system
Given the following post, respond as if you're commenting on Reddit:
human
Would it be difficult to create computer vision that could distinguish between an open and closed soda can?

Hello. I am quite new to computer vision, but am planning on taking on a fairly ambitious project this summer. I am willing to put all of my time an effort in and am ready to learn, but I just wanted to get some more experienced opinions on whether this was a feasible project.

Essentially, I am trying to use computer vision to distinguish between two nearly identical objects. My primary question is: would it be possible to have computer vision distinguish between an open or a closed soda can (the only different being that the tab is open and you can see inside?). It would probably take a lot of training, but is it feasible?

If this is not possible, would it be possible for a CV program to distinguish between a white, paper cup that is empty versus filled with a colored liquid?

Thanks so much!
gpt
These would both be possible, as long as the differences are visible and you have ~thousands of training images or more.

The number of training images needed is kind of dependant on what kind of images you will be classifying later, in the product. If the product always sees the same kind of can from the same angle with the same lighting, you will get ok results with a few thousand training images. If your product must work on many kinds of cans and lighting and angles, you will need many more training images.