Biodiversity

Microsoft Biodiversity

Open-source AI for biodiversity monitoring and conservation.
Microsoft AI for Good Lab — camera-trap detection, bioacoustic analysis, species classification, field deployment.

📣 Announcements

What we’ve been up to

Our journey started with MegaDetector — a camera-trap animal detection model that became a widely adopted tool in the conservation community. Building on that foundation, we created PyTorch-Wildlife as a unified platform to host all of our AI for biodiversity work, bringing together detection, classification, and eventually much more.

Over time, our scope grew well beyond camera-trap imagery. We now have active work in bioacoustics, overhead animal detection, and edge computing for remote field deployments. As the ecosystem expanded, it became clear that keeping everything inside a single repository was working against us. Code was harder to find, harder to maintain, and harder to extend.

So we made a deliberate decision: break the work into focused, dedicated repositories — one per project — where the code in each repo is concentrated, the ownership is clear, and future contributors know exactly where to go. This repository is the hub that ties them together. PyTorch-Wildlife now lives at microsoft/Pytorch-Wildlife, MegaDetector at microsoft/MegaDetector, and everything else is linked in the table below.

Previous versions:

• Release notes

Projects

Repo	What it is
microsoft/MegaDetector	AI model for detecting animals, people, and vehicles in camera-trap imagery — where it all started (documentation)
microsoft/MegaDetector-Acoustic	Bioacoustic AI for biodiversity monitoring — audio classification and species identification from sound
microsoft/MegaDetector-Classifier	Camera-trap species classification fine-tuning — adapt classifiers to your own datasets and geographic regions
microsoft/MegaDetector-Overhead	Overhead imagery detection — point-based wildlife localization from aerial views
microsoft/MegaDetector-Sonar	Sonar-based wildlife detection — processing and feature detection in sidescan sonar imagery
microsoft/Pytorch-Wildlife	The collaborative deep learning framework and model zoo for conservation AI
microsoft/SPARROW	Solar-Powered Acoustic and Remote Recording Observation Watch — AI edge device for remote field deployments

Cite us

When citing work that uses any of the repositories under this umbrella, please cite:

• Hernandez et al. 2024 — Pytorch-Wildlife: A Collaborative Deep Learning Framework for Conservation — for any use of the PyTorch-Wildlife framework or models accessed through it
• Beery, Morris, Yang 2019 — Efficient Pipeline for Camera Trap Image Review — for any use of MegaDetector specifically

A citation.cff file is included in this repository for automated citation tools.

Contributing

We welcome community contributions. See our Contribution Guidelines for how to participate.

Community

Have questions or want to connect with the team? Join us on Discord:

A list of organizations using MegaDetector across global conservation work — six years of partnerships, from national parks to research universities to NGOs — is maintained on the microsoft/MegaDetector repository.

About

Maintained by Microsoft AI for Good Lab.