This repository contains a Facial Recognition Attendance System that leverages machine learning and MySQL database integration to automate attendance tracking. The system detects and recognizes faces in real-time, logs attendance, and provides flexible database access for schools and administrators.
- Real-time facial detection and recognition
- MySQL database integration for centralized attendance management
- Class management: Easily organize students into classes
- Daily, Monthly, and Term-Based Attendance Tracking:
- Attendance data is stored in MySQL, allowing schools to track records by day, month, or academic term (semester).
- Supports efficient queries for generating reports based on time periods or class groups.
- Attendance logging with timestamps
- User-friendly interface
- Scalable and customizable
The mysql version we work with the most is the best version. Pandas also works well but needs adjustments and debugging. PyQT5 is still in developement and incomplete.
To run this project, ensure you have the following installed.
- Python 3.8+
- MySQL Server
- opencv-contrib-python
- dlib
- NumPy
- pandas
- mysql-connector-python
- requests
- protobuf
- yapf
- xmltodict
- xlrd
- virtualenv
- toml
- six
- python-dateutil
- pytz
- pyparsing
- Pillow
- nose
- matplotlib
- kiwisolver
- cycler
- Click
- attrs
- black
- appdirs
You can install the Python dependencies by just running: requirements.txt
pip install -r requirements.txt