DeepFaceLab

 DeepFaceLab is the leading software for creating deepfakes.

https://arxiv.org/abs/2005.05535

More than 95% of deepfake videos are created with DeepFaceLab. DeepFaceLab is used by such popular youtube channels as deeptomcruise 1facerussia arnoldschwarzneggar mariahcareyathome? diepnep mr__heisenberg deepcaprio VFXChris Ume Sham00k Collider videos iFake NextFace Futuring Machine RepresentUS Corridor Crew DeepFaker DeepFakes in movie DeepFakeCreator Jarkan
What can I do using DeepFaceLab?
Replace the face
De-age the face
https://www.youtube.com/watch?v=Ddx5B-84ebo
Replace the head
https://www.youtube.com/watch?v=xr5FHd0AdlQ
https://www.youtube.com/watch?v=RTjgkhMugVw
https://www.youtube.com/watch?v=R9f7WD0gKPo
Manipulate politicians lips (voice replacement is not included!) (also requires a skill in video editors such as Adobe After Effects or Davinci Resolve) https://www.youtube.com/watch?v=IvY-Abd2FfM https://www.youtube.com/watch?v=ERQlaJ_czHU
Deepfake native resolution progress
Unfortunately, there is no "make everything ok" button in DeepFaceLab. You should spend time studying the workflow and growing your skills. A skill in programs such as AfterEffects or Davinci Resolve is also desirable.
Mini tutorial
Releases
Windows (magnet link)	Last release. Use torrent client to download.
Windows (Mega.nz)	Contains new and prev releases.
Windows (yandex.ru)	Contains new and prev releases.
Google Colab (github)	by @chervonij . You can train fakes for free using Google Colab.
Linux (github)	by @nagadit
CentOS Linux (github)	May be outdated. By @elemantalcode
Links
Guides and tutorials
DeepFaceLab guide	Main guide
Faceset creation guide	How to create the right faceset
Google Colab guide	Guide how to train the fake on Google Colab
Compositing	To achieve the highest quality, compose deepfake manually in video editors such as Davinci Resolve or Adobe AfterEffects
Discussion and suggestions
Supplementary material
Ready to work facesets	Celebrity facesets made by community
Pretrained models	Pretrained models made by community
Communication groups
Discord	Official discord channel. English / Russian.
Telegram group	Official telegram group. English / Russian. For anonymous communication. Don't forget to hide your phone number
Русский форум
mrdeepfakes	the biggest NSFW English community
reddit r/DeepFakesSFW/	Post your deepfakes there !
reddit r/RUdeepfakes/	Постим русские дипфейки сюда !
QQ群1095077489	中文交流QQ群，商务合作找群主
dfldata.xyz	中文交流论坛，免费软件教程、模型、人脸数据
deepfaker.xyz	中文学习站（非官方)
Related works
DeepFaceLive	Real-time face swap for PC streaming or video calls
neuralchen/SimSwap	Swapping face using ONE single photo 一张图免训练换脸
deepfakes/faceswap	Something that was before DeepFaceLab and still remains in the past
How I can help the project?
Sponsor deepfake research and DeepFaceLab development.
Donate via Yandex.Money
bitcoin:bc1qkhh7h0gwwhxgg6h6gpllfgstkd645fefrd5s6z
Collect facesets
You can collect faceset of any celebrity that can be used in DeepFaceLab and share it in the community
Star this repo
Register github account and push "Star" button.
Meme zone
You don't need deepfake detector. You need to stop lying.	V.I. Lenin
#deepfacelab #deepfakes #faceswap #face-swap #deep-learning #deeplearning #deep-neural-networks #deepface #deep-face-swap #fakeapp #fake-app #neural-networks #neural-nets #tensorflow #cuda #nvidia from https://github.com/iperov/DeepFaceLab  -------------------------------------------------------------- Colab可以免费让你使用深度学习专用显卡Tesla V100 16G 来跑AI换脸哦（原K80,T4，12G），好用的话记右上角点下Star哦，谢谢！ With colab you can use tesla V100 for free. Of course there are some restrictions ；   https://www.deepfaker.xyz/ Good News Colab upgraded from the original K80 12G to T4 16G, faster, more VRAM！ Overview The purpose of this project is to provide a way to run DeepFaceLab for free. When you have learned how to use DFL, Perhaps the biggest limitation for you is the Computer performance. Highly equipped graphics cards are very expensive, and cloud services are not cheap. So how free? take this!^_^ Of course there are some restrictions The code comes from DeepFaceLab and DeepFaceLab_Linux . This rep just add the .ipynb file ,makes it simpler! No need to copy, zip, unzip multiple times, no need to worry about data loss. Features You can use tesla T4 for free Your data is saved in the google Drive You can preview the results online,No need to download Colaboratory requires interaction when in use. The system may stop long-running background calculations Loading images for the first time will be slower Long time use may be blacked out, then you can only change a google account. Guide First, You need a google account Secend,you need a DeepFaceLab_Colab_V2.ipynb file Third, Click Open in Colab ，Run it！ Fourth, View results online through Google Drive Sixth,Continue training Step 6 of using the DeepFaceLab_Colab_V2.ipynb file! About TimeOut https://research.google.com/colaboratory/faq.html#drive-timeout from https://github.com/dream80/DeepFaceLab_Colab ---------------------------------------------------------------------------------------------------------------- Deepfakes Software For All . www.faceswap.dev FaceSwap is a tool that utilizes deep learning to recognize and swap faces in pictures and videos.      Emma Stone/Scarlett Johansson FaceSwap using the Phaze-A model Jennifer Lawrence/Steve Buscemi FaceSwap using the Villain model Make sure you check out INSTALL.md before getting started. deepfakes_faceswap Manifesto FaceSwap has ethical uses. How To setup and run the project Overview Extract Train Convert GUI General notes: Help I need support! Discord Server FaceSwap Forum Donate Patreon One time Donations @torzdf @andenixa How to contribute For people interested in the generative models For devs For non-dev advanced users For end-users For haters About github.com/deepfakes What is this repo? Why this repo? Why is it named 'deepfakes' if it is not /u/deepfakes? What if /u/deepfakes feels bad about that? About machine learning How does a computer know how to recognize/shape faces? How does machine learning work? What is a neural network? Manifesto FaceSwap has ethical uses. When faceswapping was first developed and published, the technology was groundbreaking, it was a huge step in AI development. It was also completely ignored outside of academia because the code was confusing and fragmentary. It required a thorough understanding of complicated AI techniques and took a lot of effort to figure it out. Until one individual brought it together into a single, cohesive collection. It ran, it worked, and as is so often the way with new technology emerging on the internet, it was immediately used to create inappropriate content. Despite the inappropriate uses the software was given originally, it was the first AI code that anyone could download, run and learn by experimentation without having a Ph.D. in math, computer theory, psychology, and more. Before "deepfakes" these techniques were like black magic, only practiced by those who could understand all of the inner workings as described in esoteric and endlessly complicated books and papers. "Deepfakes" changed all that and anyone could participate in AI development. To us, developers, the release of this code opened up a fantastic learning opportunity. It allowed us to build on ideas developed by others, collaborate with a variety of skilled coders, experiment with AI whilst learning new skills and ultimately contribute towards an emerging technology which will only see more mainstream use as it progresses. Are there some out there doing horrible things with similar software? Yes. And because of this, the developers have been following strict ethical standards. Many of us don't even use it to create videos, we just tinker with the code to see what it does. Sadly, the media concentrates only on the unethical uses of this software. That is, unfortunately, the nature of how it was first exposed to the public, but it is not representative of why it was created, how we use it now, or what we see in its future. Like any technology, it can be used for good or it can be abused. It is our intention to develop FaceSwap in a way that its potential for abuse is minimized whilst maximizing its potential as a tool for learning, experimenting and, yes, for legitimate faceswapping. We are not trying to denigrate celebrities or to demean anyone. We are programmers, we are engineers, we are Hollywood VFX artists, we are activists, we are hobbyists, we are human beings. To this end, we feel that it's time to come out with a standard statement of what this software is and isn't as far as us developers are concerned. FaceSwap is not for creating inappropriate content. FaceSwap is not for changing faces without consent or with the intent of hiding its use. FaceSwap is not for any illicit, unethical, or questionable purposes. FaceSwap exists to experiment and discover AI techniques, for social or political commentary, for movies, and for any number of ethical and reasonable uses. We are very troubled by the fact that FaceSwap can be used for unethical and disreputable things. However, we support the development of tools and techniques that can be used ethically as well as provide education and experience in AI for anyone who wants to learn it hands-on. We will take a zero tolerance approach to anyone using this software for any unethical purposes and will actively discourage any such uses. How To setup and run the project FaceSwap is a Python program that will run on multiple Operating Systems including Windows, Linux, and MacOS. See INSTALL.md for full installation instructions. You will need a modern GPU with CUDA support for best performance. AMD GPUs are partially supported. Overview The project has multiple entry points. You will have to: Gather photos and/or videos Extract faces from your raw photos Train a model on the faces extracted from the photos/videos Convert your sources with the model Check out USAGE.md for more detailed instructions. Extract From your setup folder, run python faceswap.py extract. This will take photos from src folder and extract faces into extract folder. Train From your setup folder, run python faceswap.py train. This will take photos from two folders containing pictures of both faces and train a model that will be saved inside the models folder. Convert From your setup folder, run python faceswap.py convert. This will take photos from original folder and apply new faces into modified folder. GUI Alternatively, you can run the GUI by running python faceswap.py gui General notes: All of the scripts mentioned have -h/--help options with arguments that they will accept. You're smart, you can figure out how this works, right?! NB: there is a conversion tool for video. This can be accessed by running python tools.py effmpeg -h. Alternatively, you can use ffmpeg to convert video into photos, process images, and convert images back to the video. Some tips: Reusing existing models will train much faster than starting from nothing. If there is not enough training data, start with someone who looks similar, then switch the data. Help I need support! Discord Server Your best bet is to join the FaceSwap Discord server where there are plenty of users willing to help. Please note that, like this repo, this is a SFW Server! FaceSwap Forum Alternatively, you can post questions in the FaceSwap Forum. Please do not post general support questions in this repo as they are liable to be deleted without response. Donate The developers work tirelessly to improve and develop FaceSwap. Many hours have been put in to provide the software as it is today, but this is an extremely time-consuming process with no financial reward. If you enjoy using the software, please consider donating to the devs, so they can spend more time implementing improvements. Patreon The best way to support us is through our Patreon page: One time Donations Alternatively you can give a one off donation to any of our Devs: @torzdf There is very little FaceSwap code that hasn't been touched by torzdf. He is responsible for implementing the GUI, FAN aligner, MTCNN detector and porting the Villain, DFL-H128 and DFaker models to FaceSwap, as well as significantly improving many areas of the code. Bitcoin: bc1qpm22suz59ylzk0j7qk5e4c7cnkjmve2rmtrnc6 Ethereum: 0xd3e954dC241B87C4E8E1A801ada485DC1d530F01 Monero: 45dLrtQZ2pkHizBpt3P3yyJKkhcFHnhfNYPMSnz3yVEbdWm3Hj6Kr5TgmGAn3Far8LVaQf1th2n3DJVTRkfeB5ZkHxWozSX Paypal: @andenixa Creator of the Unbalanced and OHR models, as well as expanding various capabilities within the training process. Andenixa is currently working on new models and will take requests for donations. Paypal: How to contribute For people interested in the generative models Go to the 'faceswap-model' to discuss/suggest/commit alternatives to the current algorithm. For devs Read this README entirely Fork the repo Play with it Check issues with the 'dev' tag For devs more interested in computer vision and openCV, look at issues with the 'opencv' tag. Also feel free to add your own alternatives/improvements For non-dev advanced users Read this README entirely Clone the repo Play with it Check issues with the 'advuser' tag Also go to the 'faceswap Forum' and help others. For end-users Get the code here and play with it if you can You can also go to the faceswap Forum and help or get help from others. Be patient. This is a relatively new technology for developers as well. Much effort is already being put into making this program easy to use for the average user. It just takes time! Notice Any issue related to running the code has to be opened in the faceswap Forum! For haters Sorry, no time for that. About github.com/deepfakes What is this repo? It is a community repository for active users. Why this repo? The joshua-wu repo seems not active. Simple bugs like missing http:// in front of urls have not been solved since days. Why is it named 'deepfakes' if it is not /u/deepfakes? Because a typosquat would have happened sooner or later as project grows Because we wanted to recognize the original author Because it will better federate contributors and users What if /u/deepfakes feels bad about that? This is a friendly typosquat, and it is fully dedicated to the project. If /u/deepfakes wants to take over this repo/user and drive the project, he is welcomed to do so (Raise an issue, and he will be contacted on Reddit). Please do not send /u/deepfakes messages for help with the code you find here. About machine learning How does a computer know how to recognize/shape faces? How does machine learning work? What is a neural network? It's complicated. Here's a good video that makes the process understandable: Here's a slightly more in depth video that tries to explain the basic functioning of a neural network: tl;dr: training data + trial and error. from https://github.com/deepfakes/faceswap  -------------------------------------------------------------- DeepNude's algorithm and general image generation theory and practice research, including pix2pix, CycleGAN, UGATIT, DCGAN, SinGAN, ALAE, mGANprior, StarGAN-v2 and VAE models (TensorFlow2 implementation). DeepNude的算法以及通用生成对抗网络（GAN,Generative Adversarial Network）图像生成的理论与实践研究。    https://yuanxiaosc.github.io/2019/06/29/%E7%94%9F%E6%88%90%E5%BC%8F%E5%AF%B9%E6%8A%97%E7%BD%91%E7%BB%9C/  DeepNude-an-Image-to-Image-technology 中文版 | English Version This repository contains the pix2pixHD algorithms(proposed by NVIDIA) of DeepNude, and more importantly, the general image generation theory and practice behind DeepNude. This resource includes the TensorFlow2 (Pytorch | PaddlePaddle) implementation of image generation models such as pix2pix, CycleGAN, UGATIT, DCGAN, SinGAN, VAE, ALAE, mGANprior and StarGAN-v2, which can be used to systematically learn to Generating Adversarial Network (GAN). Content of this resource What is DeepNude? Fake Image Generation and Image-to-Image Demo DeepNude Algorithm: Normal to Pornography Image NSFW: Pornography to Normal Image, Pornographic Image Detection GAN Image Generation Theoretical Research GAN Image Generation Practice Research DeepNude to DeepFakes Future This repository is being sponsored by the following tool; please help to support us by taking a look and signing up to a free trial. What is DeepNude? DeepNude uses a slightly modified version of the pix2pixHD GAN architecture, quoted from deepnude_official. pix2pixHD is a general-purpose Image2Image technology proposed by NVIDIA. Obviously, DeepNude is the wrong application of artificial intelligence technology, but it uses Image2Image technology for researchers and developers working in other fields such as fashion, film and visual effects. Fake Image Generation Demo This section provides a fake image generation demo that you can use as you wish. They are fake images generated by StyleGAN without any copyright issues. Note: Each time you refresh the page, a new fake image will be generated, pay attention to save! Click to generate fake person image Click to generate fake cat image Click to generate fake waifu image Image-to-Image Demo This section provides a demo of Image-to-Image Demo: Black and white stick figures to colorful faces, cats, shoes, handbags. DeepNude software mainly uses Image-to-Image technology, which theoretically converts the images you enter into any image you want. You can experience Image-to-Image technology in your browser by clicking Image-to-Image Demo below. Try Image-to-faces Demo Try Image-to-Image Demo An example of using this demo is as follows： In the left side box, draw a cat as you imagine, and then click the process button, you can output a model generated cat. 🔞 DeepNude Algorithm DeepNude is a pornographic software that is forbidden by minors. If you are not interested in DeepNude itself, you can skip this section and see the general Image-to-Image theory and practice in the following chapters. DeepNude_software_itself content: Official DeepNude Algorithm(Based on Pytorch) DeepNude software usage process and evaluation of advantages and disadvantages. 👍 NSFW Recognition and conversion of five types of images [porn, hentai, sexy, natural, drawings]. Correct application of image-to-image technology. NSFW(Not Safe/Suitable For Work) is a large-scale image dataset containing five categories of images [porn, hentai, sexy, natural, drawings]. Here, CycleGAN is used to convert different types of images, such as porn->natural. Click to try pornographic image detection Demo Click Start NSFW Research Image Generation Theoretical Research This section describes DeepNude-related AI/Deep Learning theory (especially computer vision) research. If you like to read the paper and use the latest papers, enjoy it. Click here to systematically understand GAN Click here to systematically image-to-image-papers 1. Pix2Pix Berkeley 2017 paper Image-to-Image Translation with Conditional Adversarial Networks Pix2Pix homepage code pix2pix Run in Google Colab pix2pix.ipynb Result Image-to-Image Translation with Conditional Adversarial Networks is a general solution for the use of conditional confrontation networks as an image-to-image conversion problem proposed by the University of Berkeley. View more paper studies (Click the black arrow on the left to expand) Image Generation Practice Research These models are based on the latest implementation of TensorFlow2. This section explains DeepNude-related AI/Deep Learning (especially computer vision) code practices, and if you like to experiment, enjoy them. 1. Pix2Pix Use the Pix2Pix model (Conditional Adversarial Networks) to implement black and white stick figures to color graphics, flat houses to stereoscopic houses and aerial maps to maps. Click Start Experience 1 2. Pix2PixHD Under development... First you can use the official implementation 3. CycleGAN The CycleGAN neural network model is used to realize the four functions of photo style conversion, photo effect enhancement, landscape season change, and object conversion. Click Start Experience 3 4. DCGAN DCGAN is used to achieve random number to image generation tasks, such as face generation. Click Start Experience 4 5. Variational Autoencoder (VAE) VAE is used to achieve random number to image generation tasks, such as face generation. Click Start Experience 5 6. Neural style transfer Use VGG19 to achieve image style migration effects, such as photo changes to oil paintings and comics. Click Start Experience 6 If you are a user of PaddlePaddle, you can refer to the paddlepaddle version of the above model image generation model library paddegan. DeepFakes (Promotion of DeepNude) DeepFakes can be seen as an upgraded version of DeepNude, which uses a deep learning model to generate a series of techniques that can be faked, such as fake images, fake audio, and fake videos. MyVoiceYourFace Using deep fake machine learning to create a video from an image and a source video. Related paper: First Order Motion Model for Image Animation Speaker's Video + Any Image = Fake Video click to try MyVoiceYourFace Online! Realistic Speech-Driven Facial Animation with GANs One photo + One audio = Composite Video We propose a temporal GAN capable of producing animated faces using only a still image of a person and an audio clip containing speech. The videos generated using this model do not only produce lip movements that are synchronized with the audio but also exhibit characteristic facial expressions such as blinks, brow raises etc. This extends our previous model by separately dealing with audio-visual synchronization and expression generation. Our improved model works on "in-the-wild" unseen faces and is capable of capturing the emotion of the speaker and reflecting it in the facial expression. Samsung and Imperial College London 2019 paper Realistic Speech-Driven Facial Animation with GANs Facial Animation homepage code Speech-Driven Animation Interested in DeepFakes? Click to start systematic learning DeepFakes Future Click read more... from https://github.com/yuanxiaosc/DeepNude-an-Image-to-Image-technology  ---------------------------------------------------------------------------------------------- Deepnude脱衣可了解乎？原理 前阵子AI换脸很火，现在也很火，这不，又出来一个AI脱衣服，逗死我了，只要把任意一张图片上传到应用中，立即分分钟把衣服给脱光，一件都不剩，很是智能了，而且是傻瓜式操作，好东西必须要分享啊，于是就有了今天这篇文章。 应用介绍 DeepNude可以真正实现图像到图像的目的，并且生成的图像更加真实。能让所有图片都一丝不挂，所以对于众多绅士来说，绝对称得上一款神器。可以参考github上的这个项目学习， https://github.com/yuanxiaosc/DeepNude-an-Image-to-Image-technology。 使用方法 下载压缩包，解压缩文件 运行里面的exe文件，应用内上传图片 调整图片大小后，点击转换 等待30秒-2分钟左右，脱衣图片生成 温馨提示 下载链接又有了，可以下载了！ 类似应用 还有一款类似应用，名为dreamtime，功能似乎比这款更强大。		-		--

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Real-time face swap for PC streaming or video calls.

Face Swap (DFM)

You can swap your face from a webcam or the face in the video using trained face models. Here is a list of available ready-to-use public face models. These persons do not exists. Similarities with real people are accidental. Except Keanu Reeves. He exists, and he's breathtaking!

Keanu Reeves examples Irina Arty examples Millie Park examples Rob Doe examples Jesse Stat examples Bryan Greynolds examples Mr. Bean examples Ewon Spice examples Natasha Former examples Emily Winston examples Ava de Addario examples Dilraba Dilmurat examples Matilda Bobbie examples Yohanna Coralson examples Amber Song examples Kim Jarrey examples David Kovalniy examples Jackie Chan examples Nicola Badge examples Joker examples Dean Wiesel examples Silwan Stillwone examples Tim Chrys examples Zahar Lupin examples Tim Norland examples Natalie Fatman examples Liu Lice examples Albica Johns examples Meggie Merkel examples Tina Shift examples

If you want a higher quality or better face match, you can train your own face model using DeepFaceLab Here is an example of Arnold Schwarzneggar trained on a particular face and used in a video call. Read the FAQ for more information.

Face Swap (Insight)

You can swap your face from a webcam or the face in the video using your own single photo.

Face Animator

There is also a Face Animator module in DeepFaceLive app. You can control a static face picture using video or your own face from the camera. The quality is not the best, and requires fine face matching and tuning parameters for every face pair, but enough for funny videos and memes or real-time streaming at 25 fps using 35 TFLOPS GPU. Here is a mini video showing the process of setting up the Face Animator for Obama controlling Kim Chen's face.

System requirements

any DirectX12 compatible graphics card (Recommended RTX 2070+ / Radeon RX 5700 XT+ ) Modern CPU with AVX instructions 4GB RAM, 32GB+ paging file Windows 10

Documentation

Windows	Main setup additional setup for streaming additional setup for video calls Using Android phone camera
Linux	Build info
Frequently asked questions	for User for Developer
Releases
Windows 10 x64 (yandex.ru) Windows 10 x64 (mega.nz)	Contains stand-alone zero-dependency all-in-one ready-to-use portable self-extracting folder! You don't need to install anything other than video drivers. DirectX12 build : NVIDIA, AMD, Intel videocards. NVIDIA build : NVIDIA cards only, GT730 and higher. Works faster than DX12. FaceMerger can work also on AMD/Intel.
Communication groups
Discord	Official discord channel. English / Russian.
mrdeepfakes	the biggest NSFW English deepfake community
dfldata.cc	中文交流论坛，免费软件教程、模型、人脸数据

       

from https://github.com/iperov/DeepFaceLive