unbagrnd

An Android app that uses AI to remove the background from images — entirely on your device. No cloud API, no account, no telemetry, and no internet access required after a one-time setup step.

On-device AI. Background removal runs through a real neural network (ONNX Runtime), inferred locally on your device. No image, filename, or metadata is ever sent anywhere.

100% free & open source. MIT-licensed, built on a free, open-source stack — no API keys, no paid tiers, no usage limits.

Pick your AI model. Choose from several background-removal models in Settings, trading off speed vs. accuracy. Each downloads once on first use (starting at ~43 MB for the default) and is cached locally after that.

Offline after setup. The only network requests the app ever makes are those one-time model downloads. Nothing else — no analytics, no update checks.

Single and batch. Process one image, or a whole folder, from the same window.

Refine by hand. Brush over the result to erase or restore parts of the cutout, with undo/redo — for the spots the model gets almost right.

Edit the background. Fill it with a solid color and add an on-device drop shadow, no AI or network involved.

Export as PNG, WebP, or SVG. Pick the output format in Settings.

How it works

unbagrnd runs IS-Net "general use" (Apache-2.0, from Qin et al., "Highly Accurate Dichotomous Image Segmentation", ECCV 2022) as an ONNX model, via the ort Rust bindings for ONNX Runtime. This is the same model family used by the popular rembg Python tool. The whole pipeline — decode, resize, normalize, run the model, turn its predicted mask into an alpha channel, re-encode as PNG — happens in the Rust backend; the frontend never touches the network.

Installing

On first launch, or the first time you remove a background, unbagrnd downloads the model (~170 MB) and shows a progress bar while it does. That only happens once — every run after that is fully offline.

Where the model is cached, and how to clear it

The model is stored in the app's private storage under /data/user/0/com.unbagrnd.app/models/.

To clear the cached model (freeing ~170 MB, or to force a clean re-download), use the in-app Settings ("Clear model") option, or uninstall the app.

License

MIT

The bundled model, IS-Net "general use", is Apache-2.0 licensed and downloaded from rembg's (MIT-licensed) GitHub release assets.