ZeroCostDL4Mic: exploiting Google Colab to develop a free and open-source toolbox for Deep-Learning in microscopy
Tl;dr: this wiki page has everything you need to get started.
ZeroCostDL4Mic is a collection of self-explanatory Jupyter Notebooks for Google Colab that features an easy-to-use graphical user interface. They are meant to quickly get you started on learning to use deep-learning for microscopy. Google Colab itself provides the computations resources needed at no-cost. ZeroCostDL4Mic is designed for researchers that have little or no coding expertise to quickly test, train and use popular Deep-Learning networks.
| Running a ZeroCostDL4Mic notebook | Example data in ZeroCostDL4Mic | Romain's talk @ Aurox conference | Talk @ SPAOM |
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Any researcher interested in microscopy, independent of their background training. ZeroCostDL4Mic is designed for anyone with little or no coding expertise to quickly test, train and use popular Deep-Learning networks used to process microscopy data.
This project initiated as a collaboration between the Jacquemet and Henriques laboratories, considerably expanding with the help of laboratories spread across the planet. There is a long list of contributors associated with the project acknowledged in our related paper and the wiki page.
Lucas von Chamier*, Romain F. Laine*, Johanna Jukkala, Christoph Spahn, Daniel Krentzel, Elias Nehme, Martina Lerche, Sara Hernández-pérez, Pieta Mattila, Eleni Karinou, Séamus Holden, Ahmet Can Solak, Alexander Krull, Tim-Oliver Buchholz, Martin L Jones, Loic Alain Royer, Christophe Leterrier, Yoav Shechtman, Florian Jug, Mike Heilemann, Guillaume Jacquemet, Ricardo Henriques. Democratising deep learning for microscopy with ZeroCostDL4Mic. Nature Communications, 2021. DOI: https://doi.org/10.1038/s41467-021-22518-0
