Spaces:
Runtime error
Runtime error
File size: 1,752 Bytes
a0675a3 19d1db8 a0675a3 9d03195 a0675a3 addcdcf a0675a3 addcdcf a0675a3 addcdcf a0675a3 addcdcf 551fc01 226e67a 9cb1fe4 551fc01 19d1db8 551fc01 |
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 47 48 |
from PIL import Image
import torch
import requests
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="face_paint_512_v1", device="cpu")
face2paint = torch.hub.load(
'AK391/animegan2-pytorch:main', 'face2paint',
size=512, device="cpu", 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 = "Face Anime For You"
description = "Online Demo for AnimeGanv2 Face Portrait v2. To use it, simply upload your image, or click one of the examples to load them. Please use a cropped portrait picture for best results similar to the examples below."
article = "<p style='text-align: center'>❤ from Bruce</p>"
examples = [['IU.png', 'version 2 (🔺 robustness,🔻 stylization)'],
['elon.png', 'version 2 (🔺 robustness,🔻 stylization)']]
gr.Interface(inference,
[gr.inputs.Image(type="pil"), gr.inputs.Radio(
['version 1 (🔺 stylization, 🔻 robustness)',
'version 2 (🔺 robustness,🔻 stylization)'],
type="value",
default='version 2 (🔺 robustness,🔻 stylization)',
label='version')
],
gr.outputs.Image(type="pil"),
title=title,
description=description,
article=article,
enable_queue=True,
examples=examples,
allow_flagging=False).launch()
|