Giúp tìm lỗi python numpy

[Duc_Huy_Vu (Đức Huy Vũ)]

xin chào mọi người , tui đang làm một project về nhận diện khuôn mặt và tui đang bị lỗi của numpy ( The truth value of an array with more than one element is ambiguous. Use a.any() or a.all() ) tui đã thử một số cách nhưng vẫn ko đc hi vọng đc mn giúp đỡ . Đây là đoạn mã code của tui

from tkinter import *
from tkinter import ttk
from PIL import Image, ImageTk
import cv2
import numpy as np
import os
from os.path import isfile, join
from threading import Thread
from user_handler import UserData
import face_unlocker as FU

background, textColor = 'black', '#F6FAFB'
background, textColor = textColor, background

avatarChoosen = 0
choosedAvtrImage = None
user_name = ''
user_gender = ''

try:
	face_classifier = cv2.CascadeClassifier('C:/VScode/AI---TroLyAo/master/Cascade/haarcascade_frontalface_default.xml')
except Exception as e:
	print('Cascade File is missing...')
	raise SystemExit

if os.path.exists('userData')==False:
	os.mkdir('userData')
if os.path.exists('userData/faceData')==False:
	os.mkdir('userData/faceData')


###### ROOT1 ########
def startLogin():		
	try:
		result = FU.startDetecting()
		if result:
			user = UserData()
			user.extractData()
			userName = user.getName().split()[0]
			welcLbl['text'] = 'Hi '+userName+',\nWelcome to the world of\nScience & Technology'
			loginStatus['text'] = 'UNLOCKED'
			loginStatus['fg'] = 'green'
			faceStatus['text']='(Logged In)'
			os.system('python modules/gui_assistant.py')
		else:
			print('Error Occurred')

	except Exception as e:
		print(e)

####### ROOT2 ########
def trainFace():
	data_path = 'userData/faceData/'
	onlyfiles = [f for f in os.listdir(data_path) if isfile(join(data_path, f))]

	Training_data = []
	Labels = []

	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))
		Labels.append(i)

	Labels = np.asarray(Labels, dtype=np.int32)

	model = cv2.face.LBPHFaceRecognizer_create()
	model.train(np.asarray(Training_data), np.asarray(Labels))
	
	print('Model Trained Successfully !!!')
	model.save('userData/trainer.yml')
	print('Model Saved !!!')

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

	if faces == ():
		return None

	for (x, y, w, h) in faces:
		cropped_face = img[y:y+h, x:x+w]

	return cropped_face

cap = None
count = 0
def startCapturing():	
	global count, cap
	ret , frame = cap.read()
	if face_extractor(frame) is not None:
		count += 1
		face = cv2.resize(face_extractor(frame), (200, 200))
		face = cv2.cvtColor(face, cv2.COLOR_BGR2GRAY)

		file_name_path = 'userData/faceData/img' + str(count) + '.png'
		cv2.imwrite(file_name_path, face)
		print(count)
		progress_bar['value'] = count

		cv2.putText(face, str(count), (50, 50), cv2.FONT_HERSHEY_COMPLEX, 1, (0,255,0), 2)
	else:
		pass
	
	if count==100:
		progress_bar.destroy()
		lmain['image'] = defaultImg2
		statusLbl['text'] = '(Face added successfully)'
		cap.release()
		cv2.destroyAllWindows()
		Thread(target=trainFace).start()
		addBtn['text'] = '        Next        '
		addBtn['command'] = lambda:raise_frame(root3)
		return
	
	frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGBA)
	frame = cv2.flip(frame, 1)
	img = Image.fromarray(frame)
	imgtk = ImageTk.PhotoImage(image=img)
	lmain.imgtk = imgtk
	lmain.configure(image=imgtk)
	lmain.after(10, startCapturing)

def Add_Face():

	global cap, user_name, user_gender
	user_name = nameField.get()
	user_gender = r.get()
	if user_name != '' and user_gender!=0:
		if agr.get()==1:
			cap = cv2.VideoCapture(0)
			startCapturing()
			progress_bar.place(x=20, y=273)
			statusLbl['text'] = ''
		else:
			statusLbl['text'] = '(Check the Condition)'
	else:
		statusLbl['text'] = '(Please fill the details)'


def SuccessfullyRegistered():
	if avatarChoosen != 0:
		gen = 'Male'
		if user_gender==2: gen = 'Female'
		u = UserData()
		u.updateData(user_name, gen, avatarChoosen)
		usernameLbl['text'] = user_name
		raise_frame(root4)

def selectAVATAR(avt=0):
	global avatarChoosen, choosedAvtrImage
	avatarChoosen = avt
	i=1
	for avtr in (avtb1,avtb2,avtb3,avtb4,avtb5,avtb6,avtb7,avtb8):
		if i==avt:
			avtr['state'] = 'disabled'
			userPIC['image'] = avtr['image']
		else: avtr['state'] = 'normal'
		i+=1