I'm actually the author of the post as well. Two things: 1. I stated 10 cameras, not 1 so according to your calculations that would mean 190 GB per day instead of 19 GB. 2. I didn't make the assumption that there is always a unique frame but rather got this estimate by trying to save videos using OpenCV across various types of cameras. The variable I didn't change was the environment I took these videos in, which tended to be high activity ones where many frames did have some motion in them. 1 TB might be an overshoot sometimes, but the point of adding it into the article was to highlight the order of magnitude for a setup, that all things considered is pretty small. Another thing is that in the context of computer vision training data, the number of frames is something we care about more than the amount of space they take up which is why I also state 27 million frames.
Thanks for pointing it out though. Might be better not to even mention video file size given the high variability.