BIAPY: A Ready-to-Use Library for Bioimage Analysis Pipelines

In recent years, technological advances in microscopy have made available large amounts of data to biomedical researchers in the form of images. By learning from such large datasets, deep learning-based methods have successfully addressed previously inaccessible bioimage analysis tasks. However, most of the available solutions target a particular subset of problems, forcing the user to be familiarized with different applications to complete their data analysis. On top of that, other issues, such as reproducibility, lack of documentation, or access to the code, arise. For these reasons, we introduce BiaPy, an open source ready-to-use all-in-one library that provides deep-learning workflows for a large variety of bioimage analysis tasks, including 2D and 3D semantic and instance segmentation, object detection, super-resolution, denoising, self-supervised learning, and classification. All code and documentation are publicly available at https://github.com/danifranco/BiaPy.