                                        "enabled. Defaults to <input-B>/alignments.json if not "
                                        "provided."})
          argument_list.append({"opts": ("-m", "--model-dir"),
                                "action": DirFullPaths,
                                "dest": "model_dir",
                                "required": True,
                                "help": "Model directory. This is where the training data will be "
                                        "stored."})
          argument_list.append({"opts": ("-t", "--trainer"),
                                "action": Radio,
                                "type": str.lower,
                                "choices": PluginLoader.get_available_models(),
                                "default": PluginLoader.get_default_model(),
 
</s> remove         argument_list.append({"opts": ("-m", "--model-dir"),
 </s> add         argument_list.append({"opts": ("-tib", "--timelapse-input-B"), </s> remove         argument_list.append({"opts": ("-B", "--input-B"),
                              "action": DirFullPaths,
                              "dest": "input_b",
                              "required": True,
                              "help": "Input directory. A directory containing training images "
                                      "for face B."})
 </s> add  </s> remove         argument_list.append({"opts": ("-tia", "--timelapse-input-A"),
                              "action": DirFullPaths,
                              "dest": "timelapse_input_a",
                              "default": None,
                              "help": "For if you want a timelapse: "
                                      "The input folder for the timelapse. "
                                      "This folder should contain faces of A "
                                      "which will be converted for the "
                                      "timelapse. You must supply a "
                                      "--timelapse-output and a "
                                      "--timelapse-input-B parameter."})
        argument_list.append({"opts": ("-tib", "--timelapse-input-B"),
                              "action": DirFullPaths,
                              "dest": "timelapse_input_b",
                              "default": None,
                              "help": "For if you want a timelapse: "
                                      "The input folder for the timelapse. "
                                      "This folder should contain faces of B "
                                      "which will be converted for the "
                                      "timelapse. You must supply a "
                                      "--timelapse-output and a "
                                      "--timelapse-input-A parameter."})
        argument_list.append({"opts": ("-to", "--timelapse-output"),
                              "action": DirFullPaths,
                              "dest": "timelapse_output",
                              "default": None,
                              "help": "The output folder for the timelapse. "
                                      "If the input folders are supplied but "
                                      "no output folder, it will default to "
                                      "your model folder /timelapse/"})
 </s> add  </s> remove             section=section, title="dssim_loss", datatype=bool, default=True,
            info="Use DSSIM for Loss rather than Mean Absolute Error\n"
                 "May increase overall quality.")
        self.add_item(
            section=section, title="penalized_mask_loss", datatype=bool, default=True,
            info="If using a mask, This penalizes the loss for the masked area, to give higher "
                 "priority to the face area. \nShould increase overall quality and speed up "
                 "training. This should probably be left at True")
        logger.debug("Set global config")
 </s> add             section=section, title="coverage", datatype=float, default=68.75,
            min_max=(62.5, 100.0), rounding=2, fixed=True,
            info="How much of the extracted image to train on. A lower coverage will limit the model's "
                 "scope to a zoomed-in central area while higher amounts can include the entire face. "
                 "A trade-off exists between lower amounts given a bit more detail versus higher amounts "
                 "avoiding noticeable swap transitions. Sensible values to use are:"
                 "\n\t62.5%% spans from eyebrow to eyebrow."
                 "\n\t75.0%% spans from temple to temple."
                 "\n\t87.5%% spans from ear to ear."
                 "\n\t100.0%% is a mugshot.")
                              "dest": "timelapse_input_b",
                              "default": None,
                              "help": "For if you want a timelapse: "
                                      "The input folder for the timelapse. "
                                      "This folder should contain faces of B "
                                      "which will be converted for the "
                                      "timelapse. You must supply a "
                                      "--timelapse-output and a "
                                      "--timelapse-input-A parameter."})
                                        "enabled. Defaults to <input-B>/alignments.json if not "
                                        "provided."})
          argument_list.append({"opts": ("-m", "--model-dir"),
                                "action": DirFullPaths,
                              "dest": "timelapse_input_b",
                              "default": None,
                              "help": "For if you want a timelapse: "
                                      "The input folder for the timelapse. "
                                      "This folder should contain faces of B "
                                      "which will be converted for the "
                                      "timelapse. You must supply a "
                                      "--timelapse-output and a "
                                      "--timelapse-input-A parameter."})
                              "dest": "timelapse_input_b",
                              "default": None,
                              "help": "For if you want a timelapse: "
                                      "The input folder for the timelapse. "
                                      "This folder should contain faces of B "
                                      "which will be converted for the "
                                      "timelapse. You must supply a "
                                      "--timelapse-output and a "
                                      "--timelapse-input-A parameter."})
                              "dest": "timelapse_input_b",
                              "default": None,
                              "help": "For if you want a timelapse: "
                                      "The input folder for the timelapse. "
                                      "This folder should contain faces of B "
                                      "which will be converted for the "
                                      "timelapse. You must supply a "
                                      "--timelapse-output and a "
                                      "--timelapse-input-A parameter."})
                              "dest": "timelapse_input_b",
                              "default": None,
                              "help": "For if you want a timelapse: "
                                      "The input folder for the timelapse. "
                                      "This folder should contain faces of B "
                                      "which will be converted for the "
                                      "timelapse. You must supply a "
                                      "--timelapse-output and a "
                                      "--timelapse-input-A parameter."})
          argument_list.append({"opts": ("-t", "--trainer"),
                                "action": Radio,
                                "type": str.lower,
                                "choices": PluginLoader.get_available_models(),
                                "default": PluginLoader.get_default_model(),
keep keep keep keep replace replace replace replace keep keep keep keep keep
 documentation, pep8, style, clarity updates  - Prep for Segmentation (#812)

* documentation, pep8, style, clarity updates

* Update cli.py

* Update _config.py

remove extra mask and coverage

mask type as dropdown

* Update training_data.py

move coverage / LR to global
cut down on loss description

style change
losses working in PR

* simpler logging

* legacy update 
lib/cli.py