BiRefNet COD (birefnet-cod) background removal#

How to run birefnet-cod

birefnet-cod ships with rembg as the session birefnet-cod. The weights download on first use.

pip install "rembg[cpu,cli]"
rembg i -m birefnet-cod input.jpg output.png

from rembg import new_session, remove
from PIL import Image

session = new_session("birefnet-cod")  # load once, reuse for every image
output = remove(Image.open("input.jpg"), session=session)
output.save("output.png")

Other sessions: all rembg models.

BiRefNet COD as a free, open-source remove.bg alternative

remove.bg is a paid cloud service. BiRefNet COD is open weights under MIT, so commercial use is allowed. It runs on your own machine (rembg i -m birefnet-cod input.jpg output.png), offline, with no upload and no per-image cost. On Bench v0 it ranks #16 of 17 by accuracy (MAE); withoutBG Open Weights ranks #3.

remove.bg is not in Bench v0, so there is no score against it. See withoutBG Open Weights and remove.bg side by side, or compare all remove.bg alternatives.

Quick take

• Best for: Subjects that blend into the background: camouflaged animals, low contrast
• Avoid when: Everyday product or portrait cutouts: use birefnet-general
• Notes: Bench v0 is general-purpose photos, so its score here understates this model on camouflaged subjects; Bench v0 has few.

When a hosted model is worth it

birefnet-cod is free and runs on your machine; keep it if the results above are good enough. If you need finer hair and edges, or don't want to run large models locally, rembg also ships the withoutBG Pro Model as the withoutbg session, ranked #1 of 17 by accuracy on Bench v0. Images are sent to withoutBG's servers.

export WITHOUTBG_API_KEY=sk_...
rembg i -m withoutbg input.jpg output.png

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