5/1/2023 0 Comments Hyper bullet chess rulesRunning this algorithm on the Jetson Nano takes about 150 milliseconds per board. In situations where the camera and the board remain still, we have introduced in Section 4.1 an algorithm to check if the board’s location in the image is the same as in previous images. In this snapshot, also a white knight, which had a probability of 0.99 of being in square 62, and a black rook, which had a probability of 0.98 of being in square 7, have been set. The kings are set at the beginning of the algorithm. Figure 4: Outline of the data used by the inference of the position on the board. In any case, the piece is removed from its list of ordered pieces, as it has already been processed (Figure 4). If the maximum occurrences of that type of piece have not yet been reached and the square it represents on the board has not yet been filled, it is selected. Afterward, the algorithm iterates by choosing the element at the top of the list with a higher probability ( tops vector). Thus, 10 lists of pairs of pieces and squares are obtained ordered from highest to lowest probability of containing the corresponding piece (the top vertical lists in Figure 4). First, the remaining squares are sorted according to their probability of containing each of the remaining 10 classes (in total, there were 13, but the kings’ positions and the empty squares have already been decided). In order to classify the pieces that are not kings, the program follows the following steps. Notably, we have implemented a functional framework thatĪutomatically digitizes a chess position from an image in less than 1 second, Subsequently, we have analyzed different Convolutional Neural Networks forĬhess piece classification and how to map them efficiently on our embedded Our firstĬontribution has been accelerating the chessboard's detection algorithm. On an Nvidia Jetson Nano single-board computer effectively. We have investigated how to implement them Of state-of-the-art techniques still need further enhancements to allow their Work has shown promising results, but the recognition accuracy and the latency Over-the-board (OTB) games online or analyze them using chess engines. Organizers and amateur or professional players to broadcast their This problem is of much interest for tournament Automatic digitization of chess games using computer vision is a significant
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