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import gradio as gr |
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from stablepy import Model_Diffusers |
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def generate_image(prompt, num_steps, guidance_scale, sampler, img_width, img_height, upscaler_model_path, upscaler_increases_size, hires_steps, base_model_id): |
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model = Model_Diffusers( |
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base_model_id=base_model_id, |
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task_name='txt2img', |
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) |
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image, info_image = model( |
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prompt=prompt, |
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num_steps=num_steps, |
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guidance_scale=guidance_scale, |
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sampler=sampler, |
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img_width=img_width, |
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img_height=img_height, |
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upscaler_model_path=upscaler_model_path, |
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upscaler_increases_size=upscaler_increases_size, |
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hires_steps=hires_steps, |
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) |
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return image[0] |
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with gr.Blocks(gr.themes.Ocean(), title="StablePY") as demo: |
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gr.Markdown("# StablePY") |
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moelpah = gr.Textbox(label="model", placeholder="user/repo") |
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with gr.Row(): |
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prompt = gr.Textbox(label="Prompt", value="highly detailed portrait of an underwater city, with towering spires and domes rising up from the ocean floor") |
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with gr.Row(): |
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num_steps = gr.Slider(label="Number of Steps", minimum=1, maximum=100, value=30) |
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guidance_scale = gr.Slider(label="Guidance Scale", minimum=1.0, maximum=20.0, value=7.5) |
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sampler = gr.Dropdown(label="Sampler", choices=["DPM++ 2M", "DDIM", "Euler A"], value="DPM++ 2M") |
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with gr.Row(): |
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img_width = gr.Number(label="Image Width", value=1024) |
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img_height = gr.Number(label="Image Height", value=1024) |
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with gr.Row(): |
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upscaler_model_path = gr.Textbox(label="Upscaler Model Path", value="./upscaler/RealESRGAN_x4plus_anime_6B.pth", visible=False) |
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upscaler_increases_size = gr.Number(label="Upscaler Increase Size", value=1.5) |
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hires_steps = gr.Number(label="Hires Steps", value=25) |
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with gr.Row(): |
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generate_button = gr.Button("Generate") |
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with gr.Row(): |
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output_image = gr.Image(label="Generated Image") |
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generate_button.click( |
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generate_image, |
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inputs=[moelpah, prompt, num_steps, guidance_scale, sampler, img_width, img_height, upscaler_model_path, upscaler_increases_size, hires_steps], |
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outputs=[output_image] |
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) |
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demo.launch() |
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