ac7725163d
added SAEHD model ( High Definition Styled AutoEncoder ) This is a new heavyweight model for high-end cards to achieve maximum possible deepfake quality in 2020. Differences from SAE: + new encoder produces more stable face and less scale jitter before: https://i.imgur.com/4jUcol8.gifv after: https://i.imgur.com/lyiax49.gifv - scale of the face is less changed within frame size + new decoder produces subpixel clear result + pixel loss and dssim loss are merged together to achieve both training speed and pixel trueness + by default networks will be initialized with CA weights, but only after first successful iteration therefore you can test network size and batch size before weights initialization process + new neural network optimizer consumes less VRAM than before + added option <Enable 'true face' training> The result face will be more like src and will get extra sharpness. example: https://i.imgur.com/ME3A7dI.gifv Enable it for last 15-30k iterations before conversion. + encoder and decoder dims are merged to one parameter encoder/decoder dims + added mid-full face, which covers 30% more area than half face.
#deepfakes #faceswap #face-swap #deep-learning #deeplearning #deep-neural-networks #deepface #deep-face-swap #fakeapp #fake-app #neural-networks #neural-nets
DeepFaceLab is a tool that utilizes machine learning to replace faces in videos.
If you like this software, please consider a donation.
GOAL: next DeepFacelab update.
bitcoin:31mPd6DxPCzbpCMZk4k1koWAbErSyqkAXr
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Gallery
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Manuals:
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Prebuilt windows app
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Forks
Google Colab fork by @chervonij
Linux fork by @lbfs - may be outdated
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Ready to work facesets
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Build and repository info
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Communication groups:
(Chinese) QQ group 951138799 for ML/AI experts