              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(  # pylint: disable=no-member
                      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 """
 
</s> remove             aligned_landmarks = face.aligned_landmarks
 </s> add             aligned_landmarks = face.feed_landmarks </s> remove                                    for dim, faces in zip(dims,
                                                         batch.get("detected_faces", list()))]
 </s> add                                    for dim, faces in zip(dims, batch.get("detected_faces", []))] </s> remove             images = np.array([cv2.addWeighted(img, 1.0,  # pylint: disable=no-member
                                               masks3[idx], 0.3,
                                               0)
 </s> add             images = np.array([cv2.addWeighted(img,  # pylint: disable=no-member
                                               1.0, masks3[idx], 0.3, 0) </s> remove         blob = cv2.dnn.blobFromImage(face,  # pylint: disable=no-member
 </s> add         blob = cv2.dnn.blobFromImage(face[..., :3],  # pylint: disable=no-member
                cv2.circle(face.feed_face,  # pylint: disable=no-member
                           (pos_x, pos_y), 2, (0, 0, 255, 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.feed_face,  # pylint: disable=no-member
                           (pos_x, pos_y), 2, (0, 0, 255, 255), -1)
                cv2.circle(face.feed_face,  # pylint: disable=no-member
                           (pos_x, pos_y), 2, (0, 0, 255, 255), -1)
                cv2.circle(face.feed_face,  # 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 """
keep keep keep keep replace replace replace keep keep keep keep keep
 Smart Mask Exposure for Extraction & Training (#831)

Smart Masks - Initial Commit 
scripts/fsmedia.py