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DeepFaceLab is the leading software for creating deepfakes.
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here new whole_face + XSeg workflow: with XSeg model you can train your own mask segmentator for dst(and/or src) faces that will be used by the merger for whole_face. Instead of using a pretrained segmentator model (which does not exist), you control which part of faces should be masked. new scripts: 5.XSeg) data_dst edit masks.bat 5.XSeg) data_src edit masks.bat 5.XSeg) train.bat Usage: unpack dst faceset if packed run 5.XSeg) data_dst edit masks.bat Read tooltips on the buttons (en/ru/zn languages are supported) mask the face using include or exclude polygon mode. repeat for 50/100 faces, !!! you don't need to mask every frame of dst only frames where the face is different significantly, for example: closed eyes changed head direction changed light the more various faces you mask, the more quality you will get Start masking from the upper left area and follow the clockwise direction. Keep the same logic of masking for all frames, for example: the same approximated jaw line of the side faces, where the jaw is not visible the same hair line Mask the obstructions using exclude polygon mode. run XSeg) train.bat train the model Check the faces of 'XSeg dst faces' preview. if some faces have wrong or glitchy mask, then repeat steps: run edit find these glitchy faces and mask them train further or restart training from scratch Restart training of XSeg model is only possible by deleting all 'model\XSeg_*' files. If you want to get the mask of the predicted face (XSeg-prd mode) in merger, you should repeat the same steps for src faceset. New mask modes available in merger for whole_face: XSeg-prd - XSeg mask of predicted face -> faces from src faceset should be labeled XSeg-dst - XSeg mask of dst face -> faces from dst faceset should be labeled XSeg-prd*XSeg-dst - the smallest area of both if workspace\model folder contains trained XSeg model, then merger will use it, otherwise you will get transparent mask by using XSeg-* modes. Some screenshots: XSegEditor: https://i.imgur.com/7Bk4RRV.jpg trainer : https://i.imgur.com/NM1Kn3s.jpg merger : https://i.imgur.com/glUzFQ8.jpg example of the fake using 13 segmented dst faces : https://i.imgur.com/wmvyizU.gifv |
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| .github | ||
| .vscode | ||
| core | ||
| DFLIMG | ||
| doc | ||
| facelib | ||
| localization | ||
| mainscripts | ||
| merger | ||
| models | ||
| samplelib | ||
| XSegEditor | ||
| .gitignore | ||
| _config.yml | ||
| CODEGUIDELINES | ||
| LICENSE | ||
| main.py | ||
| project.code-workspace | ||
| README.md | ||
| requirements-colab.txt | ||
| requirements-cuda.txt | ||
DeepFaceLabthe leading software for creating deepfakes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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More than 95% of deepfake videos are created with DeepFaceLab. DeepFaceLab is used by such popular youtube channels as
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What can I do using DeepFaceLab? | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replace the face
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Change political speech*
* also requires a skill in video editors such as Adobe After Effects or Davinci Resolve | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Deepfake native resolution progress | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Unfortunately, there is no "make everything ok" button in DeepFaceLab. You should spend time studying the workflow and growing your skills. A skill in programs such as AfterEffects or Davince Resolve is also desirable. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Releases
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Links
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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 |
