                          font,
                          self.scaling * 0.8,
                          (0, 0, 0),
                          1,
                          lineType=cv2.LINE_AA)  # pylint: disable=no-member
          logger.debug("header_box.shape: %s", header_box.shape)
          return header_box
  
      @staticmethod
      def duplicate_headers(headers, columns):
 
</s> remove                         self.scaling * 0.8,
 </s> add                         self._scaling * 0.8, </s> remove             cv2.putText(header_box,  # pylint: disable=no-member
 </s> add             cv2.putText(header_box, </s> remove         text_sizes = [cv2.getTextSize(texts[idx],  # pylint: disable=no-member
                                      font,
                                      self.scaling * 0.8,
                                      1)[0]
 </s> add         text_sizes = [cv2.getTextSize(texts[idx], font, self._scaling * 0.8, 1)[0] </s> remove     def duplicate_headers(headers, columns):
        """ Duplicate headers for the number of columns displayed """
 </s> add     def _duplicate_headers(headers, columns):
        """ Duplicate headers for the number of columns displayed for each side.

        Parameters
        ----------
        headers: :class:`numpy.ndarray`
            The header to be duplicated
        columns: int
            The number of columns that the header needs to be duplicated for

        Returns
        -------
        :class:`numpy.ndarray`
            The original headers duplicated by the number of columns
        """ </s> remove         font = cv2.FONT_HERSHEY_SIMPLEX  # pylint: disable=no-member
 </s> add         font = cv2.FONT_HERSHEY_SIMPLEX
                        lineType=cv2.LINE_AA)
                          font,
                          self.scaling * 0.8,
                          (0, 0, 0),
                          1,
                        lineType=cv2.LINE_AA)
          logger.debug("header_box.shape: %s", header_box.shape)
          return header_box
  
      @staticmethod
      def duplicate_headers(headers, columns):
keep keep keep keep replace keep keep keep keep keep
 Smart Masks - Training Implementation (#914)

* Smart Masks - Training

- Reinstate smart mask training code
- Reinstate mask_type back to model.config
- change 'replicate_input_mask to 'learn_mask'
- Add learn mask option
- Add mask loading from alignments to plugins.train.trainer
- Add mask_blur and mask threshold options
- _base.py - Pass mask options through training_opts dict
- plugins.train.model - check for mask_type not None for learn_mask and penalized_mask_loss
- Limit alignments loading to just those faces that appear in the training folder
- Raise error if not all training images have an alignment, and alignment file is required
- lib.training_data - Mask generation code
- lib.faces_detect - cv2 dimension stripping bugfix
- Remove cv2 linting code

* Update mask helptext in cli.py

* Fix Warp to Landmarks
Remove SHA1 hashing from training data

* Update mask training config

* Capture missing masks at training init

* lib.image.read_image_batch - Return filenames with batch for ordering

* scripts.train - Documentation

* plugins.train.trainer - documentation

* Ensure backward compatibility.
Fix convert for new predicted masks

* Update removed masks to components for legacy models. 
plugins/train/trainer/_base.py