Annotated Road Surface Anomalies Dataset for Real-Time Detection Using YOLOv8

This dataset contains 4,968 annotated images of road surface anomalies across five classes: Pothole, Drain Hole, Sewer Cover, Wet Surface, and Unpaved Road. Captured under varied lighting, weather, and surface conditions, the dataset is designed for real-time object detection tasks in road safety and infrastructure monitoring.Annotations were created using Roboflow in YOLOv8 format. The data is split into training (75%), validation (16%), and test (9%) sets. It supports the development of lightweight, high-accuracy models for smart city applications.