Wildlife isn't the same on every continent, so TrailCamHub doesn't lean on a single "world" model. It runs two specialist recognition engines and picks the right one for each camera automatically — with no settings for you to manage.
Two models, chosen by location
- Cameras in Europe use a model trained on European wildlife. It knows the continent's game — roe deer, red deer, wild boar, chamois, fox and more — and is fast and precise within that range.
- Cameras anywhere else use a global model covering more than 2,000 species, from white-tailed deer and elk to kangaroos and peccaries.
For the global model, geofencing narrows the field further: the camera's country (or GPS position) rules out species that can't occur there, so a kangaroo is never proposed for a photo taken in Denmark.
Every photo, automatically
Recognition runs the moment an image arrives. Each animal is located, counted and identified by species — and overlapping detections of the same animal are merged, so two deer count as two, not three. People and vehicles are recognised separately.
One consistent result
Whichever engine runs, the output has the same shape — species, counts, confidence and on-image boxes — so you never have to think about which model did the work.
The payoff is accuracy where it matters: a regional specialist beats a generalist on home ground, while the global model means the product works on every continent without compromise.