mirror of
https://github.com/deepfakes/faceswap
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2d312a9db2
- Mask Tool - Typing + BiSeNet mask update fix - Alignments Tool - Auto search for alignments file
169 lines
8.5 KiB
Python
169 lines
8.5 KiB
Python
#!/usr/bin/env python3
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""" Command Line Arguments for tools """
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import sys
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import gettext
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from typing import Any, List, Dict
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from lib.cli.args import FaceSwapArgs
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from lib.cli.actions import DirOrFileFullPaths, DirFullPaths, FileFullPaths, Radio, Slider
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# LOCALES
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_LANG = gettext.translation("tools.alignments.cli", localedir="locales", fallback=True)
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_ = _LANG.gettext
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_HELPTEXT = _("This command lets you perform various tasks pertaining to an alignments file.")
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class AlignmentsArgs(FaceSwapArgs):
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""" Class to parse the command line arguments for Alignments tool """
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@staticmethod
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def get_info() -> str:
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""" Obtain command information.
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Returns
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-------
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str
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The help text for displaying in argparses help output
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"""
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return _("Alignments tool\nThis tool allows you to perform numerous actions on or using "
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"an alignments file against its corresponding faceset/frame source.")
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@staticmethod
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def get_argument_list() -> List[Dict[str, Any]]:
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""" Collect the argparse argument options.
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Returns
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-------
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dict
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The argparse command line options for processing by argparse
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"""
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frames_dir = _(" Must Pass in a frames folder/source video file (-fr).")
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faces_dir = _(" Must Pass in a faces folder (-fc).")
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frames_or_faces_dir = _(" Must Pass in either a frames folder/source video file OR a"
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"faces folder (-fr or -fc).")
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frames_and_faces_dir = _(" Must Pass in a frames folder/source video file AND a faces "
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"folder (-fr and -fc).")
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output_opts = _(" Use the output option (-o) to process results.")
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argument_list = []
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argument_list.append(dict(
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opts=("-j", "--job"),
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action=Radio,
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type=str,
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choices=("draw", "extract", "from-faces", "missing-alignments", "missing-frames",
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"multi-faces", "no-faces", "remove-faces", "rename", "sort", "spatial"),
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group=_("processing"),
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required=True,
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help=_("R|Choose which action you want to perform. NB: All actions require an "
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"alignments file (-a) to be passed in."
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"\nL|'draw': Draw landmarks on frames in the selected folder/video. A "
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"subfolder will be created within the frames folder to hold the output.{0}"
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"\nL|'extract': Re-extract faces from the source frames/video based on "
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"alignment data. This is a lot quicker than re-detecting faces. Can pass in "
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"the '-een' (--extract-every-n) parameter to only extract every nth frame.{1}"
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"\nL|'from-faces': Generate alignment file(s) from a folder of extracted "
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"faces. if the folder of faces comes from multiple sources, then multiple "
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"alignments files will be created. NB: for faces which have been extracted "
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"folders of source images, rather than a video, a single alignments file will "
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"be created as there is no way for the process to know how many folders of "
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"images were originally used. You do not need to provide an alignments file "
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"path to run this job. {3}"
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"\nL|'missing-alignments': Identify frames that do not exist in the alignments "
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"file.{2}{0}"
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"\nL|'missing-frames': Identify frames in the alignments file that do not "
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"appear within the frames folder/video.{2}{0}"
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"\nL|'multi-faces': Identify where multiple faces exist within the alignments "
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"file.{2}{4}"
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"\nL|'no-faces': Identify frames that exist within the alignment file but no "
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"faces were detected.{2}{0}"
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"\nL|'remove-faces': Remove deleted faces from an alignments file. The "
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"original alignments file will be backed up.{3}"
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"\nL|'rename' - Rename faces to correspond with their parent frame and "
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"position index in the alignments file (i.e. how they are named after running "
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"extract).{3}"
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"\nL|'sort': Re-index the alignments from left to right. For alignments with "
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"multiple faces this will ensure that the left-most face is at index 0."
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"\nL|'spatial': Perform spatial and temporal filtering to smooth alignments "
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"(EXPERIMENTAL!)").format(frames_dir, frames_and_faces_dir, output_opts,
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faces_dir, frames_or_faces_dir)))
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argument_list.append(dict(
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opts=("-o", "--output"),
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action=Radio,
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type=str,
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choices=("console", "file", "move"),
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group=_("processing"),
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default="console",
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help=_("R|How to output discovered items ('faces' and 'frames' only):"
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"\nL|'console': Print the list of frames to the screen. (DEFAULT)"
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"\nL|'file': Output the list of frames to a text file (stored within the "
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"source directory)."
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"\nL|'move': Move the discovered items to a sub-folder within the source "
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"directory.")))
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argument_list.append(dict(
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opts=("-a", "--alignments_file"),
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action=FileFullPaths,
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dest="alignments_file",
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type=str,
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group=_("data"),
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# hacky solution to not require alignments file if creating alignments from faces:
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required=not any(val in sys.argv for val in ["from-faces", "-fr", "-frames_folder"]),
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filetypes="alignments",
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help=_("Full path to the alignments file to be processed. If you have input a "
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"'frames_dir' and don't provide this option, the process will try to find the "
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"alignments file at the default location. All jobs require an alignments file "
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"with the exception of 'from-faces' when the alignments file will be generated "
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"in the specified faces folder.")))
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argument_list.append(dict(
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opts=("-fc", "-faces_folder"),
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action=DirFullPaths,
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dest="faces_dir",
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group=_("data"),
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help=_("Directory containing extracted faces.")))
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argument_list.append(dict(
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opts=("-fr", "-frames_folder"),
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action=DirOrFileFullPaths,
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dest="frames_dir",
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filetypes="video",
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group=_("data"),
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help=_("Directory containing source frames that faces were extracted from.")))
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argument_list.append(dict(
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opts=("-een", "--extract-every-n"),
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type=int,
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action=Slider,
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dest="extract_every_n",
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min_max=(1, 100),
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default=1,
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rounding=1,
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group=_("extract"),
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help=_("[Extract only] Extract every 'nth' frame. This option will skip frames when "
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"extracting faces. For example a value of 1 will extract faces from every "
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"frame, a value of 10 will extract faces from every 10th frame.")))
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argument_list.append(dict(
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opts=("-sz", "--size"),
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type=int,
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action=Slider,
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min_max=(256, 1024),
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rounding=64,
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default=512,
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group=_("extract"),
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help=_("[Extract only] The output size of extracted faces.")))
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argument_list.append(dict(
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opts=("-m", "--min-size"),
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type=int,
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action=Slider,
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min_max=(0, 200),
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rounding=1,
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default=0,
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dest="min_size",
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group=_("extract"),
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help=_("[Extract only] Only extract faces that have been resized by this percent or "
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"more to meet the specified extract size (`-sz`, `--size`). Useful for "
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"excluding low-res images from a training set. Set to 0 to extract all faces. "
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"Eg: For an extract size of 512px, A setting of 50 will only include faces "
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"that have been resized from 256px or above. Setting to 100 will only extract "
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"faces that have been resized from 512px or above. A setting of 200 will only "
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"extract faces that have been downscaled from 1024px or above.")))
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return argument_list
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