SpeciesNet

SpeciesNet is an ensemble of AI models designed for classifying wildlife in images captured by motion-triggered camera traps. This open-source software helps conservation practitioners by automating the processing of vast quantities of image data, reducing the manual effort required for wildlife monitoring. The repository hosts the code for running these models, making advanced AI capabilities accessible for ecological research.

The system integrates two core components: an object detector and an image classifier. The object detector, MegaDetector, identifies animals, humans, and vehicles within camera trap images. Subsequently, the species classifier, SpeciesNet itself, takes these detected objects and classifies them to the species level. This powerful combination streamlines the identification process, allowing more time to be dedicated to actual conservation efforts.

Users can set up a Python environment, run the models, and even use GPUs for accelerated processing. The repository also provides options for downloading model weights directly, details on input/output formats, and guidance on visualizing results. It's a valuable tool for anyone involved in wildlife conservation and biodiversity monitoring.