This week I focused on making the CV work on our project environment. The difference detection of our code depended on absolute difference values from RGB color code, and the current black and white pieces did not show significant difference between the difference value on a square where the change has been made, and where the change has not been made. To make the absdiff value more distinct for the squares where a change has been made, I made an order for red colored chess piece set (that distinct from green and white squares) to decrease the error rate of the difference detection. I finished an algorithm for change detection with red pieces and updated it before our interim demo. Red pieces showed significantly lower error rate when detecting changes.
I also visited the lab on Thursday and Friday and took more sample photos from webcam. So far, we did not have a web cam stand and relied on photos that we took from our phone to test our CV. Since the webcam for our project produced photos with significantly lower resolution, we needed to make an update on our CV. On Saturday, I met up with Anoushka to make edits on edge detection because our CV was not detecting every vertical and horizontal lines in the photos. We made update on houghline thresholds, change detection threshold, and rectifying algorithm to make the CV work with the photos produced from webcam with lower quality.
I have also started on integration, on unifying coordinate outputs of CV and valid move logic so that it will work well with the stockfish AI. I will be focusing on translating coordinate system of our project for integration on Sunday, and will begin to work on piece identification CV algorithm when our newly ordered black chess pieces arrive. When user makes a capturing move, a color of chess piece has to be identified before updating a board state. I am planning on comparing RGB or HSV value to identify black and red pieces.