tyreDetection Object Detection Dataset and Pre-Trained Model by calerwang

Images

1336 images

Explore Dataset

Here are a few use cases for this project:

Vehicle Inspection Automation: This model could be used in automated vehicle inspection systems in garages or service centers to detect the condition of the tires accurately and quickly. The system can help mechanics in preventative maintenance by identifying the potential risks associated with cracked or broken tires.
Tire Manufacturing Quality Control: Tire manufacturers can use tyreDetection in the quality control process to automatically identify any faulty products before they reach the consumers. Any detected cracks or breaks in the tires, which might be difficult to spot manually, could be easily identified by the model.
Roadside Assistance Services: Roadside assistance services could utilize this model to help drivers identify if the tire condition is safe enough to continue driving or if it needs immediate replacement. This could be implemented through a mobile app where drivers can capture a photo of their tires.
Vehicle Insurance Companies: Vehicle insurance companies might use this model to process insurance claims related to tire damage. This can make the claim verification process more efficient and reduce fraudulent activities.
Used Car Dealerships: Used car dealerships can use the "tyreDetection" model to assess the quality of the tires of pre-owned cars. Dealerships can provide a detailed analysis to their customers and ensure safety standards are met.

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{
                            tyredetection-damkf_dataset,
                            title = { tyreDetection Dataset },
                            type = { Open Source Dataset },
                            author = { calerwang },
                            howpublished = { \url{ https://universe.roboflow.com/calerwang/tyredetection-damkf } },
                            url = { https://universe.roboflow.com/calerwang/tyredetection-damkf },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { mar },
                            note = { visited on 2024-04-26 },
                            }