rembg
Remove Image Backgrounds with Pre-Trained Segmentation Models
Remove the background from an image using pre-trained deep learning segmentation models ('U-2-Net', 'ISNet', 'BiRefNet' and others) run through the 'ONNX' Runtime via the 'onnxr' package. Given an image, a model predicts a foreground alpha matte which is composited into a cutout with a transparent (or solid-colour) background; optional closed-form alpha matting (ported from 'pymatting') refines soft edges. An R port of the Python 'rembg' package (<https://github.com/danielgatis/rembg>). Models are downloaded on first use and cached in a per-user cache directory.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.1.1 |
rolling linux/jammy R-4.5 | rembg_0.1.1.tar.gz |
104.7 KiB |
0.1.1 |
rolling linux/noble R-4.5 | rembg_0.1.1.tar.gz |
104.5 KiB |
0.1.1 |
rolling source/ R- | rembg_0.1.1.tar.gz |
41.5 KiB |
0.1.1 |
latest linux/jammy R-4.5 | rembg_0.1.1.tar.gz |
104.7 KiB |
0.1.1 |
latest linux/noble R-4.5 | rembg_0.1.1.tar.gz |
104.5 KiB |
0.1.1 |
latest source/ R- | rembg_0.1.1.tar.gz |
41.5 KiB |
0.1.1 |
2026-04-23 source/ R- | rembg_0.1.1.tar.gz |
0 B |