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main.py
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main.py
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from scipy.spatial import distance as dist #for calculating euclidean distances
from imutils.video import VideoStream #for image processing in OpenCV
from imutils import face_utils #facedetection
from threading import Thread
import numpy as np #numpy array
import playsound #raising alarm
import argparse #optional argument parsing
import imutils
import time
import dlib #python machine learning library
import cv2 #openCV
def sound_alarm(path):
playsound.playsound(path)
ap = argparse.ArgumentParser()
ap.add_argument("-p", "--shape-predictor",default="")
ap.add_argument("-a", "--alarm", type=str, default="")
ap.add_argument("-w", "--webcam", type=int, default=0)
args = vars(ap.parse_args())
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
ear_thresh = 0.25
frame_thresh = 48
counter = 0
ear = 0
detector = dlib.get_frontal_face_detector()
args["shape_predictor"] ="shape_predictor_68_face_landmarks.dat"
args["alarm"] ="alarm.wav"
predictor = dlib.shape_predictor(args["shape_predictor"])
(lStart, lEnd) = face_utils.FACIAL_LANDMARKS_IDXS["left_eye"]
(rStart, rEnd) = face_utils.FACIAL_LANDMARKS_IDXS["right_eye"]
vs = VideoStream(src=args["webcam"]).start()
time.sleep(1.0)
while True:
frame = vs.read()
frame = imutils.resize(frame, width = 450)
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
faces = detector(gray, 0)
if len(faces) == 0:
print("No faces found!")
cv2.putText(frame, "No faces found!", (200, 300), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)
for face in faces:
shape = predictor(gray, face)
shape = face_utils.shape_to_np(shape)
leftEye = shape[lStart:lEnd]
rightEye = shape[rStart:rEnd]
leftEAR = eye_aspect_ratio(leftEye)
rightEAR = eye_aspect_ratio(rightEye)
ear = (leftEAR + rightEAR) / 2.0
print(ear)
print(counter)
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)
break
if ear < ear_thresh:
counter += 1
if counter > frame_thresh:
if args["alarm"] != "":
t = Thread(target=sound_alarm, args=(args["alarm"],))
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
cv2.putText(frame, "EAR: {:.2f}".format(ear), (300, 30), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)
cv2.imshow("Frame", frame)
key = cv2.waitKey(1) & 0xFF