Summary:
PPE Detection is a project focused on monitoring CCTV streams within factory sites to ensure that personnel are adhering to safety regulations by wearing proper personal protective equipment (PPE). The model specifically checks for the presence of safety hats and vests, generating reports for any non-compliance and saving images of infractions for further review.
Features:
- Object Detection:
- Employs YOLOv7 convolutional neural networks (CNNs) for vehicle and object detection.
- Determines the location and boundaries of individuals in the frames.
- PPE Compliance:
- Checks for the presence of safety hats and vests on individuals.
- Flags instances where individuals are not wearing the required PPE.
- Tracking and Reporting:
- Utilizes object tracking techniques (DeepSort) to follow individuals across frames.
- Employs external memory arrays and similar optimization techniques to avoid redundant processing and ensure efficient monitoring.
Implementation Highlights:
- Object Tracking:
- May utilize algorithms like Kalman filtering to track individuals across frames, reducing the need for redundant processing.
- Efficient Memory Handling:
- External memory arrays and similar optimizations are employed to store and manage tracking information efficiently.
- Event Logging and Reporting:
- Captures images or frames of non-compliant instances.
- Generates reports for the health and safety officer, providing a record of compliance violations.
Tech-stack:
- Artificial Intelligence: Python, YOLOv7 for object detection, DeepSORT for real-time tracking.
- NumPy: Efficient for data manipulation.
- This combination creates a robust solution for monitoring workplace safety through CCTV streams, ensuring adherence to safety regulations and generating reports for any non-compliance incidents.
Application:
PPE Detection serves as a crucial tool in upholding workplace safety standards. By automating the continuous monitoring of PPE compliance, it contributes to a safer working environment. The detailed reports and stored images empower safety officers to take proactive measures, fostering a culture of safety within the factory and minimizing the risk of accidents and injuries.
Results:
