Vikas2425/Safety-Helmet-Detection

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

🦺 Safety Helmet Detection System

An end-to-end Computer Vision application designed for industrial safety compliance. This system detects whether personnel are wearing safety helmets in real-time using the YOLOv8 architecture.

🚀 Key Features

• —Real-time Detection: High-speed inference using YOLOv8.
• —Production-Ready: Built with a modular coding structure for scalability.
• —Containerized: Fully dockerized for consistent deployment across environments.
• —Robust Logging: Includes custom logging and exception handling for production monitoring.

🛠️ Tech Stack

• —Model: YOLOv8 (Ultralytics)
• —Backend: Flask (Python)
• —Deployment: Docker, Hugging Face Spaces
• —Tools: OpenCV, Pandas, YAML

🏗️ Project Structure

• —src/: Core source code including components and pipelines.
• —templates/: Flask HTML interface.
• —app.py: Main entry point for the web application.
• —best.pt: Custom trained YOLOv8 weights.

📈 Impact

Ensures 24/7 monitoring of safety protocols in construction and manufacturing zones, reducing human error in safety inspections.