      swapped_faces: :class:`np.ndarray`
          The swapped faces returned from the model's predict function
      """
      inbound: ExtractMedia
      feed_faces: T.List[AlignedFace] = field(default_factory=list)
      reference_faces: T.List[AlignedFace] = field(default_factory=list)
      swapped_faces: np.ndarray = np.array([])
  
  
  class Convert():  # pylint:disable=too-few-public-methods
      """ The Faceswap Face Conversion Process.
 
</s> remove     detected_faces: T.List["DetectedFace"] = field(default_factory=list)
    feed_faces: T.List[AlignedFace] = field(default_factory=list)
 </s> add     detected_faces: list[DetectedFace] = field(default_factory=list)
    feed_faces: list[AlignedFace] = field(default_factory=list) </s> remove     data: List[Dict[str, Any]] = field(default_factory=list)
 </s> add     data: list[dict[str, T.Any]] = field(default_factory=list) </s> remove     detected_faces: List["DetectedFace"] = field(default_factory=list)
    roi_masks: List[np.ndarray] = field(default_factory=list)
    feed_faces: List[AlignedFace] = field(default_factory=list)
 </s> add     detected_faces: list[DetectedFace] = field(default_factory=list)
    roi_masks: list[np.ndarray] = field(default_factory=list)
    feed_faces: list[AlignedFace] = field(default_factory=list) </s> remove     detected_faces: List[List["DetectedFace"]] = field(default_factory=list)
    rotation_matrix: List[np.ndarray] = field(default_factory=list)
    scale: List[float] = field(default_factory=list)
    pad: List[Tuple[int, int]] = field(default_factory=list)
 </s> add     detected_faces: list[list["DetectedFace"]] = field(default_factory=list)
    rotation_matrix: list[np.ndarray] = field(default_factory=list)
    scale: list[float] = field(default_factory=list)
    pad: list[tuple[int, int]] = field(default_factory=list) </s> remove     refeeds: List[np.ndarray] = field(default_factory=list)
 </s> add     refeeds: list[np.ndarray] = field(default_factory=list)
    feed_faces: list[AlignedFace] = field(default_factory=list)
    reference_faces: list[AlignedFace] = field(default_factory=list)
      swapped_faces: :class:`np.ndarray`
          The swapped faces returned from the model's predict function
      """
      inbound: ExtractMedia
    feed_faces: list[AlignedFace] = field(default_factory=list)
    reference_faces: list[AlignedFace] = field(default_factory=list)
    feed_faces: list[AlignedFace] = field(default_factory=list)
    reference_faces: list[AlignedFace] = field(default_factory=list)
      swapped_faces: np.ndarray = np.array([])
  
  
  class Convert():  # pylint:disable=too-few-public-methods
      """ The Faceswap Face Conversion Process.
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 
scripts/convert.py