upd readme

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iperov 2018-06-05 12:14:47 +04:00
parent d23c8ecfb9
commit 29a19e7303

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@ -62,10 +62,10 @@ MTCNN produces less jitter.
* ![](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+)** - face controlling model. Usage:
- **AVATAR (4GB+)** - 256pix face controlling model. Usage:
* src - controllable face (Cage)
* dst - controller face (your face)
* 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.
* 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**:
@ -95,12 +95,6 @@ Best practice for dst faces:
1) delete first unsorted aligned groups of images what you can to delete. Dont touch target face mixed with others.
2) `hist` -> delete groups of similar and leave only target face
### **Prebuilt binary**:
Windows 7,8,8.1,10 zero dependency binary except NVidia Video Drivers can be downloaded from torrent.
Torrent page: https://rutracker.org/forum/viewtopic.php?p=75318742 (magnet link inside)
### **Facesets**:
- Nicolas Cage.
@ -109,6 +103,16 @@ Torrent page: https://rutracker.org/forum/viewtopic.php?p=75318742 (magnet link
download from here: https://mega.nz/#F!y1ERHDaL!PPwg01PQZk0FhWLVo5_MaQ
### **Build info**
dlib==19.10.0 from pip compiled without CUDA. Therefore you have to compile DLIB manually.
Command line example for windows: `python setup.py install -G "Visual Studio 14 2015" --yes DLIB_USE_CUDA`
### **Prebuilt python folder with DeepFaceLab**:
Windows 7,8,8.1,10 zero dependency (except GeForce Drivers) prebuilt Python 3.6.5 embeddable folder with DeepFaceLab can be downloaded from torrent https://rutracker.org/forum/viewtopic.php?p=75318742 (magnet link inside).
### **Pull requesting**:
I understand some people want to help. But result of mass people contribution we can see in deepfakes\faceswap.