          # predicted[predicted < 0.04] = 0.0
          # predicted[predicted > 0.96] = 1.0
          # TODO Convert landmarks_xy to numpy arrays
          for mask, face in zip(batch["prediction"], batch["detected_faces"]):
              face.add_mask(self.name,
                            mask,
                            face.feed_matrix,
                            (face.image.shape[1], face.image.shape[0]),
                            face.feed_interpolators[1])
              face.feed = None
 
</s> remove                           face.feed_interpolators[1])
 </s> add                           face.feed_interpolators[1],
                          storage_size=self._storage_size) </s> remove         self.blur_kernel = 9
 </s> add  </s> remove         self.blur_kernel = 7
 </s> add  </s> remove         self.name = "VGG Mask Network(300)"
 </s> add         self.name = "VGG Clear"
            face.add_mask(self._storage_name,
          # predicted[predicted < 0.04] = 0.0
          # predicted[predicted > 0.96] = 1.0
          # TODO Convert landmarks_xy to numpy arrays
          for mask, face in zip(batch["prediction"], batch["detected_faces"]):
            face.add_mask(self._storage_name,
                            mask,
                            face.feed_matrix,
                            (face.image.shape[1], face.image.shape[0]),
                            face.feed_interpolators[1])
              face.feed = None
keep keep keep keep replace keep keep keep keep keep
 Mask extraction fixes

- Save mask to alignments file as dict
- Remove blur_kernel param from plugins
- Correctly read out the mask buffer on decompress
- Fix full frame mask output
- Remove BORDER_TRANSPARENT in warp_affine (it is bugged. Don't use it)
- Store the affine matrix for the saved mask size 
plugins/extract/mask/_base.py