A YOLOv26-based object detection model for classifying traffic signs by physical condition. Fine-tuned on street-level imagery for use in road infrastructure monitoring and mapping pipelines.
Trained on the
traffic-sign-detection-znanc-9hhnw dataset from Roboflow. The dataset consists primarily of traffic sign images captured from a distance, representative of typical street view or dashcam footage.
The model performs well on street view imagery where signs appear at a distance, which matches the training distribution. It is well-suited for automated road surveys, mapping applications, and infrastructure audits.
