code: def __init__(
      self,
      image_size,
      mean=IMAGENET_DEFAULT_MEAN,
      std=IMAGENET_DEFAULT_STD,
  ):
      self.mean = mean
      self.std = std
  
      self.transform = transforms_coco_eval(
          image_size,
          interpolation="bilinear",
          use_prefetcher=True,
          fill_color="mean",
          mean=self.mean,
          std=self.std,
      )
  
      self.mean_tensor = torch.tensor([x * 255 for x in mean]).view(
          1, 3, 1, 1
      )
      self.std_tensor = torch.tensor([x * 255 for x in std]).view(
          1, 3, 1, 1
      )
  
file_path: layout-parser/src/layoutparser/models/effdet/layoutmodel.py
imports: from typing import List, Optional, Union, Dict, Any, Tuple
  from PIL import Image
  import numpy
  from .catalog import PathManager, LABEL_MAP_CATALOG, MODEL_CATALOG
  from ..base_layoutmodel import BaseLayoutModel
  from ...elements import Rectangle, TextBlock, Layout
  from ...file_utils import is_effdet_available, is_torch_cuda_available
label_desc: Use image node_id 1 to create a new InputTransform object  with example: obj = InputTransform(image_size, mean, std)