Why gui stop capturing video from camera(opencv with python)?

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I am new in field of programming, and the task of my project is to have gui using python and tkinter:

1. first key in menu should open the video when it pressed.
2. second key should recognize the faces when it pressed and keep recognizing until the program stop.

Issue: when I run the code and press first button, code works fine and start to capture the video. But when I press second key, program stops showing the video (also rectangle around the face does not appear) but the program still gives me output message that I expect when it recognize known faces without giving any error messages.

Why does it stop showing the video? Do I need to create class for such project or what?

Thank you in advance.

Here is my code:

import cv2
import numpy as np
import dlib
import face_recognition
import os
import time
import playsound
from gtts import gTTS
import speech_recognition as sr
import winsound
from time import sleep
from tkinter import *
from PIL import Image
from PIL import ImageTk

faces = []
encode = []
known_faces = []
names = []

white       = "#ffffff"
lightBlue2  = "#adc5ed"
font        = "Constantia"
fontButtons = (font, 12)
maxWidth    = 1000
maxHeight   = 600
mainWindow = Tk()
mainWindow.title('SUTech')
mainWindow.configure(bg=lightBlue2)
mainWindow.geometry('%dx%d+%d+%d' % (maxWidth,maxHeight,0,0))
mainFrame = Frame(mainWindow)
mainFrame.place(x=480,y=0)
lmain = Label(mainFrame)

cap = cv2.VideoCapture(0)    

def show_frame():    
    ret, frame = cap.read()    
    cv2image   = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)    
    img   = Image.fromarray(cv2image).resize((512, 512))    
    imgtk = ImageTk.PhotoImage(image=img)    
    lmain.grid(row=0, column=0)    
    lmain.grid(row=0, column=0)    
    lmain.imgtk = imgtk    
    lmain.configure(image=imgtk)    
    lmain.after(10, show_frame)

def facing():    
    x = 0    
    for filename in os.listdir('faces/'):    
        if filename.endswith('.jpg'):
           faces.append(face_recognition.load_image_file(os.path.join('faces/',filename)))
            encode.append(face_recognition.face_encodings(faces[x])[0])    
            known_faces.append(encode[x])    
            names.append(filename.replace('.jpg', ''))    
            x = x + 1    
    while(cap.isOpened()):    
        ret, frame = cap.read()    
        img = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)   
        location = face_recognition.face_locations(img, number_of_times_to_upsample=1, model=0)    
        encodings = face_recognition.face_encodings(img, location)    
        name = 'Unkown'    
        for encoding in encodings:    
            match = face_recognition.compare_faces(known_faces, encoding,tolerance=0.9)    
            distance = face_recognition.face_distance(known_faces, encoding)    
            bestMatch = np.argmin(distance)    
            if match[bestMatch]:   
                name = names[bestMatch]    
                print('Detected face:'+ str(name))    
                for (x, y, w, h) in (location):    
                    cv2.rectangle(frame,(h, x),(y, w), (0,255,0), 3)    
                    cv2.rectangle(frame,(h , w+30),(y, w), (0,255,0), -1)    
                    font = cv2.FONT_HERSHEY_DUPLEX

                    cv2.putText(frame, name, (h , w+25), cv2.FONT_HERSHEY_COMPLEX,1, (0,0,255), 2)       



#file menu    
menubar = Menu(mainWindow)    
file = Menu(menubar, tearoff = 0)    
menubar.add_cascade(label ='File', menu = file)    
file.add_command(label ='New File', command = show_frame)    
file.add_separator()    
file.add_command(label ='Face_detection', command = facing)    
file.add_separator()    
file.add_command(label ='Exit', command = lambda:mainWindow.destroy())    
mainWindow.config(menu = menubar)    
mainWindow.mainloop()