app.py

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()