Sam-Varghese / Face_Recognition_Attendance

🤖Face Recognition Attendance System made with state of the art machine learning techniques, with MySQL connectivity 🗃️

FRAS

Face Recognition Attendance System

FRAS is a facial recognition attendance system that aims at simplifying the process of attendance management with the help of state-of-art AI technologies like Tensorflow, Convolutional Neural Networks, etc.

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Requirements

• Python
• MySQL
• Laptop with a camera

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Features

• Automatically captures images of people for facial recognition.
• Integrated with MySQL database which enables this program to update records in real time.
• This program leverages Convolution Neural Networks, Tensorflow, Data Augmentation for the most accurate predictions.
• Model is saved after it's trained everytime which enables the user to re-run the saved model instead of training it again and again on images of all users.
• All the tables in MySQL are well connected and efforts are being taken constantly to reduce redundancies to max extent.
• Entity Relation diagram is also maintained.

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Installation

1. Fork the repository.
2. Clone the forked repository.
3. Move into the directory where you cloned to repository.
4. Create a new file namely connection_info.json.
5. Put the following details into this file

{
    "mysql_password": "your_mysql_password",
    "mysql_host": "localhost",
    "mysql_user": "root",
    "master_database": "FRAS"
}

6. Install the required packages by executing the following command pip install -r requirements.txt
7. Now execute face_recognition_attendance.py file.

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Description

1. This program consists of 2 entities: namely users and roles.
2. Roles are the tags assigned to a particular user.
3. Ex: If a user "A" belongs to grade 6th, then create a role "6th grade" which you can assign to the user.
4. Before program learns to recognize the face of a user, it needs to generate a dataset of all users.
5. So after you enter records of a new user, Start FRAS -> Record new face.
6. After this, just select the name of user, and program will start recording images of the user.
7. Now you need to train the model. Option 5 is Train model which needs to be selected.
8. After the model is trained, FRAS-> Start FRAS

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Future Plans

• Support incremental learning so that recorded images may be deleted, and storage space may get saved.
• Make a website for this project.
• Make the model focus more on faces of people than their physical background, which sometimes cause model to behave incorrectly.

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Technologies Used

• Python
• Tensorflow
• MySQL
• Rich
• OpenCV

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Concepts Used

• Neural Networks (Learned this during my ML Specialization from Stanford Online, and Tensorflow Developer specialization from DeepLearning.AI)
• Database Management System (Learned in my 3rd semester, at NMIMS University)

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Additional Information

• Project is licensed under MIT License
• This project is made by Sam Varghese to apply the concepts learned in my 3rd Semester, and AI courses that I completed from Coursera.

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