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# This file is adapted from https://github.com/lllyasviel/ControlNet/blob/f4748e3630d8141d7765e2bd9b1e348f47847707/gradio_hed2image.py
# The original license file is LICENSE.ControlNet in this repo.
import gradio as gr
def create_demo(process, max_images=12):
with gr.Blocks() as demo:
with gr.Row():
gr.Markdown('## Control Stable Diffusion with HED 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=1,
step=1)
image_resolution = gr.Slider(label='Image Resolution',
minimum=256,
maximum=768,
value=512,
step=256)
detect_resolution = gr.Slider(label='HED Resolution',
minimum=128,
maximum=1024,
value=512,
step=1)
ddim_steps = gr.Slider(label='Steps',
minimum=1,
maximum=100,
value=20,
step=1)
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)
eta = gr.Number(label='eta (DDIM)', value=0.0)
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_gallery = gr.Gallery(label='Output',
show_label=False,
elem_id='gallery').style(
grid=2, height='auto')
ips = [
input_image, prompt, a_prompt, n_prompt, num_samples,
image_resolution, detect_resolution, ddim_steps, scale, seed, eta
]
run_button.click(fn=process,
inputs=ips,
outputs=[result_gallery],
api_name='hed')
return demo
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