              logger.trace("Drawing Landmarks. Frame: '%s'. Face: %s",
                           detected_face["file_location"].parts[-1], idx)
              aligned_landmarks = face.aligned_landmarks
              for (pos_x, pos_y) in aligned_landmarks:
                  cv2.circle(face.feed_landmarks,  # pylint: disable=no-member
                             (pos_x, pos_y), 2, (0, 0, 255, 255), -1)
  
  
  class FaceFilter(PostProcessAction):
      """ Filter in or out faces based on input image(s)
          Extract or Convert """
 
</s> remove         retval = cv2.Laplacian(image, cv2.CV_64F).var()  # pylint: disable=no-member
 </s> add         retval = cv2.Laplacian(image, cv2.CV_64F).var() </s> remove             feature_mask = cv2.blur(  # pylint: disable=no-member
                feature_mask, (10, 10))
            isolated_face = cv2.multiply(  # pylint: disable=no-member
                feature_mask,
                resized_face.astype(float)).astype(np.uint8)
 </s> add             feature_mask = cv2.blur(feature_mask, (10, 10))
            isolated_face = cv2.multiply(feature_mask, resized_face.astype(float)).astype(np.uint8) </s> remove     """ Plugin loader for extract, training and model tasks """
 </s> add     """ Retrieve, or get information on, Faceswap plugins

    Return a specific plugin, list available plugins, or get the default plugin for a
    task.

    Example
    -------
    >>> from plugins.plugin_loader import PluginLoader
    >>> align_plugins = PluginLoader.get_available_extractors('align')
    >>> aligner = PluginLoader.get_aligner('cv2-dnn')
    """ </s> remove         gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)  # pylint: disable=no-member
 </s> add         gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) </s> remove         clahe = cv2.createCLAHE(clipLimit=2.0,  # pylint: disable=no-member
 </s> add         clahe = cv2.createCLAHE(clipLimit=2.0,
                cv2.circle(face.aligned_face, (pos_x, pos_y), 2, (0, 0, 255), -1)
              logger.trace("Drawing Landmarks. Frame: '%s'. Face: %s",
                           detected_face["file_location"].parts[-1], idx)
              aligned_landmarks = face.aligned_landmarks
              for (pos_x, pos_y) in aligned_landmarks:
                cv2.circle(face.aligned_face, (pos_x, pos_y), 2, (0, 0, 255), -1)
                cv2.circle(face.aligned_face, (pos_x, pos_y), 2, (0, 0, 255), -1)
  
  
  class FaceFilter(PostProcessAction):
      """ Filter in or out faces based on input image(s)
          Extract or Convert """
keep keep keep keep replace replace keep keep keep keep keep
 Smart Mask - Extract code review

- Lint simple_tests.py
- Only reformat alignments file if it exists otherwise change filename
- Update legacy alignments to new format at all stages
- faces_detect.Mask.from_dict - logging format fix
- convert.py fix otf for new pipeline
- cli.py - Add note that masks not used. Revert convert masks
- faces_detect.py - Revert non-extract code
- Add .p and .pickle extensions for serializer
- plugins/extract revert some changes
- scripts/fsmedia - Revert code changes
- Pipeline - cleanup
- Consistant alpha channel stripping (fixes single-process)
- Store landmarks as numpy array
- Code attribution
- Normalize feed face and reference face to 0.0 - 1.0 in convert
- Lock in mask VRAM sized
- Add documentation to plugin_loader
- Update alignments tool to work with new format 
scripts/fsmedia.py