Skip to content

Latest commit

 

History

History
36 lines (29 loc) · 978 Bytes

README.md

File metadata and controls

36 lines (29 loc) · 978 Bytes
Raw

Face and Blink Detection

Overview

Goal

  1. In this demo we will find the facial landmarks, such as eyes, nose, mouth, ears, jaw-line using the popular dlib library
  2. We will see the basics of face detection using Haar Feature-based Cascade Classifiers
  3. We will extend the same for eye detection etc.
  4. We also detect the blink counts and upload the count data to the firebase console.

Dependencies

   opencv
   numpy
   webcam

You also need shape detector, you can download it by

wget http://dlib.net/files/shape_predictor_68_face_landmarks.dat.bz2

Usage

1) python facial_landmark_detection.py --shape-predictor shape_predictor_68_face_landmarks.dat --image images/nish.jpg
2) python eye-blink.py