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5.XSeg) data_dst/src mask for XSeg trainer - fetch.bat Copies faces containing XSeg polygons to aligned_xseg\ dir. Useful only if you want to collect labeled faces and reuse them in other fakes. Now you can use trained XSeg mask in the SAEHD training process. It’s mean default ‘full_face’ mask obtained from landmarks will be replaced with the mask obtained from the trained XSeg model. use 5.XSeg.optional) trained mask for data_dst/data_src - apply.bat 5.XSeg.optional) trained mask for data_dst/data_src - remove.bat Normally you don’t need it. You can use it, if you want to use ‘face_style’ and ‘bg_style’ with obstructions. XSeg trainer : now you can choose type of face XSeg trainer : now you can restart training in “override settings” Merger: XSeg-* modes now can be used with all types of faces. Therefore old MaskEditor, FANSEG models, and FAN-x modes have been removed, because the new XSeg solution is better, simpler and more convenient, which costs only 1 hour of manual masking for regular deepfake.
26 lines
954 B
Python
26 lines
954 B
Python
from .estimate_sharpness import estimate_sharpness
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from .equalize_and_stack_square import equalize_and_stack_square
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from .text import get_text_image, get_draw_text_lines
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from .draw import draw_polygon, draw_rect
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from .morph import morph_by_points
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from .warp import gen_warp_params, warp_by_params
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from .reduce_colors import reduce_colors
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from .color_transfer import color_transfer, color_transfer_mix, color_transfer_sot, color_transfer_mkl, color_transfer_idt, color_hist_match, reinhard_color_transfer, linear_color_transfer, seamless_clone
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from .common import normalize_channels, cut_odd_image, overlay_alpha_image
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from .SegIEPolys import *
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from .blursharpen import LinearMotionBlur, blursharpen
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from .filters import apply_random_rgb_levels, \
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apply_random_hsv_shift, \
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apply_random_motion_blur, \
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apply_random_gaussian_blur, \
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apply_random_bilinear_resize
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