basel-ay/Automated-Car-Damage-Detection
Implementation of Mask-RCNN for detecting and segmenting damaged areas in car images for the purpose of damage assessment.
This project helps automotive insurance adjusters, repair shops, and inspectors quickly assess damage to vehicles. You input images of a car, and it outputs precise outlines of damaged areas, identifying their location and extent. This helps professionals efficiently estimate repair costs and process claims.
No commits in the last 6 months.
Use this if you need an automated way to accurately pinpoint and measure damage on car body images for insurance claims or repair estimations.
Not ideal if you need to detect internal mechanical issues or non-body damage, as this focuses specifically on exterior body damage visible in images.
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Jupyter Notebook
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Last pushed
Jan 11, 2023
Commits (30d)
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