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.
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.
Stars
27
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3
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Jun 01, 2025
Commits (30d)
0
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