Google CameraTrapAI
Google's wildlife recognition — MegaDetector+SpeciesNet, 2000+ species, for conservation
Google's wildlife recognition combining MegaDetector and SpeciesNet, covering 2000+ species — for the conservation scene.
Image generation and computer vision — detection, editing, 3D.
Key features
- SpeciesNet: ensemble of two AI models classifying wildlife in camera trap images
- MegaDetector object detector finds animals, humans, vehicles without species
- Species classifier trained on 65M+ camera trap images with 2000+ labels (species, taxa
- Ensemble combines both with heuristics and optional geographic info into a single category
- Also usable via Wildlife Insights, Animl, or the AddaxAI desktop tool; fine-tuning
Good for
- Conservation practitioners processing large camera trap image volumes
- Wildlife monitoring and species identification workflows
Stack & tags
Pythonwildlifecamera-trapspecies-classificationmegadetectorconservationgooglecomputer-vision
Quick start
pip install speciesnet
python -m speciesnet.scripts.run_model --folders "c:\your\image\folder" --predictions_json "c:\your\output\file.json"From the project README on GitHub.
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