预测后的人脸重组尝试面对预测值的索引，然后使索引3超出尺寸2的轴0的范围

如何解决预测后的人脸重组尝试面对预测值的索引，然后使索引3超出尺寸2的轴0的范围

在以下代码中，我得到了错误

索引3超出了尺寸2的轴0的范围

对于语句pred[0][3]。我在做什么错了？

# Face Recognition   
# Importing the libraries from PIL   
import Image from keras.applications.vgg16   
import preprocess_ input import base64 from
io  import BytesIO  import json import random  import cv2 from
keras.models  import load_model  import numpy as np

from keras.preprocessing import image model =
load_model('facefeatures_new_model_final.h5')

# Loading the cascades face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')

def face_extractor(img):
    # Function detects faces and returns the cropped face
    # If no face detected,it returns the input image
    
    #gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
    faces = face_cascade.detectMultiScale(img,1.3,5)
    
    if faces is ():
        return None
    
    # Crop all faces found
    for (x,y,w,h) in faces:
        cv2.rectangle(img,(x,y),(x+w,y+h),(0,255,255),2)
        cropped_face = img[y:y+h,x:x+w]

    return cropped_face

# Doing some Face Recognition with the webcam video_capture = cv2.VideoCapture(0) while True:
    _,frame = video_capture.read()
    #canvas = detect(gray,frame)
    #image,face =face_detector(frame)
    
    face=face_extractor(frame)
    if type(face) is np.ndarray:
        face = cv2.resize(face,(224,224))
        im = Image.fromarray(face,'RGB')
           #Resizing into 128x128 because we trained the model with this image size.
        img_array = np.array(im)
                    #Our keras model used a 4D tensor,(images x height x width x channel)
                    #So changing dimension 128x128x3 into 1x128x128x3 
        img_array = np.expand_dims(img_array,axis=0)
        pred = model.predict(img_array)
        print(pred)
                     
        name="None matching"
        
        if(pred[0][3]>0.5):
            name='Krish'
        cv2.putText(frame,name,(50,50),cv2.FONT_HERSHEY_COMPLEX,1,0),2)
    else:
        cv2.putText(frame,"No face found",2)
    cv2.imshow('Video',frame)
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break video_capture.release() cv2.destroyAllWindows()