              The aligned face
          index: int
              The face index for the given face
          """
          for area in get_args(Literal["face", "head"]):
              face.load_aligned(image, centering=area, force=True)
              color = (0, 255, 0) if area == "face" else (0, 0, 255)
              top_left = face.aligned.original_roi[0]
              top_left = (top_left[0], top_left[1] - 10)
              cv2.putText(image, str(index), top_left, cv2.FONT_HERSHEY_DUPLEX, 1.0, color, 1)
 
</s> remove     tf_min: T.Tuple[int, int] = (2, 0)
    scaling: T.Tuple[int, int] = (0, 1)
 </s> add     tf_min: tuple[int, int] = (2, 0)
    scaling: tuple[int, int] = (0, 1) </s> remove         self.rocm_version: Tuple[int, ...] = (0, 0, 0)
 </s> add         self.rocm_version: tuple[int, ...] = (0, 0, 0) </s> remove         self.rocm_version: Tuple[int, ...] = (0, 0, 0)
 </s> add         self.rocm_version: tuple[int, ...] = (0, 0, 0) </s> remove         for area in get_args(Literal["eye", "mouth"]):
 </s> add         for area in T.get_args(T.Literal["eye", "mouth"]): </s> remove                 centering: "CenteringType" = ("legacy" if self._alignments is not None and
                                              self._alignments.version == 1.0
                                              else mask.stored_centering)
 </s> add                 centering: CenteringType = ("legacy" if self._alignments is not None and
                                            self._alignments.version == 1.0
                                            else mask.stored_centering)
        for area in T.get_args(T.Literal["face", "head"]):
              The aligned face
          index: int
              The face index for the given face
          """
        for area in T.get_args(T.Literal["face", "head"]):
              face.load_aligned(image, centering=area, force=True)
              color = (0, 255, 0) if area == "face" else (0, 0, 255)
              top_left = face.aligned.original_roi[0]
              top_left = (top_left[0], top_left[1] - 10)
              cv2.putText(image, str(index), top_left, cv2.FONT_HERSHEY_DUPLEX, 1.0, color, 1)
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 
tools/alignments/jobs_frames.py