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Update app.py
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app.py
CHANGED
@@ -1,7 +1,7 @@
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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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@@ -19,24 +19,26 @@ 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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word_list_dataset = load_dataset("stabilityai/word-list", data_files="list.txt", use_auth_token=YOUR_TOKEN)
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word_list = word_list_dataset["train"]['text']
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def infer(prompt):
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for filter in word_list:
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if re.search(rf"\b{filter}\b", prompt):
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raise gr.Error("Unsafe content found. Please try again with different prompts.")
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#image = pipe(prompt, init_image=init_image)["sample"][0]
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image = pipe(prompt)["sample"][0]
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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. Warning: Slow process... ~5/10 min inference time"
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gr.Interface(fn=infer, inputs="text", outputs=
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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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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] * 1)
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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. Warning: Slow process... ~5/10 min inference time"
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gr.Interface(fn=infer, inputs="text", outputs=gallery,title=title,description=description).launch(enable_queue=True)
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