code: def _image_transform(self, path):
      img = cv2.imread(path)
      img_height = img.shape[0]
      img_width = img.shape[1]
  
      img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
      img = Image.fromarray(img)
      img, _ = self.transforms(img, target=None)
      img = img.to(DEVICE)
      return img, {"width": img_width, "height": img_height}
  
imports: import argparse
  import os
  import cv2
  import numpy
  import torch
  from maskrcnn_benchmark.config import cfg
  from maskrcnn_benchmark.data.transforms import build_transforms
  from maskrcnn_benchmark.structures.image_list import to_image_list
  from maskrcnn_benchmark.utils.checkpoint import DetectronCheckpointer
  from mmf.utils.download import download
  from PIL import Image
  from scene_graph_benchmark.AttrRCNN import AttrRCNN
  from scene_graph_benchmark.config import sg_cfg
  from tools.scripts.features.extraction_utils import chunks, get_image_files
label_desc: Use image node_id 5 for calling the FeatureExtractor obj's underlying member method code with example usage: obj._image_transform(path) and returns: img,  dict