Cut the subject out of a photo, offline, on your own machine. An AI proposes the outline, you fix it with a brush, then you drop the result on a transparent, plain or picture background (with a shadow if you like) and export.
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Français : README.fr.md
This is an independent project. It is not affiliated with any commercial product, and it contains no code, icons, translations or model weights from one.
I wanted a background remover that
- works offline (your photos never leave the computer),
- starts in a blink and doesn't eat half the RAM just to sit there,
- lets me correct the result instead of hoping the AI got it right,
- comes as one folder I can copy to a USB stick.
So that's what this is. About 240 MB of memory with a photo open (not counting the model), 28 MB when it is idle.
- Automatic cut-out the moment you open an image. The result appears next to the original; both views zoom and pan together.
- Brush correction: mark what to keep, erase what shouldn't be there, and a hair tool for soft edges.
- Group by color (green and red marks) when the AI struggles: whole areas of similar colour follow your strokes.
- Smart select: click what you want, right-click what you don't, or drag a box (needs the small SAM 2 model).
- Backgrounds: transparent, solid colour, any picture, or the original with the subject filled in. Blur, grayscale, negative, pixelate or colourize either layer.
- Clean up the edges: soft edges (hair, feathering) lose the colour of the old background, so no halo shows on the new one.
- Adjust the colours of the subject alone (brightness, saturation, warmth) so it sits right on its new background.
- Shadow (blur, opacity, colour, offset right and down), crop to a ratio, padding, then export to PNG, JPEG, WebP, TIFF or BMP. 16-bit sources can stay 16-bit.
- Output width and presets (marketplace 1000 or 2000 px, thumbnail, 16:9 banner): the result comes out at the exact size, centred, on white or transparent.
- Copy and paste: Ctrl+V opens the picture on the clipboard (or an image file copied in your file manager); one click, or Ctrl+C, copies the result with its transparency.
- Batch mode for a whole folder: drop the folder on the window, use your saved settings or those of the image you are editing, save as PNG, JPEG or WebP.
- 4 languages: English (default), Français, Deutsch, Русский.
- Plug-ins (optional, off until you turn them on): small programs that run on the file you just saved.
Windows 10/11 (64-bit) is the tested platform. The Releases page also has a Linux x64 build and a macOS Apple Silicon build, untested.
- Download the latest zip for your system from the Releases page (
OpenScissors-…-portable-win-x64.zip,…-linux-x64.zipor…-darwin-arm64.zip) and unzip it anywhere. - Run
OpenScissors.exe(OpenScissorson Linux and macOS). - Open an image (the button, Ctrl+O, drag and drop, paste with Ctrl+V, or
OpenScissors.exe photo.jpg).
The first time, no AI model is installed (they are not bundled). Click the chip at the top, pick one, press Download. The file is checked against a SHA-256 before it is used.
| Model | Download | Memory | Good for |
|---|---|---|---|
| IS-Net (default) | 179 MB | ~0.6 GB | most photos, under a second |
| BiRefNet lite | 224 MB | ~5 GB | hair and thin structures, a few seconds |
| BiRefNet lite, half precision | 115 MB | ~5 GB | the same, made for GPUs |
| BiRefNet full | 973 MB | heavy | best quality, slow on a CPU |
| SAM 2.1 tiny | 156 MB | ~1 GB while selecting | the Smart select tool |
The app picks the lightest model you have until you choose another one, and refuses a model that wouldn't fit in its memory budget instead of freezing your PC.
Everything the application writes stays in its own folder:
OpenScissors/
├── OpenScissors.exe
├── openscissors-cli.exe the same engine in a terminal
├── DirectML.dll only used by the optional GPU mode
├── models/ what you downloaded
├── data/ settings, window position, your saved defaults
├── temp/ scratch files (cleaned automatically)
└── licenses/
Delete data/ to start over, delete models/ to free space. Nothing is written to the registry or to your profile. (If the folder is read-only, for example Program Files, the app falls back to your user profile rather than failing.)
- Nothing is loaded at start. The model loads with your first image.
- The app keeps to 25 % of your RAM (50 % in Settings, if you have the memory and the patience for BiRefNet).
- Big photos are handled in bands, so an 8K image costs a few hundred MB, not gigabytes.
- The footer shows the live RAM and CPU use of the app.
| F keep · B remove (in Group by color) · E erase | S smart select · H hair · Shift+H erase hair |
| M move · hold Space to pan | [ ] brush size |
| Ctrl+O open · Ctrl+S save · Ctrl+Shift+S save as | Ctrl+Z / Y undo / redo |
| Ctrl+V paste an image | Ctrl+C copy the result |
| Ctrl+0 100 % · Ctrl+9 fit · Ctrl++ / - zoom | wheel pans, Ctrl+wheel zooms |
| Enter apply a smart selection · Backspace remove the last click · Esc cancel |
The brush is off by default: the app starts on the Move tool, so the pointer never paints by surprise.
No account, no telemetry, no network call except the model downloads you start yourself (HTTPS, checksum verified).
You only need Rust (stable).
cargo run -p openscissors --release # run it
cargo test --workspace # tests
node scripts/package-portable.mjs --build --zip # the portable folder (with the CLI) and its zip, in dist/Debug builds keep their data in portable-dev/. OPENSCISSORS_HOME points the app to another folder, and OPENSCISSORS_MODEL=/path/model.onnx loads a local IS-Net style file.
There is a command line tool too: cargo run -p openscissors-cli -- cut photo.jpg cutout.png (also predict, batch, models).
To look at the interface and drive it without touching the mouse (handy for tests and screenshots):
cargo run --release -p openscissors --example selftest -- photo.jpg out/ [tour|keys|flows|all|script steps.json]Create models/<name>/model.onnx and a model.json next to it:
{
"id": "my-model", "name": "My model", "license": "MIT",
"input_size": [1024, 1024],
"mean": [0.485, 0.456, 0.406], "std": [0.229, 0.224, 0.225],
"output": "sigmoid"
}output is sigmoid (the model returns logits), minmax (rescale the raw output) or none (already 0..1). Models are described by data only, so adding one never needs a code change.
A plug-in is a folder plugins/<id>/ next to models/, with a plugin.json:
{ "id": "optimize-png", "name": "Optimise PNG", "description": "Runs oxipng on the result",
"command": "run.cmd", "args": ["{input}"], "extensions": ["png"] }command is a file inside that folder; {input} is the file you just saved and {dir} its folder. A plug-in does nothing until you turn it on in Settings, then it runs only when you press Run on the last saved file (60 s limit, the last lines of its output are shown). It is a program you installed: OpenScissors adds no permission of its own.
crates/core: everything that isn't a window. Image I/O, the model runner (ONNX Runtime), the GrabCut and max-flow code, closed-form matting, SAM 2, the document with its undo stack, rendering and export. No GUI dependency, so it is easy to test.crates/app: the window, written with Slint and its software renderer. That choice alone saves ~100 MB compared to a GPU renderer, and a lot more compared to a web view.crates/cli: the command line.
More in docs/ARCHITECTURE.md and docs/PERF.md (memory and speed, measured).
- Windows is the platform I test. The code is portable, the Linux and macOS (Apple Silicon) builds are untested. There is no macOS Intel build: ONNX Runtime provides no binary for it.
- The GPU mode (DirectML) works but didn't make anything faster on the card I tried, so it stays optional.
- Moving the crop with the keyboard isn't there yet; the handles need a pointer.
- A picture is refused, with a message, when it would not fit the memory budget (about 24 bytes per pixel once opened: an 8K photo needs ~0.8 GB, 100 megapixels ~2.3 GB) or is over 500 megapixels. The undo history keeps at most about 384 MB: the oldest steps are forgotten first.
- Error messages coming from the Rust side are in English only.
- The translations haven't been reviewed by native speakers. Corrections are welcome.
Apache-2.0. See LICENSE, NOTICE and THIRD_PARTY.md.
The interface toolkit, Slint, is used under the Slint Royalty-free License 2.0 (free for desktop apps, with the Made with Slint attribution you can find in Menu → About). Slint can also be used under GPL-3.0, which would make a build of OpenScissors GPL-3.0 as a whole; whoever builds the source picks the license that suits them. This is not legal advice.
Models are separate works with their own licenses (MIT, Apache-2.0), listed in THIRD_PARTY.md.