ReverendBayes/YOLO11m-Car-Damage-Detector

Custom YOLO11m model for detecting and classifying car body damage (99% shattered glass, 96% flat tire detection accuracy)—optimized for high-capacity inference and assistive use in inspection and service workflows like BMW pre-loaner inspections.

34
/ 100
Emerging

This tool helps automate and standardize the visual inspection of vehicle exteriors. It takes images of cars and identifies common damage like dents, scratches, shattered glass, or flat tires, producing a detailed report of detected issues. Car dealership service advisors, fleet managers, or insurance adjusters can use this to quickly document vehicle condition.

No commits in the last 6 months.

Use this if you need to rapidly and consistently identify exterior damage on vehicles during intake, inspections, or audits to streamline workflows and reduce disputes.

Not ideal if you require perfect detection for subtle cracks or small dents, as the model's performance on these specific types of damage is less robust.

vehicle-inspection automotive-service fleet-management insurance-claims damage-assessment
Stale 6m No Package No Dependents
Maintenance 2 / 25
Adoption 7 / 25
Maturity 15 / 25
Community 10 / 25

How are scores calculated?

Stars

27

Forks

3

Language

Jupyter Notebook

License

MIT

Last pushed

Jun 01, 2025

Commits (30d)

0

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