PAIDIVERPY: An Open-Source Python package designed to create pipelines for preprocessing image data for biodiversity analysis.

Biologists and ecologists are increasingly using imaging systems to study the natural world. Getting meaningful biodiversity metrics from visual data requires reliable, reproducible image preprocessing. However, existing tools for image preprocessing are fragmented, application-specific, not well documented, and not designed for the needs of ecologists. This lack of standardization makes reproducibility difficult and slows down scientific progress. To address these challenges, we present PAIDIVERPY—an open-source modular Python package designed to simplify, standardize, and document image preprocessing workflows for biodiversity analysis. PAIDIVERPY is a flexible framework for building reproducible image preprocessing pipelines, complete with detailed documentation, and traceability for each step and image. The package is designed in collaboration with ecologists, enabling them to create and visualise preprocessing workflows without deep technical expertise. Users can easily add, remove, and customize steps, preview results at every stage, and output fully documented workflows in a standardized format. The tool supports preprocessing of complex biodiversity image datasets collected from diverse instruments and deployment strategies. Users can apply pixel-level transformations such as colour correction and backscatter removal, and subsample data to ensure unbiased metric estimation. The software also enables integration of custom algorithms alongside built-in processing steps, enhancing flexibility. To accommodate large datasets, PAIDIVERPY includes built-in support for parallelization using Dask and integration with batch schedulers for HPC environments. Its configuration system allows users to define processing steps in a structured, interoperable format, promoting reproducibility and simplifying modifications. Extensive tutorials and documentation accompany the tool. Additionally, two curated image sets from plankton and benthic surveys, complete with metadata, are provided to support testing and exploration. PAIDIVERPY enables ecologists to focus on scientific analysis while reducing the technical burden of data preparation. It bridges the gap between ecological expertise and AI-powered image analysis by making image preprocessing accessible, efficient, and reproducible.Acknowledgements This project was supported by the UK Natural Environment Research Council (NERC) through the Tools for automating image analysis for biodiversity monitoring (AIAB) Funding Opportunity, reference code UKRI052.A recording of this session is available on YouTube: https://youtu.be/kCwyjlnridY