docs: def _count_classified_pixels(self):
          """
          Count the pixels belonging to each classified class.
          """
          class_values = self.class_dictionary.values()
  
          classification_count = np.array([[[np.count_nonzero(prediction[np.nonzero(mask)] == class_val)
                                             for prediction, mask in zip(self.classification_masks, masktype)]
                                            for masktype in self.truth_masks]
                                           for class_val in class_values])
  
          classification_count = np.moveaxis(classification_count, 0, -1)
          classification_count = np.moveaxis(classification_count, 0, -2)
  
          if self.pixel_classification_counts is None:
              self.pixel_classification_counts = np.copy(classification_count)
          else:
              self.pixel_classification_counts = np.concatenate((self.pixel_classification_counts, classification_count))