Damage Detector

Industry: Insurance

Overview

Real-world damage detection from videos/photographs of vehicles being in an accident. Insurance companies have to deal with a lot many claims daily & have to employ surveyors to deal with estimations of cost. Which in the result is prone to human error & may result in some discrepancies. To avoid such cases, we were tasked to handle the damage detection part for 4 wheelers.

Technology

Python
Deep Learning
Transfer Learning
Neural Networks
Computer Vision
Image Processing

Key Technical Challenges:

Working with all types of damages like glass breakage, doors slammed, dents, scratches to name a few.
Annotating the images & getting to a sufficient amount of data points for training
Creating clustered environment for training due to huge processing taken by image kind of data
Quick inference for production system.
Making a generalized model for all categories of 4 wheelers