Create README.md

README.md

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+---
+license: mit
+---
+
+# User-Controllable Latent Transformer for StyleGAN Image Layout Editing
+
+Yuki Endo: "User-Controllable Latent Transformer for StyleGAN Image Layout Editing," Computer Graphpics Forum (Pacific Graphics 2022) [[Project](http://www.cgg.cs.tsukuba.ac.jp/~endo/projects/UserControllableLT)] [[PDF (preprint)](http://arxiv.org/abs/2208.12408)]
+
+## Prerequisites  
+1. Python 3.8
+2. PyTorch 1.9.0
+3. Flask
+4. Others (see env.yml)
+
+## Preparation
+Download and decompress <a href="https://drive.google.com/file/d/1lBL_J-uROvqZ0BYu9gmEcMCNyaPo9cBY/view?usp=sharing">our pre-trained models</a>.
+
+## Inference with our pre-trained models
+We provide an interactive interface based on Flask. This interface can be locally launched with
+```
+python interface/flask_app.py --checkpoint_path=pretrained_models/latent_transformer/cat.pt
+```
+The interface can be accessed via http://localhost:8000/.
+
+## Training
+The latent transformer can be trained with
+```
+python scripts/train.py --exp_dir=results --stylegan_weights=pretrained_models/stylegan2-cat-config-f.pt
+```
+To perform training with your dataset, you need first to train StyleGAN2 on your dataset using [rosinality's code](https://github.com/rosinality/stylegan2-pytorch) and then run the above script with specifying the trained weights. 
+
+## Citation
+Please cite our paper if you find the code useful:
+```
+@Article{endoPG2022,
+Title = {User-Controllable Latent Transformer for StyleGAN Image Layout Editing},
+Author = {Yuki Endo},
+Journal = {Computer Graphics Forum},
+volume = {41},
+number = {7},
+pages = {395-406},
+doi = {10.1111/cgf.14686},
+Year = {2022}
+}
+```
+
+## Acknowledgements
+This code heavily borrows from the [pixel2style2pixel](https://github.com/eladrich/pixel2style2pixel) and [expansion](https://github.com/gengshan-y/expansion) repositories.