Camera-mounted Helmet detection with Yolo v8 on custom dataset

The model for naturally recognizing bikes and riders in rush hour gridlocks for distinguishing images between civilians riding wearing helmets and those who are not wearing helmets. Further, the model scans to detect if the rider who is wearing a helmet, is using a camera that is attached to the helmet which is an offence as it tampers with the original structure of the helmet. This is an offense and we are automating the detection of these offenses. The model is trained with a custom-labeled dataset to identify helmets and omits the result. An annotating bounding box is used to mark the detected objects and make an accurate prediction. The classified image is printed as the final result.