In partnership with

Biowatch: Camera Trap Data, Visualized

A free, open-source desktop app that turns a folder of camera-trap images into living ecological insight — entirely offline.

Free & open-source

100% offline

Win / macOS / Linux desktop app

Source code Computer VisionMachine LearningCamera TrapsInteractive Map Live

Biowatch is Here

What started as a prototype is now Biowatch — a free, open-source desktop application that lets conservationists analyze, visualize, and explore camera trap datasets entirely offline. It runs on Windows, macOS, and Linux, and your sensitive wildlife data never leaves your computer.

From Raw Footage to Real Insight

Camera traps have transformed wildlife monitoring: they gather huge volumes of data non-invasively and at low cost. But AI that classifies the species in those images only solves half the problem. Conservationists still have to make sense of the results—spot spatial patterns, track activity over time, and turn millions of detections into ecological insight—often without specialist software or a dedicated data team.

Most tools stop at classification, or live on the web behind accounts and uploads. Biowatch is different. It’s a desktop app that keeps your data private, handles large datasets without lengthy uploads, and works in remote field locations. Installation is a simple double-click—no technical expertise required—and unlike web platforms such as Wildlife Insights, nothing ever leaves your machine.

How Biowatch works — import images or datasets, identify species on-device, explore the results on maps and activity charts, then export to GBIF or tidy per-species folders From raw images to a published study: import from anywhere, identify species on your own machine, explore patterns in space and time, then export to open standards — all without your data leaving your computer.

What Biowatch Does

Biowatch turns a folder of raw camera trap images, or a published dataset, into an interactive study you can explore.

Import from anywhere

Scan a folder of your own images, open a Camtrap DP package, or pull curated datasets straight from GBIF and LILA BC — Wildlife Insights and DeepFaune CSV exports included.

On-device species ID

Run AI models locally to detect and identify animals as a study builds: SpeciesNet (Google, 2,000+ species), MegaDetector (Microsoft), DeepFaune (CNRS, Europe) and Manas (Himalayan snow leopards), with a coverage map to pick the right one for your region.

Explore in space & time

See camera locations as species pie-charts, abundance, density heatmaps or hex grids, alongside daily-activity clocks and seasonal timelines — and filter species to compare their distributions and patterns.

Review & correct

Step through images in a gallery viewer, adjust bounding boxes, and fix AI predictions before they ever become observations.

Deployment insights

Per-camera activity timelines and heatmaps, with editable metadata you can export and re-import as CSV.

Standards-based export

Publish to GBIF as a Camtrap DP package, or export media organized into one tidy folder per species.

Everything runs locally. No cloud uploads, no accounts, no tracking—ideal for the sensitive location data of endangered species.

On-device AI model settings with coverage map

A glimpse of Biowatch in action — explore the full online manual for guided walkthroughs.

Free, Open Source, and Built in the Open

Biowatch is free to download for Windows, macOS, and Linux, and the full source is on GitHub for anyone to inspect, use, or improve. Built together with conservation partners, it closes the gap between AI classification and practical insight—making wildlife monitoring more effective, more private, and more accessible.