A Deep Learning project using Pixellib pre-trained Mask RCNN model to classify yellow hardhat and white hardhat worn by construction personnels.
While other industries have undergone profound changes in productivity via automation and artificial intelligence, the business of building has not. Construction is still one of the least digitized industries worldwide and incurs a huge demand for workers. However, construction is one of the most dangerous job sector.
Hardhats play an essential role in protecting contruction individuals from accidents. However, wearing hardhats is not strictly enforced among workers due to all kinds of reasons. To enhance construction sites safety, the majority of existing works monitors the presence and proper use of hardhats through multi-stage data processing which come with limitations on adaption and generalizability.
This program tends to train a model using Mask-RCNN that will automatically monitor whether construction personnel are wearing hardhats and identify the corresponding colors. Hardhat color codes are simple yet effective way of keeping track of who is doing what and where they are supposed to be.