ignaciodejesus / attendance-with-face-recognition

Attendance with Face Recognition

Welcome to the Attendance with Face Recognition repository! This repository is designed to facilitate attendance tracking through facial recognition and seamless database registration.

• The Attendance directory houses the core code responsible for executing the facial recognition process and registering attendance in the database.
• The Images directory is designated for storing the photographs of individuals, which the system will use for recognition purposes. Every photo will be identified and registrated by the file name.

Requirements

Before getting started, please ensure you have the following prerequisites ready:

• MySQL installed, with a database named attendance_db created within it (you have to create it).
• pip installed and properly configured in your system's PATH.
• virtualenv installed to manage the project's Python environment (see requirements.txt for dependencies).
• Store images in the Images directory, ensuring they are in either "jpg" or "png" format.

Installation and Setup

Follow these steps to set up the project on your local machine:

1. Install virtualenv using the command: pip install virtualenv.
2. Navigate to the Attendance-with-Face-Recognition directory and create a virtual environment with the command: virtualenv assistance_venv.
3. Activate the virtual environment:
   • For Windows: .\assistance_venv\Scripts\activate
   • For Unix or MacOS: source assistance_venv/bin/activate
4. Navigate to the Attendance-with-Face-Recognition/ directory and install the required Python packages with: pip install -r requirements.txt

To run It

1. Make sure the Virtual Environment is activated
2. Go to inside the 'Attendance' folder and run py .\detect_face_and_register_in_db.py
3. Export the database records of the day running py .\transfer_today_records_to_pdf.py
4. Export all the database records running py .\transfer_all_records_to_pdf.py

Visual Guide

For your convenience, here are some visual aids to help you with the expected outcomes:

• Example of Attendance Taking & Records

  

This project was developed for the Artificial Intelligence circle at the University of Lima and aims to provide a straightforward, efficient method for attendance tracking through the innovative use of facial recognition technology.