A Face Recognition Guestbook . A Web Application with Automated Testing Using Playwright

Abstract

This thesis explains the idea of creating a more user-friendly, locally running guestbook using authorization by facial recognition to check in without facing the requirement to write their names down for the record, and using their ID cards for authentication. The goal was to develop a web application that can store data and recognize the faces of registered users using a regular webcam and store their visited logs for recording. To fulfill this goal, the project is developed using Python Streamlit to build the user interface. OpenCV is used for facial recognition in the browser, and Pickle with Cv2 and Os is used for managing data storage locally within the system. The Date and Time function is used for login activities, which also maintains the visit time and date. Because this information is stored locally, it helps to keep the setup simple and secure. To ensure that every function of the application works perfectly and smoothly, automated testing was implemented using Playwright. Automated Playwright tests help users become familiar with test reports, saving time that would otherwise be spent checking each part of the application manually. This project demonstrates how facial recognition and room booking can be combined into a smooth, secure guest management experience.