Periodic Reporting for period 1 - AI4LIFE (Artificial Intelligence for Image Data Analysis in the Life Sciences)
Reporting period: 2022-09-01 to 2023-08-31
The Model Zoo and the AI4Life project in general aims to serve both method developers and end users. To increase the engagement of method developers, we are working on contributor services that will streamline, simplify and robustify the deployment of new AI-based methods through the Model Zoo. Here, the main accomplishments of the first year include the development of Python and Java libraries to operate with models and validate them locally before submission to the Zoo, as well as the development of the first version of continuous integration tools for the Zoo, automatically testing all submitted models. The ongoing integration of JupyterLite and exploration of container technologies within the Model Zoo front-end and back-end has laid the foundation for a new deployment service of Jupyter notebooks as user-facing web-apps, further lowering the barrier of entry for model developers wishing to address end users directly.
For end users, we have greatly increased the accessibility of the website, created multiple tutorials and documentation pages and performed overall improvements to the User Interface of the interaction with models. Furthermore, the user community was heavily involved in the first Open Call, submitting more than 70 projects which highlighted outstanding problems across a broad range of applications and modalities. We developed the necessary procedures for project selection and openly published them on Zenodo to seed future initiatives. Finally, we developed a standard for annotated data to enable submission of such data - usually as ground-truth for training of AI-based methods - into the BioImage Archive. As one of the first tests, the standard will be used for data annotated through Open Calls.