PPE GUARD - PERSONAL PROTECTIVE EQUIPMENT DETECTION

AI-Powered Safety Compliance Monitoring System

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Tech Stack

• Python 3.8+
• FastAPI 0.104+
• YOLOv8 (Ultralytics)
• Html, Css, Js

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📝 About

PPE Guard is an intelligent Personal Protective Equipment detection system powered by the YOLOv8 deep learning model. It automatically identifies whether individuals are wearing required safety gear including helmets, vests, gloves, boots, and face masks.

Suitable for:

• Construction sites
• Industrial zones
• Hazardous work environments

Benefits:

• Reduce human error in safety monitoring
• Ensure workplace safety compliance
• Provide instant alerts for missing equipment
• Generate safety compliance reports

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✨ Features

Core Functionality

• Real-time Webcam Detection
• Image Upload Analysis
• High Accuracy YOLOv8 Detection
• Near Real-Time GPU/CPU Processing
• Confidence Scoring Display

User Experience

• Modern Glassmorphism UI
• Fully Responsive Design
• Download Annotated Results
• Privacy First (No external data sharing)

Technical

• Custom-trained PPE model
• FastAPI Backend
• Adjustable thresholds (Confidence / IoU)
• REST API for easy integration

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📸 Demo

Screenshots:

1. Homepage –

2. Detection Results – Highlighted PPE items with confidence values

3. Webcam Detection – Live monitoring feed

🚀 Quick Start

Prerequisites

• Python 3.8+
• pip
• Webcam (optional)

Installation

1. Clone repository git clone https://github.com/your-username/ppe-guard.git cd ppe-guard

2. Create and activate virtual environment python -m venv myenv

Windows myenv\Scripts\activate

macOS/Linux source myenv/bin/activate

3. Install dependencies pip install -r requirements.txt

4. Add Trained Model Download model: https://drive.google.com/uc?export=download&id=14jNk69dfp8qO7xJXiaFggttIzH_b6z1Q

Place as: PPE-Guard/app/model.pt

5. Run Application uvicorn app.main:app --reload

Visit: http://127.0.0.1:8000

🧪 Usage

Image Upload Detection

1. Click Upload Image
2. Choose an image
3. View detection results & confidence
4. Download annotated image

Live Webcam Detection

1. Click Live Webcam
2. Allow camera permissions
3. Start detection
4. Stop when finished

# 📂 Project Structure

PPE-GUARD/
├── app/
│   ├── main.py
│   ├── utils.py
│   ├── model.pt
│   ├── static/
│   │   └── style.css
│   └── templates/
│       ├── index.html
│       └── webcam.html
├── requirements.txt
├── README.md
└── .gitignore

🛡 Supported PPE Classes

1. Safety Helmets
2. Safety Vests / High-Visibility Jackets
3. Safety Boots
4. Safety Gloves
5. Face Masks / Respirators

📦 Dependencies

1. FastAPI
2. YOLOv8 (Ultralytics)
3. OpenCV
4. Uvicorn
5. NumPy
6. Pillow (See requirements.txt)

🔮 Future Enhancements

1. Mobile App Version
2. Docker Container Support
3. Cloud Deployment Guide
4. Multi-Camera Support
5. Video File Processing
6. PDF Safety Reports
7. Integration With Security Systems