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Running
on
Zero
Running
on
Zero
#!/usr/bin/env python | |
import gradio as gr | |
from settings import (DEFAULT_IMAGE_RESOLUTION, DEFAULT_NUM_IMAGES, | |
MAX_IMAGE_RESOLUTION, MAX_NUM_IMAGES, MAX_SEED) | |
from utils import randomize_seed_fn | |
def create_demo(process): | |
with gr.Blocks() as demo: | |
with gr.Row(): | |
with gr.Column(): | |
image = gr.Image() | |
prompt = gr.Textbox(label='Prompt') | |
run_button = gr.Button(label='Run') | |
with gr.Accordion('Advanced options', open=False): | |
preprocessor_name = gr.Radio(label='Preprocessor', | |
choices=['Openpose', 'None'], | |
type='value', | |
value='Openpose') | |
num_samples = gr.Slider(label='Number of images', | |
minimum=1, | |
maximum=MAX_NUM_IMAGES, | |
value=DEFAULT_NUM_IMAGES, | |
step=1) | |
image_resolution = gr.Slider( | |
label='Image resolution', | |
minimum=256, | |
maximum=MAX_IMAGE_RESOLUTION, | |
value=DEFAULT_IMAGE_RESOLUTION, | |
step=256) | |
preprocess_resolution = gr.Slider( | |
label='Preprocess resolution', | |
minimum=128, | |
maximum=512, | |
value=512, | |
step=1) | |
num_steps = gr.Slider(label='Number of 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=0, | |
maximum=MAX_SEED, | |
step=1, | |
value=0) | |
randomize_seed = gr.Checkbox(label='Randomize seed', | |
value=True) | |
a_prompt = gr.Textbox( | |
label='Additional 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, | |
columns=2, | |
object_fit='scale-down') | |
inputs = [ | |
image, | |
prompt, | |
a_prompt, | |
n_prompt, | |
num_samples, | |
image_resolution, | |
preprocess_resolution, | |
num_steps, | |
guidance_scale, | |
seed, | |
preprocessor_name, | |
] | |
prompt.submit( | |
fn=randomize_seed_fn, | |
inputs=[seed, randomize_seed], | |
outputs=seed, | |
queue=False, | |
).then( | |
fn=process, | |
inputs=inputs, | |
outputs=result, | |
) | |
run_button.click( | |
fn=randomize_seed_fn, | |
inputs=[seed, randomize_seed], | |
outputs=seed, | |
queue=False, | |
).then( | |
fn=process, | |
inputs=inputs, | |
outputs=result, | |
api_name='openpose', | |
) | |
return demo | |
if __name__ == '__main__': | |
from model import Model | |
model = Model(task_name='Openpose') | |
demo = create_demo(model.process_openpose) | |
demo.queue().launch() | |