Pixel Classification XGBoost
A plugin for pixel classification using XGBoost
A plugin for pixel classification using XGBoost, inspired by Digital Sreeni's Youtube video.
Note: This plugin is work-in-progress. Check out the github issues to see what's currently being worked on.
Usage
Load an example image into napari. Add a Labels layer by clicking on this button:
Then, draw a sparse annotation on the image. Try to draw thin lines on background and foreground, e.g. like this:
Then click the menu Layers > Segment > Train Pixel Classifier (XGBoost).
In the dialog, select the original image and the labels layer. Also enter a filename where the model should be saved.
Afterwards, click on Run to explore the result.
Installation
You can install napari-xgboost via pip:
pip install napari-xgboost
To install latest development version :
pip install git+https://github.com/haesleinhuepf/napari-xgboost.git
Contributing
Contributions are very welcome. Tests can be run with tox, please ensure the coverage at least stays the same before you submit a pull request.
License
Distributed under the terms of the BSD-3 license, "napari-xgboost" is free and open source software
Issues
If you encounter any problems, please file an issue along with a detailed description.
Version:
- 0.1.0
Last updated:
- 2024-07-05
First released:
- 2024-07-05
License:
- Copyright (c) 2024, Robert Haa...
Operating system:
- Information not submitted
Requirements:
- numpy
- magicgui
- qtpy
- scikit-image
- xgboost
- apoc
- tox ; extra == 'testing'
- pytest ; extra == 'testing'
- pytest-cov ; extra == 'testing'
- pytest-qt ; extra == 'testing'
- napari ; extra == 'testing'
- pyqt5 ; extra == 'testing'