Personal-Protective-Equipment-Detection

Personal Protective Equipment (PPE) Detection

The PPE Detection using YOLOv8 project automates the detection of Personal Protective Equipment (PPE) in images using the YOLOv8 object detection algorithm. It ensures workplace safety by identifying whether individuals are equipped with essential PPE items such as helmets, safety vests, goggles, etc. With easy-to-use scripts and the ability to train custom models, this project offers a versatile solution tailored to specific safety requirements, contributing to safer working environments and reduced risks of workplace accidents.

Introduction

In industries where safety regulations are crucial, it’s important to ensure that workers are wearing the necessary protective gear. This project utilizes YOLO-World, a state-of-the-art object detection model, to detect PPE items such as helmets, safety vests, goggles, etc., in images.

Results

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Note:

I’ve removed the large model files to reduce the repository size. If you need them, simply rerun the notebook, and they will be automatically downloaded to your current directory.

Installation

To run this project locally, follow these steps:

1. Clone this repository:

git clone https://github.com/SannketNikam/Personal-Protective-Equipment-Detection.git

1. Navigate to the project directory:

   cd Personal Protective Equipment (PPE) Detection
   

2. Install dependencies:

pip install -r requirements.txt