main.py

import numpy as np
import cv2
from simple_facerec import SimpleFacerec


face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
eye_cascade = cv2.CascadeClassifier('haarcascade_eye_tree_eyeglasses.xml')

sfr = SimpleFacerec()
sfr.load_encoding_images("images/")
 

first_read = True
 

cap = cv2.VideoCapture(0)
ret,img = cap.read()
 
while(ret):
    ret,img = cap.read()
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    gray = cv2.bilateralFilter(gray,5,1,1)
 
    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 = 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))
 
            if(len(eyes)>=2):
                if(first_read):
                    first_read = False
                else:
                    cv2.putText(img,
                    "Eyes open!", (70,70),
                    cv2.FONT_HERSHEY_PLAIN, 2,
                    (255,255,255),2)
            else:
                if(first_read):
                    cv2.putText(img,
                    "No eyes detected", (70,70),
                    cv2.FONT_HERSHEY_PLAIN, 3,
                    (0,0,255),2)
                else:
                    print("Blink detected--------------")
                    face_locations, face_names = sfr.detect_known_faces(img)
                    for face_loc, name in zip(face_locations, face_names):
                        y1, x2, y2, x1 = face_loc[0], face_loc[1], face_loc[2], face_loc[3]
                        print('name',name)
                        cv2.putText(img, name,(x1, y1 - 10), cv2.FONT_HERSHEY_DUPLEX, 1, (0, 0, 200), 2)
                        cv2.rectangle(img, (x1, y1), (x2, y2), (0, 0, 200), 4)

                    # cv2.imshow('img',frame)
                    cv2.waitKey(3000)
                    first_read=True
             
    else:
        cv2.putText(img,
        "No face detected",(100,100),
        cv2.FONT_HERSHEY_PLAIN, 3,
        (0,255,0),2)
 
    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()