DamageLocation Object Detection Dataset and Pre-Trained Model by DamageDetection

Images

420 images

Explore Dataset

Here are a few use cases for this project:

Insurance Claims Processing: Streamline the process of submitting and analyzing car insurance claims by automatically identifying and categorizing car damage in submitted photos, allowing insurance providers to assess the extent of the damage and expedite claim processing.
Car Rental Inspections: Enhance the efficiency and accuracy of car rental inspections by using the DamageLocation model to identify and document any pre-existing damages when a customer picks up or returns a vehicle, protecting both the car rental company and the customer from disputes.
Auto Repair Shops: Assist technicians in auto repair shops to quickly evaluate the type and extent of car damage by processing images of the damaged vehicles, helping them to create accurate repair quotes and prioritize repairs based on the severity of the damage.
Online Car Auctions: Improve the credibility and transparency of online car auction platforms by using the DamageLocation model to detect and highlight any potential damages in the car images, allowing bidders to make informed decisions on their purchases.
Vehicle Maintenance Apps: Enhance vehicle maintenance apps' functionality by incorporating the DamageLocation model to analyze images captured by the users, providing personalized feedback and recommendations for car damage repair, and connecting users to appropriate local service providers.

Trained Model API

This project has a trained model available that you can try in your browser and use to get predictions via our Hosted Inference API and other deployment methods.

Cite This Project

If you use this dataset in a research paper, please cite it using the following BibTeX:

@misc{
                            damagelocation_dataset,
                            title = { DamageLocation Dataset },
                            type = { Open Source Dataset },
                            author = { DamageDetection },
                            howpublished = { \url{ https://universe.roboflow.com/damagedetection-hloj4/damagelocation } },
                            url = { https://universe.roboflow.com/damagedetection-hloj4/damagelocation },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2022 },
                            month = { sep },
                            note = { visited on 2024-04-19 },
                            }