I am building this script to detect my face through a webcam and have the model detect if Im wearing a face mask or not. If the detected face is not wearing a mask, an email is sent to an admin to alert them. Everything works correctly except for the email part. It keeps giving an SMTPAuthenticationError saying my username and password are incorrect yet they are correct. What could I be doing wrong and how do I fix this? I have authorised Google through settings to authorize less secure apps. I have also disabled 2step verification but I'm still getting this error.
This is part of the code generating the error.
if (label == "No Mask"):
# Throw a Warning Message to tell user to wear a mask if not wearing one. This will stay
#open and No Access will be given He/She wears the mask
messagebox.showwarning("Warning","Access Denied. Please wear a Face Mask")
# Send an email alert to the administrator if access denied/user not wearing face mask
message = 'Subject: {}\n\n{}'.format(SUBJECT, TEXT)
mail = smtplib.SMTP('smtp.gmail.com', 587)
mail.ehlo()
mail.starttls()
mail.login('kwerondaa@gmail.com','#####')
mail.sendmail('kwerondaa@gmail.com','kwerondaa@gmail.com',message)
mail.close
else:
pass
This is the error: SMTPAuthenticationError: (535, b'5.7.8 Username and Password not accepted. Learn more at\n5.7.8 https://support.google.com/mail/?p=BadCredentials v25sm14100155wmh.4 - gsmtp')
This is the entire script file:
from tensorflow.keras.applications.mobilenet_v2 import preprocess_input
from tensorflow.keras.preprocessing.image import img_to_array
from tensorflow.keras.models import load_model
from imutils.video import VideoStream
import numpy as np
import imutils
import time
import cv2
import os
import tkinter
from tkinter import messagebox
import smtplib
# Initialize Tkinter
root = tkinter.Tk()
root.withdraw()
SUBJECT = "Subject"
TEXT = "One Visitor violated Face Mask Policy. See in the camera to recognize user. A Person has been detected without a face mask in the Hotel Lobby Area 9. Please Alert the authorities."
def find_face_and_mask(frame, detectFace, detectMask):
#get face dimensions and construct blob
(h, w) = frame.shape[:2]
blob = cv2.dnn.blobFromImage(frame, 1.0, (224, 224),
(104.0, 177.0, 123.0))
#obtaining the face
detectFace.setInput(blob)
detections = detectFace.forward()
print(detections.shape)
faces = [] # faces
locs = [] #locations
preds = [] #predictions
for i in range(0, detections.shape[2]):
confidence = detections[0, 0, i, 2]
if confidence > 0.5: #setting min confidence
box = detections[0, 0, i, 3:7] * np.array([w, h, w, h])
(startX, startY, endX, endY) = box.astype("int")
(startX, startY) = (max(0, startX), max(0, startY))
(endX, endY) = (min(w - 1, endX), min(h - 1, endY))
# extracting the face ROI and preprocessing
face = frame[startY:endY, startX:endX]
face = cv2.cvtColor(face, cv2.COLOR_BGR2RGB)
face = cv2.resize(face, (224, 224))
face = img_to_array(face)
face = preprocess_input(face)
#append faces and locations
faces.append(face)
locs.append((startX, startY, endX, endY))
# only make a predictions if at least one face was detected
if len(faces) > 0:
# making batch predictions on *all* faces at the same time rather than one-by-one predictions
faces = np.array(faces, dtype="float32")
preds = detectMask.predict(faces, batch_size=100)
return (locs, preds) #2-tuple of the face locations and their corresponding locations
# the serialized face detector model from disk
prototxtPath = r"face_detector\deploy.prototxt"
weightsPath = r"face_detector\res10_300x300_ssd_iter_140000.caffemodel"
detectFace = cv2.dnn.readNet(prototxtPath, weightsPath)
# face mask detector model from disk
detectMask = load_model("mask_det_final_model.h5")
vid_stream = VideoStream(src=0).start()
# loop over the frames from the video stream
while True:
frame = vid_stream.read()
frame = imutils.resize(frame, width=600)
# detect faces in the frame and determine if the detected face is wearing a face mask or not
(locs, preds) = find_face_and_mask(frame, detectFace, detectMask)
for (box, pred) in zip(locs, preds):
# unpack the bounding box and predictions
(startX, startY, endX, endY) = box
(mask, withoutMask) = pred
label = "Mask" if mask > withoutMask else "No Mask" #labels of the box
color = (0, 255, 0) if label == "Mask" else (0, 0, 255)
if (label == "No Mask"):
# Throw a Warning Message to tell user to wear a mask if not wearing one. This will stay
#open and No Access will be given He/She wears the mask
messagebox.showwarning("Warning","Access Denied. Please wear a Face Mask")
# Send an email alert to the administrator if access denied/user not wearing face mask
message = 'Subject: {}\n\n{}'.format(SUBJECT, TEXT)
mail = smtplib.SMTP('smtp.gmail.com', 587)
mail.ehlo()
mail.starttls()
mail.login('kwerondaa@gmail.com','######')
mail.sendmail('kwerondaa@gmail.com','kwerondaa@gmail.com',message)
mail.close
else:
pass
# include the probability in the label
label = "{}: {:.2f}%".format(label, max(mask, withoutMask) * 100)
# display the label and bounding box rectangle on the output frame
cv2.putText(frame, label, (startX, startY - 10),
cv2.FONT_HERSHEY_SIMPLEX, 0.45, color, 2)
cv2.rectangle(frame, (startX, startY), (endX, endY), color, 2)
cv2.imshow("Face mask detector Live webcam", frame)
key = cv2.waitKey(1) & 0xFF
if key == ord("q"):
break
cv2.destroyAllWindows()
vid_stream.stop()
