sleep_detection.py

import sys
import dlib
from skimage import io
import numpy as np
from scipy.spatial import distance 

# Developed by: Taha Emara
# Website     : http://www.emaraic.com
# Email       : taha@emaraic.com

# This code is built on Eye Aspect Ratio formula by Tereza Soukupova and Jan Cech
#  https://vision.fe.uni-lj.si/cvww2016/proceedings/papers/05.pdf  

def compute_EAR(vec):

	a = distance.euclidean(vec[1], vec[5])
	b = distance.euclidean(vec[2], vec[4])
	c = distance.euclidean(vec[0], vec[3])
	# compute EAR
	ear = (a + b) / (2.0 * c)

	return ear



if len(sys.argv) != 3:
    print(
        "execute this program by running: \n"
        "python sleep_detection.py  ./face_landmark_detection.py shape_predictor_68_face_landmarks.dat /path/to/image.jpg"
        "You can download a trained facial shape predictor from:\n "
        "http://dlib.net/files/shape_predictor_68_face_landmarks.dat.bz2")
    exit()

predictor_path = sys.argv[1]
image_path = sys.argv[2]
detector = dlib.get_frontal_face_detector()
predictor = dlib.shape_predictor(predictor_path)

win = dlib.image_window()
img = io.imread(image_path)
win.clear_overlay()
win.set_image(img)
dets = detector(img, 1)
vec = np.empty([68, 2], dtype = int)

status="Not Sleeping"

print("Number of faces detected: {}".format(len(dets)))
for k, d in enumerate(dets):
        print("Detection {}: Left: {} Top: {} Right: {} Bottom: {}".format(
            k, d.left(), d.top(), d.right(), d.bottom()))
        # Get the landmarks/parts for the face in box d.
        shape = predictor(img, d)

        print("Part 0: {}, Part 1: {} ...".format(shape.part(0),
                                                  shape.part(1)))
        # Draw the face landmarks on the screen.
        
        for b in range(68):
         vec[b][0] = shape.part(b).x
         vec[b][1] = shape.part(b).y

        right_ear=compute_EAR(vec[42:48])#compute eye aspect ratio for right eye
        left_ear=compute_EAR(vec[36:42])#compute eye aspect ratio for left eye

        if (right_ear+left_ear)/2 <0.2: #if the avarage eye aspect ratio of lef and right eye less than 0.2, the status is sleeping.
              status="sleeping"

        print(status)
        
        win.add_overlay(shape)

win.add_overlay(dets)
win.set_title(status)
dlib.hit_enter_to_continue()