text: from tf_keras_vis.utils.scores import BinaryScore
  from matplotlib import cm
  from tf_keras_vis.gradcam_plus_plus import GradcamPlusPlus
  from tf_keras_vis.utils.model_modifiers import ReplaceToLinear
  from pretraineModel.model import get_model
  import tensorflow as tf
  import numpy as np
  import cv2
  import matplotlib.pypplot as plt
  
  
  # Step1 Get your model from the files provided
  model=get_model()
  
  #import Image 
  image=cv2.imread('path') ## Enter path to your image file
  image=cv2.cvtColor(image,cv2.COLOR_BGR2RGB) ##Converts color channels from BGR to RGB
  #Creating gradCamPlusPlus inferecne
  score = BinaryScore([0])
  replace2linear = ReplaceToLinear()
  gradcam = GradcamPlusPlus(model,model_modifier=replace2linear,clone=True)
  cam = gradcam(score,np.asarray([image]),penultimate_layer=-1)
  heatmap = np.uint8(cm.jet(cam[0])[..., :3] * 255)
  plt.set_title('GRADCAM INFERENCE', fontsize=16)
  plt.imshow(image)
  plt.imshow(heatmap, cmap='jet', alpha=0.5)
  plt.axis('off')
  plt.show()