The Wildlife Insights platform uses AI technology to drastically reduce how long it takes to convert camera trap data into usable biodiversity insights. Anyone who collects camera trap data can use Wildlife Insights to upload data to Google Cloud and access AI models trained to automatically classify camera trap images. The Wildlife Insights AI model is trained using Google’s open source TensorFlow library.

Here's how AI can help:

The Wildlife Insights AI model is trained with the largest curated dataset of labeled camera trap images to date, with over 35 million images across 1,295 species. You can help -- adding your data to Wildlife Insights can help expand our AI capabilities to new species, existing rare species and improve our accuracy on the species already in the dataset.

Use this table to see if a species is in our current training dataset and how the model performs for that species.

If you see “Needs More Data” in the metrics, this means our AI model is not able to make a prediction with confidence above a fixed threshold (threshold is tuned manually). If you see “Not In Holdout” in the metrics, this means that this class wasn’t part of our stable Holdout Set, and therefore we weren’t able to measure the model performance accurately enough. If you do not see your species of interest listed it means that we currently have no examples of that species in our dataset. This is all the more reason to contribute, so we can continue to grow the number of supported species in Wildlife Insights.

Learn more about assessing classification accuracy for AI models in general.