def METHOD_NAME(img_path, heatmap, cam_path="cam.jpg", alpha=0.4):
    # Load the original image
    img = keras.utils.load_img(img_path)
    img = keras.utils.img_to_array(img)
    # Rescale heatmap to a range 0-255
    heatmap = np.uint8(255 * heatmap)
    # Use jet colormap to colorize heatmap
    jet = cm.get_cmap("jet")
    # Use RGB values of the colormap
    jet_colors = jet(np.arange(256))[:, :3]
    jet_heatmap = jet_colors[heatmap]
    # Create an image with RGB colorized heatmap
    jet_heatmap = keras.utils.array_to_img(jet_heatmap)
    jet_heatmap = jet_heatmap.resize((img.shape[1], img.shape[0]))
    jet_heatmap = keras.utils.img_to_array(jet_heatmap)
    # Superimpose the heatmap on original image
    superimposed_img = jet_heatmap * alpha + img
    superimposed_img = keras.utils.array_to_img(superimposed_img)
    # Save the superimposed image
    superimposed_img.save(cam_path)
    # Display Grad CAM
    display(Image(cam_path))