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drowsiness_yawn.py
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#This is a simple program i stitched together to detect if a person is drowsy or not
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 argparse
import imutils
import time
import dlib
import cv2
import os
def alarm(msg):
global alarm_status
global alarm_status2
global saying
while alarm_status:
print('call')
s = 'espeak "'+msg+'"'
os.system(s)
if alarm_status2:
print('call')
saying = True
s = 'espeak "' + msg + '"'
os.system(s)
saying = False
def eye_aspect_ratio(eye):
A = dist.euclidean(eye[1], eye[5])
B = dist.euclidean(eye[2], eye[4])
C = dist.euclidean(eye[0], eye[3])
ear = (A + B) / (2.0 * C)
return ear
def final_ear(shape):
(lStart, lEnd) = face_utils.FACIAL_LANDMARKS_IDXS["left_eye"]
(rStart, rEnd) = face_utils.FACIAL_LANDMARKS_IDXS["right_eye"]
leftEye = shape[lStart:lEnd]
rightEye = shape[rStart:rEnd]
leftEAR = eye_aspect_ratio(leftEye)
rightEAR = eye_aspect_ratio(rightEye)
ear = (leftEAR + rightEAR) / 2.0
return (ear, leftEye, rightEye)
def lip_distance(shape):
top_lip = shape[50:53]
top_lip = np.concatenate((top_lip, shape[61:64]))
low_lip = shape[56:59]
low_lip = np.concatenate((low_lip, shape[65:68]))
top_mean = np.mean(top_lip, axis=0)
low_mean = np.mean(low_lip, axis=0)
distance = abs(top_mean[1] - low_mean[1])
return distance
ap = argparse.ArgumentParser()
ap.add_argument("-s", "--source", type=int, default=0,
help="index of webcam on system")
args = vars(ap.parse_args())
EYE_AR_THRESH = 0.28
EYE_AR_CONSEC_FRAMES = 20
YAWN_THRESH = 20
alarm_status = False
alarm_status2 = False
saying = False
COUNTER = 0
print("Loading the predictor and detector...")
detector = cv2.CascadeClassifier("haarcascade_frontalface.xml")
predictor = dlib.shape_predictor('shape_predictor_face_landmarks.dat')
print("Starting Video Stream...")
vs = VideoStream(src=args["source"]).start()
time.sleep(1.0)
while True:
frame = vs.read()
frame = imutils.resize(frame, width=600)
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
rects = detector.detectMultiScale(gray, scaleFactor=1.1,
minNeighbors=5, minSize=(30, 30),
flags=cv2.CASCADE_SCALE_IMAGE)
for (x, y, w, h) in rects:
rect = dlib.rectangle(int(x), int(y), int(x + w),int(y + h))
shape = predictor(gray, rect)
shape = face_utils.shape_to_np(shape)
eye = final_ear(shape)
ear = eye[0]
leftEye = eye [1]
rightEye = eye[2]
distance = lip_distance(shape)
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)
lip = shape[48:60]
cv2.drawContours(frame, [lip], -1, (0, 255, 0), 1)
if ear < EYE_AR_THRESH:
COUNTER += 1
if COUNTER >= EYE_AR_CONSEC_FRAMES:
if alarm_status == False:
alarm_status = True
t = Thread(target=alarm, args=('WAKE UP !',))
t.deamon = True
t.start()
cv2.putText(frame, "DROWSINESS ALERT!", (10, 30),
cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)
else:
COUNTER = 0
alarm_status = False
if (distance > YAWN_THRESH):
cv2.putText(frame, "YAWN ALERT", (10, 30),
cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)
if alarm_status2 == False and saying == False:
alarm_status2 = True
t = Thread(target=alarm, args=('ALERT !',))
t.deamon = True
t.start()
else:
alarm_status2 = False
cv2.putText(frame, "EAR: {:.2f}".format(ear), (430, 30),
cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)
cv2.putText(frame, "YAWN: {:.2f}".format(distance), (430, 60),
cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)
cv2.imshow("Drowsiness Detector - PRNXV", frame)
key = cv2.waitKey(1) & 0xFF
if key == ord("x"):
break
cv2.destroyAllWindows()
vs.stop()