          value of which is a `dict` of {**filename** (`str`): :class:`bytes`} which is a zipped \
          mouth mask.
  
      config: dict
          The configuration `dict` generated from :file:`config.train.ini` containing the trainer \
          plugin configuration options.
      """
      def __init__(self, model_input_size, model_output_shapes, coverage_ratio, augment_color,
                   no_flip, warp_to_landmarks, alignments, config):
          logger.debug("Initializing %s: (model_input_size: %s, model_output_shapes: %s, "
 
</s> remove         value of which is a `dict` of {**filename** (`str`): :class:`lib.faces_detect.Mask`}.
 </s> add         value of which is a `dict` of {**filename** (`str`): :class:`lib.align.Mask`}. </s> remove         * **landmarks** (`dict`, `optional`). Required if :attr:`warp_to_landmarks` is \
        ``True``. Returning dictionary has a key of **side** (`str`) the value of which is a \
        `dict` of {**filename** (`str`): **68 point landmarks** (:class:`numpy.ndarray`)}.
 </s> add         * **aligned_faces** (`dict`). Contains the aligned face information. Returning dictionary \
        has a key of **side** (`str`) the value of which is a `dict` of {**filename** (`str`): \
        :class:`lib.align.AlignedFace`}.

        * **versions** (`dict`). The Alignments file versions that the extracted faces originated \
        from for each key of **side** (`str`). Version 1.0 will be a legacy extract. Anything \
        above this will be a full-face extract </s> remove         A dictionary containing landmarks and masks if these are required for training:
 </s> add         A dictionary containing aligned face information and masks if these are required for
        training: </s> remove         A dictionary containing landmarks and masks if these are required for training for each
        side
 </s> add         A dictionary containing aligned face data, extract version information and masks if these
        are required for training for each side </s> remove     def __init__(self, output_size, coverage_ratio, draw_transparent, pre_encode,
 </s> add     def __init__(self, output_size, coverage_ratio, centering, draw_transparent, pre_encode,
        The configuration `dict` generated from :file:`config.train.ini` containing the trainer
          value of which is a `dict` of {**filename** (`str`): :class:`bytes`} which is a zipped \
          mouth mask.
  
      config: dict
        The configuration `dict` generated from :file:`config.train.ini` containing the trainer
          plugin configuration options.
      """
      def __init__(self, model_input_size, model_output_shapes, coverage_ratio, augment_color,
                   no_flip, warp_to_landmarks, alignments, config):
          logger.debug("Initializing %s: (model_input_size: %s, model_output_shapes: %s, "
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 
lib/training_data.py