          """
          logger.trace("Calculating center and scale")  # type:ignore[attr-defined]
          center_scale = np.empty((len(detected_faces), 68, 3), dtype='float32')
          for index, face in enumerate(detected_faces):
              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')
              center_scale[index, :, 2] = np.full(68, scale, dtype='float32')
          logger.trace("Calculated center and scale: %s", center_scale)  # type:ignore[attr-defined]
          return center_scale
  
      def _crop_image(self,
 
</s> remove         if plugins_required + batch_required <= cast(int, self._vram_stats["vram_free"]):
 </s> add         if plugins_required + batch_required <= T.cast(int, self._vram_stats["vram_free"]): </s> remove         batch.data.append(dict(center_scale=center_scale))
 </s> add         batch.data.append({"center_scale": center_scale}) </s> remove         box = cast(List[int], [face.left,
                               face.top,
                               face.right,
                               face.bottom])
        diff_height_width = cast(int, face.height) - cast(int, face.width)
 </s> add         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) </s> remove     def _generate_weights(cls, channel: Dict[str, float], domain: np.ndarray) -> tf.Tensor:
 </s> add     def _generate_weights(cls, channel: dict[str, float], domain: np.ndarray) -> tf.Tensor: </s> remove         for i, frame in enumerate(cast(Iterator[np.ndarray], reader)):
 </s> add         for i, frame in enumerate(T.cast(Iterator[np.ndarray], reader)):
            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')
          """
          logger.trace("Calculating center and scale")  # type:ignore[attr-defined]
          center_scale = np.empty((len(detected_faces), 68, 3), dtype='float32')
          for index, face in enumerate(detected_faces):
            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')
            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')
            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')
            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')
            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')
              center_scale[index, :, 2] = np.full(68, scale, dtype='float32')
          logger.trace("Calculated center and scale: %s", center_scale)  # type:ignore[attr-defined]
          return center_scale
  
      def _crop_image(self,
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/fan.py