware/requirements.txt

No model downloads - that's the entire pitch. API key from the Runware dashboard.

Gotchas

Remember what the community learned back in 2023: rembg handles simple backgrounds well and complex ones still need manual cleanup. Hair is the classic failure - that's what settings.alphaMatting is for, so don't skip it on subjects with flyaway strands. And remember the format trap: JPG has no alpha channel, so a cutout saved as JPG composites onto black (or whatever the encoder does with alpha). Set outputFormat to PNG when you want the transparent result. Since it's a paid call per image, it's worth keeping for the occasional cutout, not for batch-processing ten thousand product photos.