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# This file is adapted from https://github.com/lllyasviel/ControlNet/blob/f4748e3630d8141d7765e2bd9b1e348f47847707/gradio_scribble2image.py | |
# The original license file is LICENSE.ControlNet in this repo. | |
import gradio as gr | |
def create_demo(process, max_images=12, default_num_images=3): | |
with gr.Blocks() as demo: | |
with gr.Row(): | |
gr.Markdown('## Control Stable Diffusion with Scribble Maps') | |
with gr.Row(): | |
with gr.Column(): | |
input_image = gr.Image(source='upload', type='numpy') | |
prompt = gr.Textbox(label='Prompt') | |
run_button = gr.Button(label='Run') | |
with gr.Accordion('Advanced options', open=False): | |
num_samples = gr.Slider(label='Images', | |
minimum=1, | |
maximum=max_images, | |
value=default_num_images, | |
step=1) | |
image_resolution = gr.Slider(label='Image Resolution', | |
minimum=256, | |
maximum=768, | |
value=512, | |
step=256) | |
num_steps = gr.Slider(label='Steps', | |
minimum=1, | |
maximum=100, | |
value=20, | |
step=1) | |
guidance_scale = gr.Slider(label='Guidance Scale', | |
minimum=0.1, | |
maximum=30.0, | |
value=9.0, | |
step=0.1) | |
seed = gr.Slider(label='Seed', | |
minimum=-1, | |
maximum=2147483647, | |
step=1, | |
randomize=True) | |
a_prompt = gr.Textbox( | |
label='Added Prompt', | |
value='best quality, extremely detailed') | |
n_prompt = gr.Textbox( | |
label='Negative Prompt', | |
value= | |
'longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality' | |
) | |
with gr.Column(): | |
result = gr.Gallery(label='Output', | |
show_label=False, | |
elem_id='gallery').style(grid=2, | |
height='auto') | |
inputs = [ | |
input_image, | |
prompt, | |
a_prompt, | |
n_prompt, | |
num_samples, | |
image_resolution, | |
num_steps, | |
guidance_scale, | |
seed, | |
] | |
prompt.submit(fn=process, inputs=inputs, outputs=result) | |
run_button.click(fn=process, | |
inputs=inputs, | |
outputs=result, | |
api_name='scribble') | |
return demo | |
if __name__ == '__main__': | |
from model import Model | |
model = Model() | |
demo = create_demo(model.process_scribble) | |
demo.queue().launch() | |