              opts=("-m", "--model-dir"),
              action=DirFullPaths,
              dest="model_dir",
              required=True,
              group="data",
              help="Model directory. The directory containing the trained model you wish to use "
                   "for conversion."))
          argument_list.append(dict(
              opts=("-c", "--color-adjustment"),
              action=Radio,
              type=str.lower,
              dest="color_adjustment",
 
</s> remove             group="data",
 </s> add             group=_("data"), </s> remove             help="Model directory. A directory containing the trained model you wish to process."))
 </s> add             help=_("Model directory. A directory containing the trained model you wish to "
                   "process."))) </s> remove         argument_list.append({"opts": ("-m", "--model-dir"),
                              "action": DirFullPaths,
                              "dest": "model_dir",
                              "required": True,
                              "help": "Model directory. A directory containing the model "
                                      "you wish to restore from backup."})
 </s> add         argument_list.append(dict(
            opts=("-m", "--model-dir"),
            action=DirFullPaths,
            dest="model_dir",
            required=True,
            help=_("Model directory. A directory containing the model you wish to restore from "
                   "backup."))) </s> remove             group="model",
            help="Model directory. This is where the training data will be stored. You should "
                 "always specify a new folder for new models. If starting a new model, select "
                 "either an empty folder, or a folder which does not exist (which will be "
                 "created). If continuing to train an existing model, specify the location of "
                 "the existing model."))
 </s> add             group=_("model"),
            help=_("Model directory. This is where the training data will be stored. You should "
                   "always specify a new folder for new models. If starting a new model, select "
                   "either an empty folder, or a folder which does not exist (which will be "
                   "created). If continuing to train an existing model, specify the location of "
                   "the existing model."))) </s> remove             group="data",
            help="Only required if converting from images to video. Provide The original video "
                 "that the source frames were extracted from (for extracting the fps and "
                 "audio)."))
 </s> add             group=_("Data"),
            help=_("Only required if converting from images to video. Provide The original video "
                   "that the source frames were extracted from (for extracting the fps and "
                   "audio).")))
            group=_("Data"),
            help=_("Model directory. The directory containing the trained model you wish to use "
                   "for conversion.")))
              opts=("-m", "--model-dir"),
              action=DirFullPaths,
              dest="model_dir",
              required=True,
            group=_("Data"),
            help=_("Model directory. The directory containing the trained model you wish to use "
                   "for conversion.")))
            group=_("Data"),
            help=_("Model directory. The directory containing the trained model you wish to use "
                   "for conversion.")))
            group=_("Data"),
            help=_("Model directory. The directory containing the trained model you wish to use "
                   "for conversion.")))
          argument_list.append(dict(
              opts=("-c", "--color-adjustment"),
              action=Radio,
              type=str.lower,
              dest="color_adjustment",
keep keep keep keep replace replace replace keep keep keep keep keep
 Add Locale support for cli arguments 
lib/cli/args.py