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demo.py
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demo.py
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import gradio as gr
def create_demo_sketch(run):
cond_name = gr.State(value='sketch')
with gr.Blocks() as demo:
with gr.Row():
gr.Markdown('## Control Stable Diffusion-XL with Sketch 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')
in_type = gr.Radio(
choices=["Image", "Sketch"],
label=f"Input type for Sketch",
interactive=True,
value="Image",
)
with gr.Accordion('Advanced options', open=False):
con_strength = gr.Slider(label='Control Strength',
minimum=0.0,
maximum=1.0,
value=1.0,
step=0.1)
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=7.5,
step=0.1)
seed = gr.Slider(label='Seed',
minimum=-1,
maximum=2147483647,
step=1,
randomize=True)
a_prompt = gr.Textbox(
label='Added Prompt',
value='in real world, high quality')
n_prompt = gr.Textbox(
label='Negative Prompt',
value='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, in_type, prompt, a_prompt, n_prompt,
ddim_steps, scale, seed, cond_name, con_strength
]
run_button.click(fn=run,
inputs=ips,
outputs=[result_gallery],
api_name='sketch')
return demo
def create_demo_canny(run):
cond_name = gr.State(value='canny')
with gr.Blocks() as demo:
with gr.Row():
gr.Markdown('## Control Stable Diffusion-XL with Canny 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')
in_type = gr.Radio(
choices=["Image", "Canny"],
label=f"Input type for Canny",
interactive=True,
value="Image",
)
with gr.Accordion('Advanced options', open=False):
con_strength = gr.Slider(label='Control Strength',
minimum=0.0,
maximum=1.0,
value=1.0,
step=0.1)
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=7.5,
step=0.1)
seed = gr.Slider(label='Seed',
minimum=-1,
maximum=2147483647,
step=1,
randomize=True)
a_prompt = gr.Textbox(
label='Added Prompt',
value='in real world, high quality')
n_prompt = gr.Textbox(
label='Negative Prompt',
value='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, in_type, prompt, a_prompt, n_prompt,
ddim_steps, scale, seed, cond_name, con_strength
]
run_button.click(fn=run,
inputs=ips,
outputs=[result_gallery],
api_name='canny')
return demo
def create_demo_pose(run):
cond_name = gr.State(value='openpose')
in_type = gr.State(value='Image')
with gr.Blocks() as demo:
with gr.Row():
gr.Markdown('## Control Stable Diffusion-XL with Keypoint 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):
con_strength = gr.Slider(label='Control Strength',
minimum=0.0,
maximum=1.0,
value=1.0,
step=0.1)
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=7.5,
step=0.1)
seed = gr.Slider(label='Seed',
minimum=-1,
maximum=2147483647,
step=1,
randomize=True)
a_prompt = gr.Textbox(
label='Added Prompt',
value='in real world, high quality')
n_prompt = gr.Textbox(
label='Negative Prompt',
value='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, in_type, prompt, a_prompt, n_prompt,
ddim_steps, scale, seed, cond_name, con_strength
]
run_button.click(fn=run,
inputs=ips,
outputs=[result_gallery],
api_name='openpose')
return demo