Technologies Used
Computer Vision
YOLOv5
OpenCV
Safety Systems
Real-Time Detection
Project Overview
Developed an AI-powered image processing system using YOLOv5 to detect fire, smoke, and face masks in real-time. Integrated OpenCV for preprocessing and optimized the model for low-latency deployment in safety-critical applications.
Key Features
- Implemented using Computer Vision, YOLOv5, OpenCV
- Developed during Jun 2022 - Aug 2022
- Focused on performance, usability, and modern design principles
- Utilized best practices for code organization and maintainability
Development Process
This project was developed with a focus on creating a robust and scalable solution. The development process involved careful planning, implementation of key features, rigorous testing, and deployment.
Project Details
Project Type
Computer Vision
Timeline
Jun 2022 - Aug 2022
Primary Technologies
Computer Vision
YOLOv5
OpenCV
Related Skills
Computer VisionYOLOv5OpenCVSafety SystemsReal-Time Detection