ADVANCED VIDEO SEGMENTATION TOOL USING PyQt5 AND OpenCV

This paper presents the development of an advanced video segmentation tool leveraging PyQt5 for the graphical user interface and OpenCV for real-time object detection.The system enables users to load videos, detect blue and white objects, and adjust detection sensitivity through an intuitive interface.Key features include live object counting, real-time playback, and robust error handling.The methodology employs HSV color space filtering and multithreaded processing to ensure smooth user experience and accurate detection.Experimental results demonstrate approximately 90% detection accuracy for clear colors at real-time speeds of 30 FPS, with multithreading achieving up to 13x performance improvements.The tool provides a practical solution for surveillance, research, and industrial applications.