mirror of
https://github.com/deepfakes/faceswap
synced 2025-06-09 04:36:50 -04:00
acf1fc5612
* Add a new sorting/grouping feature based on the percentage of black pixels in images Context: - Faces are quite often moving and can get near borders of the image. - Because of that, the face image has the out of bound part replaced by black pixels. - Some are still good for training but others not. Also, one might want to keep an alignment file with the near borders faces but excluded (some of) them for training. - Having to manually move/delete those images in a dataset of thousands of them is painful and prone to mistakes. - Thus, having a way to sort and group those images would be helpful. At least, it is for me :-) Added features: - A new option in Tools/Sort for both Sort and Group By called Black-Pixels. - Sort feature: calculates the percentage of black pixels in each images and sort them from 0 to 100%. - Group By feature: Uses the Bins slider number selected and creates 100/Bins folders with the images percentage of black pixels. ie. a Bins of 5 will create 20 folders with the first one containing images with 0-5% of black pixels, the second one with 6-10%, etc. A static method as been added for the rounding error. * PEP8 fixes Co-authored-by: Olivier Gagnon <ogagnon@ludia.com>
171 lines
8.9 KiB
Python
171 lines
8.9 KiB
Python
#!/usr/bin/env python3
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""" Command Line Arguments for tools """
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import gettext
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from lib.cli.args import FaceSwapArgs
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from lib.cli.actions import DirFullPaths, SaveFileFullPaths, Radio, Slider
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# LOCALES
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_LANG = gettext.translation("tools.sort.cli", localedir="locales", fallback=True)
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_ = _LANG.gettext
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_HELPTEXT = _("This command lets you sort images using various methods.")
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class SortArgs(FaceSwapArgs):
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""" Class to parse the command line arguments for sort tool """
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@staticmethod
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def get_info():
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""" Return command information """
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return _("Sort faces using a number of different techniques")
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@staticmethod
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def get_argument_list():
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""" Put the arguments in a list so that they are accessible from both argparse and gui """
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argument_list = list()
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argument_list.append(dict(
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opts=('-i', '--input'),
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action=DirFullPaths,
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dest="input_dir",
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group=_("data"),
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help=_("Input directory of aligned faces."),
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required=True))
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argument_list.append(dict(
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opts=('-o', '--output'),
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action=DirFullPaths,
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dest="output_dir",
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group=_("data"),
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help=_("Output directory for sorted aligned faces.")))
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argument_list.append(dict(
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opts=('-s', '--sort-by'),
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action=Radio,
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type=str,
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choices=("blur", "blur-fft", "distance", "face", "face-cnn", "face-cnn-dissim",
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"face-yaw", "hist", "hist-dissim", "color-gray", "color-luma", "color-green",
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"color-orange", "size", "black-pixels"),
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dest='sort_method',
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group=_("sort settings"),
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default="face",
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help=_("R|Sort by method. Choose how images are sorted. "
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"\nL|'blur': Sort faces by blurriness."
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"\nL|'blur-fft': Sort faces by fft filtered blurriness."
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"\nL|'distance' Sort faces by the estimated distance of the alignments from an "
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"'average' face. This can be useful for eliminating misaligned faces."
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"\nL|'face': Use VGG Face to sort by face similarity. This uses a pairwise "
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"clustering algorithm to check the distances between 512 features on every "
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"face in your set and order them appropriately."
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"\nL|'face-cnn': Sort faces by their landmarks. You can adjust the threshold "
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"with the '-t' (--ref_threshold) option."
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"\nL|'face-cnn-dissim': Like 'face-cnn' but sorts by dissimilarity."
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"\nL|'face-yaw': Sort faces by Yaw (rotation left to right)."
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"\nL|'hist': Sort faces by their color histogram. You can adjust the threshold "
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"with the '-t' (--ref_threshold) option."
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"\nL|'hist-dissim': Like 'hist' but sorts by dissimilarity."
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"\nL|'color-gray': Sort images by the average intensity of the converted "
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"grayscale color channel."
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"\nL|'color-luma': Sort images by the average intensity of the converted Y "
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"color channel. Bright lighting and oversaturated images will be ranked first."
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"\nL|'color-green': Sort images by the average intensity of the converted Cg "
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"color channel. Green images will be ranked first and red images will be last."
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"\nL|'color-orange': Sort images by the average intensity of the converted Co "
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"color channel. Orange images will be ranked first and blue images will be "
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"last."
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"\nL|'size': Sort images by their size in the original frame. Faces closer to "
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"the camera and from higher resolution sources will be sorted first, whilst "
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"faces further from the camera and from lower resolution sources will be "
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"sorted last."
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"\nL|'black-pixels': Sort images by their number of black pixels. Useful when "
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"faces are near borders and a large part of the image is black."
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"\nDefault: face")))
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argument_list.append(dict(
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opts=('-k', '--keep'),
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action='store_true',
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dest='keep_original',
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default=False,
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group=_("output"),
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help=_("Keeps the original files in the input directory. Be careful when using this "
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"with rename grouping and no specified output directory as this would keep the "
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"original and renamed files in the same directory.")))
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argument_list.append(dict(
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opts=('-t', '--ref_threshold'),
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action=Slider,
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min_max=(-1.0, 10.0),
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rounding=2,
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type=float,
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dest='min_threshold',
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group=_("sort settings"),
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default=-1.0,
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help=_("Float value. Minimum threshold to use for grouping comparison with 'face-cnn' "
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"and 'hist' methods. The lower the value the more discriminating the grouping "
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"is. Leaving -1.0 will allow the program set the default value automatically. "
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"For face-cnn 7.2 should be enough, with 4 being very discriminating. For hist "
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"0.3 should be enough, with 0.2 being very discriminating. Be careful setting "
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"a value that's too low in a directory with many images, as this could result "
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"in a lot of directories being created. Defaults: face-cnn 7.2, hist 0.3")))
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argument_list.append(dict(
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opts=('-fp', '--final-process'),
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action=Radio,
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type=str,
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choices=("folders", "rename"),
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dest='final_process',
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default="rename",
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group=_("output"),
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help=_("R|Default: rename."
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"\nL|'folders': files are sorted using the -s/--sort-by method, then they are "
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"organized into folders using the -g/--group-by grouping method."
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"\nL|'rename': files are sorted using the -s/--sort-by then they are "
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"renamed.")))
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argument_list.append(dict(
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opts=('-g', '--group-by'),
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action=Radio,
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type=str,
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choices=("blur", "blur-fft", "face-cnn", "face-yaw", "hist", "black-pixels"),
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dest='group_method',
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group=_("output"),
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default="hist",
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help=_("Group by method. When -fp/--final-processing by folders choose the how the "
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"images are grouped after sorting. Default: hist")))
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argument_list.append(dict(
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opts=('-b', '--bins'),
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action=Slider,
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min_max=(1, 100),
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rounding=1,
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type=int,
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dest='num_bins',
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group=_("output"),
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default=5,
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help=_("Integer value. Number of folders that will be used to group by blur, "
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"face-yaw and black-pixels. For blur folder 0 will be the least blurry, while "
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"the last folder will be the blurriest. For face-yaw the number of bins is by "
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"how much 180 degrees is divided. So if you use 18, then each folder will be "
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"a 10 degree increment. Folder 0 will contain faces looking the most to the "
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"left whereas the last folder will contain the faces looking the most to the "
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"right. If the number of images doesn't divide evenly into the number of "
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"bins, the remaining images get put in the last bin. For black-pixels it "
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"represents the divider of the percentage of black pixels. For 10, first "
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"folder will have the faces with 0 to 10% black pixels, second 11 to 20%, "
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"etc. Default value: 5")))
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argument_list.append(dict(
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opts=('-l', '--log-changes'),
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action='store_true',
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group=_("settings"),
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default=False,
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help=_("Logs file renaming changes if grouping by renaming, or it logs the file "
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"copying/movement if grouping by folders. If no log file is specified with "
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"'--log-file', then a 'sort_log.json' file will be created in the input "
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"directory.")))
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argument_list.append(dict(
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opts=('-lf', '--log-file'),
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action=SaveFileFullPaths,
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filetypes="alignments",
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group=_("settings"),
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dest='log_file_path',
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default='sort_log.json',
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help=_("Specify a log file to use for saving the renaming or grouping information. If "
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"specified extension isn't 'json' or 'yaml', then json will be used as the "
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"serializer, with the supplied filename. Default: sort_log.json")))
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return argument_list
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