class_docstr: 注意，如果显示的图像不全，是matplotlib版本问题
  本例程使用matplotlib-3.2.1(windows and ubuntu)绘制正常
  需要额外安装prettytable库
class_docstr_tok: ["\u6ce8\u610f\uff0c\u5982\u679c\u663e\u793a\u7684\u56fe\u50cf\u4e0d\u5168\uff0c\u662fmatplotlib\u7248\u672c\u95ee\u9898","\u672c\u4f8b\u7a0b\u4f7f\u7528matplotlib-3.2.1","(","windows","and","ubuntu",")","\u7ed8\u5236\u6b63\u5e38","\u9700\u8981\u989d\u5916\u5b89\u88c5prettytable\u5e93"]
code: def update(self, preds, labels):
      for p, t in zip(preds, labels):
          self.matrix[p, t] += 1
  
file_path: deep-learning-for-image-processing/tensorflow_classification/ConfusionMatrix/main.py
imports: import os
  import math
  import json
  import glob
  from tensorflow.keras.preprocessing.image import ImageDataGenerator
  import matplotlib.pyplot
  import tensorflow
  import numpy
  from tqdm import tqdm
  from prettytable import PrettyTable
  from model import MobileNetV2
label_desc: Use image node_id 2 for calling the ConfusionMatrix obj's underlying member method code with example usage: obj.update(preds, labels) without return types