In this challenge, you will build and train a computer vision model that takes high-resolution images of chessboard positions and classifies them into the appropriate ECO volume category (A, B, C, D, or E). The images represent the final board state after the opening moves, and your model must learn to distinguish subtle differences in piece placement corresponding to different opening families.