With the power of machine learning...

Honey Batcher is able to understand what the photographer likes by observing trends in sharpness, exposure, and composition.


Every image is rated in these three categories.




Honey Batcher only selects pictures that are above a certain score.

It's okay to disagree with Honey Batcher's decisions. Correcting Honey Batcher's mistakes manually by moving photos back and forth between folders of "Good" and "Bad" photos helps Honey Batcher learn.