Facial Recognition Attendance System using Python OpenCV | Employee Attendance System using Face

Employee Attendance Monitoring System using Face Recognition in Python

• Core Logic: The main application logic will be developed in Python.
• Video Input: A webcam will be used to capture a real-time video stream.
• Face Detection: The system will use the Haar Cascade classifier, integrated via OpenCV, to detect faces from the live video feed.
• Face Recognition: Once a face is detected, the LBPH (Local Binary Patterns Histograms) algorithm will be used to match the face against a trained dataset to identify the user.
• Attendance Logging: When a user is recognized, an Attendance Marking Module developed in Python will automatically mark them as present, recording their name and a timestamp. The system will also be designed to prevent duplicate attendance entries in the same session.
• Data Storage: All user information and attendance records will be securely stored in either an SQLite or MySQL database.
• Admin Interface: A user-friendly interface will be developed, potentially as a web-based solution using Flask or a GUI using Tkinter. This interface will allow administrators to manage the system, register new faces, and view attendance logs.

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Software Requirements :-
• Coding Language : Python
• Implementation: Web Framework.
• Operating system : Windows 10 / 11.
• Graphical User Interface : HTML, CSS, Django

Hardware Requirement :-
• Input Devices : Keyboard, Mouse.
• System : Pentium i3 Processor.
• Hard Disk : 500 GB.
• Ram : 4 GB.

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