Metadata-Version: 2.1
Name: NucDetect
Version: 0.11.14.dev2
Summary: Module to identify intranuclear proteins on basis of fluorescence images.
Home-page: https://github.com/SilMon/NucDetect
Author: Romano Weiss
License: UNKNOWN
Description: [![PyPI version](https://badge.fury.io/py/NucDetect.svg)](https://badge.fury.io/py/NucDetect)
        
        NucDetect - A python package for Detection and Quantification of DNA Doublestrand Breaks
        ============
        
        NucDetect is a Python package for the detection and quantification of γH2AX and 53BP1 foci inside nuclei. Its written in 
        pure Python 3.7, obeys the PEP 8 style guidelines and includes PEP 484 type hints as well as Epytext docstrings.
        
        ### Note
        
        The current release is a very early alpha version. Please report report any detected bugs and/or improvement suggestions.
        
        Requirements
        ============
        
        NucDetect is compatible with Windows, Mac OS X and Linux operating systems. It requires 
        the following packages:
        
        * tensorflow>=2.1.0
        * numpy>=1.18.1
        * scikit-image>=0.16.2
        * matplotlib>=3.1.3
        * pyqt5>=5.14.1
        * numba>=0.48.0
        * pillow>=7.0.0
        * qtawesome>=0.6.1
        * piexif>=1.1.3
        
        Installation
        ============
        Run the following commands to clone and install from GitHub
        
        ```console
        $ git clone https://github.com/SilMon/NucDetect.git
        ```
        
        or pypi
        ```console
        python3 -m pip install NucDetect
        ```
        
        Start
        ============
        The program can be started by running the NucDetectAppQT.py:
        ```console
        cd %UserProfile%/AppData/local/Programs/Python/python37/Lib/site-packages/gui
        python -m NucDetectAppQT
        ```
        
        ### Supported Image Formats
        
        Following image formats are supported by NucDetect:
        * TIFF
        * PNG
        * JPG
        * BMP
        
        ___
        
        Author: Romano Weiss
        
        Co-Author: Stefan Rödiger
        
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python :: 3.7
Description-Content-Type: text/markdown
