People, not products
The model separates a person from the background. A product photo, a logo or a pet is refused with a message rather than returned as a bad cut-out.
Local background remover
Drop up to ten photos of people. PicRemedy separates each subject from its background in this tab, keeps the original pixel dimensions in the saved file, and asks for no account. It cuts out people, not products.
Add up to 10 photosFull resolution · up to 10 at once · nothing uploaded · no sign-up
On this device
Local separation progress
Your cut-out
Model passes over your photo
Drag across the image to compare the cut-out with the original.
Finished cut-outs
Add photos of people to fill this shelf.
The model separates a person from the background. A product photo, a logo or a pet is refused with a message rather than returned as a bad cut-out.
The saved file keeps the source pixel dimensions. There is no watermark, no preview tier and no resolution held back for a paid plan.
The mask is computed at 256 by 256 and refined against your own pixels. Strands of hair and thin gaps stay soft; compare at full size before you use the result.
No. The photo, the mask and the finished cut-out stay in this browser tab. The page downloads its own model file once and sends property-free audience measurement; it has no image endpoint to upload to.
Yes. The output keeps the source pixel dimensions exactly. The mask itself is computed at 256 by 256 and then refined against your own pixels, so fine hair is approximate, but nothing is downscaled on the way out.
People. The model is a person-versus-background segmenter, so a portrait, a team photo or a full-length shot works and a product, a logo or a pet does not. It says so rather than returning a bad cut-out.
Up to ten in one local queue, processed one at a time. A photo that fails never stops the rest, and Stop ends the run after the image being worked on.
No. It produces one foreground mask for the whole person. No facial landmark, face geometry or face template is computed, stored or sent, on purpose.
About 3.9 MB compressed the first time: a 447 KB model plus the local inference engine this site already uses. The browser caches both, so a second visit starts immediately.