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bgeraser

Remove image backgrounds on your own computer. No uploads, no API keys, no watermarks, no limits.

bgeraser web UI

Works three ways:

Command line bgeraser photo.jpg → photo-nobg.png
Python library remove_background("photo.jpg")
Local web page bgeraser serve → drag & drop in your browser

Powered by open-source U²-Net / ISNet models through rembg.

Install

pip install bgeraser            # CLI + library
pip install "bgeraser[web]"     # also the drag & drop web page

Needs Python 3.9+. The first run downloads the AI model (about 170 MB for the default isnet-general-use, one time).

Command line

# one image → transparent PNG next to it
bgeraser photo.jpg

# choose the output name
bgeraser photo.jpg -o clean.png

# solid background instead of transparent (product photos, ID photos)
bgeraser photo.jpg --bg white
bgeraser photo.jpg --bg "#00ff00"

# a whole folder → ./products/nobg/
bgeraser ./products
bgeraser ./products -o ./out --recursive

# faster (lower quality) model for big batches
bgeraser --model u2netp ./products

# finer edges for hair / fur (slower)
bgeraser photo.jpg --matting

# list models
bgeraser models

Web page (drag & drop)

bgeraser serve

Then open http://127.0.0.1:5000. Drop, paste, or pick an image; download the PNG. Everything stays on your machine.

bgeraser serve --port 8080 --model isnet-general-use to change port or model.

Python

from bgeraser import remove_background, remove_background_bytes, process_folder

remove_background("photo.jpg")                           # -> photo-nobg.png
remove_background("photo.jpg", "out.png", bg_color="white")
remove_background("photo.jpg", model="isnet-general-use", alpha_matting=True)

png_bytes = remove_background_bytes(open("photo.jpg", "rb").read())   # in-memory

process_folder("./products", "./products/out")           # batch

Models

name best for
isnet-general-use (default) cleanest edges — people, products, cars
u2net general, good quality
u2netp fastest, small, rougher edges
u2net_human_seg people / portraits
isnet-anime anime & illustrations
u2net_cloth_seg clothing segmentation
silueta u2net quality, smaller file

Why

Online background removers are slow, watermark the result, charge per image, or make you upload customer photos to a stranger's server. This does the same job offline, for free, in one command.

Contributing

Issues and pull requests welcome. Run tests with:

pip install -e ".[dev]"
pytest

License

MIT © Tavrej / Yonzon Studio

Metadata

Release files for bgeraser 0.3.0

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Table of built distributions (wheels) for bgeraser 0.3.0
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Total release size: 3.3 MB

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