Facial Attendance System

The Facial Attendance System is a web-based application built using Streamlit. It uses facial recognition to mark attendance and maintain records.

Features

• Register Faces: Add new users to the system by uploading their face images.
• Mark Attendance: Use a webcam to recognize registered users and mark their attendance.
• View Attendance Logs: Display attendance records stored in an SQLite database.

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Table of Contents

1. Technologies Used
2. Getting Started
3. Usage
4. Screenshots

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Technologies Used

1. Python
   • Libraries:
     • Streamlit: For the web application interface.
     • OpenCV: For webcam handling and image processing.
     • Face Recognition: For facial encoding and comparison.
     • SQLite: Lightweight database for storing user encodings and attendance logs.

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Getting Started

1. Prerequisites

• Install Python 3 and pip.

2. Clone the Repository

git clone https://github.com/rujeetjahagirdar/facial_attendance_system.git
cd facial_attendance_system

3. Install Dependencies

• Use pip to install the required Python libraries:

pip install -r requirements.txt

4. Run the App

• Launch the Streamlit app:

streamlit run main.py

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Usage

1. Register Face

• Navigate to the Register Face section.
• Upload a face image and provide the user’s name.
• Click Register User to save the face encoding to the database.

2. Mark Attendance

• Navigate to the Mark Attendance section.
• Click Mark Attendance to start the webcam.
• The system will detect faces and mark attendance for recognized users.

3. View Attendance

• Navigate to the View Attendance section.
• View a table of logged attendance records.

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Screenshots

Register Face

The Register Face feature allows users to upload a face image and register their name.

Mark Attendance

Mark attendance by recognizing faces using the webcam.

View Attendance Logs

See a table of attendance records.