LAFITE: Towards Language-Free Training for Text-to-Image Generation

Code for paper LAFITE: Towards Language-Free Training for Text-to-Image Generation (CVPR 2022)

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Requirements

The implementation is based on stylegan2-ada-pytorch and CLIP, the required packages can be found in the links.

Preparing Datasets

Example:

python dataset_tool.py --source=./path_to_some_dataset/ --dest=./datasets/some_dataset.zip --width=256 --height=256 --transform=center-crop

the files at ./path_to_some_dataset/ should be like:

./path_to_some_dataset/

  ├  1.png

  ├  1.txt

  ├  2.png

  ├  2.txt

  ├  …

We provide links to several commonly used datasets that we have already processed (with CLIP-ViT/B-32):

MS-COCO Training Set

MS-COCO Validation Set

LN-COCO Training Set

LN-COCO Testing Set

Multi-modal CelebA-HQ Training Set

Multi-modal

 

 

 

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