Root-Tissue-Segmentation Package
Prediction package for reproducible U-Net models, trained for semantic segmentation of microscopy images of root tissue from A. thaliana (https://github.com/qbic-pipelines/root-tissue-segmentation-core/). These models are trained using the mlf-core framework and tested for reproducibility. This package can be deployed within an analysis pipeline as a module for root tissue segmentation (rts) of fluorescence microscopy images.
Free software: MIT
Documentation: https://rts-package.readthedocs.io.
Package Tools
Segmentation prediction CLI: rts-pred
Uncertainty of prediction CLI: rts-pred-uncert
Input feature importance (Guided Grad-CAM) CLI: rts-feat-imp
Usage Examples
rts-pred -i ./brightfields -o ./predictions -m mark1-PHDFM-u2net-model.ckpt --suffix ""
rts-pred-uncert -i ./brightfields -o ./predictions -m mark1-PHDFM-u2net-model.ckpt --suffix "" -t 5
rts-feat-imp -i ./brightfields -o ./predictions -m mark1-PHDFM-u2net-model.ckpt --suffix "" -t 2
Credits
This package was created with mlf-core using cookiecutter.
Changelog
This project adheres to Semantic Versioning.
1.0.0 (2021-08-10)
Added
Fixed
Dependencies
Deprecated
0.1.0 (2021-08-10)
Added
Created the project using mlf-core
Fixed
Dependencies
Deprecated
1 maintainer
Metadata
1 maintainer
Release files for root-tissue-seg-package 1.0.7
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