face_recognition

Some results First!

Checkout the demo

Getting Started

1. Get the code:

   • Using SSH: git clone git@github.com:vijuSR/face_recognition.git
     OR
   • Using HTTP: git clone https://github.com/vijuSR/face_recognition.git

2. Setup the Virtual Environment (Recommended):

   • Create the virtual environment
     • python3 -m venv </path/to/venv>
   • Activate your virtual-environment
     • Linux: source </path/to/venv>/bin/activate
     • Windows: cd </path/to/venv> then .\Scripts\activate
   • Install the requirements
     • cd <root-dir-of-project>
     • pip install -I -r requirements.txt

     Install any missing requirement with pip install <package-name>

3. Setups

• STEP 0: Configurations

  1. There are two supported databases: sqlite and postgres
  2. Current setting is to use sqlite. For using postgres change SQLALCHEMY_SQLITE in this line to SQLALCHEMY_POSTGRES
  3. Also, if you are using postgres, change the config.ini file accordingly.
  4. In 'config.ini' file and change the path to "haarcascade_frontalface_default.xml" file path on your system. For example on my system it's: > "G:/VENVIRONMENT/computer_vision/Lib/site-packages/cv2/data/haarcascade_frontalface_default.xml" where > "G:/VENVIRONMENT/computer_vision" is my virtual environment path.

• STEP 1: Database setup

  1. Postgres:
     • Install postgres, create a database and change 'config.ini' file accordingly.
  2. Creating required tables: -cd </to/repo/root/dir>
     • in shell/notebook run

     from database_client.database import Operations
Operations.create_tables()

You did it. That's all required for the setup. 👏 😃

Using the celebrity face recognition:

You can use this project in two ways:

1. With flask app:
   1. cd </to/repo/root/dir>
   2. run python3 routes.py
   3. Available endpoints:
      • "/": home page, used to upload image for celebs recognition.
      • "/face_recognition": result of celeb recognition, can't be accessed directly.
      • "/new_celeb": presents a form for adding new celeb in the database.
      • "/add_celeb": adds the celebrity to the database.

      Disabled the public access to the '\new_celeb' endpoint at demo website: poor-mans-rekognition.herokuapp.com

2. Directly the core model package- Checkout the notebook "demo-sqlite.ipynb" (without flask app):
   1. cd </to/repo/root/dir>
   2. run jupyter notebook
   3. click on "demo-sqlite.ipynb"

Improvements:

• Transfer learning on celeb dataset with "Siamese network"
• Accuracy analysis with grayscale facial image captures.
• Better face detection

Todos:

• Change the result to json
• Extend to multiple faces in an image frame.
• Video processing (recognize celebs in video scenes).
• Top n matching celebs.
• Automate deployment.