Facial Recognition Attendance System
This project implements an automated attendance tracking system using facial recognition on a Raspberry Pi. It combines image processing, face recognition, and Excel integration to streamline and digitize classroom or organizational attendance logging.
Features
- Real-time face detection and recognition.
- Excel-based attendance sheet generation and updates.
- LCD display for visual feedback.
- Buzzer for audio confirmation.
- Duplicate attendance prevention.
- Compatible with both Pi Camera and USB cameras.
- Supports headless (console) mode.
- Organized data by class name and date.
Hardware Requirements
- Raspberry Pi (preferably with Raspbian OS 64-bit).
- Pi Camera or USB webcam.
- 16x2 LCD display.
- Buzzer.
- GPIO wires.
Software Requirements
Python 3.x and the following Python libraries:
- opencv-python
- face_recognition
- xlwt
- xlrd
- xlutils
To install all dependencies at once:
- pip install -r libraries.txt
How to Run
- Capture Known Faces Before running the main script, capture and label known faces using: python capture_face.py
This will store images in a faces/ folder by pressing SPACE or Q to quit.
- Run Attendance System Once faces are stored, launch the main attendance system: python face_recognition_code.py
The script will:
- Load known faces
- Start video capture
- Recognize and mark attendance in Excel
- Show feedback on LCD and buzzer
- Log time of attendance for each individual