code: def __init__(
      self,
      base_size: Union[int, List[int]],
      mean=(0.485, 0.456, 0.406),
      std=(0.229, 0.224, 0.225),
  ):
      self.transforms = T.Compose(
          [
              T.ToTensor(),
              T.Resize(base_size, resize_mask=False),
              T.Normalize(mean=mean, std=std),
          ]
      )
  
file_path: deep-learning-for-image-processing/pytorch_segmentation/u2net/validation.py
imports: import os
  from typing import Union, List
  import torch
  from torch.utils import data
  from src import u2net_full
  from train_utils import evaluate
  from my_dataset import DUTSDataset
  import transforms
label_desc: Use image node_id 1 to create a new SODPresetEval object  with example: obj = SODPresetEval(base_size, mean, std)