| import gradio as gr | |
| #import torch | |
| #from torch import autocast // only for GPU | |
| from PIL import Image | |
| 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 = StableDiffusionPipeline.from_pretrained("CompVis/stable-diffusion-v1-4", use_auth_token=YOUR_TOKEN) | |
| pipe.to(device) | |
| gallery = gr.Gallery(label="Generated images", show_label=False, elem_id="gallery").style(grid=[2], height="auto") | |
| def infer(prompt): | |
| #image = pipe(prompt, init_image=init_image)["sample"][0] | |
| images_list = pipe([prompt] * 4) | |
| 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", outputs=gallery,title=title,description=description).queue(max_size=10).launch(enable_queue=True) | |