  
      def _filter_face_48net(self, class_probabilities: np.ndarray,
                             roi: np.ndarray,
                             points: np.ndarray,
                             rectangles: np.ndarray) -> Tuple[np.ndarray, np.ndarray]:
          """ Filter face position and calibrate bounding box on 12net's output
  
          Parameters
          ----------
          class_probabilities: :class:`numpy.ndarray`  : class_probabilities[1] is face possibility
 
</s> remove                            scale: float) -> Tuple[np.ndarray, np.ndarray]:
 </s> add                            scale: float) -> T.Tuple[np.ndarray, np.ndarray]: </s> remove         method: str = "iom") -> Tuple[np.ndarray, np.ndarray]:
 </s> add         method: str = "iom") -> T.Tuple[np.ndarray, np.ndarray]: </s> remove             cls_probs, roi_probs, pts_probs = self.predict(
                feed_batch,
                batch_size=128 if get_backend() == "amd" else None)
 </s> add             cls_probs, roi_probs, pts_probs = self.predict(feed_batch) </s> remove     def _get_predictions(self, feed_a: np.ndarray, feed_b: np.ndarray) -> Dict[str, np.ndarray]:
 </s> add     def _get_predictions(self, feed_a: np.ndarray, feed_b: np.ndarray) -> T.Dict[str, np.ndarray]: </s> remove     def detect_faces(self, batch: np.ndarray) -> Tuple[np.ndarray, Tuple[np.ndarray]]:
 </s> add     def detect_faces(self, batch: np.ndarray) -> T.Tuple[np.ndarray, T.Tuple[np.ndarray]]:
                           rectangles: np.ndarray) -> T.Tuple[np.ndarray, np.ndarray]:
  
      def _filter_face_48net(self, class_probabilities: np.ndarray,
                             roi: np.ndarray,
                             points: np.ndarray,
                           rectangles: np.ndarray) -> T.Tuple[np.ndarray, np.ndarray]:
          """ Filter face position and calibrate bounding box on 12net's output
  
          Parameters
          ----------
          class_probabilities: :class:`numpy.ndarray`  : class_probabilities[1] is face possibility
keep keep keep keep replace keep keep keep keep keep
 Remove plaidML support (#1325)

* Remove PlaidML reference from readme files

* Remove AMD option from installers

* remove amd requirements and update setup.py

* remove plaidml test from CI workflow

* gpustats: remove plaidml backend

* plaid removals:
  - faceswap.py - python version check
  - setup.cfg - plaidml typing ignore
  - lib.keras_utils - All plaid code
  - lib.launcher.py - All plaidml checks and configuration

* remove tf2.2 specific code from GUI event reader

* lib.model - remove all plaidml implementations

* plugins.extract - remove plaidml code

* plugins.train remove plaidml code

* lib.convert - remove plaidml code

* tools.model: remove plaidml code

* Remove plaidML tests from unit tests

* remove plaidml_utils and docsting cleanups

* Remove plaidML refs from configs

* fix keras imports 
plugins/extract/detect/mtcnn.py