              performed.
          """
          logger.trace("new_face shape: %s, predicted_mask shape: %s",  # type: ignore
                       new_face.shape, predicted_mask.shape if predicted_mask is not None else None)
          old_face = cast(np.ndarray, reference_face.face)[..., :3] / 255.0
          new_face, raw_mask = self._get_image_mask(new_face,
                                                    detected_face,
                                                    predicted_mask,
                                                    reference_face)
          if self._adjustments.color is not None:
 
</s> remove         batch.feed = np.array([cast(np.ndarray, feed.face)[..., :3]
 </s> add         batch.feed = np.array([T.cast(np.ndarray, feed.face)[..., :3] </s> remove         self._image: Optional["np.ndarray"] = image
        self._image_shape = cast(Tuple[int, int, int], image.shape)
        self._detected_faces: List["DetectedFace"] = ([] if detected_faces is None
                                                      else detected_faces)
 </s> add         self._image: np.ndarray | None = image
        self._image_shape = T.cast(tuple[int, int, int], image.shape)
        self._detected_faces: list[DetectedFace] = ([] if detected_faces is None
                                                    else detected_faces) </s> remove                  image: "np.ndarray",
                 detected_faces: Optional[List["DetectedFace"]] = None,
 </s> add                  image: np.ndarray,
                 detected_faces: list[DetectedFace] | None = None, </s> remove     def set_cursor_default(self, widget: Optional[tk.Widget] = None) -> None:
 </s> add     def set_cursor_default(self, widget: tk.Widget | None = None) -> None: </s> remove         self._model: Optional[Model] = None
 </s> add         self._model: Model | None = None
        old_face = T.cast(np.ndarray, reference_face.face)[..., :3] / 255.0
              performed.
          """
          logger.trace("new_face shape: %s, predicted_mask shape: %s",  # type: ignore
                       new_face.shape, predicted_mask.shape if predicted_mask is not None else None)
        old_face = T.cast(np.ndarray, reference_face.face)[..., :3] / 255.0
          new_face, raw_mask = self._get_image_mask(new_face,
                                                    detected_face,
                                                    predicted_mask,
                                                    reference_face)
          if self._adjustments.color is not None:
keep keep keep keep 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 
lib/convert.py