                  face.thumbnail = generate_thumbnail(face.aligned.face, size=96, quality=60)
                  self._alignments.data[filename]["faces"][idx] = face.to_alignment()
              face_count += 1
          return face_count
  
      def _select_valid_faces(self, frame, image):
          """ Return the aligned faces from a frame that meet the selection criteria,
  
          Parameters
 
</s> remove             output = "{}_{}{}".format(frame_name, str(idx), extension)
            if self._arguments.large:
                self._frames.save_image(self._faces_dir, output, face.aligned.face)
            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
 </s> add             output = "{}_{}.png".format(frame_name, str(idx))
            meta = dict(alignments=face.to_png_meta(),
                        source=dict(alignments_version=self._alignments.version,
                                    original_filename=output,
                                    face_index=idx,
                                    source_filename=filename,
                                    source_is_video=self._frames.is_video))
            self._saver.save(output, encode_image(face.aligned.face, ".png", metadata=meta))
            if not self._arguments.large and self._is_legacy:
                face.thumbnail = generate_thumbnail(face.aligned.face, size=96, quality=60)
                self._alignments.data[filename]["faces"][idx] = face.to_alignment() </s> remove         extension = ".png"
 </s> add  </s> remove class Merge():  # pylint:disable=too-few-public-methods
    """ Merge multiple alignments files into one.

    Parameters
    ----------
    alignments: :class:`tools.lib_alignments.media.AlignmentData`
        The alignments data loaded from an alignments file for this rename job
    arguments: :class:`argparse.Namespace`
        The :mod:`argparse` arguments as passed in from :mod:`tools.py`
    """
    def __init__(self, alignments, arguments):
        self._alignments = alignments
        self._check_versions()
        self._faces = self._get_faces(arguments)
        self._final_alignments = alignments[0]
        self._process_alignments = alignments[1:]
        self._hashes_to_frame = None

    def _check_versions(self):
        """ Ensure all alignments files are compatible versions. If not, exit with error. """
        versions = [al.version for al in self._alignments]
        logger.debug(versions)
        if any(vers < 2.0 for vers in versions) and any(vers >= 2.0 for vers in versions):
            logger.error("You have selected incompatible alignments files for merging. You cannot "
                         "merge alignments files for legacy extracted faces with aligments files "
                         "for full-head extracted faces.")
            logger.info("You can update legacy alignments files by using the Extract job in the "
                        "Alignments tool to re-extract the faces in full-head format.")
            sys.exit(0)

    @staticmethod
    def _get_faces(arguments):
        """ If faces argument is specified, load the faces folder otherwise return ``None``.

        Parameters
        ----------
        arguments: :class:`argparse.Namespace`
            The :mod:`argparse` arguments as passed in from :mod:`tools.py`

        Returns
        -------
        :class:`tools.alignments.media.Faces` or ``None``
            The faces object or ``None`` if not faces folder specified
        """
        if not hasattr(arguments, "faces_dir") or not arguments.faces_dir:
            return None
        return Faces(arguments.faces_dir)

    def process(self):
        """Run the alignments file merging process. """
        logger.info("[MERGE ALIGNMENTS]")  # Tidy up cli output
        if self._faces is not None:
            self._remove_faces()
        self._hashes_to_frame = self._final_alignments.hashes_to_frame
        skip_count = 0
        merge_count = 0
        total_count = sum([alignments.frames_count for alignments in self._process_alignments])

        with tqdm(desc="Merging Alignments", total=total_count) as pbar:
            for alignments in self._process_alignments:
                for _, src_alignments, _, frame in alignments.yield_faces():
                    for idx, alignment in enumerate(src_alignments):
                        if not alignment.get("hash", None):
                            logger.warning("Alignment '%s':%s has no Hash! Skipping", frame, idx)
                            skip_count += 1
                            continue
                        if self._check_exists(frame, alignment, idx):
                            skip_count += 1
                            continue
                        self._merge_alignment(frame, alignment, idx)
                        merge_count += 1
                    pbar.update(1)
        logger.info("Alignments Merged: %s", merge_count)
        logger.info("Alignments Skipped: %s", skip_count)
        if merge_count != 0:
            self._set_destination_filename()
            self._final_alignments.save()

    def _remove_faces(self):
        """ Removes faces from the alignments file if a faces folder has been provided and the
        faces do not exist within each alignments file. """
        face_hashes = list(self._faces.items.keys())
        del_faces_count = 0
        del_frames_count = 0
        if not face_hashes:
            logger.error("No face hashes. This would remove all faces from your alignments file.")
            return
        for alignments in tqdm(self._alignments, desc="Filtering out faces"):
            pre_face_count = alignments.faces_count
            pre_frames_count = alignments.frames_count
            alignments.filter_hashes(face_hashes, filter_out=False)
            # Remove frames with no faces
            frames = list(alignments.data.keys())
            for frame in frames:
                if not alignments.frame_has_faces(frame):
                    del alignments.data[frame]
            post_face_count = alignments.faces_count
            post_frames_count = alignments.frames_count
            removed_faces = pre_face_count - post_face_count
            removed_frames = pre_frames_count - post_frames_count
            del_faces_count += removed_faces
            del_frames_count += removed_frames
            logger.verbose("Removed %s faces and %s frames from %s",
                           removed_faces, removed_frames, os.path.basename(alignments.file))
        logger.info("Total removed - faces: %s, frames: %s", del_faces_count, del_frames_count)

    def _check_exists(self, frame, alignment, index):
        """ Remove duplicate faces from the alignments file when an instance of the face already
        exists.

        Parameters
        ----------
        frame: str
            The frame name for the current frame being processed
        alignment: dict
            The alignment dictionary for the current face in the frame
        index: int
            The face index for the current face in the frame

        Returns
        -------
        bool
            ``True`` if the face has been already been seen, otherwise ``False``
        """
        existing_frame = self._hashes_to_frame.get(alignment["hash"], None)
        if not existing_frame:
            return False
        if frame in existing_frame.keys():
            logger.verbose("Face '%s': %s already exists in destination at position %s. "
                           "Skipping", frame, index, existing_frame[frame])
        elif frame not in existing_frame.keys():
            logger.verbose("Face '%s': %s exists in destination as: %s. "
                           "Skipping", frame, index, existing_frame)
        return True

    def _merge_alignment(self, frame, alignment, idx):
        """ Merge the source alignment into the destination final alignments dictionary

        Parameters
        ----------
        frame: str
            The frame name for the current frame being processed
        alignment: dict
            The alignment dictionary for the current face in the frame
        index: int
            The face index for the current face in the frame
        """
        logger.debug("Merging alignment: (frame: %s, src_idx: %s, hash: %s)",
                     frame, idx, alignment["hash"])
        self._hashes_to_frame.setdefault(alignment["hash"], dict())[frame] = idx
        self._final_alignments.data.setdefault(frame,
                                               dict()).setdefault("faces", []).append(alignment)

    def _set_destination_filename(self):
        """ Set the destination filename """
        folder = os.path.split(self._final_alignments.file)[0]
        ext = os.path.splitext(self._final_alignments.file)[1]
        now = datetime.now().strftime("%Y%m%d_%H%M%S")
        filename = os.path.join(folder, "alignments_merged_{}{}".format(now, ext))
        logger.debug("Output set to: '%s'", filename)
        self._final_alignments.set_filename(filename)


 </s> add  </s> remove         """ For each frame save out the faces and update the face hash back to alignments
 </s> add         """ For each frame save out the faces </s> remove             frames = self._alignments.hashes_to_frame[hsh]
            if len(frames) > 1:
                # Filter the output by filename in case of multiple frames with the same face
                logger.debug("Filtering multiple hashes to current filename: (filename: '%s', "
                             "frames: %s", filename, frames)
                lookup = os.path.splitext(os.path.basename(filename))[0]
                frames = {k: v
                          for k, v in frames.items()
                          if lookup.startswith(os.path.splitext(k)[0])}
                logger.debug("Filtered: (filename: '%s', frame: '%s')", filename, frames)

            for frame, idx in frames.items():
                self._counts["face"] += 1
                alignment = self._alignments.get_faces_in_frame(frame)[idx]
                if self._check_for_missing(frame, idx, alignment):
                    continue
                detected_face = self._get_detected_face(alignment)
                if self._update_type == "output":
                    detected_face.image = image
                    self._save(frame, idx, detected_face)
                else:
                    queue.put(ExtractMedia(filename, image, detected_faces=[detected_face]))
                    self._counts["update"] += 1
 </s> add             if self._check_for_missing(frame_name, face_index, alignment):
                continue

            detected_face = self._get_detected_face(alignment)
            if self._update_type == "output":
                detected_face.image = image
                self._save(frame_name, face_index, detected_face)
            else:
                media = ExtractMedia(filename, image, detected_faces=[detected_face])
                setattr(media, "mask_tool_face_info", metadata["source"])  # TODO formalize
                queue.put(media)
                self._counts["update"] += 1
        self._saver.close()
                  face.thumbnail = generate_thumbnail(face.aligned.face, size=96, quality=60)
                  self._alignments.data[filename]["faces"][idx] = face.to_alignment()
              face_count += 1
        self._saver.close()
          return face_count
  
      def _select_valid_faces(self, frame, image):
          """ Return the aligned faces from a frame that meet the selection criteria,
  
          Parameters
keep keep add keep 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 
tools/alignments/jobs.py