ANPR Object Detection Dataset and Pre-Trained Model by Renuka

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Explore Dataset

Here are a few use cases for this project:

Traffic Management System: This model can be used to manage traffic and parking violations by identifying vehicle and license plate details accurately. Cameras installed at strategic locations like traffic signals, highways, or parking lots can take images of vehicles, and the model can process them to gather corresponding vehicle information.
Toll Collection Automation: The ANPR model can be instrumental in making toll collection processes faster and more efficient. The system can automatically recognize the number plates, classify the vehicle type and apply different toll rates accordingly, reducing human intervention and streamlining the process.
Security Checkpoints and Surveillance: This model can assist in enhancing security at critical places like airports, seaports, border crossings, etc., by capturing and analyzing vehicle and plate numbers in real-time. This can help in tracking suspect vehicles and increasing overall security.
Logistics and Fleet Management: Companies can use this model to manage their vehicle fleets more efficiently. By recognizing number plates, the model can help track vehicle movements, unauthorized use, and even ensure timely maintenance of vehicles.
Automotive Sales and Services: For used car dealerships or automotive service centers, this model could help keep a digital record of their vehicle inventory or serviced vehicles by capturing and analyzing vehicle and license plate visuals.

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{
                            anpr-pojnu_dataset,
                            title = { ANPR Dataset },
                            type = { Open Source Dataset },
                            author = { Renuka },
                            howpublished = { \url{ https://universe.roboflow.com/renuka/anpr-pojnu } },
                            url = { https://universe.roboflow.com/renuka/anpr-pojnu },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2024 },
                            month = { mar },
                            note = { visited on 2024-04-29 },
                            }