final_data Object Detection Dataset and Pre-Trained Model by pitavision

Images

2571 images

Explore Dataset

Here are a few use cases for this project:

Traffic Law Enforcement: The "final_data" computer vision model could be used by traffic law enforcement authorities. It can automate the process of identifying and cross-referencing license plates to maintain traffic regulations, thus improving efficiency.
Toll Collection: This system could be used in automatic toll collection at toll booths. By identifying license plates, it can automate the billing process and make it faster and more efficient.
Parking Management: The model can help in managing and automating parking systems, such as finding available spaces, maintaining records of parked cars, or identifying unauthorised parking.
Vehicle Tracking: The model can use in surveillance systems, or by insurance companies for tracking stolen vehicles, thus contributing to maintaining car safety and lowering crime rates.
Re-Sale Autos Verification: It could be used by used-car dealerships or websites to match the license plate information to the correct vehicle profile to prevent scams or frauds.

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{
                            final_data-atrv7_dataset,
                            title = {  final_data Dataset },
                            type = { Open Source Dataset },
                            author = { pitavision },
                            howpublished = { \url{ https://universe.roboflow.com/pitavision/final_data-atrv7 } },
                            url = { https://universe.roboflow.com/pitavision/final_data-atrv7 },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { jun },
                            note = { visited on 2024-05-22 },
                            }