              new_size = int(full_size * self._scaling)
              images = [self._resize_sample(side, image, new_size) for image in images]
          return images
  
      @classmethod
      def _frame_overlay(cls, images, target_size, color):
          """ Add a frame overlay to preview images indicating the region of interest.
  
          This is the red border that appears in the preview images.
  
          Parameters
 
</s> remove         This is the red border that appears in the preview images.
 </s> add         This applies the red border that appears in the preview images. </s> remove             new_size = int(full_size * self._scaling)
 </s> add             new_size = int(images[0].shape[1] * self._scaling) </s> remove         images = [self._resize_sample(side, image, target_size) for image in images]
        if target_size != full_size:
            images = [self._overlay_foreground(frame, image) for image in images]
 </s> add         images = [self._overlay_foreground(full.copy(), image) for image in images]
 </s> remove         full_size = full.shape[1]
        target_size = int(full_size * self._coverage_ratio)
        if target_size != full_size:
            frame = self._frame_overlay(full, target_size, (0, 0, 255))

 </s> add  </s> remove         * Takes the first face from the image (if there) are multiple faces. Adds the images to \
            :attr:`self._input_images`.
 </s> add         * Takes the first face from the image (if there are multiple faces). Adds the images to \
        :attr:`self._input_images`.
    def _process_full(self, side, images, prediction_size, color):
              new_size = int(full_size * self._scaling)
              images = [self._resize_sample(side, image, new_size) for image in images]
          return images
  
    def _process_full(self, side, images, prediction_size, color):
    def _process_full(self, side, images, prediction_size, color):
          """ Add a frame overlay to preview images indicating the region of interest.
  
          This is the red border that appears in the preview images.
  
          Parameters
keep keep keep keep replace replace keep keep keep keep keep
 Extract - Increase area and move centering (#1095)

* Extract
  - Implement aligner re-feeding
  - Add extract type to pipeline.ExtractMedia
  - Add pose annotation to debug
* Convert
  - implement centering
  - remove usage of feed and reference face properties
  - Remove distributed option from convert
  - Force update of alignments file on legacy receive
* Train
  - Resize preview image to model output size
  - Force legacy centering if centering does not exist in model's state file
  - Enable training on legacy face sets

* Alignments Tool
  - Update draw to include head/pose
  - Remove DFL drop + linting
  - Remove remove-frames job
  - remove align-eyes option
  - Update legacy masks to new extract type
  - Exit if attempting to merge version 1.0 alignments files with version 2.0 alignments files
  - Re-generate thumbnails on legacy upgrade
* Mask Tool
  - Update for new extract + bugfix full frame
* Manual Tool
  - Update to new extraction method
   - Disable legacy alignments,
   - extract box bugfix
   - extract faces - size to 512 and center on head
* Preview Tool
  - Display based on model centering
* Sort Tool
  - Use alignments for sort by face

* lib.aligner
  - Add Pose Class
  - Add AlignedFace Class
  - center _MEAN_FACE on x
  - Add meta information with versioning to alignments file
  - lib.aligner.get_align_matrix to use landmarks not face
  - Refactor aligned faces in lib.faces_detect
* lib.logger
  - larger file log padding
* lib.config
  - Fix global changeable_items
* lib.face_filter
  - Use new extracted face images
* lib.image
  - bump thumbnail default size to 96px 
plugins/train/trainer/_base.py