O'quv auditoriyalarida shaxslarning holatini chuqur o'rganish orqali baholash uchun dataset yaratish.

Assessing students' activity and participation levels during the educational process plays a crucial role in improving the quality of education. Using modern computer vision and artificial intelligence technologies, it is possible to automatically detect students' states in the classroom in real time. This research describes a system based on the LabelImg v1.8.1 annotation tool [6] and the YOLO (You Only Look Once) deep learning algorithm to identify student conditions such as hand-raising, sleeping, and phone usage. The proposed system is expected to successfully recognize student states with 90-95% accuracy, assisting teachers in enhancing lesson effectiveness