                       "retval: %s", filter_type, distances.shape, is_match, retval)
          return retval
  
      def _filter_faces(self,
                        faces: T.List[DetectedFace],
                        sub_folders: T.List[T.Optional[str]],
                        should_filter: T.List[bool]) -> T.List[DetectedFace]:
          """ Filter the detected faces, either removing filtered faces from the list of detected
          faces or setting the output subfolder to `"_identity_filt"` for any filtered faces if
          saving output is enabled.
  
          Parameters
 
</s> remove         retval: T.List[DetectedFace] = []
 </s> add         retval: list[DetectedFace] = [] </s> remove     def sub_folders(self) -> List[Optional[str]]:
 </s> add     def sub_folders(self) -> list[str | None]: </s> remove         sub_folders: List[Optional[str]] = [None for _ in range(len(faces))]
 </s> add         sub_folders: list[str | None] = [None for _ in range(len(faces))] </s> remove                  faces: T.List[DetectedFace],
                 sub_folders: T.List[T.Optional[str]]) -> T.List[DetectedFace]:
 </s> add                  faces: list[DetectedFace],
                 sub_folders: list[str | None]) -> list[DetectedFace]: </s> remove     def get_image_copy(self, color_format: Literal["BGR", "RGB", "GRAY"]) -> "np.ndarray":
 </s> add     def get_image_copy(self, color_format: T.Literal["BGR", "RGB", "GRAY"]) -> np.ndarray:
                      faces: list[DetectedFace],
                      sub_folders: list[str | None],
                      should_filter: list[bool]) -> list[DetectedFace]:
                       "retval: %s", filter_type, distances.shape, is_match, retval)
          return retval
  
      def _filter_faces(self,
                      faces: list[DetectedFace],
                      sub_folders: list[str | None],
                      should_filter: list[bool]) -> list[DetectedFace]:
                      faces: list[DetectedFace],
                      sub_folders: list[str | None],
                      should_filter: list[bool]) -> list[DetectedFace]:
                      faces: list[DetectedFace],
                      sub_folders: list[str | None],
                      should_filter: list[bool]) -> list[DetectedFace]:
          """ Filter the detected faces, either removing filtered faces from the list of detected
          faces or setting the output subfolder to `"_identity_filt"` for any filtered faces if
          saving output is enabled.
  
          Parameters
keep keep keep keep 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/recognition/_base.py