code: def extract_image_feat(img_file):
      img = Image.open(img_file).convert("RGB")
      img_transform = data_transforms(img)
      # make sure grey scale image is processed correctly
      if img_transform.shape[0] == 1:
          img_transform = img_transform.expand(3, -1, -1)
      img_var = Variable(img_transform.unsqueeze(0))
      if use_cuda:
          img_var = img_var.cuda()
  
      img_feat = _resnet_module(img_var)
      return img_feat
  
file_path: mmf/tools/scripts/features/extract_resnet152_feat.py
imports: import argparse
  import os
  from glob import glob
  import numpy
  import torch
  import torch.nn
  import torchvision.models
  import torchvision.transforms
  from mmf.common.constants import IMAGE_COLOR_MEAN, IMAGE_COLOR_STD
  from PIL import Image
  from torch.autograd import Variable
label_desc: Use image node_id 1 for calling a global function with example usage: extract_image_feat(img_file) and returns: img_feat