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DeepFaceLab is the leading software for creating deepfakes.
Basic usage instruction: https://i.imgur.com/w7LkId2.jpg 'whole_face' requires skill in Adobe After Effects. For using whole_face you have to extract whole_face's by using 4) data_src extract whole_face and 5) data_dst extract whole_face Images will be extracted in 512 resolution, so they can be used for regular full_face's and half_face's. 'whole_face' covers whole area of face include forehead in training square, but training mask is still 'full_face' therefore it requires manual final masking and composing in Adobe After Effects. added option 'masked_training' This option is available only for 'whole_face' type. Default is ON. Masked training clips training area to full_face mask, thus network will train the faces properly. When the face is trained enough, disable this option to train all area of the frame. Merge with 'raw-rgb' mode, then use Adobe After Effects to manually mask, tune color, and compose whole face include forehead. |
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core | ||
DFLIMG | ||
doc | ||
facelib | ||
localization | ||
mainscripts | ||
merger | ||
models | ||
samplelib | ||
.gitignore | ||
CODEGUIDELINES | ||
LICENSE | ||
main.py | ||
project.code-workspace | ||
README.md | ||
requirements-colab.txt | ||
requirements-cuda.txt |
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DeepFaceLabthe leading software for creating deepfakes | ||||||||||||||||||||||||||||||||||||
More than 95% of deepfake videos are created with DeepFaceLab. DeepFaceLab is used by such popular youtube channels as
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deepfake quality progress
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How I can help the project?
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Meme zone
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#deepfacelab #deepfakes #faceswap #face-swap #deep-learning #deeplearning #deep-neural-networks #deepface #deep-face-swap #fakeapp #fake-app #neural-networks #neural-nets #tensorflow #cuda #nvidia |