Student Identification Gender Detection

The Student Identification Gender Detection project aims to predict the gender and identify specific clothing items of students based on an uploaded image using YOLOv8, a state-of-the-art object detection algorithm. The system operates by first predicting the student's gender—either male or female—and then detecting relevant clothing items associated with each gender. For male students, the system detects items such as an ID card, formal shirt, formal pants, belt, and shoes. For female students, the system identifies an ID card, chunni, and kurta. The total score is calculated based on the detection results, providing an efficient way to monitor and track student uniforms and accessories. The backend of the system is developed using Python, with a frontend interface designed in Flask/Streamlit, allowing users to upload images. Additionally, an email notification is sent to both the parent and mentor for each prediction, ensuring effective communication and monitoring.

Keywords: Gender detection, YOLOv8, Student identification, Object detection, Flask, Streamlit, Clothing detection, Email notifications.