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https://github.com/shadowaniket/attendance_using_face_recognition

Python-OpenCV-Django Face Recognition Attendance System Project For Marking Attendance Automatically On Facial Recognition Generally Used In College And Offices.
https://github.com/shadowaniket/attendance_using_face_recognition

attendance-system automatic college-project computer-vision django face-recognition hacktoberfest hacktoberfest2024 machine-learning opencv proxy-feature python sqlite

Last synced: 18 days ago
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Python-OpenCV-Django Face Recognition Attendance System Project For Marking Attendance Automatically On Facial Recognition Generally Used In College And Offices.

Host: GitHub
URL: https://github.com/shadowaniket/attendance_using_face_recognition
Owner: ShadowAniket
License: mit
Created: 2024-09-28T17:56:16.000Z (about 2 months ago)
Default Branch: main
Last Pushed: 2024-10-24T05:50:53.000Z (24 days ago)
Last Synced: 2024-10-24T15:30:45.343Z (24 days ago)
Topics: attendance-system, automatic, college-project, computer-vision, django, face-recognition, hacktoberfest, hacktoberfest2024, machine-learning, opencv, proxy-feature, python, sqlite
Language: HTML
Homepage:
Size: 368 MB
Stars: 1
Watchers: 2
Forks: 1
Open Issues: 0
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE

Awesome Lists containing this project

README

# Attendance Management System Using Face Recognition

**Attendance Using Face Recognition** is a Python-based project that automates attendance tracking in educational institutions and corporate offices using facial recognition technology. This system offers a fast, secure, and efficient way to manage attendance records for both students and staff members.

## Table of Contents
- [Features](#features)
- [Technologies Used](#technologies-used)
- [Installation](#installation)
- [Usage](#usage)
- [Contributing](#contributing)
- [License](#license)

## Features
- **Face Recognition**: Automatically recognize and record attendance based on facial images.
- **Real-time Attendance**: Mark attendance as students or faculty members check in and out.
- **Proxy Prevention**: Prevents proxies of user by various algorithms.
- **Admin Panel**: Manage users, attendance records, and generate attendance reports.
- **Secure and Efficient**: Reduces manual errors and ensures that attendance is recorded accurately.
- **Responsive Web Interface**: Manage and view attendance data via a Django-based web interface.

## Technologies Used

![Python](https://img.shields.io/badge/Python-3.8-blue?style=for-the-badge&logo=python)
![OpenCV](https://img.shields.io/badge/OpenCV-4.x-green?style=for-the-badge&logo=opencv)
![dlib](https://img.shields.io/badge/dlib-Face%20Recognition-orange?style=for-the-badge)
![Django](https://img.shields.io/badge/Django-3.x-green?style=for-the-badge&logo=django)
![SQLite](https://img.shields.io/badge/SQLite-3-lightgrey?style=for-the-badge&logo=sqlite)

## Installation

1. **Clone the repository:**
```bash
git clone https://github.com/ShadowAniket/Attendance_using_Face_Recognition.git
cd Attendance_using_Face_Recognition
```

2. **Set up the virtual environment:**
```bash
python3 -m venv env # On Windows: py -3.8 -m venv .venv
source env/bin/activate # On Windows: .\.venv\Scripts\activate
```

3. **Install the required dependencies:**
```bash
pip install -r requirements.txt
```

4. **Set up the database:**
```bash
python manage.py migrate
```

5. **Run the server:**
```bash
python manage.py runserver
```
Open your browser and go to `http://127.0.0.1:8000/` to access the system.

## Usage

1. **Admin Panel Access**:
- Username- admin, Password- Shadow use this to log in as an admin and manage users and attendance records.

2. **Attendance Capture**:
- Use the web interface to capture faces through a connected camera.
- The system will automatically recognize the face and record attendance for the recognized individual.

3. **Generating Reports**:
- Use the admin panel to generate and download attendance reports filtered by date, user, or department.

## Updates
The plugins folder has been removed, and the JavaScript files have been made available online to streamline the project and reduce unnecessary files. This will not affect offline functionality of face recognition and attendance marking. Only html files may require online connectivity to load javascript files.

## Contributing

We welcome contributions! Please check out the [Contributing Guidelines](CONTRIBUTING.md) for more details on how to get started.

### Steps to Contribute:
1. Fork the repository.
2. Create a new feature branch (`git checkout -b feature-name`).
3. Commit your changes (`git commit -m 'Add some feature'`).
4. Push to the branch (`git push origin feature-name`).
5. Open a Pull Request.

For more detailed guidelines, see the [CONTRIBUTING.md](CONTRIBUTING.md) file.

## License

This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.

If you find this project useful, please give it a ⭐ and fork it to contribute!
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