Metadata-Version: 2.1
Name: deepflash2
Version: 0.0.3
Summary: A Deep learning pipeline for segmentation of fluorescent labels in microscopy images
Home-page: https://github.com/matjesg/deepflash2
Author: Matthias Griebel
Author-email: matthias.griebel@uni-wuerzburg.com
License: Apache Software License 2.0
Keywords: unet,deep learning,semantic segmentation,microscopy,fluorescent labels
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Requires-Dist: fastai (>=2.0.0)
Requires-Dist: imageio
Requires-Dist: scikit-image

# DeepFLaSH2
> Official repository of DeepFLasH - a deep learning pipeline for segmentation of fluorescent labels in microscopy images.


## Install

`pip install deepflash2`

## How to use

Links to tutorial Notebooks

## Model Library

This list contains download links to the weights of the selected models as well as an example of their corresponding training images and masks.

You can select and apply these models within our Jupyter Notebook.

## Acronym

A Deep-learning pipeline for Fluorescent Label Segmentation that learns from Human experts


