singhsidhukuldeep / Facial-landmarks-recognition

Identifying faces in photos or videos is very cool, but this isn’t enough information to create powerful applications, we need more information about the person’s face, like position, whether the mouth is opened or closed, whether the eyes are opened, closed, looking up and etc.

Facial-landmarks-recognition

Identifying faces in photos or videos is very cool, but this isn’t enough information to create powerful applications, we need more information about the person’s face, like position, whether the mouth is opened or closed, whether the eyes are opened, closed, looking up and etc.

Here we are using Dlib, a library capable of giving you 68 points (land marks) of the face.

Results

Single face

Input	Landmarks detected	Jawline detected

Multiple faces

Input	Landmarks detected	Jawline detected

Setup

Important: To install the required libraries you will need CMake

• Linux Systems:

  sudo pip3 install virtualenv
  
  virtualenv -p python3 venv --no-site-packages
  
  source venv/bin/activate
  
  pip3 install -r requirements.txt

  deactivate

• Windows Systems:

  pip3 install virtualenv
  
  virtualenv -p python3 venv --no-site-packages
  
  venv\Scripts\activate
  
  pip3 install -r requirements.txt

  venv\Scripts\deactivate

  If getting issue in installing virtualenv on windows, use administrator privileges

Running

• Using from command line

  python3 faces.py ./face.jpg ./model/shape_predictor_68_face_landmarks.dat

  images will be saved in the same directory as the given image

• Importing as a module

  # importing
  from faces import detectFaces
  
  # running the function
  detectFaces (image_loaction = "face.jpg", model_location = "./model/shape_predictor_68_face_landmarks.dat")
  detectFaces (image_loaction = "multiple_faces.png", model_location = "./model/shape_predictor_68_face_landmarks.dat")
  
  # images will be saved in the same directory as the given image

  images will be saved in the same directory as the given image

CREDITS

Kuldeep Singh Sidhu

Github: github/singhsidhukuldeep https://github.com/singhsidhukuldeep

Website: Kuldeep Singh Sidhu (Website) http://kuldeepsinghsidhu.com

LinkedIn: Kuldeep Singh Sidhu (LinkedIn) https://www.linkedin.com/in/singhsidhukuldeep/