          offset: int
              The offset of the box (difference between half width vs height)
          """
  
          box = cast(List[int], [face.left,
                                 face.top,
                                 face.right,
                                 face.bottom])
          diff_height_width = cast(int, face.height) - cast(int, face.width)
          offset = int(abs(diff_height_width / 2))
          return box, offset
  
      def align_image(self, batch: AlignerBatch) -> Tuple[List[np.ndarray],
                                                          List[List[int]],
 
</s> remove     def align_image(self, batch: AlignerBatch) -> Tuple[List[np.ndarray],
                                                        List[List[int]],
                                                        List[Tuple[int, int]]]:
 </s> add     def align_image(self, batch: AlignerBatch) -> tuple[list[np.ndarray],
                                                        list[list[int]],
                                                        list[tuple[int, int]]]: </s> remove         batch.data.append(dict(roi=roi, offsets=offsets))
 </s> add         batch.data.append({"roi": roi, "offsets": offsets}) </s> remove                  box: List[int],
                 offset: Tuple[int, int]) -> List[int]:
 </s> add                  box: list[int],
                 offset: tuple[int, int]) -> list[int]: </s> remove     def _get_box_and_offset(self, face: "DetectedFace") -> Tuple[List[int], int]:
 </s> add     def _get_box_and_offset(self, face: DetectedFace) -> tuple[list[int], int]: </s> remove             x_center = (cast(int, face.left) + face.right) / 2.0
            y_center = (cast(int, face.top) + face.bottom) / 2.0 - cast(int, face.height) * 0.12
            scale = (cast(int, face.width) + cast(int, face.height)) * self.reference_scale
            center_scale[index, :, 0] = np.full(68, x_center, dtype='float32')
            center_scale[index, :, 1] = np.full(68, y_center, dtype='float32')
 </s> add             x_ctr = (T.cast(int, face.left) + face.right) / 2.0
            y_ctr = (T.cast(int, face.top) + face.bottom) / 2.0 - T.cast(int, face.height) * 0.12
            scale = (T.cast(int, face.width) + T.cast(int, face.height)) * self.reference_scale
            center_scale[index, :, 0] = np.full(68, x_ctr, dtype='float32')
            center_scale[index, :, 1] = np.full(68, y_ctr, dtype='float32')
        box = T.cast(list[int], [face.left,
                                 face.top,
                                 face.right,
                                 face.bottom])
        diff_height_width = T.cast(int, face.height) - T.cast(int, face.width)
          offset: int
              The offset of the box (difference between half width vs height)
          """
  
        box = T.cast(list[int], [face.left,
                                 face.top,
                                 face.right,
                                 face.bottom])
        diff_height_width = T.cast(int, face.height) - T.cast(int, face.width)
        box = T.cast(list[int], [face.left,
                                 face.top,
                                 face.right,
                                 face.bottom])
        diff_height_width = T.cast(int, face.height) - T.cast(int, face.width)
        box = T.cast(list[int], [face.left,
                                 face.top,
                                 face.right,
                                 face.bottom])
        diff_height_width = T.cast(int, face.height) - T.cast(int, face.width)
        box = T.cast(list[int], [face.left,
                                 face.top,
                                 face.right,
                                 face.bottom])
        diff_height_width = T.cast(int, face.height) - T.cast(int, face.width)
        box = T.cast(list[int], [face.left,
                                 face.top,
                                 face.right,
                                 face.bottom])
        diff_height_width = T.cast(int, face.height) - T.cast(int, face.width)
          offset = int(abs(diff_height_width / 2))
          return box, offset
  
      def align_image(self, batch: AlignerBatch) -> Tuple[List[np.ndarray],
                                                          List[List[int]],
keep keep keep keep replace replace replace replace replace keep keep keep keep keep
 Rebase code (#1326)

* Remove tensorflow_probability requirement

* setup.py - fix progress bars

* requirements.txt: Remove pre python 3.9 packages

* update apple requirements.txt

* update INSTALL.md

* Remove python<3.9 code

* setup.py - fix Windows Installer

* typing: python3.9 compliant

* Update pytest and readthedocs python versions

* typing fixes

* Python Version updates
  - Reduce max version to 3.10
  - Default to 3.10 in installers
  - Remove incompatible 3.11 tests

* Update dependencies

* Downgrade imageio dep for Windows

* typing: merge optional unions and fixes

* Updates
  - min python version 3.10
  - typing to python 3.10 spec
  - remove pre-tf2.10 code
  - Add conda tests

* train: re-enable optimizer saving

* Update dockerfiles

* Update setup.py
  - Apple Conda deps to setup.py
  - Better Cuda + dependency handling

* bugfix: Patch logging to prevent Autograph errors

* Update dockerfiles

* Setup.py - Setup.py - stdout to utf-8

* Add more OSes to github Actions

* suppress mac-os end to end test 
plugins/extract/align/cv2_dnn.py