face-recognition

Overview

This repository contains the code for a self-driving bus authentication system that uses facial recognition to authenticate users for check-in and check-out. The system comprises both a frontend and a backend, with the backend utilizing the Python library dlib and face_recognition for face recognition and FastAPI for the API. The frontend uses Flask to serve webcam images to the backend for recognition.

Features

• Facial recognition for user authentication.
• User check-in and check-out functionality.
• Integration with a database for user management and tracking.
• Real-time webcam image serving and recognition.

Prerequisites

Before running the application, make sure you have the following prerequisites installed:

• Python 3.10 or higher
• pip package manager
• Required Python packages (see the requirements.txt file)
• A webcam for image capture

Installation

1. Clone this repository to your local machine:

   git clone https://github.com/nihaalnz/face-recognition

2. Navigate to the project directory:

   cd face-recognition

3. Create a virtual environment (recommended)

   python -m venv venv

4. Activate the virtual environment:

   • On Windows:

     venv\Scripts\activate

   • On macOS or Linux:

     source venv/bin/activate

5. Install the required packages:

   5.1 Install the required python packages (Requires C++ Build Tools and CMake):

   pip install -r requirements.txt

   5.2 Install the required node packages (need to have node and npm installed):

   5.2.1 Navigate to frontend package (new terminal):

   cd face-recognition/frontend

   5.2.2 Install the npm packages:

   npm install

   5.2.3 Build the css using tailwind:

   npm run build

Configuration

1. Configure the database connection details in .env.

2. Ensure that the necessary models for dlib and face_recognition are downloaded and placed in the appropriate directories. You can follow the instructions provided by these libraries for their installation.

Usage

1. Make an .env file by filling the contents in sample.env

2. Start the backend FastAPI server:

   python backend

   The backend server will start at http://localhost:8000.

3. Start the frontend Flask server (in a separate terminal):

   python frontend

4. Access the application in your web browser at http://localhost:5000.

Contributing

Contributions to this project are welcome! If you find a bug or have an enhancement in mind, please open an issue or create a pull request.

License

This project is licensed under the MIT License. See the LICENSE file for details.

Acknowledgments

• Thanks to the developers of dlib, face_recognition, FastAPI, and Flask for their excellent libraries and frameworks.