This repository contains the details and associated code for the paper: A Machine Learning Application to Camera-Traps: Robust Species Interactions Datasets for Analysis of Mutualistic Networks. The ms is now under review, available at bioRxiv, here.
You can use this repository as a guide for processing large numbers of video-file sets generated during camera trap surveys for monitoring animal-plant interactions (i.e., visits of animal frugivores to fruiting plants). We combine a camera trap field protocol (preprocessing) with several tools for time-saving processing (and post processing).
This workflow aids to manage camera traps in the field, transfer and store data to the lab and post-process large video files batches, reducing effort and time in the database compilation. The method combines a field protocol based on camera trap operation and data standards together with Artificial Intelligence for image recognition and a viewer interface to visualize and tag images. The main objective is to build an accurate and fully annotated dataset for animal-plant interactions records while time effort is minimised. This paper accompanies Villava et al. (2024).
Villalva, P., Arroyo‐Correa, B., Calvo, G., Homet, P., Isla, J., Mendoza, I., Moracho, E., Quintero, E., Rodríguez‐Sánchez, F., & Jordano, P. (2024). FRUGIVORY CAMTRAP: A dataset of plant–animal interactions recorded with camera traps. Ecology, 105(11), e4424. https://doi.org/10.1002/ecy.4424