Update README.md

Author: williamyang1991

README.md

@@ -78,6 +78,7 @@ Pretrained models can be downloaded from [Google Drive](https://drive.google.com
 | Model | Description |
 | :--- | :--- |
 | [encoder](https://drive.google.com/file/d/1NgI4mPkboYvYw3MWcdUaQhkr0OWgs9ej/view?usp=sharing) | Pixel2style2pixel encoder that embeds FFHQ images into StyleGAN2 Z+ latent code |
+| [encoder_wplus](https://drive.google.com/file/d/1IVMWKfF8Yp41tsoLLZ8edwjVg_tkjmqQ/view?usp=share_link) | Original Pixel2style2pixel encoder that embeds FFHQ images into StyleGAN2 W+ latent code |
 | [cartoon](https://drive.google.com/drive/folders/1xPo8PcbMXzcUyvwe5liJrfbA5yx4OF1j?usp=sharing) | DualStyleGAN and sampling models trained on Cartoon dataset, 317 (refined) extrinsic style codes |
 | [caricature](https://drive.google.com/drive/folders/1BwLXWkSyWDApblBPvaHKsRCTqnhiHxUZ?usp=sharing) | DualStyleGAN and sampling models trained on Caricature dataset, 199 (refined) extrinsic style codes |
 | [anime](https://drive.google.com/drive/folders/1YvFj33Bfum4YuBeqNNCYLfiBrD4tpzg7?usp=sharing) | DualStyleGAN and sampling models trained on Anime dataset, 174 (refined) extrinsic style codes |
@@ -93,6 +94,7 @@ The saved checkpoints are under the following folder structure:
 ```
 checkpoint
 |--encoder.pt                     % Pixel2style2pixel model
+|--encoder_wplus.pt               % Pixel2style2pixel model (optional)
 |--cartoon
     |--generator.pt               % DualStyleGAN model
     |--sampler.pt                 % The extrinsic style code sampling model
@@ -134,10 +136,12 @@ python style_transfer.py --content ./data/content/unsplash-rDEOVtE7vOs.jpg --ali
 
 <img src="https://user-images.githubusercontent.com/18130694/159124661-fbb58871-7c7b-449f-95b5-83e44f5973e8.jpg" width="32%"> → <img src="./output/arcane_transfer_13_unsplash-rDEOVtE7vOs_overview.jpg" width="64%">
 
-More options can be found via `python style_transfer.py  -h`.
+Specify `--wplus` to use the original pSp encoder to extract the W+ intrinsic style code, which may better preserve the face features of the content image.
+
+**Remarks**: Our trained pSp encoder on Z+/W+ space cannot perfectly encode the content image. If the style transfer result more consistent with the content image is desired, one may use latent optimization to better fit the content image or using other StyleGAN encoders (as discussed in https://github.com/williamyang1991/DualStyleGAN/issues/11 and https://github.com/williamyang1991/DualStyleGAN/issues/29).
 
+More options can be found via `python style_transfer.py  -h`.
 
-**Remarks**: Our trained pSp encoder on Z+ space cannot perfectly encode the content image. If the style transfer result more consistent with the content image is desired, one may use latent optimization to better fit the content image or using other StyleGAN encoders (as discussed in https://github.com/williamyang1991/DualStyleGAN/issues/11 and https://github.com/williamyang1991/DualStyleGAN/issues/29).
 
 ### Artistic Portrait Generation
 Generate random Cartoon face images (Results are saved in the `./output/` folder):