The counter-detection* files relate to the Fast-YOLOv4-SmallObj model, while the counter-recognition* ones relate to the Fast-OCR model. The YOLO-based models (i.e., Fast-YOLOv4-SmallObj and Fast-OCR) were trained using the Darknet framework, while CDCC-NET was trained using Keras. If you use the models trained by us in your research, please cite our paper: - R. Laroca, A. B. Araujo, L. A. Zanlorensi, E. C. de Almeida, D. Menotti, “Towards Image-based Automatic Meter Reading in Unconstrained Scenarios: A Robust and Efficient Approach,” IEEE Access, vol. 9, pp. 67569-67584, 2021. --------------------------------- You may also be interested in our previous research, where we introduced the UFPR-AMR dataset: - R. Laroca, V. Barroso, M. A. Diniz, G. R. Gonçalves, W. R. Schwartz, D. Menotti, “Convolutional Neural Networks for Automatic Meter Reading,” Journal of Electronic Imaging, vol. 28, no. 1, p. 013023, 2019.