import os
os.system("pip install gradio==2.4.6")
import gradio as gr
from PIL import Image
import torch


def greet(num):
    return num+69

iface = gr.Interface(fn=greet, inputs="number", outputs="number")
iface.launch(share=True)


def inference(img):
    out = face2paint(model1, img)
    return out
  
title = "Pivotal Tuning for Latent Based Real Image Editing"
description = "Gradio Demo for Pivotal Tuning Inversion. 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/danielroich/PTI' target='_blank'>Github Repo Pytorch</a>"
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,enable_queue=True).launch(share=True)