          if not np.any(identities):
              logger.trace("All faces already filtered: %s", sub_folders)  # type: ignore
              return faces
  
          should_filter: T.List[np.ndarray] = []
          for f_type in get_args(Literal["filter", "nfilter"]):
              if not getattr(self, f"_{f_type}_enabled"):
                  continue
              should_filter.append(self._get_matches(f_type, identities))
  
          # If any of the filter or nfilter evaluate to 'should filter' then filter out face
 
</s> remove         final_filter: T.List[bool] = np.array(should_filter).max(axis=0).tolist()
 </s> add         final_filter: list[bool] = np.array(should_filter).max(axis=0).tolist() </s> remove         retval: T.List[DetectedFace] = []
 </s> add         retval: list[DetectedFace] = [] </s> remove         retval: List[np.ndarray] = []
        filtered_landmarks: List[np.ndarray] = []
 </s> add         retval: list[np.ndarray] = []
        filtered_landmarks: list[np.ndarray] = [] </s> remove     def _filter_small_faces(self, detected_faces: List[List[DetectedFace]]
                            ) -> List[List[DetectedFace]]:
 </s> add     def _filter_small_faces(self, detected_faces: list[list[DetectedFace]]
                            ) -> list[list[DetectedFace]]: </s> remove         ret: T.List[np.ndarray] = []
 </s> add         ret: list[np.ndarray] = []
        should_filter: list[np.ndarray] = []
        for f_type in T.get_args(T.Literal["filter", "nfilter"]):
          if not np.any(identities):
              logger.trace("All faces already filtered: %s", sub_folders)  # type: ignore
              return faces
  
        should_filter: list[np.ndarray] = []
        for f_type in T.get_args(T.Literal["filter", "nfilter"]):
        should_filter: list[np.ndarray] = []
        for f_type in T.get_args(T.Literal["filter", "nfilter"]):
              if not getattr(self, f"_{f_type}_enabled"):
                  continue
              should_filter.append(self._get_matches(f_type, identities))
  
          # If any of the filter or nfilter evaluate to 'should filter' then filter out face
keep keep keep keep 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