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import gradio as gr
from random import randint
from all_models import models
from datetime import datetime
now2 = 0
kii=" mohawk femboy racecar driver ";
def get_current_time():
now = datetime.now()
now2 = now
current_time = now2.strftime("%Y-%m-%d %H:%M:%S")
ki = f'{kii} {current_time}'
return ki
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 = gr.Interface(lambda txt: None, ['text'], ['image'])
models_load.update({model: m})
load_fn(models)
num_models = len(models)
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, negative_prompt):
if model_str == 'NA':
return None
noise = str(randint(0, 9999))
combined_prompt = f'{prompt} {model_str} {negative_prompt} {noise}'
print(f"Generating with prompt: {combined_prompt}") # Debug line
# result = models_load[model_str](f'{prompt} {negative_prompt} {noise}')
# end_time = time.time() # End timing
# runtime = end_time - start_time
# model_timings[model_str] = runtime # Log the model's execution time
# queue_size -= 1 # Decrement queue size after processing
# return f"Model {model_str} ran for {runtime:.2f} seconds", result
return models_load[model_str](f'{prompt} {negative_prompt} {noise}')
def make_me():
# with gr.Tab('The Dream'):
with gr.Row():
txt_input = gr.Textbox(lines=2, value=kii, width=300, max_height=100)
#txt_input = gr.Textbox(label='Your prompt:', lines=2, value=kii)
negative_prompt_input = gr.Textbox(lines=2, value="", label="Negative Prompt", width=300, max_height=100)
gen_button = gr.Button('Generate images', width=150, height=30)
stop_button = gr.Button('Stop', variant='secondary', interactive=False, width=150, height=30)
gen_button.click(lambda s: gr.update(interactive=True), None, stop_button)
gr.HTML("""
<div style="text-align: center; max-width: 100%; margin: 0 auto;">
<body>
</body>
</div>
""")
with gr.Row():
output = [gr.Image(label=m, min_width=170, height=170) 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, negative_prompt_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' {num_models} different models selected', value=default_models, multiselect=True, max_choices=num_models, interactive=True, filterable=False)
# 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> 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>
# """)
js_code = """
<script>
const originalScroll = window.scrollTo;
const originalShowToast = gradio.Toast.show;
gradio.Toast.show = function() {
originalShowToast.apply(this, arguments);
window.scrollTo = function() {};};
setTimeout(() => {
window.scrollTo = originalScroll;
}, 300000); // Restore scroll function after 3 seconds
</script>
"""
with gr.Blocks(css="div.float.svelte-1mwvhlq { position: absolute; top: var(--block-label-margin); left: var(--block-label-margin); background: none; border: none;}") as demo:
gr.Markdown("<div></div>")
make_me()
gr.Markdown(js_code)
demo.queue(concurrency_count=50)
demo.launch()
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