Totally; the model does a good job finding what you teach it to find!
On the flip side, someone in the YouTube comments mentioned that we missed the ones on the wheels and license plates. So I added them to the dataset this morning and kicked off another train job.
I also noticed some false positives. It is a good demonstration of the difficulty of the task: there is no easy, automated, out of the box solution that will arrive at the correct answer. You could make a decent approximation if you could correlate frames and track individual bottles but even that is beyond the scope of this demo.
The official rules state that each reflected bottle is its OWN "counted bottle".
I was otherwise rather confused by the "count each bottle only once": there are a few in marquees and such where it's hard to tell if it's a repeat or a new bottle, frankly.
On the flip side, someone in the YouTube comments mentioned that we missed the ones on the wheels and license plates. So I added them to the dataset this morning and kicked off another train job.