Helmet Detection on Construction Site using OpenCV Python
Construction Helmet Detection with Neural Networks enhances workplace safety in construction sites by automating the monitoring of proper safety gear usage. Using neural networks, the system analyzes images or video feeds to identify workers wearing or not wearing helmets. This real-time detection ensures compliance with safety regulations, reducing the risk of head injuries and promoting a safer working environment in the construction industry.
Construction Helmet Recognition with Neural Networks builds on the foundation of safety in construction by recognizing and categorizing different types of helmets worn by workers. Leveraging neural networks, the system analyzes images to identify helmet variations, ensuring that the correct safety headgear is used for specific tasks. This application contributes to maintaining strict safety standards in construction environments, preventing accidents and protecting the well-being of workers.
Deep Learning based Workers Safety Helmet Wearing Detection on Construction Sites
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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