code: def get_image(
      self, rel_path: str, size: Tuple[int, int]
  ) -> torch.Tensor:
      import os
  
      from PIL import Image
      from torchvision.transforms import functional as F
  
      data_dir = os.path.join(os.path.dirname(__file__), "assets")
      path = os.path.join(data_dir, *rel_path.split("/"))
      image = (
          Image.open(path).convert("RGB").resize(size, Image.BILINEAR)
      )
  
      return F.convert_image_dtype(F.pil_to_tensor(image))
  
imports: import io
  from collections import OrderedDict
  from typing import List, Optional, Tuple
  import pytest
  import torch
  from common_utils import assert_equal, set_rng_seed
  from torchvision import models, ops
  from torchvision.models.detection.faster_rcnn import FastRCNNPredictor, TwoMLPHead
  from torchvision.models.detection.image_list import ImageList
  from torchvision.models.detection.roi_heads import RoIHeads
  from torchvision.models.detection.rpn import AnchorGenerator, RegionProposalNetwork, RPNHead
  from torchvision.models.detection.transform import GeneralizedRCNNTransform
  from torchvision.ops import _register_onnx_ops
label_desc: Use image node_id 20 for calling the TestONNXExporter obj's underlying member method code with example usage: obj.get_image(rel_path, size) and returns: F