**A Face Recognition System, designed for real-time surveillance and locating missing persons or items **
- Real-time face recognition using ML Model.
- Surveillance and monitoring for missing persons or items during mass gatherings.
- Easy-to-use web interface built with React and Tailwind CSS.
- Robust backend API using Flask and Python.
π¬ Check out a live demo here or watch a preview below:
- React βοΈ for building the user interface
- Tailwind CSS π¨ for responsive and attractive styling
- Axios for API calls to the backend
- Flask π for building the API
- face_recognition library for facial detection and recognition
- OpenCV for handling image and video processing
- Python as the main backend language
- Docker π³ for containerization of Backend
face-recognition-system/
β
βββ frontend/
β βββ public/
β βββ src/
β β βββ components/
β β βββ pages/
β β βββ App.tsx
β β βββ Home.tsx
β β βββ Main.tsx
β β βββ navbar.tsx
β β βββ NotFound.tsx
β β βββ ReportForm.tsx
β β βββ SearchMissing.tsx
β β βββ Survillance.tsx
β βββ tailwind.config.js
β βββ package.json
β
βββ backend/
βββ app.py
βββ models/
βββ static/Images
βββ requirements.tx
-
Clone the repository:
git clone git@github.com:kartik-212004/hackathon-iiit.git cd hackathon-iiit
-
Backend Setup:
- Navigate to the backend folder and set up a virtual environment:
cd backend python3 -m venv venv source venv/bin/activate # On Linux/macOS .\venv\Scripts\activate # On Windows
- Install dependencies:
pip install -r requirements.txt
- Navigate to the backend folder and set up a virtual environment:
-
Frontend Setup:
- Navigate to the frontend folder and install dependencies:
cd frontend npm install npm run dev
- Navigate to the frontend folder and install dependencies:
-
Run the Application:
- Start the Flask backend server:
cd backend python app.py
- Start the React frontend development server:
cd frontend npm start
- Start the Flask backend server:
You can also run the entire system using Docker for seamless deployment:
-
Build and run the Docker containers:
cd backend docker build -t flask-backend . docker run -p 5000:5000 flask-backend
-
Visit
http://localhost:3000
for the frontend andhttp://172.17.0.2:5000/
for the backend.
- Face Registration: Known personsβ images are uploaded and stored in the system for future recognition.
- Real-time Face Detection: The system captures video feeds or images to detect faces.
- Real-time video stream integration for live surveillance.
- Alert System: Notify authorities when a person is identified.
Contributions are always welcome! Feel free to:
- Fork the repo.
- Create a feature branch.
- Submit a pull request with a detailed description of the changes.
- THE OGs - GitHub Profile
This project is licensed under the MIT License.
β If you like this project, donβt forget to star the repository!
- Special thanks to the open-source community for amazing resources.
- Inspiration from real-world applications of AI in surveillance systems .