          image: numpy.ndarray
              The image that contains the face to be aligned
          size: int
              The size of the output face in pixels
          coverage_ratio: float
              The metric determining the field of view of the returned face
          dtype: str, optional
              Optionally set a ``dtype`` for the final face to be formatted in. Default: ``None``
  
          Notes
          -----
 
</s> remove     image: np.ndarray, optional
        This is a generic image placeholder that should not be relied on to be holding a particular
        image. It may hold the source frame that holds the face, a cropped face or a scaled image
        depending on the method using this object.
 </s> add     image: numpy.ndarray, optional
        Original frame that holds this face. Optional (not required if just storing coordinates) </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 </s> remove             This should be a ``list`` or ``numpy.array`` of :attr:`batchsize` containing a
            ``list``, ``tuple`` or ``numpy.array`` of `(x, y)` co-ords of the 68 point landmarks
            as calculated from the :attr:`model`.
 </s> add             This should be a ``list`` or ``numpy.ndarray`` of :attr:`batchsize` containing a
            ``list``, ``tuple`` or ``numpy.ndarray`` of `(x, y)` coordinates of the 68 point
            landmarks as calculated from the :attr:`model`. </s> remove         This should be set prior to :func:`launch` if the batchsize is to be manually overriden
 </s> add         This should be set prior to :func:`launch` if the batch size is to be manually overridden </s> remove             a ``list``, ``tuple`` or ``numpy.array`` with the first 4 items being the `left`,
 </s> add             a ``list``, ``tuple`` or ``numpy.ndarray`` with the first 4 items being the `left`,
          image: numpy.ndarray
              The image that contains the face to be aligned
          size: int
              The size of the output face in pixels


          dtype: str, optional
              Optionally set a ``dtype`` for the final face to be formatted in. Default: ``None``
  
          Notes
          -----
keep keep keep keep replace 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