              else:
                  output = os.path.join(self._faces_dir, output)
                  f_hash = self._extracted_faces.save_face_with_hash(output,
                                                                     extension,
                                                                     face.aligned_face)
                  self._alignments.data[filename]["faces"][idx]["hash"] = f_hash
              face_count += 1
          return face_count
  
      def _select_valid_faces(self, frame, image):
 
</s> remove                 self._frames.save_image(self._faces_dir, output, face.aligned_face)
 </s> add                 self._frames.save_image(self._faces_dir, output, face.aligned.face) </s> remove             if f_hash not in self.alignments.hashes_to_frame:
 </s> add             if f_hash not in self._alignments.hashes_to_frame: </s> remove 
    @staticmethod
    def align_eyes(face, image):
        """ Re-extract a face with the pupils forced to be absolutely horizontally aligned """
        umeyama_landmarks = face.aligned_landmarks
        left_eye_center = umeyama_landmarks[42:48].mean(axis=0)
        right_eye_center = umeyama_landmarks[36:42].mean(axis=0)
        d_y = right_eye_center[1] - left_eye_center[1]
        d_x = right_eye_center[0] - left_eye_center[0]
        theta = np.pi - np.arctan2(d_y, d_x)
        rot_cos = np.cos(theta)
        rot_sin = np.sin(theta)
        rotation_matrix = np.array([[rot_cos, -rot_sin, 0.],
                                    [rot_sin, rot_cos, 0.],
                                    [0., 0., 1.]])

        mat_umeyama = np.concatenate((face.aligned["matrix"], np.array([[0., 0., 1.]])), axis=0)
        corrected_mat = np.dot(rotation_matrix, mat_umeyama)
        face.aligned["matrix"] = corrected_mat[:2]
        face.aligned["face"] = AlignerExtract().transform(image,
                                                          face.aligned["matrix"],
                                                          face.aligned["size"],
                                                          int(face.aligned["size"] * 0.375) // 2)
        logger.trace("Adjusted matrix: %s", face.aligned["matrix"])
        return face
 </s> add  </s> remove             frame_idx = [(frame, idx)
                         for frame, idx in self.alignments.hashes_to_frame[f_hash].items()]
 </s> add             frame_idx = list(self._alignments.hashes_to_frame[f_hash].items())
                                                                   face.aligned.face)
                if self._is_legacy:  # Generate the new thumbnail and store new face data for save
                    face.thumbnail = generate_thumbnail(face.aligned.face, size=96, quality=60)
                    self._alignments.data[filename]["faces"][idx] = face.to_alignment()
              else:
                  output = os.path.join(self._faces_dir, output)
                  f_hash = self._extracted_faces.save_face_with_hash(output,
                                                                     extension,
                                                                   face.aligned.face)
                if self._is_legacy:  # Generate the new thumbnail and store new face data for save
                    face.thumbnail = generate_thumbnail(face.aligned.face, size=96, quality=60)
                    self._alignments.data[filename]["faces"][idx] = face.to_alignment()
                  self._alignments.data[filename]["faces"][idx]["hash"] = f_hash
              face_count += 1
          return face_count
  
      def _select_valid_faces(self, frame, image):
keep keep keep keep 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/alignments/jobs.py