A background remover separates the subject of a photo (a person, a product, a pet) from everything behind it, so you can save the subject on a transparent background or on a plain colour. This tool does it with ISNet, an open AI segmentation model (Apache-2.0 licence) that was trained to find the main object in an image. The model looks at a 1024 × 1024 copy of your photo, marks how likely each pixel is to belong to the subject, and that mask is then scaled back up and applied to your photo at its full original resolution.
Everything happens inside your browser with onnxruntime-web. The first time you use the tool on a device it downloads the model (about 47 MB including the engine) from Hugging Face and keeps it in your browser's storage, so later runs start straight away. Your photo is never sent anywhere. After the run you can switch between a transparent background, white, black or any colour, choose soft or crisp edges, and flip between Before and After, all without spending another run.
Honest limits: fine hair, fur, glass, smoke and subjects that share colours with the background are the hardest cases, and edges there may need touching up in an editor. Group photos and busy scenes can keep or drop the wrong object, because the model picks what it judges to be the main subject. One photo is processed per run, up to 50 MB.