          for side, detected_faces in self._detected_faces.items():
              ret_side = dict()
              size = get_centered_size("legacy" if self._alignments_version[side] == 1.0 else "head",
                                       self._config["centering"],
                                       input_sizes[side])
              for fhash, face in detected_faces.items():
                  face.aligned = AlignedFace(face.landmarks_xy,
                                             centering=self._config["centering"],
                                             size=size,
                                             is_aligned=True)
                  for filename in self._hash_to_filenames(side, fhash):
                      ret_side[filename] = face.aligned
              retval[side] = ret_side
          return retval
  
      # Get masks
      @property
      def masks(self):
 
</s> remove             ret_side = dict()
 </s> add             retval[side] = dict() </s> remove             filename as key and :class:`lib.faces.detected_face.AlignedFace` object as value.
 </s> add             filename as key and :class:`lib.align.AlignedFace` object as value. </s> remove             The face filenames as keys with the zip compressed mask as value.
 </s> add             The face filenames as keys with the :func:`functools.partial` of the mask as value </s> remove         closest_hashes = [self._cache["nearest_landmarks"].get(filename) for filename in filenames]
        if None in closest_hashes:
 </s> add         closest_matches = [self._cache["nearest_landmarks"].get(filename)
                           for filename in filenames]
        if None in closest_matches:
                                     self._image_sizes[side])
            for filename, face in detected_faces.items():
                retval[side][filename] = AlignedFace(face.landmarks_xy,
                                                     centering=self._config["centering"],
                                                     size=size,
                                                     is_aligned=True)
        logger.debug("Loaded aligned faces: %s", {k: len(v) for k, v in retval.items()})
          for side, detected_faces in self._detected_faces.items():
              ret_side = dict()
              size = get_centered_size("legacy" if self._alignments_version[side] == 1.0 else "head",
                                       self._config["centering"],
                                     self._image_sizes[side])
            for filename, face in detected_faces.items():
                retval[side][filename] = AlignedFace(face.landmarks_xy,
                                                     centering=self._config["centering"],
                                                     size=size,
                                                     is_aligned=True)
        logger.debug("Loaded aligned faces: %s", {k: len(v) for k, v in retval.items()})
                                     self._image_sizes[side])
            for filename, face in detected_faces.items():
                retval[side][filename] = AlignedFace(face.landmarks_xy,
                                                     centering=self._config["centering"],
                                                     size=size,
                                                     is_aligned=True)
        logger.debug("Loaded aligned faces: %s", {k: len(v) for k, v in retval.items()})
                                     self._image_sizes[side])
            for filename, face in detected_faces.items():
                retval[side][filename] = AlignedFace(face.landmarks_xy,
                                                     centering=self._config["centering"],
                                                     size=size,
                                                     is_aligned=True)
        logger.debug("Loaded aligned faces: %s", {k: len(v) for k, v in retval.items()})
                                     self._image_sizes[side])
            for filename, face in detected_faces.items():
                retval[side][filename] = AlignedFace(face.landmarks_xy,
                                                     centering=self._config["centering"],
                                                     size=size,
                                                     is_aligned=True)
        logger.debug("Loaded aligned faces: %s", {k: len(v) for k, v in retval.items()})
                                     self._image_sizes[side])
            for filename, face in detected_faces.items():
                retval[side][filename] = AlignedFace(face.landmarks_xy,
                                                     centering=self._config["centering"],
                                                     size=size,
                                                     is_aligned=True)
        logger.debug("Loaded aligned faces: %s", {k: len(v) for k, v in retval.items()})
                                     self._image_sizes[side])
            for filename, face in detected_faces.items():
                retval[side][filename] = AlignedFace(face.landmarks_xy,
                                                     centering=self._config["centering"],
                                                     size=size,
                                                     is_aligned=True)
        logger.debug("Loaded aligned faces: %s", {k: len(v) for k, v in retval.items()})
                                     self._image_sizes[side])
            for filename, face in detected_faces.items():
                retval[side][filename] = AlignedFace(face.landmarks_xy,
                                                     centering=self._config["centering"],
                                                     size=size,
                                                     is_aligned=True)
        logger.debug("Loaded aligned faces: %s", {k: len(v) for k, v in retval.items()})
                                     self._image_sizes[side])
            for filename, face in detected_faces.items():
                retval[side][filename] = AlignedFace(face.landmarks_xy,
                                                     centering=self._config["centering"],
                                                     size=size,
                                                     is_aligned=True)
        logger.debug("Loaded aligned faces: %s", {k: len(v) for k, v in retval.items()})
                                     self._image_sizes[side])
            for filename, face in detected_faces.items():
                retval[side][filename] = AlignedFace(face.landmarks_xy,
                                                     centering=self._config["centering"],
                                                     size=size,
                                                     is_aligned=True)
        logger.debug("Loaded aligned faces: %s", {k: len(v) for k, v in retval.items()})
          return retval
  
      # Get masks
      @property
      def masks(self):
keep keep keep keep replace replace replace replace replace replace replace replace replace keep keep keep keep keep
 Update extracted faces to use PNG EXIF data (#1123)

Documentation
  - Update Usage.md, align.rst and image.rst
lib.image.py
  - read_image - Remove hash return, add metadata return
  - Remove read_image_hash functions
  - Add read_image_meta functios
  - Replace encode_image_with_hash with encode_image (to store metadata)
  - Add png meta reading and writing functions
  - Update Image Loaders/Savers to handle metadata rather than hashes
lib.training_data
  - Naming updates to remove references to hashes
lib.align.Alignments
  - Add versioning notes
  - Increment alignments version to 2.1
  - Deprecate hashing lookup functions
  - Replace filter_hashes with filter_faces
lib.align.detected_face
  - DetectedFace
    - Remove hash property
    - Add png header data serializing/deserializing functions
  - Mask
    - Add png header data serializing/deserializing functions
  - add update_legacy_png_header function to update png meta data
lib.cli.args - Deprecate alignments files for training
- plugins.train.trainer
  - Update alignments/mask code to read png header data
- scripts.convert
  - Aligned images folder - read data from png headers
- scripts.extract
  - Write png header information and no longer store hash of face
- tools.alignments
  - remove leftover-faces, merge and update-hashes jobs
  - Update jobs to use png meta data rather than hashes
- tools.manual
  - Update extract code to output png meta data and don't store hashes
  - Perform check on launch that tool is not pointing at a faces folder
tools.mask
  - Update to use png meta data
tools.sort
  - Update to use png meta data 
plugins/train/trainer/_base.py