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d5f72bc 7210c28 d5f72bc bb852ba d5f72bc 41504fb d5f72bc d84ab71 d5f72bc d84ab71 d5f72bc d84ab71 d5f72bc d84ab71 d5f72bc d84ab71 d5f72bc d84ab71 d5f72bc d84ab71 e5fb5d2 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 | from PIL import Image
import torch
import gradio as gr
#from torch.fx import symbolic_trace
device = 'cuda' if torch.cuda.is_available() else 'cpu'
token = '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'
model1 = torch.hub.load('bryandlee/animegan2-pytorch:main','generator',pretrained='face_paint_512_v1',device=device)
model2 = torch.hub.load('bryandlee/animegan2-pytorch:main','generator',pretrained='face_paint_512_v2',device=device)
model3 = torch.hub.load('bryandlee/animegan2-pytorch:main','generator',pretrained='celeba_distill', device=device)
model4 = torch.hub.load('bryandlee/animegan2-pytorch:main','generator',pretrained='paprika',device=device)
face2paint = torch.hub.load(
'bryandlee/animegan2-pytorch:main', 'face2paint',
size=512, device=device,side_by_side=False
)
def inference(img, ver):
if ver == 'version 1':
return face2paint(model1,img)
elif ver == 'version 2':
return face2paint(model2,img)
elif ver == 'version 3':
return face2paint(model3, img)
elif ver == 'version 4':
return face2paint(model4, img)
title = 'KNU BrainAI LAB : Face to Paint'
description = '๋งํ๋ก ๋ฐ๋ ๋ด ์ผ๊ตด์ ํ์ธํด๋ณด์ธ์!'
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=[['์์ด์ .png','version 1-์์ด์ '],['์์ํ๊ต์๋.png','version 2-์์ํ๊ต์๋'],['์ผ๋ก ๋จธ์คํฌ.png','version 3-์ผ๋ก ๋จธ์คํฌ'],['ํ๋น.png','version 4-ํ๋น']]
#gr.Interface(inference, [gr.inputs.Image(type="pil"),gr.inputs.Radio(['version 1','version 2','version 3','version 4'], type="value", default='version 2', label='version')],
#gr.outputs.Image(type="pil"),title=title,description=description,article=article,examples=examples,allow_flagging='never',css="body {background-image: url('file=brainai.png')}").launch(share=True)
demo = gr.Interface(
inference,[gr.Image(type="pil"),gr.Radio(['version 1','version 2','version 3','version 4'],label='version')],outputs="image")
if __name__ == "__main__":
demo.launch() |