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import gradio as gr |
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from diffusers import StableDiffusionImg2ImgPipeline |
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import torch |
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from PIL import Image |
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model_id = "radames/stable-diffusion-2-1-img2img" |
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device = "cuda" if torch.cuda.is_available() else "cpu" |
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pipeline = StableDiffusionImg2ImgPipeline.from_pretrained(model_id, use_auth_token=True).to(device) |
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def generate_image(img, prompt): |
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image = img.resize((512, 512)) |
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with torch.no_grad(): |
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output_image = pipeline(prompt=prompt, init_image=image, strength=0.75, guidance_scale=7.5)["sample"][0] |
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return output_image |
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gr.Interface(fn=generate_image, |
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inputs=[gr.Image(type="pil", label="Initial Image"), gr.Textbox(label="Prompt")], |
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outputs=gr.Image(type="pil"), |
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title="Image-to-Image with Stable Diffusion", |
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description="Generate an image based on an initial image and a prompt.").launch() |
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