app.py

from PIL import Image
import torch
import gradio as gr

model = torch.hub.load(
    "bryandlee/animegan2-pytorch:main",
    "generator",
    pretrained=True, # or give URL to a pretrained model
    device="cuda", # or "cpu" if you don't have a GPU
    progress=False, # show progress
)

face2paint = torch.hub.load(
    'bryandlee/animegan2-pytorch:main', 'face2paint', 
    size=512, device="cuda"
)

def inference(img):
    out = face2paint(model, img)
    return out
      
  
title = "Animeganv2"
description = "Gradio demo for AnimeGanv2 Face Portrait v2. 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> | <a href='https://github.com/Kazuhito00/AnimeGANv2-ONNX-Sample' target='_blank'>Github Repo ONNX</a></p><p style='text-align: center'>samples from repo: <img src='https://user-images.githubusercontent.com/26464535/129888683-98bb6283-7bb8-4d1a-a04a-e795f5858dcf.gif' alt='animation'/> <img src='https://user-images.githubusercontent.com/26464535/137619176-59620b59-4e20-4d98-9559-a424f86b7f24.jpg' alt='animation'/></p>"

examples=[['groot.jpeg'],['bill.png'],['tony.png'],['elon.png'],['IU.png'],['billie.png'],['will.png'],['beyonce.jpeg'],['gongyoo.jpeg']]
gr.Interface(inference, gr.inputs.Image(type="pil"), gr.outputs.Image(type="pil"),title=title,description=description,article=article,enable_queue=True,examples=examples).launch()