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# This file is adapted from https://github.com/lllyasviel/ControlNet/blob/f4748e3630d8141d7765e2bd9b1e348f47847707/gradio_scribble2image_interactive.py
# The original license file is LICENSE.ControlNet in this repo.
import gradio as gr
import numpy as np
def create_canvas(w, h):
return np.zeros(shape=(h, w, 3), dtype=np.uint8) + 255
def create_demo(process, max_images=12):
with gr.Blocks() as demo:
with gr.Row():
gr.Markdown(
'## Control Stable Diffusion with Interactive Scribbles')
with gr.Row():
with gr.Column():
canvas_width = gr.Slider(label='Canvas Width',
minimum=256,
maximum=1024,
value=512,
step=1)
canvas_height = gr.Slider(label='Canvas Height',
minimum=256,
maximum=1024,
value=512,
step=1)
create_button = gr.Button(label='Start',
value='Open drawing canvas!')
input_image = gr.Image(source='upload',
type='numpy',
tool='sketch')
gr.Markdown(
value=
'Do not forget to change your brush width to make it thinner. (Gradio do not allow developers to set brush width so you need to do it manually.) '
'Just click on the small pencil icon in the upper right corner of the above block.'
)
create_button.click(fn=create_canvas,
inputs=[canvas_width, canvas_height],
outputs=[input_image])
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)
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, ddim_steps, scale, seed, eta
]
run_button.click(fn=process, inputs=ips, outputs=[result_gallery])
return demo
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