CTT-Cooling Tower Tracker (GeoKITS)
Jan 2024 - Feb 2024
This advanced desktop application, engineered using Python and QT Designer, integrates a sophisticated YOLO machine learning model for high-precision detection of cooling towers in satellite imagery. The system quantifies detection confidence, facilitating critical infrastructural analysis and planning.
Python
Machine Learning
YOLO v5
Qt Designer
Figma
Detailed Overview
Project Overview
The CTT-Cooling Tower Tracker project was developed to enhance the identification and analysis of cooling towers using advanced machine learning techniques.
Key Features
- High-Precision Detection: Utilizes YOLO v5 for accurate detection.
- Confidence Quantification: Measures and displays detection confidence.
- User-Friendly Interface: Developed with Qt Designer for ease of use.
- Detailed Analysis: Provides comprehensive analysis reports.
Technical Details
- Programming Language: Python
- Machine Learning Model: YOLO v5
- UI/UX Design: Figma and Qt Designer
Further Images
Testimonials
John Doe
This project exceeded our expectations. The level of detail and professionalism was outstanding.
Jane Smith
A truly remarkable project that delivered excellent results. Highly recommended!
Platforms & Tools
This project was developed using a variety of platforms and tools, ensuring high-quality results and seamless performance.