withoutBG: Open-Weights Background Removal Model
An open-weights background removal model that outperforms several open-source and commercial models on our evaluation benchmarks.
Apache-2.0 · Python · Docker · macOS · GIMP
How to run it#
Self-host with a Mac app, GIMP plugin, Python package, or Docker. Same open weights across the stack. See also self-hosted background removal.
macOS App
- Native desktop app with drag-and-drop batch processing
- Optional Local API for GIMP, Blender, and scripts on localhost
- On-device Apple Silicon inference, works offline after install
GIMP Plugin
- Remove backgrounds from the GIMP 3.0 Tools menu
- Calls a local withoutBG server on localhost
- Attaches the alpha matte as an unapplied layer mask
Python Library
- Install with uv add withoutbg
- Process images in 3 lines of Python
- Runs on CPU or GPU, Apache-2.0 licensed
Docker
- Web UI: one docker run command, inference on port 80
- Headless API: same /v1.0/image-without-background schema as cloud
- Images stay on your network, nothing leaves the container
Examples#
Sample outputs from the open-weights model. Switch between transparency, chroma key, and alpha matte on each result.
Photo by Niko Tsviliov on Unsplash
Compare to other open models#
Same Bench images and ground-truth metrics against rembg sessions (u2net, IS-Net, BiRefNet, BRIA, and more). The directory is the evaluation surface; this page is where you install and ship.
WithoutBG Ecosystem
ONNX weights on Hugging Face and open-source repositories.