          """ queue images for detection and alignment """
          in_queue = extractor.input_queue
          for fname, img in self.filters.items():
              logger.debug("Adding to filter queue: '%s' (%s)", fname, img["type"])
              feed_dict = dict(filename=fname, image=img["image"])
              if img.get("detected_faces", None):
                  feed_dict["detected_faces"] = img["detected_faces"]
              logger.debug("Queueing filename: '%s' items: %s",
                           fname, list(feed_dict.keys()))
              in_queue.put(feed_dict)
          logger.debug("Sending EOF to filter queue")
          in_queue.put("EOF")
  
      def load_aligned_face(self):
 
</s> remove 
        if self._model.command_line_arguments.warp_to_landmarks:
            logger.debug("Adding landmarks to training opts dict")
            retval["landmarks"] = alignments.landmarks
 </s> add         if (any(version == 1.0 for version in alignments.versions.values())
                and self._config["centering"] != "legacy"):
            logger.warning("You are using legacy extracted faces but have selected '%s' "
                           "centering which is incompatible. Switching centering to 'legacy'",
                           self._config["centering"])
            self._config["centering"] = "legacy"
            self._model.config["centering"] = "legacy"
        retval = dict(aligned_faces=alignments.aligned_faces,
                      versions=alignments.versions) </s> remove     def check(self, detected_face):
        """ Check the extracted Face """
 </s> add     def check(self, image, detected_face):
        """ Check the extracted Face

        Parameters
        ----------
        image: :class:`numpy.ndarray`
            The original frame that contains the face to be checked
        detected_face: :class:`lib.align.DetectedFace`
            The detected face object that contains the face to be checked

        Returns
        -------
        bool
            ``True`` if the face matches a filter otherwise ``False``
        """
 </s> remove         """ Override the parent :func:`~lib.alignments.Alignments._load` to handle skip existing
 </s> add         """ Override the parent :func:`~lib.align.Alignments._load` to handle skip existing </s> remove     @staticmethod
    def convert_dfl_alignment(dfl_alignments, f_hash, alignments):
        """ Add Deep Face Lab Alignments to alignments in Faceswap format """
        sourcefile = dfl_alignments["source_filename"]
        left, top, right, bottom = dfl_alignments["source_rect"]
        alignment = {"x": left,
                     "w": right - left,
                     "y": top,
                     "h": bottom - top,
                     "hash": f_hash,
                     "landmarks_xy": np.array(dfl_alignments["source_landmarks"], dtype="float32")}
        logger.trace("Adding alignment: (frame: '%s', alignment: %s", sourcefile, alignment)
        alignments.setdefault(sourcefile, dict()).setdefault("faces", []).append(alignment)


class Draw():
    """ Draw Alignments on passed in images """
    def __init__(self, alignments, arguments):
        logger.debug("Initializing %s: (arguments: %s)", self.__class__.__name__, arguments)
        self.arguments = arguments
        self.alignments = alignments
        self.frames = Frames(arguments.frames_dir)
        self.output_folder = self.set_output()
        self.extracted_faces = None
        logger.debug("Initialized %s", self.__class__.__name__)
 </s> add         Returns
        -------
        str
            Full path to the output folder </s> remove         for frame in tqdm(self.frames.file_list_sorted, desc="Drawing landmarks"):
 </s> add         for frame in tqdm(self._frames.file_list_sorted, desc="Drawing landmarks"):
            feed_dict = ExtractMedia(fname, img["image"], detected_faces=img.get("detected_faces"))
            logger.debug("Queueing filename: '%s' items: %s", fname, feed_dict)

          """ queue images for detection and alignment """
          in_queue = extractor.input_queue
          for fname, img in self.filters.items():
              logger.debug("Adding to filter queue: '%s' (%s)", fname, img["type"])
            feed_dict = ExtractMedia(fname, img["image"], detected_faces=img.get("detected_faces"))
            logger.debug("Queueing filename: '%s' items: %s", fname, feed_dict)
            feed_dict = ExtractMedia(fname, img["image"], detected_faces=img.get("detected_faces"))
            logger.debug("Queueing filename: '%s' items: %s", fname, feed_dict)
            feed_dict = ExtractMedia(fname, img["image"], detected_faces=img.get("detected_faces"))
            logger.debug("Queueing filename: '%s' items: %s", fname, feed_dict)
            feed_dict = ExtractMedia(fname, img["image"], detected_faces=img.get("detected_faces"))
            logger.debug("Queueing filename: '%s' items: %s", fname, feed_dict)
            feed_dict = ExtractMedia(fname, img["image"], detected_faces=img.get("detected_faces"))
            logger.debug("Queueing filename: '%s' items: %s", fname, feed_dict)
              in_queue.put(feed_dict)
          logger.debug("Sending EOF to filter queue")
          in_queue.put("EOF")
  
      def load_aligned_face(self):
keep keep keep keep replace replace replace replace replace keep keep keep keep keep
 Extract - Increase area and move centering (#1095)

* Extract
  - Implement aligner re-feeding
  - Add extract type to pipeline.ExtractMedia
  - Add pose annotation to debug
* Convert
  - implement centering
  - remove usage of feed and reference face properties
  - Remove distributed option from convert
  - Force update of alignments file on legacy receive
* Train
  - Resize preview image to model output size
  - Force legacy centering if centering does not exist in model's state file
  - Enable training on legacy face sets

* Alignments Tool
  - Update draw to include head/pose
  - Remove DFL drop + linting
  - Remove remove-frames job
  - remove align-eyes option
  - Update legacy masks to new extract type
  - Exit if attempting to merge version 1.0 alignments files with version 2.0 alignments files
  - Re-generate thumbnails on legacy upgrade
* Mask Tool
  - Update for new extract + bugfix full frame
* Manual Tool
  - Update to new extraction method
   - Disable legacy alignments,
   - extract box bugfix
   - extract faces - size to 512 and center on head
* Preview Tool
  - Display based on model centering
* Sort Tool
  - Use alignments for sort by face

* lib.aligner
  - Add Pose Class
  - Add AlignedFace Class
  - center _MEAN_FACE on x
  - Add meta information with versioning to alignments file
  - lib.aligner.get_align_matrix to use landmarks not face
  - Refactor aligned faces in lib.faces_detect
* lib.logger
  - larger file log padding
* lib.config
  - Fix global changeable_items
* lib.face_filter
  - Use new extracted face images
* lib.image
  - bump thumbnail default size to 96px 
lib/face_filter.py