IN
introverthacker11/CompVision-SafeSightAI-PPE-DetectionSystem___r36
PPE Detection | Computer Vision | Sreamlit | YoloV8 | OpenCV | imageio & imageio-ffmpeg
🦺 PPE Detection & Tracking System (SafeSight AI)
🔗 Live App:
Visit Live App
📌 Overview
The PPE Detection & Tracking System is an AI-powered computer vision application designed to automatically detect Personal Protective Equipment (PPE) such as:
- 🪖 Safety Helmets
- 🦺 Reflective Safety Vests
The system works on images and videos, drawing bounding boxes and labels in real time to help improve workplace safety compliance at construction sites, factories, and industrial zones.
This project is built using YOLOv8 and deployed as an interactive Streamlit web application.
🚀 Key Features
- 📸 Image-based PPE Detection
- 🎥 Video-based PPE Detection
- 🧠 Powered by YOLOv8 (Ultralytics)
- 📊 Real-time progress bar for video processing
- 📥 Download detected video output
- 🖥️ Clean & professional UI for portfolio/demo
- ⚡ Fast inference with optimized frame processing
🛠️ Tech Stack
| Technology | Usage |
|---|---|
| YOLOv8 (Ultralytics) | Object detection model |
| OpenCV | Video & image processing |
| NumPy | Numerical operations |
| Streamlit | Web application framework |
| ImageIO / FFmpeg | Video writing & encoding |
| PIL (Pillow) | Image handling |
🧠 Model Details
- Model: YOLOv8s (Custom trained)
- Classes:
- Helmet
- Reflective Vest
- Framework: PyTorch (Ultralytics)
- Inference Type:
- Single image prediction
- Frame-by-frame video prediction
📂 Input Types Supported
✅ Images
- JPG
- JPEG
- PNG
✅ Videos
- MP4
🖼️ Application Workflow
- Upload an image or video
- Click Run Detection
- AI model detects PPE items
- Bounding boxes & labels are drawn
- View detected output
- Download processed video (for videos)
📦 Installation (Local Setup)
git clone https://github.com/your-username/ppe-detection-system.git
cd ppe-detection-system
pip install -r requirements.txt
streamlit run app.py📁 Project Structure
├── app.py
├── saved_trained_model.pt
├── requirements.txt
├── README.md
👨💻 Developer
- Rayyan Ahmed
- Google Certified AI Prompt Specialist
- IBM Certified Advanced LLM FineTuner
- Hugging Face Certified LLM Fundamentals
- Expertise: CV, ML, DL, YOLO, NLP, LLMs
🎯 Use Cases
- 🏗️ Construction site safety monitoring
- 🏭 Industrial worker compliance
- 📹 CCTV safety automation
- 📊 Safety audits & reporting
- 🎓 Academic & portfolio demonstration
📜 License
This project is for educational and portfolio purposes.
For commercial use, please contact the developer.