AnimeGANv2 / app.py
from PIL import Image
import torch
import gradio as gr
model2 = torch.hub.load(
"AK391/animegan2-pytorch:main",
"generator",
pretrained=True,
device="cuda",
progress=False
)
model1 = torch.hub.load("AK391/animegan2-pytorch:main", "generator", pretrained="face_paint_512_v1", device="cuda")
face2paint = torch.hub.load(
'AK391/animegan2-pytorch:main', 'face2paint',
size=512, device="cuda",side_by_side=False
)
def inference(img, ver):
if ver == 'version 2 (πŸ”Ί robustness,πŸ”» 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 = "<p style='text-align: center'><a href='https://github.com/bryandlee/animegan2-pytorch' target='_blank'>Github Repo Pytorch</a></p> <center><img src='https://visitor-badge.glitch.me/badge?page_id=akhaliq_animegan' alt='visitor badge'></center></p>"
examples=[['groot.jpeg','version 2 (πŸ”Ί robustness,πŸ”» stylization)'],['bill.png','version 1 (πŸ”Ί stylization, πŸ”» robustness)'],['tony.png','version 1 (πŸ”Ί stylization, πŸ”» robustness)'],['elon.png','version 2 (πŸ”Ί robustness,πŸ”» stylization)'],['IU.png','version 1 (πŸ”Ί stylization, πŸ”» robustness)'],['billie.png','version 2 (πŸ”Ί robustness,πŸ”» stylization)'],['will.png','version 2 (πŸ”Ί robustness,πŸ”» stylization)'],['beyonce.png','version 1 (πŸ”Ί stylization, πŸ”» robustness)'],['gongyoo.jpeg','version 1 (πŸ”Ί stylization, πŸ”» robustness)']]
gr.Interface(inference, [gr.inputs.Image(type="pil"),gr.inputs.Radio(['version 1 (πŸ”Ί stylization, πŸ”» robustness)','version 2 (πŸ”Ί robustness,πŸ”» stylization)'], type="value", default='version 2 (πŸ”Ί robustness,πŸ”» stylization)', label='version')
], gr.outputs.Image(type="pil"),title=title,description=description,article=article,examples=examples,allow_flagging=False,allow_screenshot=False).launch()