how to send email when condition be comes true using python

I'm doing a face mask detection project. i have already trained the dataset and created the model. then i deployed that model to detect the masked face. actually its working as expected. now i want to send an email when the system detects a person without mask and show a warning message. here is the code :

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 smtplib  import tkinter  from tkinter import messagebox    def detect_and_predict_mask(frame, faceNet, maskNet):            (h, w) = frame.shape[:2]      blob = cv2.dnn.blobFromImage(frame, 1.0, (224, 224),          (104.0, 177.0, 123.0))        faceNet.setInput(blob)      detections = faceNet.forward()      print(detections.shape)              faces = []      locs = []      preds = []              for i in range(0, detections.shape[2]):                    confidence = detections[0, 0, i, 2]            if confidence > 0.5:                            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))                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)                faces.append(face)              locs.append((startX, startY, endX, endY))              if len(faces) > 0:                    faces = np.array(faces, dtype="float32")          preds = maskNet.predict(faces, batch_size=32)              return (locs, preds)      prototxtPath = r"face_detector\deploy.prototxt"  weightsPath = r"face_detector\res10_300x300_ssd_iter_140000.caffemodel"  faceNet = cv2.dnn.readNet(prototxtPath, weightsPath)      maskNet = load_model("mask_detector.model")      print("[INFO] starting video stream...")  vs = VideoStream(src=0).start()      while True:            frame = vs.read()      frame = imutils.resize(frame, width=400)        (locs, preds) = detect_and_predict_mask(frame, faceNet, maskNet)        for (box, pred) in zip(locs, preds):                    (startX, startY, endX, endY) = box          (mask, withoutMask) = pred                    label = "Mask" if mask > withoutMask else "No Mask"          color = (0, 255, 0) if label == "Mask" else (0, 0, 255)            label = "{}: {:.2f}%".format(label, max(mask, withoutMask) * 100)                      cv2.putText(frame, label, (startX, startY - 10),              cv2.FONT_HERSHEY_SIMPLEX, 0.45, color, 2)          cv2.rectangle(frame, (startX, startY), (endX, endY), color, 2)                    if(label == "No Mask"):              messagebox.showwarning("warning access denied","please put your mask.")              with smtplib.SMTP('smtp.gmail.com',587)as smtp:                  smtp.ehlo()                  smtp.starttls()                  smtp.ehlo()                  smtp.login('helpdeskadhi@gmail.com','pnfnvboatmczopkn')                  subject = "Warning"                  body = "one visitor violated the rule."                  msg = f'Subject: {subject}\n\n{body}'                  smtp.sendmail('helpdeskadhi@gmail.com','helpdeskadhi@gmail.com',msg)          else:              pass              break                cv2.imshow("Frame", frame)      key = cv2.waitKey(1) & 0xFF              if key == ord("q"):          break  cv2.destroyAllWindows()  vs.stop()  

when i run this code it is still working as before. but its not sending any email and not showing any warning message.

i'm new to python . so please help to correct this.

https://stackoverflow.com/questions/65376965/how-to-send-email-when-condition-be-comes-true-using-python December 20, 2020 at 12:40PM