from diffusers import StableDiffusionXLInpaintPipeline
import gradio as gr
import numpy as np
import imageio
from PIL import Image
import torch
import modin.pandas as pd

device = "cuda" if torch.cuda.is_available() else "cpu"
pipe = StableDiffusionXLInpaintPipeline.from_pretrained("stabilityai/sdxl-turbo", safety_checker=None)
pipe = pipe.to(device)

def resize(value,img):
    img = Image.open(img)
    img = img.resize((value,value))
    return img

def predict(source_img, prompt):
    imageio.imwrite("data.png", source_img['image'])
    imageio.imwrite("data_mask.png", source_img["mask"])
    src = resize(768, "data.png")
    src.save("src.png")
    mask = resize(768, "data_mask.png")  
    mask.save("mask.png")
    image = pipe(prompt=prompt, image=src, mask_image=mask, num_inference_steps=4, strength=0.5, guidance_scale=0.0).images[0]
    return image

title="SDXL Turbo Inpainting CPU"
description="Inpainting with SDXL Turbo <br><br> <b>Please use square .png image as input, 512x512, 768x768, or 1024x1024</b>"
gr.Interface(fn=predict, inputs=[gr.Image(sources=("upload"), tools='sketch', label='Source Image'), 
                                 gr.Textbox(label='What you want the AI to Generate, 77 Token limit')], 
             outputs='image', 
             title=title, 
             description=description, 
             article = "Code Monkey: <a href=\"https://huggingface.co/Manjushri\">Manjushri</a>").launch(max_threads=True, debug=True)