code: def image_load(fn):
      img_folder = BASEDIR / "validation/data"
      img = Image.open(img_folder / fn).convert("RGB")
      import torchvision.transforms.functional as F
  
      ret = F.resize(img, size=(800, 800))
      ret = np.array(ret)
      return ret, img.size[::-1]
  
file_path: tinygrad/extra/datasets/openimages.py
imports: import os
  import math
  import json
  import numpy
  from PIL import Image
  import pathlib
  import boto3, botocore
  from tinygrad.helpers import fetch
  from tqdm import tqdm
  import pandas
  import concurrent.futures
label_desc: Use image node_id 7 for calling a global function with example usage: image_load(fn) and returns: ret,  img