This post presents a dataset designed for detecting road cracks and potholes using YOLOv11, a state-of-the-art object detection model. The dataset includes annotated images of various road defects, making it suitable for training models for infrastructure inspection. This is particularly relevant for smart city initiatives and maintenance automation. The post likely covers data collection, annotation, and model training tips. For developers, this is a practical resource to build or enhance inspection systems. The commercial value is high due to the demand for automated road maintenance solutions.
A dataset for detecting road cracks and potholes using YOLOv11, useful for infrastructure inspection and smart city applications.