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app.py
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pip install -U git+https://github.com/huggingface/diffusers
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import gradio as gr
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#import torch
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#from torch import autocast // only for GPU
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from PIL import Image
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import os
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MY_SECRET_TOKEN=os.environ.get('HF_TOKEN_SD')
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from diffusers import StableDiffusionPipeline
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#from diffusers import StableDiffusionImg2ImgPipeline
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print("hello sylvain")
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YOUR_TOKEN=MY_SECRET_TOKEN
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device="cpu"
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pipe = StableDiffusionPipeline.from_pretrained("CompVis/stable-diffusion-v1-4", use_auth_token=YOUR_TOKEN)
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pipe.to(device)
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gallery = gr.Gallery(label="Generated images", show_label=False, elem_id="gallery").style(grid=[2], height="auto")
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def infer(prompt):
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#image = pipe(prompt, init_image=init_image)["sample"][0]
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images_list = pipe([prompt] * 4)
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images = []
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safe_image = Image.open(r"unsafe.png")
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for i, image in enumerate(images_list["sample"]):
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if(images_list["nsfw_content_detected"][i]):
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images.append(safe_image)
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else:
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images.append(image)
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return images
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print("Great sylvain ! Everything is working fine !")
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title="Stable Diffusion CPU"
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description="Stable Diffusion example using CPU and HF token. <br />Warning: Slow process... ~5/10 min inference time. <b>NSFW filter enabled.</b>"
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gr.Interface(fn=infer, inputs="text", outputs=gallery,title=title,description=description).launch(enable_queue=True)
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