This background remover runs the open-source MODNet matting model (Apache-2.0) directly in your browser via transformers.js and WebAssembly. Drop in a photo, click remove, and get a transparent PNG: the model estimates an alpha value for every pixel, so edges fade out instead of cutting hard. The weights — 25 MB full-precision or 6.3 MB quantized — load once from a CDN and cache; your image never leaves the page. It's strongest on people (that's what MODNet was trained for) and honest where it's weak: fine hair and glass.

Remove a Background

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Drop an image here or click to choose

JPG, PNG, or WebP · processed on your device

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Browser Matting Models Compared

ModelLicenseDownload sizeBest atIn this tool
MODNet (full precision)Apache-2.024.7 MBPortraits, peopleYes — Balanced mode
MODNet (8-bit quantized)Apache-2.06.3 MBSame, slightly softer edgesYes — Fast mode
U2-NetApache-2.0~168 MB (fp32)General objectsNo — too heavy for a page load
BRIA RMBG-1.4Custom, non-commercial~44 MBGeneral purposeNo — license forbids commercial use

License matters as much as quality here. Several popular background-removal models carry non-commercial terms, which is why they're excluded even though they benchmark well. Everything this tool loads is Apache-2.0, both the runtime (transformers.js) and the weights (MODNet).

How It Works

Old-school background removal drew a hard boundary around a subject. Modern matting models do something better: for every pixel they predict an alpha value between 0 and 1 — how much of that pixel belongs to the person and how much belongs to the background. Semi-transparent pixels along hair and shoulders stay semi-transparent, which is what makes cutouts look natural when you paste them somewhere new.

The pipeline

Your image is decoded, resized to what the model expects, and pushed through MODNet as a tensor. The model outputs a single-channel matte; transformers.js multiplies it into an alpha channel, reattaches your original colors, and hands back a full RGBA image. From there the page composites it onto transparent, white, or a color you pick, and encodes a PNG.

How to use it

Drop a photo, pick a quality setting, and wait for the matte. First run downloads the model; after that it's cached and each image takes seconds. Use the output-background selector to flatten onto white for a clean product-card look, or leave it transparent and drop the PNG into a slide deck, an email, or a marketplace listing.

A worked example with real numbers

Take a 1920×1080 photo. That's 2,073,600 pixels (2.07 megapixels). Before the model runs, the raw color data is 1920 × 1080 × 3 bytes = 6,220,800 bytes, about 5.93 MiB. The output adds an alpha channel: 1920 × 1080 × 4 = 8,294,400 bytes of raw RGBA, 7.91 MiB — a third more data, because each pixel now carries opacity alongside red, green, and blue. PNG compression typically squeezes that back down below the original JPEG's size for clean cutouts with large empty regions.

On the model side, the trade is the download: full-precision MODNet is 24.7 MB, while the 8-bit quantized build is 6.3 MB — 25.5% of the original size, a 74.5% saving, at the cost of slightly softer edge gradation. If you're processing one photo on a phone, Fast mode is usually the right call; for headshots going on a company page, let Balanced load once and cache.

Frequently Asked Questions

Is this background remover really free and private?

Yes. The tool downloads the open-source MODNet model (Apache-2.0) straight from a public CDN and runs it on your device with WebAssembly. Your photo is never uploaded to any server — you can watch the network tab and see that nothing leaves the page after the model files arrive. There is no watermark, no signup, and no image limit because there is no server doing the work.

Why does the first run take longer?

The first removal downloads the model weights — about 25 MB for the full-precision version or 6.3 MB for the quantized one — plus the WebAssembly runtime. Your browser caches both, so the second and later images process in seconds. If you switch between the Balanced and Fast quality settings, each setting's model is downloaded once.

What kind of photos work best?

MODNet is a portrait matting model, so photos of people give the cleanest cutouts. Product shots, pets, and objects with clear edges usually work well too. Fine details like individual hair strands, glass, and sheer fabric are where free in-browser models fall short of paid services — expect soft edges there instead of perfect ones.

Why does my download have a checkerboard pattern in it?

It doesn't — that checkerboard is only the on-page preview showing you where the image is transparent. The exported PNG keeps true transparency. If a program shows a solid white background instead, that app filled transparent pixels for display; the alpha channel is still in the file.

Should I export PNG or JPEG?

PNG. JPEG has no alpha channel, so a transparent cutout saved as JPEG gets a solid background baked in. PNG and WebP both support transparency; PNG is the safe universal choice for pasting into slides, docs, and editors.

How is this different from remove.bg?

remove.bg runs a large server-side model, which is why it handles complex hair and edges better. This tool trades some edge quality for privacy and price: the model runs on your machine, so nothing is uploaded, there are no credits, and there is no resolution cap imposed by an upload limit. For profile photos, product shots, and presentation cutouts, the results are usually indistinguishable.

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