File size: 1,240 Bytes
1645f92
 
 
 
 
 
 
 
 
 
3c8b284
1645f92
 
 
 
2820490
1645f92
 
2975d8e
1645f92
36a0ef9
9229411
dae8b2b
1645f92
 
 
 
 
e36d01e
49672eb
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
from PIL import Image
import torch
import gradio as gr



model2 = torch.hub.load(
    "AK391/animegan2-pytorch:main",
    "generator",
    pretrained=True,
    device="cpu",
    progress=False
)


model1 = torch.hub.load("AK391/animegan2-pytorch:main", "generator", pretrained="celeba_distill",  device="cpu")
face2paint = torch.hub.load(
    'AK391/animegan2-pytorch:main', 'face2paint', 
    size=1024, device="cpu",side_by_side=False
)
def inference(img):
   
    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>"
gr.Interface(inference, [gr.inputs.Image(type="pil")
], gr.outputs.Image(type="pil"),title=title,description=description,article=article,allow_flagging=False,allow_screenshot=False).launch()