detect_drowsiness.py

#python drowsiness_yawn.py --webcam 0 --alarm alarm.wav

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
import playsound
from twilio.rest import Client

import geocoder
g = geocoder.ip('me')
print(str(g.latlng))

account_sid = 'GET FROM YOUR TWILIO ACCOUNT'
auth_token = 'GET FROM YOUR TWILIO ACCOUNT'
client = Client(account_sid, auth_token)

def sound_alarm(path):
	# play an alarm sound
	playsound.playsound('alarm.wav', 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("-p", "--shape-predictor", required=True, help="path to facial landmark predictor")
ap.add_argument("-a", "--alarm", type=str, default="", help="path alarm .WAV file")
ap.add_argument("-w", "--webcam", type=int, default=0, help="index of webcam on system")
args = vars(ap.parse_args())
 
EYE_AR_THRESH = 0.3
EYE_AR_CONSEC_FRAMES = 30
YAWN_THRESH = 20
sms_eye = 1
sms_yawn = 1

# initialize the frame counter as well as a boolean used to
# indicate if the alarm is going off
COUNTER = 0
ALARM_ON = False

print("-> Loading the predictor and detector...")
#detector = dlib.get_frontal_face_detector()
detector = cv2.CascadeClassifier("haarcascade_frontalface_default.xml")    #Faster but less accurate
predictor = dlib.shape_predictor('shape_predictor_68_face_landmarks.dat')


print("-> Starting Video Stream")
vs = VideoStream(src=args["webcam"]).start()
#vs= VideoStream(usePiCamera=True).start()       //For Raspberry Pi
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)
    rects = detector.detectMultiScale(gray, scaleFactor=1.1, minNeighbors=5, minSize=(30, 30), flags=cv2.CASCADE_SCALE_IMAGE)

    #for rect in rects:
    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 not ALARM_ON:
                    ALARM_ON = True
                    if(sms_eye==1):
                        message = client.messages \
                                  .create(
                                      body = "Drowsy driver detected at location " + str(g.latlng),
				      from_='+183xxxxxxxx',
                                      to='+91xxxxxxxxxx'
                                      )
                        print(message.sid)
                        sms_eye = 0
                        print('SMS Sent')
                        
                    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
            sms_eye = 1
            ALARM_ON = False

        if (distance > YAWN_THRESH):
                cv2.putText(frame, "Yawn Alert", (10, 30),
                            cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)
                if not ALARM_ON:
                    ALARM_ON = True
                    if(sms_yawn==1):
                        message = client.messages \
                                  .create(
                                      body = "Drowsy driver detected at location " + str(g.latlng),
				      from_='+183xxxxxxxx',
                                      to='+91xxxxxxxxxx'
                                      )
                        print(message.sid)
                        sms_yawn = 0
                        print('SMS Sent')
                    if args["alarm"] != "":
                        t = Thread(target=sound_alarm, args=(args["alarm"],))
                        t.deamon = True
                        t.start()
        else:
            sms_yawn = 1
            ALARM_ON = False

        cv2.putText(frame, "EAR: {:.2f}".format(ear), (300, 30),
                    cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)
        cv2.putText(frame, "YAWN: {:.2f}".format(distance), (300, 60),
                    cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)


    cv2.imshow("Frame", frame)
    key = cv2.waitKey(1) & 0xFF

    if key == ord("q"):
        break

cv2.destroyAllWindows()
vs.stop()