AI for Earth Camera Trap Stuff

A classifier tells you what an image is:

A detector tells you where in the image something is:

Detectors can also identify things:

Even though we don’t care about where in an image animals occur, and we do care about species classification, we want to convince you that it’s useful and important to build a “generic” detector for camera traps.

Why bother with detectors?

1. Natural way to get rid of non-animal images
2. Get value from lots of data, even in new ecosystems
3. Make classification a lot easier:
   Classifying an animal vs. classifying an animal and lots of background goop
4. Naturally handle classifying multiple species in an image
5. Naturally handle training data that’s labeled at the sequence level, and is unreliable at the image level
6. Natural way to get rid of non-animal images (so important we’re saying it twice)
7. Natural way to get rid of non-animal images (and a third time, now in bold)
8. Natural path to counting (sort of)

1. Available (code and model) on our GitHub page
2. Trained on several hundred thousand bounding boxes from a variety of ecosystems
3. Mostly about animals, but we recently added a “beta” people class, about to improve this and add a “vehicle” class