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README.md
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README.md
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## **DeepFaceLab** is a tool that utilizes deep learning to recognize and swap faces in pictures and videos.
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Based on original FaceSwap repo. **Facesets** of FaceSwap or FakeApp are **not compatible** with this repo. You should to run extract again.
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### **Features**:
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- new models
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- new architecture, easy to experiment with models
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- works on 2GB old cards , such as GT730. Example of fake trained on 2GB gtx850m notebook in 18 hours https://www.youtube.com/watch?v=bprVuRxBA34
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- face data embedded to png files
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- automatic GPU manager, chooses best gpu(s) and supports --multi-gpu
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- new preview window
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- extractor in parallel
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- converter in parallel
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- added **--debug** option for all stages
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- added **MTCNN extractor** which produce less jittered aligned face than DLIBCNN, but can produce more false faces. Comparison dlib (at left) vs mtcnn on hard case:
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MTCNN produces less jitter.
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- added **Manual extractor**. You can fix missed faces manually or do full manual extract, click on video:
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[](https://webm.video/i/ogL0DL.mp4)
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- standalone zero dependencies ready to work prebuilt binary for all windows versions, see below
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### **Model types**:
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- **H64 (2GB+)** - half face with 64 resolution. It is as original FakeApp or FaceSwap, but with new TensorFlow 1.8 DSSIM Loss func and separated mask decoder + better ConverterMasked. for 2GB and 3GB VRAM model works in reduced mode.
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* H64 Robert Downey Jr.:
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* 
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* 
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- **H128 (3GB+)** - as H64, but in 128 resolution. Better face details. for 3GB and 4GB VRAM model works in reduced mode.
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* H128 Cage:
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* 
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* H128 asian face on blurry target:
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* 
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* 
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- **DF (5GB+)** - @dfaker model. As H128, but fullface model.
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* DF example - later
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- **LIAEF128 (5GB+)** - new model. Result of combining DF, IAE, + experiments. Model tries to morph src face to dst, while keeping facial features of src face, but less agressive morphing. Model has problems with closed eyes recognizing.
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* LIAEF128 Cage:
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* 
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* 
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* LIAEF128 Cage video:
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* [](https://www.youtube.com/watch?v=mRsexePEVco)
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- **LIAEF128YAW (5GB+)** - currently testing. Useful when your src faceset has too many side faces vs dst faceset. It feeds NN by sorted samples by yaw.
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- **MIAEF128 (5GB+)** - as LIAEF128, but also it tries to match brightness/color features.
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* MIAEF128 model diagramm:
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* 
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* MIAEF128 Ford success case:
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* 
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* 
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* MIAEF128 Cage fail case:
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* 
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- **AVATAR (4GB+)** - face controlling model. Usage:
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* src - controllable face (Cage)
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* dst - controller face (your face)
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* converter --input-dir contains aligned dst faces in sequence to be converted, its mean you can train on 1500 dst faces, but use only 100 for convert.
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### **Sort tool**:
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`hist` groups images by similar content
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`hist-dissim` places most similar to each other images to end.
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`hist-blur` sort by blur in groups of similar content
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`brightness`
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`hue`
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`face` and `face-dissim` currently useless
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Best practice for gather src faceset:
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1) delete first unsorted aligned groups of images what you can to delete. Dont touch target face mixed with others.
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2) `blur` -> delete ~half of them
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3) `hist` -> delete groups of similar and leave only target face
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4) `hist-blur` -> delete blurred at end of groups of similar
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5) `hist-dissim` -> leave only first **1000-1500 faces**, because number of src faces can affect result. For YAW feeder model skip this step.
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6) `face-yaw` -> just for finalize faceset
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Best practice for dst faces:
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1) delete first unsorted aligned groups of images what you can to delete. Dont touch target face mixed with others.
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2) `hist` -> delete groups of similar and leave only target face
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### **Prebuilt binary**:
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Windows 7,8,8.1,10 zero dependency binary except NVidia Video Drivers can be downloaded from torrent.
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Torrent page: https://rutracker.org/forum/viewtopic.php?p=75318742 (magnet link inside)
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### **Facesets**:
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- Nicolas Cage.
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- Cage/Trump workspace
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download from here: https://mega.nz/#F!y1ERHDaL!PPwg01PQZk0FhWLVo5_MaQ
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### **Pull requesting**:
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I understand some people want to help. But result of mass people contribution we can see in deepfakes\faceswap.
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High chance I will decline PR. Therefore before PR better ask me what you want to change or add to save your time.
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