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Create App.py
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App.py
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import gradio as gr
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from huggingface_hub import snapshot_download
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from diffusers import StableDiffusion
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from gradio_tools import StableDiffusionTool
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# Download the model files
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snapshot_download("model-repository/stable-diffusion", "main", "model", "1.5")
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# Load the Stable Diffusion model
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model = StableDiffusion.from_pretrained("stable-diffusion")
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# Define a function to generate images and captions
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def generate_image_and_caption(prompt, guidance_scale=7.5):
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# Generate an image from the prompt
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image = model.generate_from_prompt(
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prompt, guidance_scale=guidance_scale, num_images=1, batch_size=1
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)
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# Improve the prompt and generate a caption
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improved_prompt = "A photo of " + prompt
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caption = model.caption_image(improved_prompt, image[0])
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return image[0], caption
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# Create a StableDiffusionTool instance
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stable_diffusion_tool = StableDiffusionTool(model)
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# Create the Gradio interface
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interface = gr.Interface(
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fn=generate_image_and_caption,
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inputs=[
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gr.inputs.Textbox(lines=5, label="Image Prompt"),
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gr.inputs.Slider(
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minimum=0, maximum=10, default=7.5, step=0.5, label="Guidance Scale"
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),
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],
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outputs=["image", "text"],
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allow_flagging=True,
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flagging_options=["Inappropriate"],
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title="Stable Diffusion Gradio App",
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description="Generate images and captions from text prompts using Stable Diffusion.",
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article="This Gradio app showcases the capabilities of Stable Diffusion, a state-of-the-art defusion model. You can generate images and their captions by providing text prompts and adjusting the guidance scale.",
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examples=[
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["A red apple on a table", 7.5],
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["A sunset over a beach", 5.0],
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["A dog riding a skateboard", 8.0],
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],
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show_input=True,
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enable_queue=True,
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queue_message="Generating image and caption. Please wait...",
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tools=[stable_diffusion_tool],
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)
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# Launch the app
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interface.launch()
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