Helmet and Number Plate Detection and Recognition using Machine Learning
Helmet and Number Plate Detection, in this project it works on helmet and number plate detection, user have to upload any image and video to machine learning model and ML model detects that person is wearing helmet or not, if person not wearing helmet, then it will show in red boundary box and if rider wears then it shows in green box. Simultaneously it detects number plate and after detection it will store whole image in separate folder. This project is trained on large dataset of image and videos. Machine learning is used to trained that model so it can easily identify the violated riders.
Helmet and License Plate Recognition using Machine Learning, this project will detect helmet and license plate detection and if person not wearing helmet, then it will fetch number from the license plate and sent challan on registered mobile number. First user has to browse any input image or video then machine learning model will detect that person is wearing helmet or not, after that it will detect number plate. In second option it will detect without helmet person and model will fetch number from license plate. Once the license plate fetch then it will send an alert message on registered mobile number that person is doing violation.
Helmet and Number Plate Detection using YOLO
Software Requirements :-
- Coding Language : Python
- Implementation: Software Framework.
- Operating system : Windows 10 / 11.
- Graphical User Interface : Tkinter
Hardware Requirement:-
- Input Devices : Keyboard, Mouse.
- System : Pentium i3 Processor.
- Hard Disk : 500 GB.
- RAM : 4 GB.
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