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home/image-tools/remove-background

Remove Backgrounds Instantly with AI

Remove the background.
See the mask it leaves.

Plain backgrounds are removed by flooding in from the edges; people are cut out by MODNet, a matting model that runs on your device. You can see and tune the mask itself, edge colour is cleaned of the old background, and the PNG is written by this page with exact alpha.

3cutout methods
MODNetAI on this device
PNGwritten with exact alpha
0 Buploaded
Add a photo, or the three generated samples: a product on white, a logo with enclosed holes, and a figure on a studio gradient.preview
cutoutmaskedge pixels
checkerwhiteblackteal
fit4×
background_replaceDrop images hereJPG, PNG, WebP, AVIF, GIF, BMP · several at once · worked on at up to 3,000 pxphoto_library3 generated samples
AI model · MODNetnot loaded
Only needed for people and busy backgrounds. Downloaded once from huggingface.co (Apache-2.0 licensed MODNet); your image still never leaves the device.downloadLoad the model
inboxno images yet
downloadremove
It all runs on your device; settings apply to every image.
folder_zipcontent_cutAdd images first
method
autoflood from edgescolour keyAI · MODNet
Auto floods from the edges when the border is one plain colour, and uses MODNet otherwise (once loaded).
background match
only touching the edgealso enclosed areas
Distance is weighted 2:4:3 for red, green and blue, roughly how strongly the eye sees each.
edgeClip turns near-zero and near-full values solid. Shrink removes a fringe of 0 px; feather blurs the mask twice with a box of 3 px.
colour & file
clean edge colouras photographed
transparent PNGJPG on backdrop
Written by this page: straight RGBA, per-row filter chosen by smallest sum, zlib via CompressionStream, then decoded again to check every alpha value. Fully transparent pixels get colour 0 so the old background isn’t hidden in the file.
~/the-mask-itself

What the cutout is really made of.

A cutout is a mask: one number per pixel from 0 (gone) to 255 (kept). The interesting part is in between, the hair, soft shadows and anti-aliased edges, where a pixel is part subject and part old background. These figures are counted from the mask of the selected image with the settings above.

Select an image above to see its mask.
alpha histogram · 32 bins · log scale · pixels
0 · removedpartial255 · kept
edge colour · 48 px crop at 4× · on dark
colour as photographed
old background unmixed
~/three-ways-one-image

Flood fill, colour key or AI: where they disagree.

All three methods run on the selected image and their raw masks are shown side by side. Agreement is measured as intersection over union of what each keeps; the disagreement map shows exactly which pixels are in dispute.

compareSelect an image first
Add or select an image above.
~/premultiplied

Why this page doesn't save through a canvas.

Browsers usually keep canvas pixels premultiplied: colour × alpha, rounded to 8 bits. At low alpha almost every colour collapses into a few values, and reading the canvas back can't restore them. Below, 256 red levels were written into this browser's canvas at each alpha and read back.

alphared levels that survivekeptworst error
12 / 256±127
23 / 256±64
34 / 256±42
45 / 256±32
67 / 256±21
89 / 256±16
1617 / 256±8
3233 / 256±4
6465 / 256±2
128129 / 256±1
255256 / 256±0
At alpha 1 this browser’s canvas kept 2 of 256 red levels, and at alpha 8 9. Those faint pixels are exactly the soft edges of a cutout. Saving through canvas.toBlob would bake that loss into the file; writing the PNG from the mask and the unmixed colours keeps all 256.
PNGcheck_circlealpha 128
WEBPcheck_circlealpha 128
AVIFremoveno encoder
The three tiles: a pixel at alpha 128 encoded by this browser's canvas.toBlob and decoded again. PNG is written by this page instead, from the straight-alpha mask, so faint edge colour reaches the file intact.
wherehow transparency is storeddepthcolour stored as
PNGColour types 4 and 6 carry an alpha sample per pixel; palette images give each entry an alpha in tRNS.8 or 16 bitstraight
WebPSeparate ALPH plane, compressed losslessly or quantised, even inside a lossy picture.8 bitstraight
AVIFAn auxiliary AV1 image marked urn:mpeg:mpegB:cicp:systems:auxiliary:alpha; can itself be lossy.8-12 bitstraight, or premultiplied with a prem reference
GIFOne palette index declared transparent in the Graphic Control Extension.1 bitno partial values
JPEGNo alpha channel; a cutout has to be flattened onto a colour.none-
TIFFExtraSamples tag: 1 means associated (premultiplied), 2 unassociated.8-32 biteither, declared
HEICAuxiliary alpha image linked to the main item with an auxl reference.8-10 bitstraight
PDFA soft-mask (SMask) image attached to the image XObject.1-16 bitstraight
Canvas 2DBacking store is usually premultiplied; ImageData converts to straight on read.8 bitpremultiplied inside
1940Blue screenLarry Butler’s travelling mattes for The Thief of Bagdad win the Oscar for special effects.
1977Integral alphaEd Catmull and Alvy Ray Smith at NYIT store a fourth, opacity channel in every pixel.
1984Porter: Duff“Compositing Digital Images” defines premultiplied alpha and the over operator.
1996PNG 1.0Full 8- and 16-bit alpha arrives in a web image format.
2001Bayesian mattingChuang et al. estimate subject, background and alpha per pixel from a trimap.
2012WebP alphalibwebp 0.2 adds the ALPH plane and lossless mode.
2017Deep Image MattingXu et al. train the first deep network to predict alpha from an image and trimap.
2020MODNetKe et al. predict portrait alpha with no trimap at all; the model this page runs.
2024BiRefNetHigh-resolution dichotomous segmentation for objects of any kind.

After the background is gone

Frequently Asked Questions

Is the background remover free to use?

Yes, it is completely free with no account, sign-up, or watermark, and there is no limit on how many images you can process. The tool runs entirely in your browser using a background-removal model that loads on your device, so you can remove backgrounds from as many photos as you need without any cost or usage cap.

Are my images uploaded to a server?

No. Every image is processed locally in your browser on your own device, and nothing is sent to or stored on a server. The removal model downloads once on your first image, then runs against each photo in memory, so your files never leave your computer and remain fully private throughout the process.

What image formats can I use, and what do I get back?

You can upload JPEG, JPG, PNG, WebP, BMP, TIFF, and GIF images. Whatever you start with, the tool always returns a transparent PNG with an alpha channel, named after your original file with a _no-bg suffix. Apple HEIC photos are not supported directly, so convert those to JPG first, then remove the background here.

Can I remove backgrounds from several images at once?

Yes. Add multiple images and each one is processed in turn, with a Download button appearing beside each finished cutout. When you have more than one image, a Download All as ZIP button collects every transparent PNG into a single archive, which makes batch work such as product photos or profile pictures much faster.

Why is the first image slower than the rest?

The first run downloads the background-removal model before it can start, which is a one-time download that depends on your connection speed. Once the model is loaded it stays in memory for the rest of your session, so every image after the first is processed noticeably faster with no additional download.