Flask-OpenCV-Face-Recognition

1. Setup MongoDB:

   • Install MongoDB on your system if not already installed.
   • Start the MongoDB service.
   • Create a new database named flask_db using the MongoDB shell or a GUI tool like MongoDB Compass.

2. Database Structure: The application uses the following collections in the flask_db database:

   • prs_mstr: Stores master personnel data.
   • img_dataset: Stores dataset image information.
   • accs_hist: Stores access history (personnel entering restricted areas).

3. Application Overview: This is a room access control application where individuals must undergo facial scanning before entering restricted areas. The system records personnel data in the database upon entry.

4. Create Project and Install Packages:

   • Create a new project in your preferred IDE (e.g., PyCharm, VSCode).
   • Name the project FlaskOpenCV_FaceRecognition.
   • Set up a virtual environment for the project.
   • Install the required packages using pip:

     pip install Flask pymongo opencv-python opencv-contrib-python Pillow
     

5. Project Setup:

   • Clone this repository or download the source code.
   • Extract the contents into your project's root folder.

6. Configuration:

   • Update the MongoDB connection string in app.py if your MongoDB setup differs from the default (localhost:27017).
   • Ensure that the paths to resources (like haarcascade files) are correct for your system.

7. Running the Application:

   • Run app.py to start the Flask server.
   • Access the application through your web browser at http://localhost:5000.

Note: Make sure to handle sensitive data securely and follow best practices for production deployments.