Face Recognition Attendance System

The Face Recognition Attendance System project is designed to automate the process of taking attendance using facial recognition technology. By simply facing the camera, students can register their attendance, making it a convenient and efficient solution for classrooms or other group settings.

Contents

1. About
2. Files
3. Face Recognition Attendance System.ipynb
4. Take Picture.ipynb
5. Dependencies
6. Additional Resources
7. Author

About

This project leverages facial recognition to detect and recognize individuals, thus allowing for automated attendance tracking. The system is capable of detecting faces, matching them with pre-trained data, and registering attendance based on the recognized individuals.

Files

1. test_image: Directory containing test images for face recognition.
2. traning_image: Directory containing training images used for model training.
3. Face Recognition Attendance System.ipynb: Jupyter Notebook containing the code for the face recognition attendance system.
4. Face Recognition Attendance System.pdf: Documentation providing details about the project.
5. README.md: This file, providing an overview of the project.
6. Take Picture.ipynb: Jupyter Notebook for taking training images from the camera.
7. haarcascade_frontalface_default.xml: XML file containing the pre-trained Haar Cascade classifier for face detection.

Face Recognition Attendance System.ipynb

This Jupyter Notebook contains the code for the face recognition attendance system. It includes functions for loading image files, training the model, testing the model, and taking attendance using facial recognition.

The notebook is divided into the following sections:

1. Load Image Files: Function to load image files with categories as subfolder names.
2. Training: Code for training the model using the provided training images.
3. Testing: Code for testing the trained model with test images.
4. Prediction: Code for predicting the attendance of recognized individuals.
5. Take Picture: Code for taking training images from the camera.

Take Picture.ipynb

This Jupyter Notebook contains the code for taking training images from the camera. It prompts the user to input their name and ID, creates a folder for storing training images, and captures multiple images for training the face recognition model.

Dependencies

This project requires the following dependencies:

• Python 3.x
• NumPy
• Matplotlib
• OpenCV
• scikit-learn
• pandas
• datetime

You can install these dependencies using pip:

pip install numpy matplotlib opencv-python scikit-learn pandas

Additional Resources

• PDF

• Project Trailer
  
  

Author

Gulam Kibria Chowdhury
Software Developer || Competitive Programmer
Sylhet, Bangladesh
Gmail: gkchowdhury101@gmail.com