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 = '만화로 바뀐 내 얼굴을 확인해보세요!'

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=[['아이유.png','version 1-아이유'],['안상태교수님.png','version 2-안상태교수님'],['일론머스크.png','version 3-일론머스크'],['현빈.png','version 4-현빈']]



#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()