Helmet Detection and Number Plate Recognition using Machine Learning
Helmet and Number Plate Detection, this project works on helmet detection and license plate detection, user can upload any video or image to machine learning model and it detects that rider is wearing helmet or not, if rider not wearing helmet, then it will make red boundary box and if rider wears then it shows in green box. Parallel it detects number plate and after detection it will store whole image in separate folder. This ML Model trained on large dataset of image. Machine learning is used to trained that model so it can easily identify the violated riders.
Helmet is important just in the event of moving bicycle riders, so preparing full casing becomes computational overhead which doesn’t increase the value of discovery rate. So as to continue further, we apply foundation subtraction on dim scale outlines, with an aim to recognize moving and static items. Next, we present advances associated with foundation displaying.
Helmet Detection Project using Python
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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