Building a U.S. License Plate Detection Model And Sharing It On Roboflow Universe

A U.S. License Plate dataset and model, featured on Roboflow Universe, was developed using images sourced from Google and Central Florida parks, and is designed for applications like police work, toll roads, and fast-food drive-throughs. The model was created through a series of steps including image uploading, annotation, preprocessing, and augmentation, with techniques such as auto-orientation and resizing to ensure uniformity, and enhancements like cropping and rotation to improve detection. The model achieved a mean average precision (mAP) of 94.9%, a precision of 95.7%, and a recall of 90.4%, indicating high accuracy and reliability. To comply with Roboflow Universe guidelines, the project emphasized originality, non-duplication, and appropriate naming conventions, alongside a well-crafted README and a comprehensive set of useful labels. The project encourages users to build upon this work and share their datasets on Roboflow, ensuring each entry includes a license and health check for legal and functional transparency.