As the name suggests this project recognizes faces from a webcam feed. This project is part of a much bigger project to implement a robust face recognition based hassle free entry and exit system.

Follow the instructions below to setup and run this project on your system.

This project needs the following packages to be installed to run.

1) scipy
2) Flask_SQLAlchemy
3) numpy
4) Flask
5) tensorflow
6) six
7) imutils
8) Pillow
9) imageio
10) scikit_learn

I strongly suggest to make a virtual environment and then run this project. I've provided the simplest instructions for getting the project up and running on a linux or windows machine.

1. Make sure you have git installed. Go to https://git-scm.com/ to install it.
2. Open the terminal.
3. Type in "git clone https://github.com/dotslash21/FaceAccessServer.git" to clone this repository.
4. Type in "pip install -r requirements.txt" to install the required packages.
5. Put your labelled images in img_db folder.
6. Run the align_face.py file using "python align_face.py" command.
7. Run the train_classifier.py using "python train_classifier.py" command.
8. Finally run the app.py with the required arguments. (e.g.- python app.py -i localhost -o 8080)

This project is licensed under the MIT License - see the LICENSE.md file for details

• David Sandberg for his FaceNet implementation.