Metadata-Version: 1.1
Name: instantdl
Version: 1.0.5
Summary: An easy and convenient Deep Learning pipeline for image segmentation and classification
Home-page: https://github.com/marrlab/InstantDL
Author: Dominik Waibel, Ali Boushehri
Author-email: dominik.waibel@helmholtz-muenchen.de, ali.boushehri@roche.com
License: MIT
Description: # InstandDL: An easy and convenient deep learning pipeline for image segmentation and classification
        
        [![Build Status](https://travis-ci.com/marrlab/InstantDL.svg?branch=develop-test)](https://travis-ci.com/marrlab/InstantDL)
        
        InstantDL enables experts and non-experts to use state-of-the art deep learning methods on biomedical image data. InstantDL offers the four most common tasks in medical image processing: Semantic segmentation, instance segmentation, pixel-wise regression and classification. For more in depth discussion on the methods, as well as comparing the results and bechmarks using this package, please refer to our preprint on bioRxiv [here](https://doi.org/10.1101/2020.06.22.164103)
        
        <p align="center">
        <img src="docs/Instand_DL_farbig_RGB.png"  width="400" />
        </p>
        
        ---------------------------------------------------------------------
        
        ## Documentation
        
        For documentation please refere to [docs](docs)
        
        For a short video introducing InstantDL please see:
        
        <a href="http://www.youtube.com/watch?v=Wy4wlEyE2fA">
        <p align="center">
        <img href="InstantDL" src="http://img.youtube.com/vi/Wy4wlEyE2fA/0.jpg"
        width="500" align="center">
        </p>
        <a>
        
        ## Contributing
        
        We are happy about any contributions. For any suggested changes, please send a pull request to the *develop* branch.
        
        ## Citation
        
        If you use InstantDL, please cite this paper:
        
        ```
        @article {
        author = {Waibel, Dominik Jens Elias and Shetab Boushehri, Sayedali and Marr, Carsten},
        title = {InstantDL - An easy-to-use deep learning pipeline for image segmentation and classification},
        year = {2021},
        doi = {10.1186/s12859-021-04037-3},
        URL = {https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-021-04037-3#article-info},
        eprint = {https://doi.org/10.1186/s12859-021-04037-3},
        journal = {BMC Bioinformatics}
        }
        ```
        
Keywords: Computational Biology Deep Learning
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Topic :: Scientific/Engineering :: Image Recognition
Classifier: License :: OSI Approved :: MIT License
