📚 Attendance System Using Face Recognition
🎯 Overview
This project implements a face recognition attendance system using Python, OpenCV, and the Twilio API. It captures real-time video feed, recognizes registered individuals, marks their attendance, and sends a confirmation message via SMS.
🛠️ Key Features
Real-time Face Recognition: Detects faces in a live video stream using face_recognition and OpenCV.
Attendance Tracking: Records attendance by writing recognized names, timestamps, and dates into a CSV file.
SMS Notifications: Sends an SMS to registered attendees notifying them of their marked attendance using Twilio.
📦 Requirements
To run this project, you'll need the following Python packages:
face_recognition
opencv-python
numpy
csv
pyttsx3
streamlit
twilio
You can install the required packages using pip:
pip install face_recognition opencv-python numpy pyttsx3 streamlit twilio
⚙️ Setup Instructions
Clone the Repository:
git clone https://github.com/yourusername/attendance-system.git
Navigate to the Project Directory:
cd attendance-system
Update Twilio Credentials:
Replace the placeholder account_sid and auth_token with your Twilio account credentials.
Update the attendee_phone_numbers dictionary with the names and phone numbers of your attendees.
Add Sample Images:
Include sample images of the attendees in the project directory, naming them as follows:
Sample_image1.jpeg
Sample_image2.jpg
Sample_image3.jpg
Sample_image4.jpg
Run the Application:
python attendance_system.py
📸 How to Use
When prompted, allow the application to access your camera.
The program will start capturing video frames and recognizing faces.
When a registered attendee is recognized, their attendance will be marked, and they will receive an SMS notification.
To stop the video stream, click the "Stop Streamlit" button.
📄 Output
Attendance records will be saved in a CSV file named with the current date (e.g., 09-Oct-2024.csv).
🤝 Contributions
Feel free to fork the repository, make changes, and submit pull requests!
📄 License
This project is open-source and available under the MIT License.