AI Face Recognition Entry System

This project is a complete AI-powered face recognition system with a GUI for tracking attendance. It uses the OpenCV and face_recognition libraries to detect and recognize faces, and stores the data in a SQLite database. The system has a user-friendly interface for adding new faces, tracking attendance, and managing subscriptions. The system also includes a live view feature that allows users to view the camera feed in real-time.

The project consists of the following components:

• A GUI built with tkinter for adding new faces, tracking attendance, and managing subscriptions
• A live view feature that displays the camera feed in real-time
• A database built with SQLite for storing face encodings and attendance data
• A face recognition system built with OpenCV and face_recognition for detecting and recognizing faces
• A function for validating Iranian National IDs
• A simple subscription system that tracks entries and exits, with the entry time being the first detection of the day and the exit time being the last detection of the day
• A feature to save an excel file per day in the Export folder, with the filename being the day date in jalali format, such as 1403-10-16.xlsx

The system is designed to be user-friendly and easy to use, with clear instructions and minimal setup required.

The face recognition system uses the face_recognition library, which is a simple and easy-to-use library based on the dlib library. It uses a convolutional neural network to detect and recognize faces, and is highly accurate and robust. The system supports face recognition on both still images and video streams.

The face_recognition library is available on the official website: https://github.com/ageitgey/face_recognition

System Requirements

• Python version: 3.10.0

Ensure that you have Python 3.10.0 installed on your system. You can verify your Python version by running the following command:

python --version

If you do not have Python 3.10.0 installed, you can download it from the official Python website.

Virtual Environment (venv)

A virtual environment is a self-contained directory that contains a Python interpreter and libraries. It is recommended to use a virtual environment to isolate your project's dependencies from the system Python environment.

To create a virtual environment, run the following command in your terminal:

python -m venv venv

Once the virtual environment is created, you can activate it by running the following command:

source venv/bin/activate

Install requirements from requirements.txt

You can install all the requirements specified in the requirements.txt file using the following command:

pip install -r requirements.txt

This will install all the required packages and their dependencies.

Run the Project

To run the project, execute the following command in your terminal:

python main.py

This will start the project and open the GUI for adding new faces, tracking attendance, and managing subscriptions.

License

This project is licensed under the MIT License.

Author

This project was created by Saeid Kasiri.

Contact

If you have any questions or feedback, please contact Saeid Kasiri on GitHub.