Usage

Get CUDA and latest Nvidia drivers. After that, follow the following steps:

WARNING FOR WINDOWS USERS: Docker Desktop 4.17.1 is broken. I confirmed that 4.25.0 should work. Older tested versions are 4.16.3 or 4.17.0. I would recommend to use 4.25.0. 4.17.1 results in Docker not starting which is mentioned in this issue.

ANOTHER WARNING FOR PEOPLE WITHOUT AVX512: Instead of using styler00dollar/vsgan_tensorrt:latest, which I build with my 7950x and thus with all AVX, use styler00dollar/vsgan_tensorrt:latest_no_avx512 in compose.yaml to avoid Illegal instruction (core dumped) which is mentioned in this issue.

AND AS A FINAL INFO, Error opening input file pipe: IS NOT A REAL ERROR MESSAGE. That means invalid data got piped into ffmpeg and can be piped error messages for example. To see the actual error messages and what got piped, you can use vspipe -c y4m inference.py -.

Quickstart:

# if you have Windows, install Docker Desktop https://www.docker.com/products/docker-desktop/
# if you encounter issues, install one of the following versions:
# 4.16.3: https://desktop.docker.com/win/main/amd64/96739/Docker%20Desktop%20Installer.exe
# 4.17.0: https://desktop.docker.com/win/main/amd64/99724/Docker%20Desktop%20Installer.exe

# if you have Arch, install the following dependencies
yay -S docker nvidia-docker nvidia-container-toolkit docker-compose docker-buildx

# run the docker with docker-compose
# you need to be inside the vsgan folder with cli before running the following step, git clone repo and cd into it
# go into the vsgan folder, inside that folder should be compose.yaml, run this command
# you can adjust folder mounts in the yaml file
docker-compose run --rm vsgan_tensorrt

There are now multiple containers to choose from, if you don't want the default, then edit compose.yaml and set a different tag image: styler00dollar/vsgan_tensorrt:x prior to running docker-compose run --rm vsgan_tensorrt.

• latest: Default docker with everything. Trying to keep everything updated and fixed.
• latest_no_avx512 is for cpus without avx512 support, otherwise it just crashes if you try to run avx512 binaries on cpus without such support. Use this if your cpu does not support all instruction sets.
• minimal: Bare minimum to run ffmpeg, mlrt and a few video readers.

Piping usage:

# you can use it in various ways, ffmpeg example
vspipe -c y4m inference.py - | ffmpeg -i pipe: example.mkv -y

# example without vspipe
ffmpeg -f vapoursynth -i inference.py example.mkv -y

# example with ffmpeg trt plugin + nvenc
ffmpeg -hwaccel cuda -hwaccel_output_format cuda -i input.mp4 -vf scale_npp=1280:720,format_cuda=rgbpf32le,tensorrt=my_engine.engine,format_cuda=nv12 -c:v hevc_nvenc -preset lossless output.mkv -y
# example with ffmpeg trt plugin + hwdownload (cpu encoding)
ffmpeg -hwaccel cuda -hwaccel_output_format cuda -i input.mp4 -vf format_cuda=rgbpf32le,tensorrt=my_engine.engine,format_cuda=nv12,hwdownload,format=nv12 -vcodec ffv1 output.mkv -y

If docker does not want to start, try this before you use docker:

# fixing docker errors
sudo systemctl start docker
sudo chmod 666 /var/run/docker.sock

Linux docker autostart:

sudo systemctl enable --now docker

The following stuff is for people who want to run things from scratch. Manual ways of downloading the docker image:

# Download prebuild image from dockerhub (recommended)
docker pull styler00dollar/vsgan_tensorrt:latest

# if you have `unauthorized: authentication required` problems, download the docker with
git clone https://github.com/NotGlop/docker-drag
cd docker-drag
python docker_pull.py styler00dollar/vsgan_tensorrt:latest
docker load -i