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import gradio as gr
#import torch
#from torch import autocast // only for GPU
from PIL import Image
import numpy as np
from io import BytesIO
import os
MY_SECRET_TOKEN=os.environ.get('HF_TOKEN_SD')
#from diffusers import StableDiffusionPipeline
from diffusers import StableDiffusionImg2ImgPipeline
print("hello sylvain")
YOUR_TOKEN=MY_SECRET_TOKEN
device="cpu"
pipe = StableDiffusionImg2ImgPipeline.from_pretrained("CompVis/stable-diffusion-v1-4", use_auth_token=YOUR_TOKEN)
pipe.to(device)
source_img = gr.Image(source="upload", type="numpy")
gallery = gr.Gallery(label="Generated images", show_label=False, elem_id="gallery").style(grid=[2], height="auto")
def infer(prompt, init_image):
print(init_image)
return init_image
print("Great sylvain ! Everything is working fine !")
title="Stable Diffusion CPU"
description="Stable Diffusion example using CPU and HF token. <br />Warning: Slow process... ~5/10 min inference time. <b>NSFW filter enabled.</b>"
gr.Interface(fn=infer, inputs=["text", source_img], outputs=gallery,title=title,description=description).launch(enable_queue=True) |