mirror of
https://github.com/deepfakes/faceswap
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03f5c671bc
* Remove PlaidML reference from readme files * Remove AMD option from installers * remove amd requirements and update setup.py * remove plaidml test from CI workflow * gpustats: remove plaidml backend * plaid removals: - faceswap.py - python version check - setup.cfg - plaidml typing ignore - lib.keras_utils - All plaid code - lib.launcher.py - All plaidml checks and configuration * remove tf2.2 specific code from GUI event reader * lib.model - remove all plaidml implementations * plugins.extract - remove plaidml code * plugins.train remove plaidml code * lib.convert - remove plaidml code * tools.model: remove plaidml code * Remove plaidML tests from unit tests * remove plaidml_utils and docsting cleanups * Remove plaidML refs from configs * fix keras imports
140 lines
6.3 KiB
Python
140 lines
6.3 KiB
Python
#!/usr/bin/env python3
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""" Default configurations for extract """
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import gettext
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import logging
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import os
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from lib.config import FaceswapConfig
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# LOCALES
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_LANG = gettext.translation("plugins.extract._config", localedir="locales", fallback=True)
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_ = _LANG.gettext
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logger = logging.getLogger(__name__)
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class Config(FaceswapConfig):
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""" Config File for Extraction """
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def set_defaults(self) -> None:
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""" Set the default values for config """
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logger.debug("Setting defaults")
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self.set_globals()
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self._defaults_from_plugin(os.path.dirname(__file__))
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def set_globals(self) -> None:
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"""
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Set the global options for extract
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"""
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logger.debug("Setting global config")
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section = "global"
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self.add_section(section, _("Options that apply to all extraction plugins"))
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self.add_item(
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section=section,
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title="allow_growth",
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datatype=bool,
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default=False,
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group=_("settings"),
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info=_("Enable the Tensorflow GPU `allow_growth` configuration option. "
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"This option prevents Tensorflow from allocating all of the GPU VRAM at launch "
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"but can lead to higher VRAM fragmentation and slower performance. Should only "
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"be enabled if you are having problems running extraction."))
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self.add_item(
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section=section,
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title="aligner_min_scale",
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datatype=float,
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min_max=(0.0, 1.0),
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rounding=2,
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default=0.07,
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group=_("filters"),
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info=_("Filters out faces below this size. This is a multiplier of the minimum "
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"dimension of the frame (i.e. 1280x720 = 720). If the original face extract "
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"box is smaller than the minimum dimension times this multiplier, it is "
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"considered a false positive and discarded. Faces which are found to be "
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"unusually smaller than the frame tend to be misaligned images, except in "
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"extreme long-shots. These can be usually be safely discarded."))
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self.add_item(
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section=section,
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title="aligner_max_scale",
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datatype=float,
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min_max=(0.0, 10.0),
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rounding=2,
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default=2.00,
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group=_("filters"),
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info=_("Filters out faces above this size. This is a multiplier of the minimum "
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"dimension of the frame (i.e. 1280x720 = 720). If the original face extract "
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"box is larger than the minimum dimension times this multiplier, it is "
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"considered a false positive and discarded. Faces which are found to be "
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"unusually larger than the frame tend to be misaligned images except in "
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"extreme close-ups. These can be usually be safely discarded."))
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self.add_item(
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section=section,
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title="aligner_distance",
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datatype=float,
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min_max=(0.0, 45.0),
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rounding=1,
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default=22.5,
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group=_("filters"),
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info=_("Filters out faces who's landmarks are above this distance from an 'average' "
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"face. Values above 15 tend to be fairly safe. Values above 10 will remove "
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"more false positives, but may also filter out some faces at extreme angles."))
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self.add_item(
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section=section,
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title="aligner_roll",
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datatype=float,
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min_max=(0.0, 90.0),
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rounding=1,
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default=45.0,
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group=_("filters"),
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info=_("Filters out faces who's calculated roll is greater than zero +/- this value "
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"in degrees. Aligned faces should have a roll value close to zero. Values that "
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"are a significant distance from 0 degrees tend to be misaligned images. These "
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"can usually be safely disgarded."))
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self.add_item(
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section=section,
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title="aligner_features",
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datatype=bool,
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default=True,
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group=_("filters"),
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info=_("Filters out faces where the lowest point of the aligned face's eye or eyebrow "
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"is lower than the highest point of the aligned face's mouth. Any faces where "
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"this occurs are misaligned and can be safely disgarded."))
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self.add_item(
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section=section,
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title="filter_refeed",
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datatype=bool,
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default=True,
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group=_("filters"),
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info=_("If enabled, and 're-feed' has been selected for extraction, then interim "
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"alignments will be filtered prior to averaging the final landmarks. This can "
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"help improve the final alignments by removing any obvious misaligns from the "
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"interim results, and may also help pick up difficult alignments. If disabled, "
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"then all re-feed results will be averaged."))
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self.add_item(
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section=section,
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title="save_filtered",
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datatype=bool,
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default=False,
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group=_("filters"),
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info=_("If enabled, saves any filtered out images into a sub-folder during the "
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"extraction process. If disabled, filtered faces are deleted. Note: The faces "
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"will always be filtered out of the alignments file, regardless of whether you "
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"keep the faces or not."))
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self.add_item(
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section=section,
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title="realign_refeeds",
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datatype=bool,
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default=True,
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group=_("re-align"),
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info=_("If enabled, and 're-align' has been selected for extraction, then all re-feed "
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"iterations are re-aligned. If disabled, then only the final averaged output "
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"from re-feed will be re-aligned."))
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self.add_item(
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section=section,
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title="filter_realign",
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datatype=bool,
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default=True,
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group=_("re-align"),
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info=_("If enabled, and 're-align' has been selected for extraction, then any "
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"alignments which would be filtered out will not be re-aligned."))
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