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Running
on
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Running
on
Zero
Update examples.
Browse files- webui/tab_texture_synthesis.py +46 -46
webui/tab_texture_synthesis.py
CHANGED
@@ -1,46 +1,46 @@
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import os
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from PIL import Image
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import gradio as gr
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def create_interface_texture_synthesis(runner):
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with gr.Blocks():
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with gr.Row():
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gr.Markdown('1. Upload the texture image as input.\n'
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'2. (Optional) Customize the configurations below as needed.\n'
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'3. Cilck `Run` to start synthesis.')
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with gr.Row():
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with gr.Column():
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with gr.Row():
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texture_image = gr.Image(label='Input Texture Image', type='pil', interactive=True,
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value=Image.open('examples/s1.jpg').convert('RGB') if os.path.exists('examples/s1.jpg') else None)
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run_button = gr.Button(value='Run')
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with gr.Accordion('Options', open=True):
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height = gr.Number(label='Height', value=512, precision=0, minimum=2, maximum=4096)
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width = gr.Number(label='Width', value=1024, precision=0, minimum=2, maximum=4096)
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seed = gr.Number(label='Seed', value=2025, precision=0, minimum=0, maximum=2**31)
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num_steps = gr.Slider(label='Number of Steps', minimum=1, maximum=1000, value=200, step=1)
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iterations = gr.Slider(label='Iterations', minimum=0, maximum=10, value=2, step=1)
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lr = gr.Slider(label='Learning Rate', minimum=0.01, maximum=0.5, value=0.05, step=0.01)
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mixed_precision = gr.Radio(choices=['bf16', 'no'], value='bf16', label='Mixed Precision')
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num_images_per_prompt = gr.Slider(label='Num Images Per Prompt', minimum=1, maximum=10, value=1, step=1)
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base_model_list = ['stable-diffusion-v1-5/stable-diffusion-v1-5',]
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model = gr.Radio(choices=base_model_list, label='Select a Base Model', value='stable-diffusion-v1-5/stable-diffusion-v1-5')
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synthesis_way = gr.Radio(['Sampling', 'MultiDiffusion'], label='Synthesis Way', value='MultiDiffusion')
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with gr.Column():
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gr.Markdown('#### Output Image:\n')
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result_gallery = gr.Gallery(label='Output', elem_id='gallery', columns=2, height='auto', preview=True)
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gr.Examples(
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[[Image.open('./webui/images/42.jpg').convert('RGB'), '
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[texture_image, synthesis_way, height, width]
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)
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ips = [texture_image, height, width, seed, num_steps, iterations, lr, mixed_precision, num_images_per_prompt, synthesis_way,model]
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run_button.click(fn=runner.run_texture_synthesis, inputs=ips, outputs=[result_gallery])
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import os
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from PIL import Image
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import gradio as gr
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def create_interface_texture_synthesis(runner):
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with gr.Blocks():
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with gr.Row():
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gr.Markdown('1. Upload the texture image as input.\n'
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'2. (Optional) Customize the configurations below as needed.\n'
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'3. Cilck `Run` to start synthesis.')
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with gr.Row():
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with gr.Column():
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with gr.Row():
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texture_image = gr.Image(label='Input Texture Image', type='pil', interactive=True,
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value=Image.open('examples/s1.jpg').convert('RGB') if os.path.exists('examples/s1.jpg') else None)
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run_button = gr.Button(value='Run')
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with gr.Accordion('Options', open=True):
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height = gr.Number(label='Height', value=512, precision=0, minimum=2, maximum=4096)
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width = gr.Number(label='Width', value=1024, precision=0, minimum=2, maximum=4096)
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seed = gr.Number(label='Seed', value=2025, precision=0, minimum=0, maximum=2**31)
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num_steps = gr.Slider(label='Number of Steps', minimum=1, maximum=1000, value=200, step=1)
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iterations = gr.Slider(label='Iterations', minimum=0, maximum=10, value=2, step=1)
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lr = gr.Slider(label='Learning Rate', minimum=0.01, maximum=0.5, value=0.05, step=0.01)
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mixed_precision = gr.Radio(choices=['bf16', 'no'], value='bf16', label='Mixed Precision')
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num_images_per_prompt = gr.Slider(label='Num Images Per Prompt', minimum=1, maximum=10, value=1, step=1)
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base_model_list = ['stable-diffusion-v1-5/stable-diffusion-v1-5',]
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model = gr.Radio(choices=base_model_list, label='Select a Base Model', value='stable-diffusion-v1-5/stable-diffusion-v1-5')
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synthesis_way = gr.Radio(['Sampling', 'MultiDiffusion'], label='Synthesis Way', value='MultiDiffusion')
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with gr.Column():
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gr.Markdown('#### Output Image:\n')
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result_gallery = gr.Gallery(label='Output', elem_id='gallery', columns=2, height='auto', preview=True)
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gr.Examples(
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[[Image.open('./webui/images/42.jpg').convert('RGB'), 'Sampling', 512, 1024, 50]],
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[texture_image, synthesis_way, height, width, num_steps]
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)
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ips = [texture_image, height, width, seed, num_steps, iterations, lr, mixed_precision, num_images_per_prompt, synthesis_way,model]
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run_button.click(fn=runner.run_texture_synthesis, inputs=ips, outputs=[result_gallery])
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