      def sort_face(self):
          """ Sort by identity similarity """
          logger.info("Sorting by identity similarity...")
  
          # TODO This should be set in init
          self._loader = ImagesLoader(self.args.input_dir)
  
          filenames = []
          preds = np.empty((self._loader.count, 512), dtype="float32")
          for idx, (filename, image) in enumerate(tqdm(self._loader.load(),
                                                       desc="Classifying Faces...",
                                                       total=self._loader.count)):
 
</s> remove         preds = np.empty((self._loader.count, 512), dtype="float32")
        for idx, (filename, image) in enumerate(tqdm(self._loader.load(),
                                                     desc="Classifying Faces...",
                                                     total=self._loader.count)):
 </s> add         preds = []
        no_hash = 0
        for filename, image, hsh in tqdm(self._loader.load(),
                                         desc="Classifying Faces...",
                                         total=self._loader.count):
            if self._alignments is not None and self._alignments.version != 1.0:
                face = self._alignments.hashes_to_alignment.get(hsh)
                if face:
                    image = AlignedFace(face["landmarks_xy"],
                                        image=image,
                                        centering="legacy",
                                        size=self._vgg_face.input_size,
                                        is_aligned=True).face
                elif image.shape[0] != image.shape[1]:
                    logger.warning("Skipping image '%s' as it is not square (probably not a "
                                   "face)", filename)
                    continue
                else:  # Center crop the image and add count to warning count
                    center = image.shape[0] // 2
                    crop = slice(center - int(center * ratio), center + int(center * ratio))
                    image = image[crop, crop, :]
                    no_hash += 1
 </s> remove             preds[idx] = self.vgg_face.predict(image)
 </s> add             preds.append(self._vgg_face.predict(image)) </s> remove         indices = self.vgg_face.sorted_similarity(preds, method="ward")
 </s> add         indices = self._vgg_face.sorted_similarity(np.array(preds), method="ward") </s> remove         self.vgg_face = None
        # TODO set this as ImagesLoader in init. Need to move all processes to use it
 </s> add         self._vgg_face = None
        # TODO set this as FacesLoader in init. Need to move all processes to use it
        self._loader = FacesLoader(self._args.input_dir)  # TODO This should be set in init
        ratio = _EXTRACT_RATIOS["legacy"] / _EXTRACT_RATIOS["head"]
      def sort_face(self):
          """ Sort by identity similarity """
          logger.info("Sorting by identity similarity...")
  
        self._loader = FacesLoader(self._args.input_dir)  # TODO This should be set in init
        ratio = _EXTRACT_RATIOS["legacy"] / _EXTRACT_RATIOS["head"]
        self._loader = FacesLoader(self._args.input_dir)  # TODO This should be set in init
        ratio = _EXTRACT_RATIOS["legacy"] / _EXTRACT_RATIOS["head"]
        self._loader = FacesLoader(self._args.input_dir)  # TODO This should be set in init
        ratio = _EXTRACT_RATIOS["legacy"] / _EXTRACT_RATIOS["head"]
          filenames = []
          preds = np.empty((self._loader.count, 512), dtype="float32")
          for idx, (filename, image) in enumerate(tqdm(self._loader.load(),
                                                       desc="Classifying Faces...",
                                                       total=self._loader.count)):
keep keep keep keep 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 
tools/sort/sort.py