code: def infer(model, img):
      img = np.array(Image.fromarray(img).resize((608, 608)))
      img = img[:, :, ::-1].transpose((2, 0, 1))
      img = img[np.newaxis, :, :, :] / 255.0
      prediction = model.forward(Tensor(img.astype(np.float32)))
      return prediction
  
imports: import sys
  import io
  import time
  import math
  import cv2
  import numpy
  from PIL import Image
  from tinygrad.tensor import Tensor
  from tinygrad.nn import BatchNorm2d, Conv2d
  from tinygrad.helpers import fetch
label_desc: Use image node_id 5 for calling a global function with example usage: infer(model, img) and returns: prediction