class_docstr: 对图像标准化处理,该方法应放在ToTensor后
class_docstr_tok: ["\u5bf9\u56fe\u50cf\u6807\u51c6\u5316\u5904\u7406",",","\u8be5\u65b9\u6cd5\u5e94\u653e\u5728ToTensor\u540e"]
code: def __init__(self, mean=None, std=None):
      if mean is None:
          mean = [0.485, 0.456, 0.406]
      if std is None:
          std = [0.229, 0.224, 0.225]
      self.normalize = t.Normalize(mean=mean, std=std)
  
imports: import random
  import torch
  import torchvision.transforms
  from torchvision.transforms import functional
  from src import dboxes300_coco, calc_iou_tensor, Encoder
label_desc: Use image node_id 1 to create a new Normalization object from inherited base classes: object with example: obj = Normalization(mean, std)