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added new model U-net Face Morpher.

Browse source 
removed AVATAR - useless model was just for demo
removed MIAEF128 - use UFM insted
removed LIAEF128YAW - use model option sort by yaw on start for any model
All models now ask some options on start.
Session options (such as target epoch, batch_size, write_preview_history etc) can be overrided by special command arg.
Converter now always ask options and no more support to define options via command line.
fix bug when ConverterMasked always used not predicted mask.
SampleGenerator now always generate samples with replicated border, exclude mask samples.
refactorings
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iperov 2019-01-02 17:26:12 +04:00
commit 7b70e7eec1
29 changed files with 673 additions and 1013 deletions
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README.md
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@ -1,7 +1,5 @@
## **DeepFaceLab** is a tool that utilizes deep learning to recognize and swap faces in pictures and videos.
Based on original FaceSwap repo. **Facesets** of FaceSwap or FakeApp are **not compatible** with this repo. You should to run extract again.
### **Features**:
- new models
@ -34,6 +32,8 @@ MTCNN produces less jitter.
- standalone zero dependencies ready to work prebuilt binary for all windows versions, see below
### Warning: **Facesets** of FaceSwap or FakeApp are **not compatible** with this repo. You should to run extract again.
### **Model types**:
- **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.
@ -60,7 +60,7 @@ H128 asian face on blurry target:
![](https://github.com/iperov/DeepFaceLab/blob/master/doc/DF_Cage_0.jpg)
- **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.
- **LIAEF128 (5GB+)** - Less agressive Improved Autoencoder Fullface 128 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.
LIAEF128 Cage:
@ -72,47 +72,10 @@ LIAEF128 Cage video:
[![Watch the video](https://img.youtube.com/vi/mRsexePEVco/0.jpg)](https://www.youtube.com/watch?v=mRsexePEVco)
- **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.
- **MIAEF128 (5GB+)** - as LIAEF128, but also it tries to match brightness/color features.
MIAEF128 model diagramm:
![](https://github.com/iperov/DeepFaceLab/blob/master/doc/MIAEF128_diagramm.png)
MIAEF128 Ford success case:
![](https://github.com/iperov/DeepFaceLab/blob/master/doc/MIAEF128_Ford_0.jpg)
MIAEF128 Cage fail case:
![](https://github.com/iperov/DeepFaceLab/blob/master/doc/MIAEF128_Cage_fail.jpg)
- **AVATAR (4GB+)** - non GAN, 256x256 face controlling model.
![](https://github.com/iperov/DeepFaceLab/blob/master/doc/AVATAR_Navalniy_0.jpg)
Video:
[![](https://img.youtube.com/vi/3M0E4QnWMqA/0.jpg)](https://www.youtube.com/watch?v=3M0E4QnWMqA)
Usage:
src - controllable face (Cage)
dst - controller face (your face)
converter --input-dir must contains *extracted dst faces* in sequence to be converted, its mean you can train on for example 1500 dst faces, but use for example 100 faces for convert.
- **UFM (4GB+)** - U-net Face Morpher model. If "match_style" option choosed, then this model tries to morph src face to target face and fill around face same background. UFM is result of combining modified U-Net, classic face autoencoder, DSSIM and style losses.
![](https://github.com/iperov/DeepFaceLab/blob/master/doc/DeepFaceLab_convertor_overview.png)
- Video comparison of different Cage facesets.
Vertical: 1 - mix of various Cage face shape and light conditions. 2,3,4 - without mix.
Horizontal: 1 - DF, 2 - LIAEF128.
[![](https://img.youtube.com/vi/C1nFgrmtm_o/0.jpg)](https://youtu.be/C1nFgrmtm_o)
Conclusion: **better not to mix and use only same shape faces with same light**
### **Sort tool**:
@ -164,6 +127,10 @@ CPU mode enabled by arg --cpu-only for all stages. Follow requirements-cpu.txt t
Do not use DLIB extractor in CPU mode, its too slow.
Only H64 model reasonable to train on home CPU.
### Mac/linux/docker script support.
This repo supports only windows build of scripts. If you want to support mac/linux/docker - create such fork, it will be referenced here.
### Prebuilt windows app:
Windows 7,8,8.1,10 zero dependency (just install/update your GeForce Drivers) prebuilt DeepFaceLab (include GPU and CPU versions) can be downloaded from