Ismailjm / PPE_detection_using_YOLOV8

Enhance workplace safety with real-time detection of Personal Protective Equipment using deep learning and the YOLO algorithm in the 'PPE Detection' project.

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PPE Detection

The "PPE Detection" project is a computer vision application developed to detect and recognize Personal Protective Equipment (PPE) in industrial settings. Leveraging the power of deep learning and the YOLO (You Only Look Once) object detection algorithm, this project aims to enhance workplace safety by identifying and ensuring the proper usage of essential safety equipment such as helmets, safety vests, gloves, and safety glasses. By detecting the presence or absence of PPE in real-time video streams or images, this application provides valuable insights to help prevent workplace accidents and promote a culture of safety.

Key Features:

  • Real-time detection of Personal Protective Equipment (PPE) including helmets, safety vests, gloves, and safety glasses.
  • Utilizes the YOLO object detection algorithm for accurate and efficient detection.
  • Supports both video streams and static images for versatile usage.
  • Easily customizable and extensible for integration into various safety monitoring systems.
  • Designed with simplicity and effectiveness in mind to ensure user-friendly experience.

Usage:

  1. Clone the repository to your local machine.
  2. Install the necessary dependencies.
  3. Run the main script to start detecting PPE in video streams or images.
  4. Customize parameters or integrate into your own safety monitoring systems as needed.

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Enhance workplace safety with real-time detection of Personal Protective Equipment using deep learning and the YOLO algorithm in the 'PPE Detection' project.


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