code: def load_model(model_class, folder):
      with open(os.path.join(folder, "params.pkl"), "rb") as f:
          params = pickle.load(f)
  
      model = model_class(*params)
  
      model.load_weights(os.path.join(folder, "weights/weights.h5"))
  
      return model
  
imports: import pickle
  import os
  from keras.datasets import mnist, cifar100, cifar10
  from keras.preprocessing.image import ImageDataGenerator, load_img, save_img, img_to_array
  import pandas
  import numpy
  from os import walk, getcwd
  import h5py
  import scipy
  from glob import glob
  from keras.applications import vgg19
  from keras import backend
  from keras.utils import to_categorical
  import pdb
label_desc: Use image node_id 1 for calling a global function with example usage: load_model(model_class, folder) and returns: model