          return landmarks
  
      @property
      def reference_matrix(self):
          """ numpy.ndarray: The adjusted matrix face sized for refence against a face coming out of
           a model. Only available after :func:`load_reference_face` has been called, otherwise
           returns ``None``"""
          if not self.reference:
              return None
          mat = AlignerExtract().transform_matrix(self.reference["matrix"],
 
</s> remove         self._intepolator = None
 </s> add         self._interpolator = None </s> remove         padding = int((size * (coverage_ratio - 0.625)) / 2)
 </s> add         adjusted_ratio = coverage_ratio - (1 - self._extract_ratio)
        padding = round((size * adjusted_ratio) / 2) </s> remove         """ Return a list of available models """
 </s> add         """ Return a list of available training models

        Returns
        -------
        list:
            A list of the available training model plugin names
        """ </s> remove     def training_coverage(self):
        """ The coverage ratio to add for training images """
        return 1.0
 </s> add     def _extract_ratio(self):
        """ float: The ratio of padding to add for training images """
        return 0.375
        """ numpy.ndarray: The adjusted matrix face sized for reference against a face coming out of
          return landmarks
  
      @property
      def reference_matrix(self):
        """ numpy.ndarray: The adjusted matrix face sized for reference against a face coming out of
           a model. Only available after :func:`load_reference_face` has been called, otherwise
           returns ``None``"""
          if not self.reference:
              return None
          mat = AlignerExtract().transform_matrix(self.reference["matrix"],
keep keep keep keep replace keep keep keep keep keep
 Smart Mask - Extract code review

- Lint simple_tests.py
- Only reformat alignments file if it exists otherwise change filename
- Update legacy alignments to new format at all stages
- faces_detect.Mask.from_dict - logging format fix
- convert.py fix otf for new pipeline
- cli.py - Add note that masks not used. Revert convert masks
- faces_detect.py - Revert non-extract code
- Add .p and .pickle extensions for serializer
- plugins/extract revert some changes
- scripts/fsmedia - Revert code changes
- Pipeline - cleanup
- Consistant alpha channel stripping (fixes single-process)
- Store landmarks as numpy array
- Code attribution
- Normalize feed face and reference face to 0.0 - 1.0 in convert
- Lock in mask VRAM sized
- Add documentation to plugin_loader
- Update alignments tool to work with new format 
lib/faces_detect.py