test_rev1.py

# Program for detecting drowsiness of the driver 

from scipy.spatial import distance
from imutils import face_utils
import imutils
import dlib
import cv2
import time
from image_detection import detect_faces
import requests
from places import recommend_places
import sys

def eye_aspect_ratio(eye):
	A = distance.euclidean(eye[1], eye[5])
	B = distance.euclidean(eye[2], eye[4])
	C = distance.euclidean(eye[0], eye[3])
	ear = (A + B) / (2.0 * C)
	return ear

thresh = 0.25
frame_check = 20
detect = dlib.get_frontal_face_detector()
predict = dlib.shape_predictor("/home/yogesh/ford/shape_predictor_68_face_landmarks.dat")# Dat file is the crux of the code

(lStart, lEnd) = face_utils.FACIAL_LANDMARKS_68_IDXS["left_eye"]
(rStart, rEnd) = face_utils.FACIAL_LANDMARKS_68_IDXS["right_eye"]
flag=0

try:
    while True:
        capture = cv2.VideoCapture(0)
        capture.set(3, 640)
        capture.set(4, 480)
        img_counter = 0
        frame_set = []
        start_time = time.time()
        count = 5

        while True:
            ret, frame = capture.read()
            frame = imutils.resize(frame, width=450)
            gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
            # cv2.imshow('frame', gray)
            subjects = detect(gray, 0)

            for subject in subjects:
                shape = predict(gray, subject)
                shape = face_utils.shape_to_np(shape)#converting to NumPy Array
                leftEye = shape[lStart:lEnd]
                rightEye = shape[rStart:rEnd]
                leftEAR = eye_aspect_ratio(leftEye)
                rightEAR = eye_aspect_ratio(rightEye)
                ear = (leftEAR + rightEAR) / 2.0
                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)
                
                if ear < thresh:
                    flag += 1
                    
                    # print (flag)
                    if flag >= frame_check:
                        cv2.putText(frame, "****************ALERT!****************", (10, 30),
                            cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)
                        cv2.putText(frame, "****************ALERT!****************", (10,325),
                            cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)
                        # print("a", flag)
                        if (count==5):                    
                            url = 'https://jsonbase.com/drowsy1/data'
                            headers = {'content-type':'application/json'}
                            data = "{\"drowsy\":\"1\"}"
                            r = requests.request("PUT",url,data = data,headers=headers)
                            recommend_places()
                            count+=1
                            
                else:
                    flag = 0
                    count=5
                    # print("flag:", flag)
                    url = 'https://jsonbase.com/drowsy1/data'
                    headers = {'content-type':'application/json'}
                    data = "{\"drowsy\":\"0\"}"
                    r = requests.request("PUT",url,data = data,headers=headers)
                    # print("b")

            cv2.imshow("Frame", frame)
            if cv2.waitKey(1) & 0xFF == ord('q'):
                break
            if time.time() - start_time >= 15: #<---- Check if 5 sec passed
                img_name = "opencv_frame.jpg" #.format(img_counter)
                cv2.imwrite(img_name, frame)
                detect_faces(img_name)
                # print("{} written!".format(img_counter))
                start_time = time.time()
            img_counter += 1

except KeyboardInterrupt:
    url = 'https://jsonbase.com/drowsy1/data'
    headers = {'content-type':'application/json'}
    data = "{\"drowsy\":\"0\"}"
    r = requests.request("PUT",url,data = data,headers=headers)
    sys.exit(0)