In this example, the class index always outputs 1 even if the person in the camera changes. How can I make the index change according to the person?

I want the class index to change according to the person who appears on the camera. I trained pictures of 2 different people using the Teachable Machine platform, and I use it as 'keras_model.h5'. However, when I run the program the class index is always equals to 1, so it always outputs the same person's name.

OUTPUTS: When the first person comes to the camera, the program prints this

CLASSINDEX: [1]
PREDICTION: [[0.025007 0.97499305]]
1/1 [================================] - 0s 25ms/step

When the second person comes to the camera, the program prints this

CLASSINDEX: [1]
PREDICTION: [[2.5015764e-04 9.9974984e-01]]
1/1 [================================] - 0s 20ms/step

import tensorflow as tf
from tensorflow import keras
import numpy as np
import cv2
from keras.models import load_model
import numpy as np


facedetect = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')

cap=cv2.VideoCapture(0)
cap.set(3, 640)
cap.set(4, 480)
font=cv2.FONT_HERSHEY_COMPLEX


model = load_model('keras_model.h5')


def get_className(classNo):
    if classNo==0:
        return "numan"
    elif classNo==1:
        return "tony"

while True:
    sucess, imgOrignal=cap.read()
    faces = facedetect.detectMultiScale(imgOrignal,1.3,5)
    for x,y,w,h in faces:
        crop_img=imgOrignal[y:y+h,x:x+h]
        img=cv2.resize(crop_img, (224,224))
        img=img.reshape(1, 224, 224, 3)
        prediction=model.predict(img)
        classIndex = np.argmax(prediction,axis=1)
        probabilityValue=np.amax(prediction)
        print("CLASSINDEX:",classIndex)
        print("PREDICTION:",prediction)
        if classIndex==0:
            cv2.rectangle(imgOrignal,(x,y),(x+w,y+h),(0,255,0),2)
            cv2.rectangle(imgOrignal, (x,y-40),(x+w, y), (0,255,0),-2)
            cv2.putText(imgOrignal, str(get_className(classIndex)),(x,y-10), font, 0.75, 
(255,255,255),1, cv2.LINE_AA)
        elif classIndex==1:
            cv2.rectangle(imgOrignal,(x,y),(x+w,y+h),(0,255,0),2)
            cv2.rectangle(imgOrignal, (x,y-40),(x+w, y), (0,255,0),-2)
            cv2.putText(imgOrignal, str(get_className(classIndex)),(x,y-10), font, 0.75, 
(255,255,255),1, cv2.LINE_AA)

        cv2.putText(imgOrignal,str(round(probabilityValue*100, 2))+"%" ,(180, 75), font, 
0.75, (255,0,0),2, cv2.LINE_AA)
    cv2.imshow("Result",imgOrignal)
    k=cv2.waitKey(1)
    if k==ord('q'):
        break


cap.release()
cv2.destroyAllWindows()