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import gradio as gr | |
import torch | |
model2 = torch.hub.load( | |
"AK391/animegan2-pytorch:main", | |
"generator", | |
pretrained=True, | |
progress=False | |
) | |
model1 = torch.hub.load("AK391/animegan2-pytorch:main", "generator", pretrained="face_paint_512_v1") | |
face2paint = torch.hub.load( | |
'AK391/animegan2-pytorch:main', 'face2paint', | |
size=512,side_by_side=False | |
) | |
def inference(img, ver): | |
if ver == 'version 2 (🔺 robustness,🔻 stylization)': | |
out = face2paint(model2, img) | |
else: | |
out = face2paint(model1, img) | |
return out | |
title = "AnimeGANv2" | |
description = "Gradio Demo for AnimeGanv2 Face Portrait. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below. Please use a cropped portrait picture for best results similar to the examples below." | |
article = "Github Repo Pytorch " | |
demo = gr.Interface( | |
fn=inference, | |
inputs=[gr.Image(type="pil"),gr.Radio(['version 1 (🔺 stylization, 🔻 robustness)','version 2 (🔺 robustness,🔻 stylization)'], type="value", label='version')], | |
outputs=gr.Image(type="pil"), | |
title=title, | |
description=description, | |
article=article) | |
gr.close_all() | |
demo.launch() |