## PyTorch Implementation of [AnimeGANv2](https://github.com/TachibanaYoshino/AnimeGANv2)
**Updates**
* `2021-10-17` Add weights for [FacePortraitV2](#additional-model-weights). [![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/bryandlee/animegan2-pytorch/blob/main/colab_demo.ipynb)
![sample](https://user-images.githubusercontent.com/26464535/142294796-54394a4a-a566-47a1-b9ab-4e715b901442.gif)
* `2021-11-07` Thanks to [ak92501](https://twitter.com/ak92501), a [web demo](https://huggingface.co/spaces/akhaliq/AnimeGANv2) is integrated to [Huggingface Spaces](https://huggingface.co/spaces) with [Gradio](https://github.com/gradio-app/gradio). [![Hugging Face Spaces](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue)](https://huggingface.co/spaces/akhaliq/AnimeGANv2)
* `2021-11-07` Thanks to [xhlulu](https://github.com/xhlulu), the `torch.hub` model is now available. See [Torch Hub Usage](#torch-hub-usage).
## Basic Usage
**Inference**
```
python test.py --input_dir [image_folder_path] --device [cpu/cuda]
```
## Torch Hub Usage
You can load the model via `torch.hub`:
```python
import torch
model = torch.hub.load("bryandlee/animegan2-pytorch", "generator").eval()
out = model(img_tensor) # BCHW tensor
```
Currently, the following `pretrained` shorthands are available:
```python
model = torch.hub.load("bryandlee/animegan2-pytorch:main", "generator", pretrained="celeba_distill")
model = torch.hub.load("bryandlee/animegan2-pytorch:main", "generator", pretrained="face_paint_512_v1")
model = torch.hub.load("bryandlee/animegan2-pytorch:main", "generator", pretrained="face_paint_512_v2")
model = torch.hub.load("bryandlee/animegan2-pytorch:main", "generator", pretrained="paprika")
```
You can also load the `face2paint` util function:
```python
from PIL import Image
face2paint = torch.hub.load("bryandlee/animegan2-pytorch:main", "face2paint", size=512)
img = Image.open(...).convert("RGB")
out = face2paint(model, img)
```
More details about `torch.hub` is in [the torch docs](https://pytorch.org/docs/stable/hub.html)
## Weight Conversion from the Original Repo (Tensorflow)
1. Install the [original repo's dependencies](https://github.com/TachibanaYoshino/AnimeGANv2#requirements): python 3.6, tensorflow 1.15.0-gpu
2. Install torch >= 1.7.1
3. Clone the original repo & run
```
git clone https://github.com/TachibanaYoshino/AnimeGANv2
python convert_weights.py
```
<details>
<summary>samples</summary>
<br>
Results from converted `Paprika` style model (input image, original tensorflow result, pytorch result from left to right)
<img src="./samples/compare/1.jpg" width="960">
<img src="./samples/compare/2.jpg" width="960">
<img src="./samples/compare/3.jpg" width="960">
</details>
**Note:** Results from converted weights slightly different due to the [bilinear upsample issue](https://github.com/pytorch/pytorch/issues/10604)
## Additional Model Weights
**Webtoon Face** [[ckpt]](https://drive.google.com/file/d/10T6F3-_RFOCJn6lMb-6mRmcISuYWJXGc)
<details>
<summary>samples</summary>
Trained on <b>256x256</b> face images. Distilled from [webtoon face model](https://github.com/bryandlee/naver-webtoon-faces/blob/master/README.md#face2webtoon) with L2 + VGG + GAN Loss and CelebA-HQ images.
![face_results](https://user-images.githubusercontent.com/26464535/143959011-1740d4d3-790b-4c4c-b875-24404ef9c614.jpg)
</details>
**Face Portrait v1** [[ckpt]](https://drive.google.com/file/d/1WK5Mdt6mwlcsqCZMHkCUSDJxN1UyFi0-)
<details>
<summary>samples</summary>
Trained on <b>512x512</b> face images.
[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1jCqcKekdtKzW7cxiw_bjbbfLsPh-dEds?usp=sharing)
![samples](https://user-images.githubusercontent.com/26464535/127134790-93595da2-4f8b-4aca-a9d7-98699c5e6914.jpg)
[ðº](https://youtu.be/CbMfI-HNCzw?t=317)
![sample](https://user-images.githubusercontent.com/26464535/129888683-98bb6283-7bb8-4d1a-a04a-e795f5858dcf.gif)
</details>
**Face Portrait v2** [[ckpt]](https://drive.google.com/uc?id=18H3iK09_d54qEDoWIc82SyWB2xun4gjU)
<details>
<summary>samples</summary>
Trained on <b>512x512</b> face images. Compared to v1, `ð»beautify` `ðºrobustness`
[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1jCqcKekdtKzW7cxiw_bjbbfLsPh-dEds?usp=sharing)
![face_portrait_v2_0](https://user-images.githubusercontent.com/26464535/137619176-59620b59-4e20-4d98-9559-a424f86b7f24.jpg)
![face_portrait_v2_1](https://user-images.githubusercontent.com/26464535/137619181-a45c9230-f5e7-4f3c-8002-7c266f89de45.jpg)
ð¦ ð® ð¥
![face_portrait_v2_squid_game](https://user-images.githubusercontent.com/26464535/137619183-20e94f11-7a8e-4c3e-9b45-378ab63827ca.jpg)
</details>
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温馨提示
Python使用AI animegan2-pytorch制作属于你的漫画头像/风景图片 plot_sample.py 绘制原始图/效果图demo test.py 用于生成人物/风景模型的文件 samples/inputs 输入风景图及人物图示例 convert_weights.py 解析模型文件 demo.ipynb model.py 解析模型/重新训练的文件 weights/ 4个适用于人物/风景的模型文件 celeba_distill.pt face_paint_512_v1.pt face_paint_512_v2.pt paprika.pt
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animegan2-pytorch.rar (60个子文件)
animegan2-pytorch
weights
face_paint_512_v1.pt 8.2MB
face_paint_512_v2.pt 8.2MB
paprika.pt 8.2MB
celeba_distill.pt 8.2MB
LICENSE 1KB
samples
compare
2.jpg 1.26MB
1.jpg 863KB
3.jpg 1.4MB
respaprika
2.jpg 145KB
ml.jpg 18KB
1.jpg 152KB
dlrb.png 364KB
ml2.jpg 21KB
3.jpg 83KB
dlrb.jpg 179KB
faces
ml.jpg 38KB
dlrb.png 689KB
photo_test.jpg 607KB
ml2.jpg 51KB
dlrb.jpg 153KB
inputs
2.jpg 536KB
ml.jpg 38KB
1.jpg 719KB
dlrb.png 689KB
photo_test.jpg 607KB
ml2.jpg 51KB
3.jpg 227KB
dlrb.jpg 153KB
resv1
2.jpg 166KB
ml.jpg 13KB
1.jpg 162KB
dlrb.png 403KB
ml2.jpg 23KB
3.jpg 80KB
dlrb.jpg 164KB
resceledistill
2.jpg 179KB
ml.jpg 14KB
1.jpg 204KB
dlrb.png 364KB
ml2.jpg 20KB
3.jpg 97KB
dlrb.jpg 161KB
resv2
2.jpg 156KB
ml.jpg 17KB
1.jpg 176KB
dlrb.png 422KB
ml2.jpg 23KB
3.jpg 90KB
dlrb.jpg 189KB
hubconf.py 2KB
demo.ipynb 812KB
model.py 4KB
convert_weights.py 4KB
colab_demo.ipynb 38KB
plot_sample.py 5KB
requirements.txt 26B
.gitignore 2KB
__pycache__
model.cpython-37.pyc 3KB
test.py 2KB
README.md 5KB
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