mirror of
https://github.com/deepfakes/faceswap
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f2e4c5a12c
* Implement s3fd detect plugin * s3fd: Add confidence slider to config. Update cli helptext
59 lines
2.5 KiB
Python
59 lines
2.5 KiB
Python
#!/usr/bin/env python3
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""" Default configurations for extract """
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import logging
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from lib.config import FaceswapConfig
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logger = logging.getLogger(__name__) # pylint: disable=invalid-name
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class Config(FaceswapConfig):
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""" Config File for Models """
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def set_defaults(self):
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""" Set the default values for config """
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logger.debug("Setting defaults")
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# << GLOBAL OPTIONS >> #
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# section = "global"
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# self.add_section(title=section,
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# info="Options that apply to all models")
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# << MTCNN DETECTOR OPTIONS >> #
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section = "detect.mtcnn"
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self.add_section(title=section,
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info="MTCNN Detector options")
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self.add_item(
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section=section, title="minsize", datatype=int, default=20, rounding=10,
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min_max=(20, 1000),
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info="The minimum size of a face (in pixels) to be accepted as a positive match.\n"
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"Lower values use significantly more VRAM and will detect more false positives")
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self.add_item(
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section=section, title="threshold_1", datatype=float, default=0.6, rounding=2,
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min_max=(0.1, 0.9),
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info="First stage threshold for face detection. This stage obtains face candidates")
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self.add_item(
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section=section, title="threshold_2", datatype=float, default=0.7, rounding=2,
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min_max=(0.1, 0.9),
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info="Second stage threshold for face detection. This stage refines face candidates")
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self.add_item(
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section=section, title="threshold_3", datatype=float, default=0.7, rounding=2,
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min_max=(0.1, 0.9),
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info="Third stage threshold for face detection. This stage further refines face "
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"candidates")
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self.add_item(
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section=section, title="scalefactor", datatype=float, default=0.709, rounding=3,
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min_max=(0.1, 0.9),
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info="The scale factor for the image pyramid")
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# << S3FD DETECTOR OPTIONS >> #
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section = "detect.s3fd"
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self.add_section(title=section,
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info="S3FD Detector options")
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self.add_item(
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section=section, title="confidence", datatype=int, default=50, rounding=5,
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min_max=(25, 100),
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info="The confidence level at which the detector has succesfully found a face.\n"
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"Higher levels will be more discriminating, lower levels will have more false "
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"positives")
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