code: def predict(img):
      if not os.path.exists("trained_models/nn_trained_model_hog.sav"):
          print("Please wait while training the NN-HOG model....")
          train("NN", "hog", "nn_trained_model_hog")
  
      model = pickle.load(
          open("trained_models/nn_trained_model_hog.sav", "rb")
      )
      features = extract_features(img, "hog")
      labels = model.predict([features])
  
      return labels
  
imports: import cv2
  import numpy
  from box import Box
  from train import *
  import os
  import pickle
label_desc: Use image node_id 1 for calling a global function with example usage: predict(img) and returns: labels