|
import gradio as gr |
|
|
|
|
|
|
|
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 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="filepath", label="init_img") |
|
gallery = gr.Gallery(label="Generated images", show_label=False, elem_id="gallery").style(grid=[2], height="auto") |
|
|
|
def resize(width,img): |
|
basewidth = width |
|
img = Image.open(img) |
|
wpercent = (basewidth/float(img.size[0])) |
|
hsize = int((float(img.size[1])*float(wpercent))) |
|
img = img.resize((basewidth,hsize), Image.Resampling.LANCZOS) |
|
return img |
|
|
|
|
|
def infer(prompt, source_img): |
|
init_image = resize(512,source_img) |
|
init_image.save('source.png') |
|
images_list = pipe([prompt] * 2, init_image=init_image, strength=0.75) |
|
images = [] |
|
safe_image = Image.open(r"unsafe.png") |
|
for i, image in enumerate(images_list["sample"]): |
|
if(images_list["nsfw_content_detected"][i]): |
|
images.append(safe_image) |
|
else: |
|
images.append(image) |
|
|
|
return images |
|
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) |
