I spent most of my time this week testing CV on new images from the webcam. The webcam image quality was much lower than that of our chessboard, so I had to experiment with and change parameters for hough_line to discretise the image of the chessboard. The discretisation into squares works now. The first image below is that of the line detection for the webcam image, and the second is the extracted square.
The moves for the tested images are detected correctly 18/20 times. One of the wrong detections is for castling, which Yoorae and I will work on this week.
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I also worked on integrating CV with the chess game logic that Yoorae developed. I set up a capstone-integrated repo so Demi can also add her code there. I created a script that lets the user specify the path to 2 images. These images are then cropped by the neural network and CV detects the move. Then this move is validated by Yoorae’s code. It takes the current state of the chessboard (2d array) and the initial_position and final_position of the piece that moved. If the move is valid, I update the current state of the board.
This week, I plan to refine the script to deal with castling and promotion. I will also generate more testing metrics for the CV move detection. I am on track with the schedule.
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