Описание
We worked on a consumer-facing model ported on mobile devices to help reduce cycling accidents. Our iOS application is designed to detect potholes in real-time when mounted on a cycle with the camera facing the road.
We use SOTA algorithms for object detection and tracking to complete our software. The SSD MobileNet model is trained for over 30,000 images of 4 types of potholes. We integrated this SSD model into an app and then are in the process of using this app to register potholes for local municipal corporations. The model works with an mAP of 60% and is definitely going to benefit both the government with automatic road analysis and the general public with avoiding accidents. We used the TF converter to create an edge device compatible model and adapt real-time detections on a phone. The project can help governments significantly reduce accidents and better register pothole data.