Damage-Detection Object Detection Dataset and Pre-Trained Model by sankett gorey

Images

3192 images

Explore Dataset

Here are a few use cases for this project:

Insurance Claims Processing: The model can be utilized by insurance companies to quickly assess damage to vehicles involved in accidents. By feeding accident photos into the model, the extent and location of damage can be efficiently determined, thus streamlining the claims process.
Vehicle Maintenance and Repair: Automobile repair shops can use this model to diagnose visible damage. This way, mechanics have a preliminary idea of the repair needed before physically inspecting the vehicle.
Shipping Industry: Companies can use it to detect damage in shipping containers or goods during transportation. This can help to hold the relevant parties accountable for the damages.
Road Safety: Traffic authorities can deploy this model on traffic cameras to identify damaged vehicles on the road, helping to maintain road safety by flagging vehicles that may be unfit for the road.
Infrastructure Maintenance: Government agencies or construction companies can use the model to spot physical damage on infrastructure like bridges, buildings, or roads. This could aid in early detection, preventing further deterioration and potential dangers.

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{
                            damage-detection-l36f0_dataset,
                            title = { Damage-Detection Dataset },
                            type = { Open Source Dataset },
                            author = { sankett gorey },
                            howpublished = { \url{ https://universe.roboflow.com/sankett-gorey-pwlku/damage-detection-l36f0 } },
                            url = { https://universe.roboflow.com/sankett-gorey-pwlku/damage-detection-l36f0 },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { feb },
                            note = { visited on 2024-04-26 },
                            }