          return mat
  
      @property
      def reference_interpolators(self):
          """ Return the interpolators for an output face """
          return get_matrix_scaling(self.reference_matrix)
 
</s> remove         """ Return the interpolators for an input face """
        return get_matrix_scaling(self.feed_matrix)
 </s> add         """ tuple:  Tuple of (`interpolator` and `reverse interpolator`) for the adjusted feed
        matrix. Only available after :func:`load_feed_face` has been called, otherwise returns
        ``None``"""
        if not self.feed:
            return None
        return get_matrix_scaling(self._feed_matrix) </s> remove     def feed_matrix(self):
        """ Return matrix for transforming feed face back to image """
 </s> add     def _feed_matrix(self):
        """ numpy.ndarray: The adjusted matrix face sized for feeding into a model. Only available
        after :func:`load_feed_face` has been called with an image, otherwise returns ``None`` """
        if not self.feed:
            return None </s> remove         """ Return aligned detected face """
        return self.aligned["face"]
 </s> add         """ numpy.ndarray: The aligned detected face. Only available after :func:`load_aligned`
        has been called with an image, otherwise returns ``None`` """
        return self.aligned.get("face", None) </s> remove         """ Return the interpolator and reverse interpolator for the adjusted matrix """
        return get_matrix_scaling(self.adjusted_matrix)
 </s> add         """ tuple:  Tuple of (`interpolator` and `reverse interpolator`) for the adjusted matrix.
        Only available after :func:`load_aligned` has been called, otherwise returns ``None``"""
        if not self.aligned:
            return None
        return get_matrix_scaling(self._adjusted_matrix) </s> remove         """ Return matrix for transforming output face back to image """
 </s> add         """ numpy.ndarray: The adjusted matrix face sized for refence against a face coming out of
         a model. Only available after :func:`load_reference_face` has been called, otherwise
         returns ``None``"""
        if not self.reference:
            return None
        """ tuple:  Tuple of (`interpolator` and `reverse interpolator`) for the reference
        matrix. Only available after :func:`load_reference_face` has been called, otherwise
        returns ``None``"""
        if not self.reference:
            return None
          return mat
  
      @property
      def reference_interpolators(self):
        """ tuple:  Tuple of (`interpolator` and `reverse interpolator`) for the reference
        matrix. Only available after :func:`load_reference_face` has been called, otherwise
        returns ``None``"""
        if not self.reference:
            return None
          return get_matrix_scaling(self.reference_matrix)
keep keep keep keep replace keep
 De-Multiprocess Extract (#871)

* requirements.txt: - Pin opencv to 4.1.1 (fixes cv2-dnn error)

* lib.face_detect.DetectedFace: change LandmarksXY to landmarks_xy. Add left, right, top, bottom attributes

* lib.model.session: Session manager for loading models into different graphs (for Nvidia + CPU)

* plugins.extract._base: New parent class for all extract plugins

* plugins.extract.pipeline. Remove MultiProcessing. Dynamically limit batchsize for Nvidia cards. Remove loglevel input

* S3FD + FAN plugins. Standardise to Keras version for all backends

* Standardize all extract plugins to new threaded codebase

* Documentation. Start implementing Numpy style docstrings for Sphinx Documentation

* Remove s3fd_amd. Change convert OTF to expect DetectedFace object

* faces_detect - clean up and documentation

* Remove PoolProcess

* Migrate manual tool to new extract workflow

* Remove AMD specific extractor code from cli and plugins

* Sort tool to new extract workflow

* Remove multiprocessing from project

* Remove multiprocessing queues from QueueManager

* Remove multiprocessing support from logger

* Move face_filter to new extraction pipeline

* Alignments landmarksXY > landmarks_xy and legacy handling

* Intercept get_backend for sphinx doc build

# Add Sphinx documentation 
lib/faces_detect.py