#All the imports go here
import numpy as np
import cv2

#Initializing the face and eye cascade classifiers from xml files
face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
eye_cascade = cv2.CascadeClassifier('haarcascade_eye_tree_eyeglasses.xml')

#Variable store execution state
first_read = True

#Starting the video capture
cap = cv2.VideoCapture(0)
ret,img = cap.read()

while(ret):
    ret,img = cap.read()
    #Converting the recorded image to grayscale
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    #Applying filter to remove impurities
    gray = cv2.bilateralFilter(gray,5,1,1)

    #Detecting the face for region of image to be fed to eye classifier
    faces = face_cascade.detectMultiScale(gray, 1.3, 5,minSize=(200,200))
    if(len(faces)>0):
        for (x,y,w,h) in faces:
            img = cv2.rectangle(img,(x,y),(x+w,y+h),(0,255,0),2)

            #roi_face is face which is input to eye classifier
            roi_face = gray[y:y+h,x:x+w]
            roi_face_clr = img[y:y+h,x:x+w]
            eyes = eye_cascade.detectMultiScale(roi_face,1.3,5,minSize=(50,50))

            #Examining the length of eyes object for eyes
            if(len(eyes)>=2):
                #Check if program is running for detection 
                if(first_read):
                    cv2.putText(img, 
                    "Eye detected press s to begin", 
                    (70,70),  
                    cv2.FONT_HERSHEY_PLAIN, 3,
                    (0,255,0),2)
                else:
                    cv2.putText(img, 
                    "Eyes open!", (70,70), 
                    cv2.FONT_HERSHEY_PLAIN, 2,
                    (255,255,255),2)
            else:
                if(first_read):
                    #To ensure if the eyes are present before starting
                    cv2.putText(img, 
                    "No eyes detected", (70,70),
                    cv2.FONT_HERSHEY_PLAIN, 3,
                    (0,0,255),2)
                else:
                    #This will print on console and restart the algorithm
                    print("Blink detected--------------")
                    cv2.waitKey(3000)
                    first_read=True
            
    else:
        cv2.putText(img,
        "No face detected",(100,100),
        cv2.FONT_HERSHEY_PLAIN, 3, 
        (0,255,0),2)

    #Controlling the algorithm with keys
    cv2.imshow('img',img)
    a = cv2.waitKey(1)
    if(a==ord('q')):
        break
    elif(a==ord('s') and first_read):
        #This will start the detection
        first_read = False

cap.release()
cv2.destroyAllWindows()