We weren't given many constraints related to the chess piece recognition itself. The course instead asks us to implement a CV research paper, and we chose an existing research project which focused on chess piece recognition.

That lack of constraints led us into running face first into issues of generalisation and variability within datasets. As in, exactly what you allude to with limiting the piece sets.

I think in my undergraduate naivety my aspirations were too high with what could reasonably be accomplished. I've spent a lot of time trying to improve an aspect of the project that really didn't need to be improved, which prevented meaningful progress.

Now finals are coming up and I feel terribly stressed. Having trouble functioning. Brain fog, etc. I feel so sad right now.

EDIT: I keep forgetting my password so apparently I have multiple throwaway now. Sorry.

That's correct. If you're curious about the architecture: the vision part detects a chessboard, then corrects the perspective and restricts the image to just the square of the board, then looks at each square and has some simple thresholds to decide if it's occupied by a piece, and of what color. From there, the camera is treated as a black box sensor that continuously streams two 64-bit masks, for where it thinks it sees white and black pieces. There is a second program (controller) that turns that stream into a stream of chess positions (and a Unix pipe in between). The sensor is faulty of course and the controller has logic for ignoring bits from the mask where there cannot possibly be pieces etc.