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113 lines
3.4 KiB
Markdown
113 lines
3.4 KiB
Markdown
# faceit_live3
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This is an update to http://github.com/faceit_live using [first order model](https://github.com/AliaksandrSiarohin/first-order-model) by Aliaksandr Siarohin to generate the images. This model only requires a single image, so no training is needed and things are much easier.
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# Setup
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## Requirements
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This has been tested on **Ubuntu 18.04 with a Titan RTX/X GPU**.
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You will need the following to make it work:
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Linux host OS
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NVidia fast GPU (GTX 1080, GTX 1080i, Titan, etc ...)
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Fast Desktop CPU (Quad Core or more)
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NVidia CUDA 10 and cuDNN 7 libraries installed
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Webcam
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## Setup Host System
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To use the fake webcam feature to enter conferences with our stream we need to insert the **v4l2loopback** kernel module in order to create */dev/video1*. Follow the install instructions at (https://github.com/umlaeute/v4l2loopback), then let's setup our fake webcam:
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```
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$ git clone https://github.com/umlaeute/v4l2loopback.git
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$ make && sudo make install
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$ sudo depmod -a
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$ sudo modprobe v4l2loopback devices=1
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$ sudo modprobe v4l2loopback exclusive_caps=1 card_label="faceit_live" video_nr=1
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$ v4l2-ctl -d /dev/video1 -c timeout=1000
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```
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# v4l2loopback-ctl set-timeout-image caio.png /dev/video1
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Change the video_nr above in case you already have a webcam running on /dev/video1
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To check if things are working, try running an mp4 to generate a video the */dev/video1* (replace ale.mp4 with your own video).
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```
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$ ffmpeg -re -i media/ale.mp4 -f v4l2 /dev/video1 -loop 10
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```
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And view it
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```
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$ ffplay -f v4l2 /dev/video1
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```
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On Ubuntu 18, I had to make a minor change to the source code of v4l2loopback.c to get loopback working. In case the above doesn't work, you can try this change before running *make* :
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```
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# v4l2loopback.c
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from
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#if LINUX_VERSION_CODE >= KERNEL_VERSION(2, 6, 29)
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to
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#if LINUX_VERSION_CODE >= KERNEL_VERSION(3,7,0)
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```
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You can also inspect your /dev/video* devices:
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```
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$ v4l2-ctl --list-devices
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$ v4l2-ctl --list-formats -d /dev/video1
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```
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If you have more than one GPU, you might need to set some environment variables:
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```
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# specify which display to use for rendering
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$ export DISPLAY=:1
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# which CUDA DEVICE to use (run nvidia-smi to discover the ID)
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$ export CUDA_VISIBLE_DEVICES = 0
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```
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## Clone this repository
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Don't forget to use the *--recurse-submodules* parameter to checkout all dependencies.
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$ git clone --recurse-submodules https://github.com/alew3/faceit_live3.git /local_path/
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## Create an Anaconda environment and install requirments
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```
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$ conda create -n faceit_live3 python=3.8
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$ source activate faceit_live3
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$ conda install pytorch=1.4 torchvision=0.5 cudatoolkit=10.1 -c pytorch
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$ pip install -r requirements.txt
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```
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## Download 'vox-adv-cpk.pth.tar' to /models folder
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You can find it at: [google-drive](https://drive.google.com/open?id=1PyQJmkdCsAkOYwUyaj_l-l0as-iLDgeH) or [yandex-disk](https://yadi.sk/d/lEw8uRm140L_eQ).
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# Usage
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Put in the `./media/` directory the images in jpg/png you want to play with.
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# Run the program
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```
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$ python faceit_live.py
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```
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## Parameters
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--webcam # the videoid of the Webcam e.g. 0 if /dev/video0 (default is 0)
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--image # the face to use for transformations, put the files inside media (by default it loads the first image in the folder)
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--streamto # the /dev/video number to stream to (default is 1)
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## Example
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```
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$ python faceit_live.py --webcam 0 --stream 1 --image oliver.jpg
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```
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