text: import glob
  
  from archive.preprocessing import *
  from generate_matched_filter_kernel import *
  from archive import matched_filtering as mf
  
  path = '../data/hw01_preds/preds.json'
  kernel_path = '../data/kernels'
  image_base_path = '../data/RedLights2011_Medium'
  
  
  image_paths = sorted(glob.glob(image_base_path + '/*'))
  
  image_path = image_paths[0]
  img = load_image(image_path)
  img_arr = image_to_array(img)
  # search_for_kernel(img, kernel_path)
  kernel = mf.load_kernel(0, kernel_path)
  # skernel = kernel_smoothing(kernel)
  convolved_image = mf.dot_product_filter(img_arr, kernel)
  np.save('../data/convolved_images/ci04', convolved_image)
  viz.visualize_convolved_image(convolved_image)
  # for i in range(3):
  #     fk = np.flip(kernel[:, :, i]).transpose()
  #     k2 = kernel[:, :, i]
  #
  #     b = fk * k2
  #     a = (fk/np.sum(fk) + k2/np.sum(k2))
  #     plt.figure()
  #
  #     plt.subplot(3, 2, 1)
  #     plt.imshow(fk)
  #
  #     plt.subplot(3, 2, 2)
  #     plt.imshow(k2)
  #
  #     plt.subplot(3, 2, 3)
  #     plt.imshow(a)
  #
  #     plt.subplot(3, 2, 4)
  #     plt.imshow(b)
  #
  #     plt.subplot(3, 2, 5)
  #     plt.imshow(fk/np.sum(fk))
  #
  # plt.show()
  
  print()