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82 lines
3.8 KiB
Python
82 lines
3.8 KiB
Python
#!/usr/bin/env python3
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"""
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The default options for the faceswap Dfaker Model plugin.
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Defaults files should be named <plugin_name>_defaults.py
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Any items placed into this file will automatically get added to the relevant config .ini files
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within the faceswap/config folder.
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The following variables should be defined:
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_HELPTEXT: A string describing what this plugin does
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_DEFAULTS: A dictionary containing the options, defaults and meta information. The
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dictionary should be defined as:
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{<option_name>: {<metadata>}}
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<option_name> should always be lower text.
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<metadata> dictionary requirements are listed below.
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The following keys are expected for the _DEFAULTS <metadata> dict:
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datatype: [required] A python type class. This limits the type of data that can be
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provided in the .ini file and ensures that the value is returned in the
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correct type to faceswap. Valid datatypes are: <class 'int'>, <class 'float'>,
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<class 'str'>, <class 'bool'>.
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default: [required] The default value for this option.
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info: [required] A string describing what this option does.
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choices: [optional] If this option's datatype is of <class 'str'> then valid
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selections can be defined here. This validates the option and also enables
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a combobox / radio option in the GUI.
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gui_radio: [optional] If <choices> are defined, this indicates that the GUI should use
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radio buttons rather than a combobox to display this option.
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min_max: [partial] For <class 'int'> and <class 'float'> datatypes this is required
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otherwise it is ignored. Should be a tuple of min and max accepted values.
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This is used for controlling the GUI slider range. Values are not enforced.
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rounding: [partial] For <class 'int'> and <class 'float'> datatypes this is
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required otherwise it is ignored. Used for the GUI slider. For floats, this
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is the number of decimal places to display. For ints this is the step size.
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fixed: [optional] [train only]. Training configurations are fixed when the model is
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created, and then reloaded from the state file. Marking an item as fixed=False
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indicates that this value can be changed for existing models, and will override
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the value saved in the state file with the updated value in config. If not
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provided this will default to True.
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"""
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_HELPTEXT = ("A lightweight, high resolution Dfaker variant "
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"(Adapted from https://github.com/dfaker/df)")
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_DEFAULTS = dict(
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features=dict(
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default="best",
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info="Higher settings will allow learning more features such as tatoos, piercing and "
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"wrinkles.\nStrongly affects VRAM usage.",
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datatype=str,
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choices=["lowmem", "fair", "best"],
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group="settings",
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gui_radio=True,
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fixed=True,
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),
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details=dict(
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default="good",
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info="Defines detail fidelity. Lower setting can appear 'rugged' while 'good' might take "
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"a longer time to train.\nAffects VRAM usage.",
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datatype=str,
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choices=["fast", "good"],
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group="settings",
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gui_radio=True,
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fixed=True,
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),
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output_size=dict(
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default=256,
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info="Output image resolution (in pixels).\nBe aware that larger resolution will increase "
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"VRAM requirements.\nNB: Must be either 128, 256, or 384.",
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datatype=int,
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rounding=128,
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min_max=(128, 384),
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choices=[],
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group="settings",
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gui_radio=False,
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fixed=True,
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),
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)
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