This dataset contains images of serial numbers extracted from diverse avionic parts manufactured by SAFRAN, the international high-technology group and world leader operating in the aviation (propulsion, equipment and interiors), defense and space markets. This dataset resembles the well-known MNIST dataset, but with a focus to industrial contexts, encompassing variations in lighting conditions, orientations, writing styles and surface textures. The dataset contains 32 classes depicting numbers, alphabetic characters, and symbols, namely: [0, 1, 2, 3, 4, 5, 5, 6, 7, 8, 9, A, B, C, D, E, F, G, H, J, K, L, M, N, P, R, S, T, U, W, Y, /, .] April 30th, 2024 : Training dataset containing 9314 images without labels is released. December 5th, 2024 : Testing and validation datasets released, ground-truth labels for training, validation and testing released. This dataset has been proposed in the context of ICPR24 DAGECC Competition