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https://github.com/ray8118/flask_face_recognition--multiple_cameras
https://github.com/ray8118/flask_face_recognition--multiple_cameras
Last synced: about 1 month ago
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- Host: GitHub
- URL: https://github.com/ray8118/flask_face_recognition--multiple_cameras
- Owner: RaY8118
- Created: 2024-04-16T04:52:17.000Z (8 months ago)
- Default Branch: master
- Last Pushed: 2024-04-26T17:20:50.000Z (8 months ago)
- Last Synced: 2024-05-01T12:09:18.014Z (8 months ago)
- Language: Python
- Size: 47.9 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Face Recognition Attendance System Multiple Cameras
This project is a web application built with Flask that utilizes face recognition technology for managing attendance. It allows multiple cameras to stream video over HTTP, enabling real-time attendance tracking. The application supports three user roles: Students, Teachers, and Admins, each with specific functionalities.
## 🚀 Features
- **Face Recognition**: Automatically recognizes students' faces for attendance logging using the `face_recognition` Python library. 📸
- **Multiple Camera Support**: Stream from multiple cameras over HTTP, allowing flexibility in attendance monitoring. 🎥
- **Role-Based Access**:
- **Students**: View their own attendance records. 📅
- **Teachers**: Access attendance data for their classes. 📊
- **Admins**: Add or remove face data and manage student records. ⚙️
- **MySQL Database**: Efficiently stores and manages user data and attendance records. 🗄️
## 🛠️ Technologies Used
- **Flask**: The web framework for building the application. ⚗️
- **face_recognition**: For facial recognition capabilities. 👤
- **OpenCV**: For video capturing and processing. 🖥️
- **MySQL**: For database management. 🐬
- **HTML/CSS/JavaScript**: For front-end development. 🌐
## 📌 Installation
1. Clone the repository:
```bash
git clone https://github.com/RaY8118/Flask_Face_Recognition--multiple_Cameras.git
```
2. Navigate to the project directory:
```bash
cd Flask_Face_Recognition--multiple_Cameras
```
3. Install the required packages:
```bash
pip install -r requirements.txt
```
4. Set up the MySQL database and configure the connection in the application.
5. Run the Flask application:
```bash
python app.py
```
6. Access the web application at `http://127.0.0.1:5000`.
## 🌟 Acknowledgments
- [face_recognition](https://github.com/ageitgey/face_recognition) for the facial recognition capabilities.
- [OpenCV](https://opencv.org/) for image and video processing support.