Outcomes of the Hackathon “deep Learning in Java”

Milan, 6-10 February 2023

by Florian Jug

Global BioImaging and AI4Life organized a hackathon in Milan from February 6-10, 2023. The overarching goal of this event was to improve the accessibility of Deep Learning methods in Java-based image analysis tools and libraries. The event was held at the Human Technopole and was attended by a total of 21 participants from various parts of the world. 

The participants, representing tools such as, deepImageJ, Fiji, Icy, ImageJ, ImJoy, and QuPath, self-organized into topic-groups on day one and then tackled various challenges to bridge the system gap between typically python-based deep learning methods and Java (i.e. ImgLib2 based) image processing. 

These topic-groups made significant progress on different fronts over the 5-day event. A more in-depth report will soon be made available as an BioHackrXiv preprint. Among the highlights was the integration of a library by Carlos Garcia and colleagues (model-runner-java) into deepImageJ (and therefore into Fiji) and several other participants using this new way of running deep learning models on images opened in ImgLib2 containers (e.g. directly from Fiji). This was even pushed to extremes by combining the execution of models live from within BigDataViewer, e.g., enabling lazy prediction on terabyte sized datasets.

Additionally, another topic-group explored alternative ways to use the model-runner-java library, by directly sharing memory between native python processes and running Java VMs. Similar solutions exist (see for example imglyb or PyImageJ), but the newly explored idea is not any longer based on sub-processes but instead on inter-process communication. The big advantage of this approach is that parallel processes can be started independently, hook into each other on demand using shared memory, work together but die alone.

All participants are now continuing to flesh out the work that was started during the event and releases of updated versions of deepImageJ and a Fiji and Icy based deep learning integration are on their way. These updates will benefit hundreds of users world-wide.