Deep Learning Approach for Vehicle Damage Analysis and Repair cost Estimation

As more cars hit the roads, accidents and damage are just part of the deal. Usually, experts handle vehicle damage assessments by hand—lots of waiting, high costs, and sometimes you don’t even get the same answer twice. That’s why this paper introduces a deep learning system to automate the whole process, from spotting damage on your car to figuring out what it’ll cost to fix. Here’s how it works: The system pulls in the YOLOv5 object detection model to scan uploaded photos for damage—think dents, scratches, busted parts, or crumpled panels. Then, OpenAI GPT-4o- mini steps in, crunches the damage data, estimates repair costs, and delivers a straightforward explanation. You don’t need any fancy tech skills to use it, either. It’s all packed into a web app, with React.js running the front and Python Flask running the back.