Metadata-Version: 2.1
Name: instantdl
Version: 1.0.4
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
Keywords: Computational Biology Deep Learning
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Topic :: Scientific/Engineering :: Image Recognition
Classifier: License :: OSI Approved :: MIT License
Requires-Dist: keras (>=2.2.4)
Requires-Dist: tensorboard (<=1.15.2,>=1.13.0)

# 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>

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## 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 in a project, you can cite the preprint on bioRxiv

```
@article {Waibel2020.06.22.164103,
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},
elocation-id = {2020.06.22.164103},
year = {2020},
doi = {10.1101/2020.06.22.164103},
publisher = {Cold Spring Harbor Laboratory},
URL = {https://www.biorxiv.org/content/early/2020/06/23/2020.06.22.164103},
eprint = {https://www.biorxiv.org/content/early/2020/06/23/2020.06.22.164103.full.pdf},
journal = {bioRxiv}
}
```

The main publication will be added soon.


