          frame, otherwise it is generated from the jpg thumbnail.
  
          Parameters
          ----------
          face: :class:`lib.faces_detect.DetectedFace`
              A detected face object to create the :class:`TKFace` from
          image: :class:`numpy.ndarray`
              The jpg thumbnail or the 3 channel image for the face
          is_active: bool
              ``True`` if the face in the currently active frame otherwise ``False``
 
</s> remove     def _generate_thumbnail(self, face):
        """ Generate the jpg thumbnail from the currently active frame for the detected face and
        assign to it's `thumbnail` attribute.

        Parameters
        ----------
        face: class:`~lib.faces_detect.DetectedFace`
            The detected face object to generate the thumbnail for
        """
        face.load_aligned(self._globals.current_frame["image"], 80, force=True)
        jpg = cv2.imencode(".jpg", face.aligned_face, [cv2.IMWRITE_JPEG_QUALITY, 60])[1]
        face.thumbnail = jpg
        face.aligned = dict()

 </s> add  </s> remove         face: :class:`~lib.faces_detect.DetectedFace`
 </s> add         face: :class:`~lib.align.DetectedFace` </s> remove     def check(self, detected_face):
        """ Check the extracted Face """
 </s> add     def check(self, image, detected_face):
        """ Check the extracted Face

        Parameters
        ----------
        image: :class:`numpy.ndarray`
            The original frame that contains the face to be checked
        detected_face: :class:`lib.align.DetectedFace`
            The detected face object that contains the face to be checked

        Returns
        -------
        bool
            ``True`` if the face matches a filter otherwise ``False``
        """
 </s> remove     def check_exists(self, frame, alignment, idx):
        """ Check whether this face already exists """
 </s> add     def _check_exists(self, frame, alignment, index):
        """ Remove duplicate faces from the alignments file when an instance of the face already
        exists.

        Parameters
        ----------
        frame: str
            The frame name for the current frame being processed
        alignment: dict
            The alignment dictionary for the current face in the frame
        index: int
            The face index for the current face in the frame

        Returns
        -------
        bool
            ``True`` if the face has been already been seen, otherwise ``False``
        """ </s> remove         ``False`` if the standard random warp method should be used. If ``True`` then
        the key `landmarks` must be provided in the alignments dictionary.
 </s> add         ``False`` if the standard random warp method should be used.
        face: :class:`lib.align.DetectedFace`
          frame, otherwise it is generated from the jpg thumbnail.
  
          Parameters
          ----------
        face: :class:`lib.align.DetectedFace`
              A detected face object to create the :class:`TKFace` from
          image: :class:`numpy.ndarray`
              The jpg thumbnail or the 3 channel image for the face
          is_active: bool
              ``True`` if the face in the currently active frame otherwise ``False``
keep keep keep keep 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 
tools/manual/faceviewer/viewport.py