Package: rembg 0.1.1
Troy Hernandez
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.
Authors:
rembg_0.1.1.tar.gz
rembg_0.1.1.tar.gz(r-4.7-any)rembg_0.1.1.tar.gz(r-4.6-any)
rembg_0.1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
rembg/json (API)
| # Install 'rembg' in R: |
| install.packages('rembg', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/cornball-ai/rembg/issues
Last updated from:344001d671. Checks:4 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 108 | ||
| source / vignettes | OK | 155 | ||
| linux-release-x86_64 | OK | 111 | ||
| wasm-release | OK | 111 |
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Directory where downloaded models are cached | model_home |
| Create a background-removal session | new_session |
| Remove the background from an image | rembg |
| Available background-removal models | rembg_models |
