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facelockdoor.py
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facelockdoor.py
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import cv2
import numpy as np
from os import listdir
from os.path import isfile,join
import serial
import time
import pyttsx3
import smtplib
q=1
x=0
c=0
m=0
d=0
while q<=2:
data_path = 'C:/Users/Arjun/Desktop/Python/image/'
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('C:/Users/Arjun/Music/FACELOCKING-DOOR-USING-PYTHON-AND-ARDUINO-PROGRAMING-master/requirements/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('com4' ,9600)
time.sleep(2)
var = 'a'
c=var.encode()
speak("Face recognition complete..it is matching with database...welcome..sir..Door is openning for 5 seconds")
ard.write(c)
time.sleep(4)
elif c==30:
speak("face is not matching..please try again")
# creates SMTP session
s = smtplib.SMTP('smtp.gmail.com', 587)
# start TLS for security
s.starttls()
# Authentication
s.login("[email protected]", "muuldeubdwdonoxr")
# message to be sent
message = "Some Strange Person Found In Front Of Door "
# sending the mail
s.sendmail("[email protected]", "[email protected]", message)
# terminating the session
s.quit()
elif d==20:
speak("face is not found please try again ")
if m==1:
speak("door is closing")