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@ -35,37 +35,64 @@ MTCNN produces less jitter.
### **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.
* H64 Robert Downey Jr.:
* ![](https://github.com/iperov/DeepFaceLab/blob/master/doc/H64_Downey_0.jpg)
* ![](https://github.com/iperov/DeepFaceLab/blob/master/doc/H64_Downey_1.jpg)
H64 Robert Downey Jr.:
![](https://github.com/iperov/DeepFaceLab/blob/master/doc/H64_Downey_0.jpg)
![](https://github.com/iperov/DeepFaceLab/blob/master/doc/H64_Downey_1.jpg)
- **H128 (3GB+)** - as H64, but in 128 resolution. Better face details. for 3GB and 4GB VRAM model works in reduced mode.
* H128 Cage:
* ![](https://github.com/iperov/DeepFaceLab/blob/master/doc/H128_Cage_0.jpg)
* H128 asian face on blurry target:
* ![](https://github.com/iperov/DeepFaceLab/blob/master/doc/H128_Asian_0.jpg)
* ![](https://github.com/iperov/DeepFaceLab/blob/master/doc/H128_Asian_1.jpg)
H128 Cage:
![](https://github.com/iperov/DeepFaceLab/blob/master/doc/H128_Cage_0.jpg)
H128 asian face on blurry target:
![](https://github.com/iperov/DeepFaceLab/blob/master/doc/H128_Asian_0.jpg)
![](https://github.com/iperov/DeepFaceLab/blob/master/doc/H128_Asian_1.jpg)
- **DF (5GB+)** - @dfaker model. As H128, but fullface model.
* DF example - later
DF example - later
- **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 Cage:
* ![](https://github.com/iperov/DeepFaceLab/blob/master/doc/LIAEF128_Cage_0.jpg)
* ![](https://github.com/iperov/DeepFaceLab/blob/master/doc/LIAEF128_Cage_1.jpg)
* LIAEF128 Cage video:
* [![Watch the video](https://img.youtube.com/vi/mRsexePEVco/0.jpg)](https://www.youtube.com/watch?v=mRsexePEVco)
LIAEF128 Cage:
![](https://github.com/iperov/DeepFaceLab/blob/master/doc/LIAEF128_Cage_0.jpg)
![](https://github.com/iperov/DeepFaceLab/blob/master/doc/LIAEF128_Cage_1.jpg)
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)
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+)** - 256pix face controlling model. 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 1500 dst faces, but use only 100 for convert.
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 1500 dst faces, but use only 100 for convert.
### **Sort tool**:
@ -116,4 +143,4 @@ Windows 7,8,8.1,10 zero dependency (except GeForce Drivers) prebuilt Python 3.6.
### **Pull requesting**:
I understand some people want to help. But result of mass people contribution we can see in deepfakes\faceswap.
High chance I will decline PR. Therefore before PR better ask me what you want to change or add to save your time.
High chance I will decline PR. Therefore before PR better ask me what you want to change or add to save your time.