AI-based foreground extraction in scientific and natural images.
Project description
napari-rembg
Select the foreground of images using AI in Napari. This plugin is based on the rembg project.
Why use napari-rembg?
- It runs fast even on a laptop's CPU (a few seconds per image).
- It is easy to install compared to other AI tools for segmentation.
- It is a quick and easy solution to automatically extract the foreground of scientific and natural images.
Installation
You can install napari-rembg via pip:
pip install napari-rembg
Usage
Start napari-rembg from the Plugins menu of Napari:
Plugins > Select foreground (napari-rembg)
Contributing
Contributions are very welcome. Please get in touch if you'd like to be involved in improving or extending the package.
License
Distributed under the terms of the BSD-3 license, "napari-rembg" is free and open source software.
Issues
If you encounter any problems, please file an issue along with a detailed description.
This napari plugin was generated with Cookiecutter using @napari's cookiecutter-napari-plugin template.
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file napari-rembg-0.0.2.tar.gz.
File metadata
- Download URL: napari-rembg-0.0.2.tar.gz
- Upload date:
- Size: 5.4 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.10.12
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
cc40ffa0619621fe6cecdb238e7b9dcb01ac11011b14a5c59b1b0ac0ab979fc3
|
|
| MD5 |
7aa75588a0349f70a538146492023ca3
|
|
| BLAKE2b-256 |
32d61352ae5505960f6fb171976a5c7cdf7cc6199a26fd596d0ce5fe062334e3
|
File details
Details for the file napari_rembg-0.0.2-py3-none-any.whl.
File metadata
- Download URL: napari_rembg-0.0.2-py3-none-any.whl
- Upload date:
- Size: 5.8 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.10.12
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
0aa251d8b51245b9894909d1520ab4967da3910cbb983c6d123791922efad1b2
|
|
| MD5 |
240a28b5398d9895c798aa3af6ee9480
|
|
| BLAKE2b-256 |
a71ab9db4d9eff8ffe8797ac06958c1e69f1a0683a37dc4868c9a158db9c5539
|
