          scale = self.input_size / max(image_size)
          logger.trace("Detector scale: %s", scale)  # type:ignore[attr-defined]
          return scale
  
      def _set_padding(self, image_size: Tuple[int, int], scale: float) -> Tuple[int, int]:
          """ Set the image padding for non-square images
  
          Parameters
          ----------
          image_size: tuple
 
</s> remove     def _scale_image(image: np.ndarray, image_size: Tuple[int, int], scale: float) -> np.ndarray:
 </s> add     def _scale_image(image: np.ndarray, image_size: tuple[int, int], scale: float) -> np.ndarray: </s> remove     def _set_scale(self, image_size: Tuple[int, int]) -> float:
 </s> add     def _set_scale(self, image_size: tuple[int, int]) -> float: </s> remove     def __init__(self, level: int, scale: float, crop: T.Tuple[int, int]):
 </s> add     def __init__(self, level: int, scale: float, crop: tuple[int, int]): </s> remove                            scale: float) -> T.Tuple[np.ndarray, np.ndarray]:
 </s> add                            scale: float) -> tuple[np.ndarray, np.ndarray]: </s> remove             x_center = (cast(int, face.left) + face.right) / 2.0
            y_center = (cast(int, face.top) + face.bottom) / 2.0 - cast(int, face.height) * 0.12
            scale = (cast(int, face.width) + cast(int, face.height)) * self.reference_scale
            center_scale[index, :, 0] = np.full(68, x_center, dtype='float32')
            center_scale[index, :, 1] = np.full(68, y_center, dtype='float32')
 </s> add             x_ctr = (T.cast(int, face.left) + face.right) / 2.0
            y_ctr = (T.cast(int, face.top) + face.bottom) / 2.0 - T.cast(int, face.height) * 0.12
            scale = (T.cast(int, face.width) + T.cast(int, face.height)) * self.reference_scale
            center_scale[index, :, 0] = np.full(68, x_ctr, dtype='float32')
            center_scale[index, :, 1] = np.full(68, y_ctr, dtype='float32')
    def _set_padding(self, image_size: tuple[int, int], scale: float) -> tuple[int, int]:
          scale = self.input_size / max(image_size)
          logger.trace("Detector scale: %s", scale)  # type:ignore[attr-defined]
          return scale
  
    def _set_padding(self, image_size: tuple[int, int], scale: float) -> tuple[int, int]:
          """ Set the image padding for non-square images
  
          Parameters
          ----------
          image_size: tuple
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 
plugins/extract/detect/_base.py