aboutsummaryrefslogtreecommitdiff
path: root/pythonProgram/function-specific-programs/ear.py
blob: a40e0651ab3c33e15ffb2b6d38681caeef91f738 (plain)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
# Using Eye aspect ratio
from scipy.spatial import distance as dist
from imutils.video import VideoStream
from imutils import face_utils
from threading import Thread
import numpy as np
import playsound
import argparse
import imutils
import time
import dlib
import cv2

def sound_alarm():
	print('You Sleep You Lose')

def eye_aspect_ratio(eye):
	# Computes the euclidean distances between the two sets of eyes
	A = dist.euclidean(eye[1], eye[5])
	B = dist.euclidean(eye[2], eye[4])
 
	# compute the euclidean distance between the horizontal
	# eye landmark (x, y)-coordinates
	C = dist.euclidean(eye[0], eye[3])
 
	# compute the eye aspect ratio
	ear = (A + B) / (2.0 * C)
	# return the eye aspect ratio
	return ear

shape_predictor = "../files/shape_predictor_68_face_landmarks.dat"


EYE_AR_THRESH = 0.2 # If the EAR goes < this for 48 frames, it is counted as drowsiness
EYE_AR_CONSEC_FRAMES = 48
 
COUNTER = 0
ALERT = False

# initialize dlib's face detector (HOG-based) and then create
# the facial landmark predictor
print("Initialising Facial Landmark Predictor...")
detector = dlib.get_frontal_face_detector()
predictor = dlib.shape_predictor(shape_predictor)

(lStart, lEnd) = face_utils.FACIAL_LANDMARKS_IDXS["left_eye"]
(rStart, rEnd) = face_utils.FACIAL_LANDMARKS_IDXS["right_eye"]

print("Starting Video Stream...")
vs = VideoStream(src=0).start()
time.sleep(1.0)
 
while True:
	frame = vs.read()
	frame = imutils.resize(frame, width=450)
	gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
 
	rects = detector(gray, 0)
	for rect in rects:
		shape = predictor(gray, rect)
		shape = face_utils.shape_to_np(shape)
 
		# extract the left and right eye coordinates, then use the
		# coordinates to compute the eye aspect ratio for both eyes
		leftEye = shape[lStart:lEnd]
		rightEye = shape[rStart:rEnd]
		leftEAR = eye_aspect_ratio(leftEye)
		rightEAR = eye_aspect_ratio(rightEye)
 
		# average the eye aspect ratio together for both eyes
		ear = (leftEAR + rightEAR) / 2.0
		# compute the convex hull for the left and right eye, then
		# visualize each of the eyes
		leftEyeHull = cv2.convexHull(leftEye)
		rightEyeHull = cv2.convexHull(rightEye)
		cv2.drawContours(frame, [leftEyeHull], -1, (0, 255, 0), 1)
		cv2.drawContours(frame, [rightEyeHull], -1, (0, 255, 0), 1)
		# check to see if the eye aspect ratio is below the blink
		# threshold, and if so, increment the blink frame counter
		if ear < EYE_AR_THRESH:
			COUNTER += 1
 
			# if the eyes were closed for a sufficient number of
			# then sound the alarm
			if COUNTER >= EYE_AR_CONSEC_FRAMES:
				# if the alarm is not on, turn it on
				if not ALARM_ON:
					ALARM_ON = True
 
				# draw an alarm on the frame
				cv2.putText(frame, "Sleepiness Detected!", (10, 30),
					cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)
				print("Sleepiness Detected!")
				print("\a");print("\a");print("\a");print("\a");print("\a")
				print("\a");print("\a");print("\a");print("\a");print("\a")
				print("\a");print("\a");print("\a");print("\a");print("\a")


 
		else:
			COUNTER = 0
			ALARM_ON = False

		cv2.putText(frame, "Ratio: {:.2f}".format(ear), (300, 30),
			cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)
 
	# show the frame
	cv2.imshow("Frame", frame)
	key = cv2.waitKey(1) & 0xFF
 
	# if the `q` key was pressed, break from the loop
	if key == ord("q"):
		break
 
# do a bit of cleanup
cv2.destroyAllWindows()
vs.stop()