full Notebooks also Avaliable on notebook folder
notebooks:
Install Pytorch in the new enviroment:
pip install torch==1.9.0+cu111 torchvision==0.10.0+cu111 torchaudio==0.9.0 -f https://download.pytorch.org/whl/torch_stable.htmlInstall other required Python packages:
pip install ftfy regex tqdm omegaconf pytorch-lightning IPython kornia imageio imageio-ffmpeg einops torch_optimizer setuptools==59.5.0Or use the requirements.txt file, which includes version numbers.
Clone required repositories:
git clone 'https://github.com/nerdyrodent/VQGAN-CLIP'
cd VQGAN-CLIP
git clone 'https://github.com/openai/CLIP'
git clone 'https://github.com/CompVis/taming-transformers'mkdir checkpoints
curl -L -o checkpoints/vqgan_imagenet_f16_16384.yaml -C - 'https://heibox.uni-heidelberg.de/d/a7530b09fed84f80a887/files/?p=%2Fconfigs%2Fmodel.yaml&dl=1' #ImageNet 16384
curl -L -o checkpoints/vqgan_imagenet_f16_16384.ckpt -C - 'https://heibox.uni-heidelberg.de/d/a7530b09fed84f80a887/files/?p=%2Fckpts%2Flast.ckpt&dl=1' #ImageNet 16384Note that users of curl on Microsoft Windows should use double quotes.
The download_models.sh script is an optional way to download a number of models. By default, it will download just 1 model.
See https://github.com/CompVis/taming-transformers#overview-of-pretrained-models for more information about VQGAN pre-trained models, including download links.
By default, the model .yaml and .ckpt files are expected in the checkpoints directory.
See https://github.com/CompVis/taming-transformers for more information on datasets and models.
To generate images from text, specify your text prompt as shown in the example below:
python generate.py -p "A painting of an apple in a fruit bowl"
Text and image prompts can be split using the pipe symbol in order to allow multiple prompts. You can also use a colon followed by a number to set a weight for that prompt. For example:
python generate.py -p "A painting of an apple in a fruit bowl | psychedelic | surreal:0.5 | weird:0.25"