code: def __call__(self, image):
      if self.to_bgr255:
          image = image[[2, 1, 0]] * 255
      else:
          image = image[[0, 1, 2]] * 255
      image = Ft.normalize(image, mean=self.mean, std=self.std)
      return image
  
imports: from extra.models.mask_rcnn import MaskRCNN
  from extra.models.resnet import ResNet
  from extra.models.mask_rcnn import BoxList
  from torch.nn import functional
  from torchvision import transforms
  from torchvision.transforms import functional
  import random
  from tinygrad.tensor import Tensor
  from PIL import Image
  import numpy
  import torch
  import argparse
  import cv2
label_desc: Use image node_id 2 for calling the Normalize obj's underlying member method code with example usage: obj.__call__(image) and returns: image