          logger.trace("mask shape: %s", mask.shape)
          return mask
  
      @property
      def original_roi(self):
          """ :class: `numpy.ndarray`: The original region of interest of the mask in the
          source frame. """
          points = np.array([[0, 0],
                             [0, self.stored_size - 1],
 
</s> remove         """ numpy.ndarray: The mask at the size of :attr:`stored_size` with any requested blurring
        and threshold amount applied."""
        dims = (self.stored_size, self.stored_size, 1)
        mask = np.frombuffer(decompress(self._mask), dtype="uint8").reshape(dims)
 </s> add         """ numpy.ndarray: The mask at the size of :attr:`stored_size` with any requested blurring,
        threshold amount and centering applied."""
        mask = self.stored_mask </s> remove         for (frame_idx, face_idx), det_faces in zip(
 </s> add         for (frame_idx, face_idx), det_face in zip( </s> remove         a safe manner (i.e. handle for non-numerics)
 </s> add         a safe manner (i.e. handle for non-numeric)
    @property
    def stored_mask(self):
        """ :class:`numpy.ndarray`: The mask at the size of :attr:`stored_size` as it is stored
        (i.e. with no blurring/centering applied). """
        dims = (self.stored_size, self.stored_size, 1)
        mask = np.frombuffer(decompress(self._mask), dtype="uint8").reshape(dims)
        logger.trace("stored mask shape: %s", mask.shape)
        return mask

          logger.trace("mask shape: %s", mask.shape)
          return mask
  
    @property
    def stored_mask(self):
        """ :class:`numpy.ndarray`: The mask at the size of :attr:`stored_size` as it is stored
        (i.e. with no blurring/centering applied). """
        dims = (self.stored_size, self.stored_size, 1)
        mask = np.frombuffer(decompress(self._mask), dtype="uint8").reshape(dims)
        logger.trace("stored mask shape: %s", mask.shape)
        return mask

      @property
      def original_roi(self):
          """ :class: `numpy.ndarray`: The original region of interest of the mask in the
          source frame. """
          points = np.array([[0, 0],
                             [0, self.stored_size - 1],
keep keep add keep keep keep keep keep keep
 Manual Tool - Update to support masks with different centering 
lib/align/detected_face.py