                                         filename,
                                         output_shape=output_shape): filename
                         for filename in filenames}
          logger.debug("Succesfully submitted %s items to executor", len(filenames))
          for future in futures.as_completed(read_hashes):
              retval = (read_hashes[future],
                        *future.result()) if output_shape else (read_hashes[future], future.result())
              logger.trace("Yielding: %s", retval)
              yield retval
  
  
  def encode_image_with_hash(image, extension):
 
</s> remove         read_hashes = {executor.submit(read_image_hash,
                                       filename,
                                       output_shape=output_shape): filename
                       for filename in filenames}
 </s> add         read_meta = {executor.submit(read_image_meta, filename): filename
                     for filename in filenames} </s> remove def encode_image_with_hash(image, extension):
    """ Encode an image, and get the encoded image back with its `sha1` hash.
 </s> add def encode_image(image, extension, metadata=None):
    """ Encode an image. </s> remove             image_read = read_image(filename, raise_error=False, with_hash=False)
 </s> add             image_read = read_image(filename, raise_error=False) </s> remove             image_read = read_image(filename, raise_error=False, with_hash=True)
 </s> add             image_read = read_image(filename, raise_error=False, with_metadata=True) </s> remove                                      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
 </s> add                                      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 future in futures.as_completed(read_meta):
            retval = (read_meta[future], future.result())
                                         filename,
                                         output_shape=output_shape): filename
                         for filename in filenames}
          logger.debug("Succesfully submitted %s items to executor", len(filenames))
        for future in futures.as_completed(read_meta):
            retval = (read_meta[future], future.result())
        for future in futures.as_completed(read_meta):
            retval = (read_meta[future], future.result())
        for future in futures.as_completed(read_meta):
            retval = (read_meta[future], future.result())
              logger.trace("Yielding: %s", retval)
              yield retval
  
  
  def encode_image_with_hash(image, extension):
keep keep keep keep 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 
lib/image.py