          """
          retval = [True for _ in range(len(faces))]
          for idx, (face, dim) in enumerate(zip(faces, minimum_dimension)):
              aligned = AlignedFace(landmarks=face.landmarks_xy)
              if self._scale_test(aligned, dim) is not None:
                  continue
              if 0.0 < self._distance < aligned.average_distance:
                  continue
 
</s> remove         self._active = not disable and (max_scale > 0.0 or min_scale > 0.0 or distance > 0.0)
        self._counts: Dict[str, int] = dict(min_scale=0, max_scale=0, distance=0, roll=0)
 </s> add         self._active = not disable and (feature_filter or
                                        max_scale > 0.0 or
                                        min_scale > 0.0 or
                                        distance > 0.0 or
                                        roll > 0.0)
        self._counts: Dict[str, int] = dict(features=0,
                                            min_scale=0,
                                            max_scale=0,
                                            distance=0,
                                            roll=0) </s> remove         logger.debug("Initializing %s: (min_scale: %s, max_scale: %s, distance: %s, roll, %s"
                     "save_output: %s, disable: %s)", self.__class__.__name__, min_scale,
                     max_scale, distance, roll, save_output, disable)
 </s> add         logger.debug("Initializing %s: (feature_filter: %s, min_scale: %s, max_scale: %s, "
                     "distance: %s, roll, %s, save_output: %s, disable: %s)",
                     self.__class__.__name__, feature_filter, min_scale, max_scale, distance, roll,
                     save_output, disable)
        self._features = feature_filter
            if self._features and aligned.relative_eye_mouth_position < 0.0:
                continue
          """
          retval = [True for _ in range(len(faces))]
          for idx, (face, dim) in enumerate(zip(faces, minimum_dimension)):
              aligned = AlignedFace(landmarks=face.landmarks_xy)
            if self._features and aligned.relative_eye_mouth_position < 0.0:
                continue
              if self._scale_test(aligned, dim) is not None:
                  continue
              if 0.0 < self._distance < aligned.average_distance:
                  continue
keep keep keep add keep keep keep keep
 Aligner - Add feature position filter 
plugins/extract/align/_base.py