          min_max=(2, 16),
          group="evaluation"),
      zoom_amount=dict(
          default=5,
          info="Percentage amount to randomly zoom each training image in and out.",
          datatype=int,
          rounding=1,
          min_max=(0, 25),
 
</s> remove     scaling: float, optional
        The amount to scale the final preview image by. Default: `1.0`
 </s> add  </s> remove     def __init__(self, model: "ModelBase", coverage_ratio: float) -> None:
        logger.debug("Initializing %s: model: '%s', coverage_ratio: %s)",
                     self.__class__.__name__, model, coverage_ratio)
 </s> add     def __init__(self,
                 model: "ModelBase",
                 coverage_ratio: float,
                 mask_opacity: int,
                 mask_color: str) -> None:
        logger.debug("Initializing %s: model: '%s', coverage_ratio: %s, mask_opacity: %s, "
                     "mask_color: %s)",
                     self.__class__.__name__, model, coverage_ratio, mask_opacity, mask_color) </s> remove     config: :class:`lib.config.FaceswapConfig`
 </s> add     config: dict
    mask_opacity=dict(
        default=30,
        info="The opacity of the mask overlay in the training preview. Lower values are more "
             "transparent.",
        datatype=int,
        rounding=2,
        min_max=(0, 100),
        group="evaluation"),
    mask_color=dict(
        default="#ff0000",
        choices="colorchooser",
        info="The RGB hex color to use for the mask overlay in the training preview.",
        datatype=str,
        group="evaluation"),
          min_max=(2, 16),
          group="evaluation"),
    mask_opacity=dict(
        default=30,
        info="The opacity of the mask overlay in the training preview. Lower values are more "
             "transparent.",
        datatype=int,
        rounding=2,
        min_max=(0, 100),
        group="evaluation"),
    mask_color=dict(
        default="#ff0000",
        choices="colorchooser",
        info="The RGB hex color to use for the mask overlay in the training preview.",
        datatype=str,
        group="evaluation"),
      zoom_amount=dict(
          default=5,
          info="Percentage amount to randomly zoom each training image in and out.",
          datatype=int,
          rounding=1,
          min_max=(0, 25),
keep add keep keep keep keep keep keep
 Preview - Allow mask color/opacity configuration
  - typing: lib.config
  - docs: lib.config
  - bugfix: popup_configure - keep assets on top 
plugins/train/trainer/original_defaults.py