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Delete app_hed.py

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  1. app_hed.py +0 -83
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- # This file is adapted from https://github.com/lllyasviel/ControlNet/blob/f4748e3630d8141d7765e2bd9b1e348f47847707/gradio_hed2image.py
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- # The original license file is LICENSE.ControlNet in this repo.
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- import gradio as gr
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-
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-
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- def create_demo(process, max_images=12, default_num_images=3):
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- with gr.Blocks() as demo:
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- with gr.Row():
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- gr.Markdown('## Control Stable Diffusion with HED Maps')
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- with gr.Row():
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- with gr.Column():
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- input_image = gr.Image(source='upload', type='numpy')
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- prompt = gr.Textbox(label='Prompt')
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- run_button = gr.Button(label='Run')
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- with gr.Accordion('Advanced options', open=False):
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- num_samples = gr.Slider(label='Images',
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- minimum=1,
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- maximum=max_images,
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- value=default_num_images,
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- step=1)
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- image_resolution = gr.Slider(label='Image Resolution',
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- minimum=256,
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- maximum=512,
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- value=512,
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- step=256)
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- detect_resolution = gr.Slider(label='HED Resolution',
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- minimum=128,
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- maximum=512,
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- value=512,
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- step=1)
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- num_steps = gr.Slider(label='Steps',
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- minimum=1,
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- maximum=100,
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- value=20,
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- step=1)
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- guidance_scale = gr.Slider(label='Guidance Scale',
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- minimum=0.1,
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- maximum=30.0,
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- value=9.0,
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- step=0.1)
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- seed = gr.Slider(label='Seed',
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- minimum=-1,
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- maximum=2147483647,
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- step=1,
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- randomize=True)
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- a_prompt = gr.Textbox(
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- label='Added Prompt',
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- value='best quality, extremely detailed')
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- n_prompt = gr.Textbox(
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- label='Negative Prompt',
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- value=
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- 'longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality'
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- )
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- with gr.Column():
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- result = gr.Gallery(label='Output',
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- show_label=False,
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- elem_id='gallery').style(grid=2,
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- height='auto')
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- inputs = [
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- input_image,
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- prompt,
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- a_prompt,
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- n_prompt,
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- num_samples,
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- image_resolution,
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- detect_resolution,
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- num_steps,
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- guidance_scale,
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- seed,
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- ]
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- prompt.submit(fn=process, inputs=inputs, outputs=result)
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- run_button.click(fn=process,
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- inputs=inputs,
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- outputs=result,
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- api_name='hed')
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- return demo
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-
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-
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- if __name__ == '__main__':
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- from model import Model
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- model = Model()
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- demo = create_demo(model.process_hed)
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- demo.queue().launch()