JDLL: A library to run Deep Learning models on Java bioimage informatics platforms

TL;DR

JDLL is a Java library that simplifies the integration and deployment of deep learning models in bioimage analysis platforms, enabling seamless use of pre-trained models without complex setup.

Contribution

It introduces a comprehensive Java API for deep learning in bioimage informatics, bridging Python frameworks and supporting model deployment from the Bioimage Model Zoo.

Findings

Enables seamless deep learning model integration in Java bioimage platforms

Supports deployment of pre-trained models from Bioimage Model Zoo

Streamlines installation and maintenance of deep learning tools

Abstract

We present JDLL, an agile Java library that offers a comprehensive toolset/API to unify the development of high-end applications of DL for bioimage analysis and to streamline their installation and maintenance. JDLL provides all the functions required to consume DL models seamlessly, without being burdened by the configuration of the Python-based DL frameworks, within Java bioimage informatics platforms. Moreover, it allows the deployment of pre-trained models in the Bioimage Model Zoo (BMZ) by shipping the logic to connect to the BMZ website, download and run a selected model inference.