StyleGAN workshop

Setup

1. Signing into Jupyterhub via keycloak

key in your keycloak credentials here

Choose an XS slice

make sure to choose cuda 11.7 from the dropdown

2. Installing Stylegan3

git clone https://github.com/NVlabs/stylegan3.git

cd stylegan3

conda init bash

source ~/.bashrc

conda env create -f environment.yml

conda activate stylegan3

conda install cudatoolkit

downloading models

make 'pretrained' directory

mkdir pretrained

ffhq flicker faces

wget --no-check-certificate --content-disposition https://th-koeln.sciebo.de/s/j06LuPxYHRRtnQE/download -O pretrained/ffhq_faces.pkl

Wikiart

wget --no-check-certificate --content-disposition https://th-koeln.sciebo.de/s/tbjJS7XBezbAC3B/download -O pretrained/wikiart.pkl

Metfaces

wget --no-check-certificate --content-disposition https://th-koeln.sciebo.de/s/eFZAmR6dDLelSo7/download -O pretrained/metfaces.pkl

Inference

activating conda environment

this needs to be done before every session if you want to use stylegan

conda init bash

source ~/.bashrc

conda activate stylegan3

inference images

python gen_images.py --outdir=out --trunc=1 --seeds=2 --network=https://api.ngc.nvidia.com/v2/models/nvidia/research/stylegan3/versions/1/files/stylegan3-r-afhqv2-512x512.pkl

inference video

python gen_video.py --output=out/wikiart.mp4 --trunc=1 --seeds=0-31 --network=pretrained/wikiart.pkl

Training

Dowload Training data

mkdir trainingdata

Group 01

wget --no-check-certificate --content-disposition https://th-koeln.sciebo.de/s/7SzJ55ZroKPf5zY/download -O trainingdata/group01.zip

Group 02

wget --no-check-certificate --content-disposition https://th-koeln.sciebo.de/s/7SzJ55ZroKPf5zY/download -O trainingdata/group02.zip

Group 03

wget --no-check-certificate --content-disposition https://th-koeln.sciebo.de/s/YGR7BaeoIBSePNl/download -O trainingdata/group03.zip

Group 04

wget --no-check-certificate --content-disposition https://th-koeln.sciebo.de/s/SsrPKyPcyswd8z2/download -O trainingdata/group04.zip

Group 05

wget --no-check-certificate --content-disposition https://th-koeln.sciebo.de/s/b1I0rgEaPcyaP44/download -O trainingdata/group05

Group 06

wget --no-check-certificate --content-disposition https://th-koeln.sciebo.de/s/Orv9FDqqKwtBMlB/download -O trainingdata/group06

Prepare training data

python dataset_tool.py --source=trainingdata/group01.zip --destination=trainingdata/group01 --resolution=512x512

start training

python train.py --help

downloading dangerzones models

go into directory pretrained:

cd pretrained

Download our trained models from the KISD Modelzoo:

Group 01 - androids gynoids

wget --no-check-certificate --content-disposition https://th-koeln.sciebo.de/s/B7rOZIRzPN5rev1/download -O pretrained/group_01_220.pkl

Group 02 TBF - dataset error

Group 03 - grayscale faces

wget --no-check-certificate --content-disposition https://th-koeln.sciebo.de/s/SRcjw6DPv9AIacn/download -O pretrained/group_03_500.pkl

Group 04 -future cities

wget --no-check-certificate --content-disposition https://th-koeln.sciebo.de/s/CW8uQ2dsQbVOiXa/download -O pretrained/group_04_20.pkl

Group 05 - lamppost and sunflowers

wget --no-check-certificate --content-disposition https://th-koeln.sciebo.de/s/eFZAmR6dDLelSo7/download -O pretrained/metfaces.pkl

Group 05 - encoded data