class_docstr: 自定义数据集
code: def __getitem__(self, item):
      img = Image.open(self.images_path[item])
      # RGB为彩色图片，L为灰度图片
      if img.mode != "RGB":
          raise ValueError(
              "image: {} isn't RGB mode.".format(self.images_path[item])
          )
      label = self.images_class[item]
  
      if self.transform is not None:
          img = self.transform(img)
  
      return img, label
  
file_path: deep-learning-for-image-processing/pytorch_classification/Test7_shufflenet/my_dataset.py
imports: from PIL import Image
  import torch
  from torch.utils.data import Dataset
label_desc: Use image node_id 3 for calling the MyDataSet obj's underlying member method code with example usage: obj.__getitem__(item) and returns: img,  label