This repository contains individual training codes of SSD and Mask R-CNN models for object recognition of human faces and license plates. In addition, it includes the implementation of a technology that selects and loads one trained model from YOLO, SSD, and Mask R-CNN using OpenCV and detects and blurs a face or license plate from a video.
By leveraging the advanced capabilities of YOLOv8, the system can efficiently recognize potholes on various road surfaces, aiding in timely maintenance and improving road safety. This project can be integrated into vehicles or drones to automate the process of pothole detection, providing a cost-effective solution for infrastructure monitoring.
Yolov11n model benchmarking on 20000+ fire images across multiple epochs.
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