facelockdoor.py

import cv2
import numpy as np
from os import listdir
from os.path import isfile,join
import serial
import time
import pyttsx3
q=1
x=0
c=0
m=0
d=0
while q<=2:
    data_path = 'D:/FACE/'
    onlyfiles = [f for f in listdir(data_path) if isfile(join(data_path,f))]
    Training_data, Lebels = [],[]
    for i , files in enumerate(onlyfiles):
        image_path = data_path + onlyfiles[i]
        images = cv2.imread(image_path,cv2.IMREAD_GRAYSCALE)
        Training_data.append(np.asarray(images, dtype = np.uint8)) 
        Lebels.append(i)

    Lebels = np.asarray(Lebels, dtype = np.int32)
    model = cv2.face.LBPHFaceRecognizer_create()
    model.train(np.asarray(Training_data),np.asarray(Lebels))
    print("training complete")
    q+=1
face_classifier = cv2.CascadeClassifier('D:\\Downloads\\Face Recognition Door Lock/haarcascade_frontalface_default.xml')


def speak(audio):
    engine.say(audio)
    engine.runAndWait()
engine = pyttsx3.init('sapi5')
voices=engine.getProperty('voices')
engine.setProperty("voice",voices[0].id)
engine.setProperty("rate",140)
engine.setProperty("volume",1000)






def face_detector(img, size= 0.5):
    gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
    faces = face_classifier.detectMultiScale(gray,1.3,5)

    if faces is():
        return img,[]
    for(x,y,w,h) in faces:
        cv2.rectangle(img, (x,y),(x+w,y+h),(0,255,255),2)
        roi = img[y:y+h, x:x+w]
        roi = cv2.resize(roi,(200,200))
    
    return img,roi

cap = cv2.VideoCapture(0)
while True:
    ret, frame = cap.read()

    image, face = face_detector(frame)

    try:
        face = cv2.cvtColor(face,cv2.COLOR_BGR2GRAY)
        result= model.predict(face)
        if result[1]<500:
            
            confidence = int((1-(result[1])/300)*100)
            display_string = str(confidence)
            cv2.putText(image, display_string,(100,120),cv2.FONT_HERSHEY_SCRIPT_COMPLEX,1,(0,255,0))

        if confidence>=83:
            cv2.putText(image,"unlocked",(250,450),cv2.FONT_HERSHEY_SCRIPT_COMPLEX,1,(0,255,255))
            cv2.imshow('face',image)
            x+=1
        else:
            cv2.putText(image,"locked",(250,450),cv2.FONT_HERSHEY_SCRIPT_COMPLEX,1,(0,255,255))
            cv2.imshow('face',image)
            c+=1
    except:
        cv2.putText(image,"Face not found",(250,450),cv2.FONT_HERSHEY_SCRIPT_COMPLEX,1,(0,255,255))
        cv2.imshow('face',image)
        d+=1
        pass
    
    if cv2.waitKey(1)==13 or x==10 or c==30 or d==20:
        break
cap.release()
cv2.destroyAllWindows()
if x>=5:
    m=1
    ard = serial.Serial('com9' ,9600)
    time.sleep(2)
    var = 'a'
    c=var.encode()
    speak("Face recognition complete..")
    speak("Face is matching with database...")
    speak("Welcome home..boss..")
    speak("Door is openning for 5 seconds")
    ard.write(c)
    time.sleep(4)
elif c==30:
    speak("face is not matching..please try again")
elif d==20:
    speak("face is not found please try again ")
if m==1:  
    speak("door is closing")