Road Crack Segmentation

This project showcases an advanced, AI-assisted pavement inspection tool designed to automatically identify road cracks and major surface distresses using deep learning–based semantic segmentation.

The system analyzes high-resolution road imagery and accurately classifies defects such as cracks, potholes, raveling, and surface wear. By leveraging state-of-the-art segmentation models, it delivers pixel-level precision, enabling faster, safer, and more cost-effective road-condition assessment for municipalities, contractors, and infrastructure planners.

This tool significantly reduces manual inspection effort while improving consistency and reliability in road-health monitoring.

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