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poojan1202
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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 diffusers import StableDiffusionInstructPix2PixPipeline
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import torch
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# Load the uploaded model from Hugging Face
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model = StableDiffusionInstructPix2PixPipeline.from_pretrained("poojan1202/image_modification")
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model.to("cuda") # If you have access to GPU
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# Define the image-to-image function
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def instruct_pix2pix(image, instruction):
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edited_image = model(image=image, prompt=instruction).images[0]
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return edited_image
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# Create the Gradio interface
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with gr.Blocks() as demo:
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gr.Markdown("# InstructPix2Pix: Image-to-Image Editing")
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with gr.Row():
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with gr.Column():
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image_input = gr.Image(source="upload", type="pil")
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instruction_input = gr.Textbox(label="Instruction", placeholder="Describe the edit you want...")
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submit_button = gr.Button("Generate")
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with gr.Column():
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image_output = gr.Image()
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submit_button.click(instruct_pix2pix, inputs=[image_input, instruction_input], outputs=image_output)
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# Launch the app
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demo.launch()
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