From 9545774c594108d481b1ad1d4070239b0896c769 Mon Sep 17 00:00:00 2001 From: iperov Date: Thu, 7 Feb 2019 21:59:52 +0400 Subject: [PATCH] upd README.md --- README.md | 44 ++++++++++++++++++++------------------------ 1 file changed, 20 insertions(+), 24 deletions(-) diff --git a/README.md b/README.md index ca8c385..495dae7 100644 --- a/README.md +++ b/README.md @@ -14,11 +14,13 @@ bitcoin:31mPd6DxPCzbpCMZk4k1koWAbErSyqkAXr ### **Features**: +- standalone zero dependencies ready to work prebuilt binary for all windows versions, see below + - new models - new architecture, easy to experiment with models -- face data embedded to png files +- face data embedded to JPG files - cpu mode. 8th gen Intel core CPU able to train H64 model in 2 days. @@ -28,20 +30,16 @@ bitcoin:31mPd6DxPCzbpCMZk4k1koWAbErSyqkAXr - converter in parallel -- added **--debug** option for all stages +- **--debug** option for all stages -- 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: +- **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: ![](https://i.imgur.com/5qLiiOV.gif) MTCNN produces less jitter. -- added **Manual extractor**. You can fix missed faces manually or do full manual extract: +- **Manual extractor**. You can fix missed faces manually or do full manual extract: ![](https://github.com/iperov/DeepFaceLab/blob/master/doc/manual_extractor_0.jpg) ![Result](https://user-images.githubusercontent.com/8076202/38454756-0fa7a86c-3a7e-11e8-9065-182b4a8a7a43.gif) -- 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. @@ -199,11 +197,21 @@ Best practice for dst faces: ### **Ready to work facesets**: -Nicolas Cage 4 facesets (1 mix + 3 different), Steve Jobs, Putin +Nicolas Cage, Steve Jobs, Putin, Elon Musk. https://mega.nz/#F!y1ERHDaL!PPwg01PQZk0FhWLVo5_MaQ -download from here: https://mega.nz/#F!y1ERHDaL!PPwg01PQZk0FhWLVo5_MaQ +### **CPU only mode** -### Video tutorials for prebuilt windows binary +CPU mode enabled by arg --cpu-only for all stages. Follow requirements-cpu.txt to install req packages. +Do not use DLIB extractor in CPU mode, it's too slow. +Only H64 or SAE (with low settings) models reasonable to train on home CPU. + +### 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 +1) torrent https://rutracker.org/forum/viewtopic.php?p=75318742 (magnet link inside). +2) https://mega.nz/#F!b9MzCK4B!zEAG9txu7uaRUjXz9PtBqg + +### Video tutorials for prebuilt windows app: Basic workflow: https://www.youtube.com/watch?v=K98nTNjXkq8 @@ -219,21 +227,9 @@ dlib==19.10.0 from pip compiled without CUDA. Therefore you have to compile DLIB Command line example for windows: `python setup.py install -G "Visual Studio 14 2015" --yes DLIB_USE_CUDA` -### **CPU only mode** - -CPU mode enabled by arg --cpu-only for all stages. Follow requirements-cpu.txt to install req packages. -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 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 -1) torrent https://rutracker.org/forum/viewtopic.php?p=75318742 (magnet link inside). -2) https://mega.nz/#F!b9MzCK4B!zEAG9txu7uaRUjXz9PtBqg +If you want to support mac/linux/docker - create fork, it will be referenced here. ### Communication groups: