Avatarify Python - Avatars for Zoom, Skype and other video-conferencing apps.

Overview

Avatarify Python

Photorealistic avatars for video-conferencing.

Avatarify Python requires manually downloading and installing some dependencies, and is therefore best suited for users who have some experience with command line applications. Avatarify Desktop, which aims to be easier to install and use, is recommended for most users. If you still want to use Avatarify Python, proceed to the install instructions.

Based on First Order Motion Model.

Avatarify Python is not affiliated with Avatarify Inc.

News

  • 7 Mar 2021. Renamed project to Avatarify Python to distinguish it from other versions of Avatarify
  • 14 December 2020. Released Avatarify Desktop. Check it out here.
  • 11 July 2020. Added Docker support. Now you can run Avatarify from Docker on Linux. Thanks to mikaelhg and mintmaker for contribution!
  • 22 May 2020. Added Google Colab mode. Now you can run Avatarify on any computer without GPU!
  • 7 May 2020. Added remote GPU support for all platforms (based on mynameisfiber's solution). Demo. Deployment instructions.
  • 24 April 2020. Added Windows installation tutorial.
  • 17 April 2020. Created Slack community. Please join via invitation link.
  • 15 April 2020. Added StyleGAN-generated avatars. Just press Q and now you drive a person that never existed. Every time you push the button – new avatar is sampled.
  • 13 April 2020. Added Windows support (kudos to 9of9).
Comments
  • Dockerize the

    Dockerize the "Remote GPU" service

    This PR needs some testing before merging, so I'm creating it as a draft.

    Based on my previous contribution to AliaksandrSiarohin/first-order-model#55.

    Building

    docker build -t avatarify .
    

    Running

    docker run -it --rm --gpus=all -p 5557:5557 -p 5558:5558 avatarify
    
    opened by mikaelhg 47
  • Broken pipe

    Broken pipe

    ffmpeg version 4.1.4-1build2 Copyright (c) 2000-2019 the FFmpeg developers
      built with gcc 9 (Ubuntu 9.2.1-4ubuntu1)
      configuration: --prefix=/usr --extra-version=1build2 --toolchain=hardened --libdir=/usr/lib/x86_64-linux-gnu --incdir=/usr/include/x86_64-linux-gnu --arch=amd64 --enable-gpl --disable-stripping --enable-avresample --disable-filter=resample --enable-avisynth --enable-gnutls --enable-ladspa --enable-libaom --enable-libass --enable-libbluray --enable-libbs2b --enable-libcaca --enable-libcdio --enable-libcodec2 --enable-libflite --enable-libfontconfig --enable-libfreetype --enable-libfribidi --enable-libgme --enable-libgsm --enable-libjack --enable-libmp3lame --enable-libmysofa --enable-libopenjpeg --enable-libopenmpt --enable-libopus --enable-libpulse --enable-librsvg --enable-librubberband --enable-libshine --enable-libsnappy --enable-libsoxr --enable-libspeex --enable-libssh --enable-libtheora --enable-libtwolame --enable-libvidstab --enable-libvorbis --enable-libvpx --enable-libwavpack --enable-libwebp --enable-libx265 --enable-libxml2 --enable-libxvid --enable-libzmq --enable-libzvbi --enable-lv2 --enable-omx --enable-openal --enable-opengl --enable-sdl2 --enable-libdc1394 --enable-libdrm --enable-libiec61883 --enable-chromaprint --enable-frei0r --enable-libx264 --enable-shared
      libavutil      56. 22.100 / 56. 22.100
      libavcodec     58. 35.100 / 58. 35.100
      libavformat    58. 20.100 / 58. 20.100
      libavdevice    58.  5.100 / 58.  5.100
      libavfilter     7. 40.101 /  7. 40.101
      libavresample   4.  0.  0 /  4.  0.  0
      libswscale      5.  3.100 /  5.  3.100
      libswresample   3.  3.100 /  3.  3.100
      libpostproc    55.  3.100 / 55.  3.100
    0: ./avatars/mona.jpg
    cam_fomm.py:26: YAMLLoadWarning: calling yaml.load() without Loader=... is deprecated, as the default Loader is unsafe. Please read https://msg.pyyaml.org/load for full details.
      config = yaml.load(f)
    [mjpeg @ 0x561a4d0f8a00] Format mjpeg detected only with low score of 25, misdetection possible!
    Input #0, mjpeg, from 'pipe:0':                                                                                                                           
      Duration: N/A, bitrate: N/A
        Stream #0:0: Video: mjpeg, yuvj420p(pc, bt470bg/unknown/unknown), 640x480 [SAR 1:1 DAR 4:3], 25 tbr, 1200k tbn, 25 tbc
    Stream mapping:
      Stream #0:0 -> #0:0 (mjpeg (native) -> rawvideo (native))
    [swscaler @ 0x561a4d153040] deprecated pixel format used, make sure you did set range correctly
    [video4linux2,v4l2 @ 0x561a4d0fe680] ioctl(VIDIOC_G_FMT): Invalid argument                                                                                
    Could not write header for output file #0 (incorrect codec parameters ?): Invalid argument                                                                
    Error initializing output stream 0:0 --                                                                                                                   
    Conversion failed!                                                                                                                                        
    Traceback (most recent call last):
      File "cam_fomm.py", line 173, in <module>
        sys.stdout.buffer.write(buf)
    BrokenPipeError: [Errno 32] Broken pipe
    Exception ignored in: <_io.TextIOWrapper name='<stdout>' mode='w' encoding='utf-8'>
    BrokenPipeError: [Errno 32] Broken pipe
    
    opened by zuenko 42
  • Error when run

    Error when run "bash run.sh"

    Hi,

    I pull the last commit, executed again the install.sh and tryed run:

    bash run.sh

    But this error occours:

    (avatarify) [email protected]:~/Repository/others/avatarify$ bash run.sh 0: ./avatars/einstein.jpg 1: ./avatars/eminem.jpg 2: ./avatars/jobs.jpg 3: ./avatars/mona.jpg 4: ./avatars/obama.jpg 5: ./avatars/potter.jpg 6: ./avatars/ronaldo.png 7: ./avatars/schwarzenegger.png load checkpoints.. cam_fomm.py:34: YAMLLoadWarning: calling yaml.load() without Loader=... is deprecated, as the default Loader is unsafe. Please read https://msg.pyyaml.org/load for full details. config = yaml.load(f) Traceback (most recent call last): File "cam_fomm.py", line 231, in stream = pyfakewebcam.FakeWebcam(f'/dev/video{opt.virt_cam}', frame.shape[1], frame.shape[0]) File "/home/eltonnunes/.conda/envs/avatarify/lib/python3.8/site-packages/pyfakewebcam/pyfakewebcam.py", line 54, in init fcntl.ioctl(self._video_device, _v4l2.VIDIOC_S_FMT, self._settings) OSError: [Errno 22] Invalid argument

    Anyone can help ?

    My OS: Linux Mint 19.3 Cinnamon

    opened by eltonnuness 27
  • When run_windows.bat is finished, the two windows do not pop up. (avatarify does not launch)

    When run_windows.bat is finished, the two windows do not pop up. (avatarify does not launch)

    Describe the bug

    To Reproduce

    Info (please complete the following information):

    • OS (e.g., Linux):
    • GPU model:
    • Any other relevant information:

    Screenshots

    Logs

    duplicate 
    opened by board808 19
  • Getting multiple cam windows opened while running run.sh

    Getting multiple cam windows opened while running run.sh

    I am on latest Ubuntu I have installed correctly and updated everything but when I run bash run.sh then it didn't. Run so I run with sudo bash run.sh but so it sometime shows me avatar list to select and sometimes it open webcam and when I press X and configure my face than multiple cam windows start opening and I can't understand what's the issue and how to fix it please help me out

    opened by shwetkanwal24 19
  • Error with run_windows.bat

    Error with run_windows.bat

    RuntimeError: CUDA error: no kernel image is available for execution on the device

    I have a Windows 10 machine with Nvidia GTX Titan card. Nvidia says it supports CUDA 3.5 which I think is the minimum required?

    Also I read in the notes that it should fall to the CPU if the GPU isn't supported? How would I configure that if the card is the problem?

    opened by virtualmonster 17
  • No module named 'sync_batchnorm'

    No module named 'sync_batchnorm'

    Windows 10 system.

    Traceback (most recent call last): File "cam_fomm.py", line 13, in from sync_batchnorm import DataParallelWithCallback ModuleNotFoundError: No module named 'sync_batchnorm'

    opened by newtonke 17
  • Add overlay drawing of landmarks

    Add overlay drawing of landmarks

    Seeing the landmarks of both the current frame and the avatar can make it easier to get a good pose. I also thought it was interesting to expose a little of the underlying techniques

    opened by JohanAR 16
  • How to find the IP address of Google Colab Notebook

    How to find the IP address of Google Colab Notebook

    Hi, I want to run avatarify on macOS, but I need to use google colab... How do I find the IP address of the notebook so I can connect to the server? I tried to put the !curl ipecho.net/plain command in the notebook and I received an IP, but when I use this IP, the terminal is stuck on Receiving from.

    This is the google colab command:

    google_colab_command

    and this is what I see in the terminal: terminal

    opened by tvtr04 16
  • DLL load failed: The specified module could not be found.

    DLL load failed: The specified module could not be found.

    Error when running run_windows.bat

    File "cam_fomm.py", line 11, in import cv2 ImportError: DLL load failed: The specified module could not be found.

    Tried to install different opencv libraries to no avail. Any ideas how to solve this?

    more info needed 
    opened by kratadata 16
  • ModuleNotFoundError: No module named 'yaml'

    ModuleNotFoundError: No module named 'yaml'

    (base) E:\avatarify>run_windows.bat --is-client --in-addr tcp://2.tcp.eu.ngrok.io:10176 --out-addr tcp://0.tcp.eu.ngrok.io:12257 Traceback (most recent call last): File "afy/cam_fomm.py", line 4, in import yaml ModuleNotFoundError: No module named 'yaml'

    opened by fazelukario 15
  • Corrupt vox-adv-cpk.pth.tar

    Corrupt vox-adv-cpk.pth.tar

    Describe the bug

    initially the tar file has a 3 textbook icon but whenever I download it now it shows a regular file icon and that is the problem. Even if you move it into the right directory it’s still gonna show file not found

    Info (please complete the following information):

    • OS (windows 10 home):
    • GPU model: GeForce 1660 ti,windows 10 home, 6gb graphics
    • Any other relevant information:

    Screenshots

    Logs

    opened by Denvercraig 3
  • TROUBLE RUNNING AVATARIFY ON COLAB SERVER FOR MAC

    TROUBLE RUNNING AVATARIFY ON COLAB SERVER FOR MAC

    Hello guys, I really need a bit of help running Avatarify on the Google Colab server since I use a Mac. I already have Miniconda and unpacked the repositories in the Avatarify Folder. I was following the steps for running on google collab, everything was going just about right until the "start the worker" section of the code. Can anyone advise on what to do. I have a screenshot of th result attached to thisScreen Shot 2022-12-29 at 11 04 52 AM

    cloud gpu 
    opened by oveentheproduza 0
  • Avatar folder missing after forced shutdown

    Avatar folder missing after forced shutdown

    Laptop shutdown due to overheating, now I open avatarify.... it’s working fine but I can’t find the avatar folder to add new model or remove existing ones. I’ve search every where but nothing. Pls help.

    opened by Twabor 1
  • Python avatarify

    Python avatarify

    I have a problem, after I give the git clone command and equip it using the cd avatarify python command, I try to compile with the other command and this error returns me "avatarify python failed solving environment",what i do?

    opened by Bitchlinux 0
  • Error any time I try to run windows.bat

    Error any time I try to run windows.bat

    option --use-feature: invalid choice: '2020-resolver' (choose from "fast-deps', 'truststor che')

    I tried installing from scratch as I always does that work fine but now when I try ruining the scripts.windows.bat it gives me this at the end process

    opened by mandontsmile 11
Releases(v0.2.0)
Owner
Ali Aliev
Computer graphics
Ali Aliev
Revisiting Contrastive Methods for Unsupervised Learning of Visual Representations. [2021]

Revisiting Contrastive Methods for Unsupervised Learning of Visual Representations This repo contains the Pytorch implementation of our paper: Revisit

Wouter Van Gansbeke 80 Nov 20, 2022
Transformer based SAR image despeckling

Transformer based SAR image despeckling Using the code: The code is stable while using Python 3.6.13, CUDA =10.1 Clone this repository: git clone htt

27 Nov 13, 2022
DGN pymarl - Implementation of DGN on Pymarl, which could be trained by VDN or QMIX

This is the implementation of DGN on Pymarl, which could be trained by VDN or QM

4 Nov 23, 2022
Lane follower: Lane-detector (OpenCV) + Object-detector (YOLO5) + CAN-bus

Lane Follower This code is for the lane follower, including perception and control, as shown below. Environment Hardware Industrial Camera Intel-NUC(1

Siqi Fan 3 Jul 07, 2022
WaveFake: A Data Set to Facilitate Audio DeepFake Detection

WaveFake: A Data Set to Facilitate Audio DeepFake Detection This is the code repository for our NeurIPS 2021 (Track on Datasets and Benchmarks) paper

Chair for Sys­tems Se­cu­ri­ty 27 Dec 22, 2022
Code, environments, and scripts for the paper: "How Private Is Your RL Policy? An Inverse RL Based Analysis Framework"

Privacy-Aware Inverse RL (PRIL) Analysis Framework Code, environments, and scripts for the paper: "How Private Is Your RL Policy? An Inverse RL Based

1 Dec 06, 2021
Music Source Separation; Train & Eval & Inference piplines and pretrained models we used for 2021 ISMIR MDX Challenge.

Introduction 1. Usage (For MSS) 1.1 Prepare running environment 1.2 Use pretrained model 1.3 Train new MSS models from scratch 1.3.1 How to train 1.3.

Leo 100 Dec 25, 2022
Python wrappers to the C++ library SymEngine, a fast C++ symbolic manipulation library.

SymEngine Python Wrappers Python wrappers to the C++ library SymEngine, a fast C++ symbolic manipulation library. Installation Pip See License section

136 Dec 28, 2022
DECAF: Generating Fair Synthetic Data Using Causally-Aware Generative Networks

DECAF (DEbiasing CAusal Fairness) Code Author: Trent Kyono This repository contains the code used for the "DECAF: Generating Fair Synthetic Data Using

van_der_Schaar \LAB 7 Nov 24, 2022
It's like Shape Editor in Maya but works with skeletons (transforms).

Skeleposer What is Skeleposer? Briefly, it's like Shape Editor in Maya, but works with transforms and joints. It can be used to make complex facial ri

Alexander Zagoruyko 1 Nov 11, 2022
A very simple tool to rewrite parameters such as attributes and constants for OPs in ONNX models. Simple Attribute and Constant Modifier for ONNX.

sam4onnx A very simple tool to rewrite parameters such as attributes and constants for OPs in ONNX models. Simple Attribute and Constant Modifier for

Katsuya Hyodo 6 May 15, 2022
Evaluating AlexNet features at various depths

Linear Separability Evaluation This repo provides the scripts to test a learned AlexNet's feature representation performance at the five different con

Yuki M. Asano 32 Dec 30, 2022
PyTorch implementation for paper Neural Marching Cubes.

NMC PyTorch implementation for paper Neural Marching Cubes, Zhiqin Chen, Hao Zhang. Paper | Supplementary Material (to be updated) Citation If you fin

Zhiqin Chen 109 Dec 27, 2022
Tensorflow Implementation of the paper "Spectral Normalization for Generative Adversarial Networks" (ICML 2017 workshop)

tf-SNDCGAN Tensorflow implementation of the paper "Spectral Normalization for Generative Adversarial Networks" (https://www.researchgate.net/publicati

Nhat M. Nguyen 248 Nov 25, 2022
IOT: Instance-wise Layer Reordering for Transformer Structures

Introduction This repository contains the code for Instance-wise Ordered Transformer (IOT), which is introduced in the ICLR2021 paper IOT: Instance-wi

IOT 19 Nov 15, 2022
Orthogonal Over-Parameterized Training

The inductive bias of a neural network is largely determined by the architecture and the training algorithm. To achieve good generalization, how to effectively train a neural network is of great impo

Weiyang Liu 11 Apr 18, 2022
Towards Understanding Quality Challenges of the Federated Learning: A First Look from the Lens of Robustness

FL Analysis This repository contains the code and results for the paper "Towards Understanding Quality Challenges of the Federated Learning: A First L

3 Oct 17, 2022
This is a repo of basic Machine Learning!

Basic Machine Learning This repository contains a topic-wise curated list of Machine Learning and Deep Learning tutorials, articles and other resource

Ekram Asif 53 Dec 31, 2022
The implement of papar "Enhanced Graph Learning for Collaborative Filtering via Mutual Information Maximization"

SIGIR2021-EGLN The implement of paper "Enhanced Graph Learning for Collaborative Filtering via Mutual Information Maximization" Neural graph based Col

15 Dec 27, 2022
My implementation of transformers related papers for computer vision in pytorch

vision_transformers This is my personnal repo to implement new transofrmers based and other computer vision DL models I am currenlty working without a

samsja 1 Nov 10, 2021