Attendance System Using Face Recognition

Overview

This is a Face Recognition-based Attendance System built using Streamlit and face_recognition library. The system allows users to register, log in, and view attendance records.

Key Features:

• Face recognition-based login and attendance marking.
• User registration via file upload or camera.
• Attendance records stored in text files.
• Simple and interactive Streamlit UI.

🛠️ Installation

Prerequisites:

Ensure you have Python installed (>=3.7) and git installed.

Clone the Repository:

git clone https://github.com/codderrrrr/Attendance_system.git
cd Attendance_system

Install Required Dependencies:

pip install -r requirements.txt

🚀 How to Run

Start the Streamlit application:

streamlit run app.py

Features

1️⃣ Home Page

• Register as a new user
• Log in using face recognition
• View attendance records

2️⃣ User Registration

• Enter personal details (name, roll number, degree, section)
• Choose registration method:
  • Upload an image file
  • Capture a photo using the webcam

3️⃣ Log In (Face Recognition)

• Capture an image using a webcam
• Face is matched with the stored dataset
• If recognized, attendance is marked
• If unrecognized, the user is prompted to register

4️⃣ View Attendance Records

• Users can enter their name to check past attendance records

Deployment on Streamlit Cloud

To deploy on Streamlit Cloud:

1. Push your repository to GitHub.
2. Go to Streamlit Cloud.
3. Select your GitHub repo and deploy.
4. Ensure required dependencies are in requirements.txt.

Project Structure

Attendance_system/
│── dataset/
│   ├── known/  # Stores registered user images
│   ├── unknown/  # Stores temp images for face matching
│── attendance/  # Stores attendance records as text files
│── app.py  # Main Streamlit application
│── requirements.txt  # Required Python libraries
│── README.md  # Project documentation

License

This project is licensed under the MIT License.

Acknowledgments

• This project uses the face_recognition library by Adam Geitgey, licensed under the MIT License.