import spaces 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 @spaces.GPU def img2img(source_img, prompt, strength): 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=6, strength=strength, guidance_scale=0.0).images[0] return image title="SDXLturbo CPU/GPU" description="GoldExtra Preview OpenCV --> I2I (Zeichnung > 2.5D) --> " gr.Interface(fn=img2img, inputs=[gr.Image(source="upload", tool="sketch", label="Source Image"), gr.Textbox(label='What you want the AI to Generate, 77 Token limit'), gr.Slider(minimum=.5, maximum=1, value=.75, step=.025, label='Strength')], outputs='image', title=title, description=description).launch(max_threads=True, debug=True) # article = "Code Monkey: Manjushri").launch(max_threads=True, debug=True)