code: def read_csv_classes(csv_dir: str, csv_name: str):
      data = pd.read_csv(os.path.join(csv_dir, csv_name))
      # print(data.head(1))  # filename, label
  
      label_set = set(data["label"].drop_duplicates().values)
  
      print(
          "{} have {} images and {} classes.".format(
              csv_name, data.shape[0], len(label_set)
          )
      )
      return data, label_set
  
file_path: deep-learning-for-image-processing/pytorch_classification/mini_imagenet/restructure_csv.py
imports: import os
  import json
  import pandas
  from PIL import Image
  import matplotlib.pyplot
label_desc: Use image node_id 1 for calling a global function with example usage: read_csv_classes(csv_dir, csv_name) and returns: data,  label_set