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plugins/train/model/realface_defaults.py
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torzdf
Faceswap 3 (#1516)
21 дек 2025, 05:45
Не верифицирован
21 дек 2025, 05:45
837bc2d
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#!/usr/bin/env python3 """ The default options for the faceswap Realface Model plugin. Defaults files should be named `<plugin_name>_defaults.py` Any qualifying items placed into this file will automatically get added to the relevant config .ini files within the faceswap/config folder and added to the relevant GUI settings page. The following variable should be defined: Parameters ---------- HELPTEXT: str A string describing what this plugin does Further plugin configuration options are assigned using: >>> <config_item> = ConfigItem(...) where <config_item> is the name of the configuration option to be added (lower-case, alpha-numeric + underscore only) and ConfigItem(...) is the [`~lib.config.objects.ConfigItem`] data for the option. See the docstring/ReadtheDocs documentation required parameters for the ConfigItem object. Items will be grouped together as per their `group` parameter, but otherwise will be processed in the order that they are added to this module. from lib.config import ConfigItem """ # pylint:disable=duplicate-code from lib.config import ConfigItem HELPTEXT = ( "An extra detailed variant of Original model.\n" "Incorporates ideas from Bryanlyon and inspiration from the Villain model.\n" "Requires about 6GB-8GB of VRAM (batchsize 8-16).\n" ) input_size = ConfigItem( datatype=int, default=64, group="size", info="Resolution (in pixels) of the input image to train on.\n" "BE AWARE Larger resolution will dramatically increase VRAM requirements.\n" "Higher resolutions may increase prediction accuracy, but does not effect the " "resulting output size.\nMust be between 64 and 128 and be divisible by 16.", rounding=16, min_max=(64, 128), fixed=True) output_size = ConfigItem( datatype=int, default=128, group="size", info="Output image resolution (in pixels).\nBe aware that larger resolution will " "increase VRAM requirements.\nNB: Must be between 64 and 256 and be divisible " "by 16.", rounding=16, min_max=(64, 256), fixed=True) dense_nodes = ConfigItem( datatype=int, default=1536, group="network", info="Number of nodes for decoder. Might affect your model's ability to learn in " "general.\nNote that: Lower values will affect the ability to predict " "details.", rounding=64, min_max=(768, 2048), fixed=True) complexity_encoder = ConfigItem( datatype=int, default=128, group="network", info="Encoder Convolution Layer Complexity. sensible ranges: 128 to 150.", rounding=4, min_max=(96, 160), fixed=True) complexity_decoder = ConfigItem( datatype=int, default=512, group="network", info="Decoder Complexity.", rounding=4, min_max=(512, 544), fixed=True)