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import gradio as gr | |
from random import randint | |
from all_models import models | |
from gradio import Interface | |
# Define Bootstrap CSS styles | |
bootstrap_css = """ | |
<link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/[email protected]/dist/css/bootstrap.min.css" integrity="sha384-zCbKRCUGaJDkqO4aIfeHaHNVy2QWhv2P+nvf4jCF0S42kqR8YcOrHndjw6qplMFZrk" crossorigin="anonymous"> | |
""" | |
gr.Config.css = [bootstrap_css] | |
def load_fn(models): | |
global models_load | |
models_load = {} | |
for model in models: | |
if model not in models_load.keys(): | |
try: | |
m = gr.load(f'models/{model}') | |
except Exception as error: | |
m = Interface(lambda txt: None, ['text'], ['image']) | |
models_Multiplier = {model: m} | |
load_fn(models) | |
num_models = 150 | |
default_models = models[:num_models] | |
def extend_choices(choices): | |
return choices + (num_models - len(choices)) * ['NA'] | |
def update_imgbox(choices): | |
choices_plus = extend_choices(choices) | |
return [gr.Image(None, label=m, visible=(m != 'NA')) for m in choices_plus] | |
def gen_fn(model_str, prompt): | |
if model_str == 'NA': | |
return None | |
noise = str(randint(0, 99999999999)) | |
return models_load[model_str](f'{prompt} {noise}') | |
with gr.Blocks() as demo: | |
with gr.Tab('The Dream'): | |
txt_input = gr.Textbox(label='Your prompt:', lines=4).style( | |
'text-align: left;', | |
'width: 100%;', | |
'margin-bottom: 20px;', | |
'font-size: 16px;' | |
) | |
gen_button = gr.Button( | |
'Generate up to 150 images in up to 3 minutes total', | |
style='margin-bottom: 20px;' | |
) | |
stop_button = gr.Button( | |
'Stop', | |
variant='danger', | |
interactive=False, | |
style='margin-bottom: 20px;' | |
) | |
gen_button.click(lambda s: gr.update(interactive=True), None, stop_button) | |
gr.HTML( | |
""" | |
<div style="text-align: left; max-width: 800px; margin: 0 auto;"> | |
<p style="margin-bottom: 10px; color: #333333;">Enter your prompt in the text box and click "Generate" to start generating images.</p> | |
</div> | |
""" | |
) | |
with gr.Row(): | |
output = [gr.Image(label=m, min_width=250) for m in default_models] | |
current_models = [gr.Textbox(m, visible=False) for m in default_models] | |
for m, o in zip(current_models, output): | |
gen_event = gen_button.click(gen_fn, [m, txt_input], o) | |
stop_button.click(lambda s: gr.update(interactive=False), None, stop_button, cancels=[gen_event]) | |
with gr.Accordion('Model selection'): | |
model_choice = gr.CheckboxGroup( | |
models, | |
label=f'Choose up to {num_models} different models out of {len(models)} available!', | |
value=default_models, | |
multiselect=True, | |
max_choices=num_models, | |
interactive=True, | |
filterable=True, | |
style='width: 100%;' | |
) | |
model_choice.change(update_imgbox, model_choice, output) | |
model_choice.change(extend_choices, model_choice, current_models) | |
with gr.Row(): | |
gr.HTML( | |
""" | |
<div class="footer"> | |
<p style="font-size: 14px; color: #666666;"> | |
Based on the <a href="https://huggingface.co/spaces/derwahnsinn/TestGen">TestGen</a> Space by derwahnsinn, | |
the <a href="https://huggingface.co/spaces/RdnUser77/SpacIO_v1">SpacIO</a> Space by RdnUser77 and Omnibus's Maximum Multiplier! | |
</p> | |
</div> | |
""" | |
) | |
demo.queue(concurrency_count=200) | |
demo.launch() | |