Face landmark detection using dlib

dlib_face_landmarks.py

#!/usr/bin/env python

import sys
import dlib
import cv2
import numpy as np
from opencv_webcam_multithread import WebcamVideoStream

# dlib predictor can be found in 
# http://dlib.net/files/shape_predictor_68_face_landmarks.dat.bz2

if __name__ == "__main__" :
    detector = dlib.get_frontal_face_detector()
    assert detector is not None
    
    face_predictor_path = "shape_predictor_68_face_landmarks.dat"
    predictor = dlib.shape_predictor(face_predictor_path)

    INNER_EYES_AND_BOTTOM_LIP = [39, 42, 57]
    OUTER_EYES_AND_NOSE = [36, 45, 33]
    all_landmark_indices = np.array(INNER_EYES_AND_BOTTOM_LIP + OUTER_EYES_AND_NOSE)

    assert predictor is not None

    vs = WebcamVideoStream().start()

    assert vs is not None

    while True :
        frame = vs.read()

        # 0 in second argument so that we don't upsample face
        faces = detector(frame, 0) 
    
        # draw face rectangle
        for f in faces : 
            cv2.rectangle(frame, (f.left(), f.top()), (f.right(), f.bottom()), (255, 255, 0), 2)
    
            l = predictor(frame, f).parts()
            pp = list(map(lambda i : (l[i].x, l[i].y), all_landmark_indices))
            # draw landmarks           
            for p in pp : 
                cv2.circle(frame, p, 2, (0, 0, 255))
            
    
        cv2.imshow('webcam', frame)
        if cv2.waitKey(1) == 27 :
            break

    vs.stop()
    cv2.destroyAllWindows()