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import gradio as gr | |
from random import randint | |
from all_models import models | |
from externalmod import gr_Interface_load | |
import asyncio | |
import os | |
from threading import RLock | |
lock = RLock() | |
HF_TOKEN = os.environ.get("HF_TOKEN") if os.environ.get("HF_TOKEN") else None # If private or gated models aren't used, ENV setting is unnecessary. | |
def load_fn(models): | |
global models_load | |
models_load = {} | |
for model in models: | |
if model not in models_load.keys(): | |
try: | |
m = gr_Interface_load(f'models/{model}', hf_token=HF_TOKEN) | |
except Exception as error: | |
print(error) | |
m = gr.Interface(lambda: None, ['text'], ['image']) | |
models_load.update({model: m}) | |
load_fn(models) | |
num_models = 6 | |
MAX_SEED = 3999999999 | |
default_models = models[:num_models] | |
inference_timeout = 600 | |
starting_seed = randint(1941, 2024) | |
def extend_choices(choices): | |
return choices[:num_models] + (num_models - len(choices[:num_models])) * ['NA'] | |
def update_imgbox(choices): | |
choices_plus = extend_choices(choices[:num_models]) | |
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('') #str(randint(0, 99999999999)) | |
return models_load[model_str](f'{prompt} {noise}') | |
async def infer(model_str, prompt, seed=1, timeout=inference_timeout): | |
from pathlib import Path | |
kwargs = {} | |
noise = "" | |
kwargs["seed"] = seed | |
task = asyncio.create_task(asyncio.to_thread(models_load[model_str].fn, | |
prompt=f'{prompt} {noise}', **kwargs, token=HF_TOKEN)) | |
await asyncio.sleep(0) | |
try: | |
result = await asyncio.wait_for(task, timeout=timeout) | |
except (Exception, asyncio.TimeoutError) as e: | |
print(e) | |
print(f"Task timed out: {model_str}") | |
if not task.done(): task.cancel() | |
result = None | |
if task.done() and result is not None: | |
with lock: | |
png_path = "image.png" | |
result.save(png_path) | |
image = str(Path(png_path).resolve()) | |
return image | |
return None | |
def gen_fnseed(model_str, prompt, seed=1): | |
if model_str == 'NA': | |
return None | |
try: | |
loop = asyncio.new_event_loop() | |
result = loop.run_until_complete(infer(model_str, prompt, seed, inference_timeout)) | |
except (Exception, asyncio.CancelledError) as e: | |
print(e) | |
print(f"Task aborted: {model_str}") | |
result = None | |
finally: | |
loop.close() | |
return result | |
css=""" | |
.wrapper img {font-size: 98% !important; white-space: nowrap !important; text-align: center !important; | |
display: inline-block !important;} | |
""" | |
with gr.Blocks(css=css) as demo: | |
gr.HTML( | |
""" | |
<div style="text-align: center; max-width: 1200px; margin: 0 auto;"> | |
<div> | |
<body> | |
<div class="wrapper"><p style="margin-bottom: 10px;"><img src="https://huggingface.co/Yntec/DucHaitenLofi/resolve/main/NEW.webp" alt="NEW!" style="width:32px;height:16px;"> - A tab where you can use seeds has been added!</p> | |
</div> | |
</body> | |
</div> | |
</div> | |
""" | |
) | |
with gr.Tab('Toy World'): | |
txt_input = gr.Textbox(label='Your prompt:', lines=4) | |
gen_button = gr.Button('Generate up to 6 images in up to 3 minutes total') | |
#stop_button = gr.Button('Stop', variant = 'secondary', interactive = False) | |
gen_button.click(lambda s: gr.update(interactive = True), None) | |
gr.HTML( | |
""" | |
<div style="text-align: center; max-width: 1200px; margin: 0 auto;"> | |
<div> | |
<body> | |
<div class="center"><p style="margin-bottom: 10px; color: #000000;">Scroll down to see more images and select models.</p> | |
</div> | |
</body> | |
</div> | |
</div> | |
""" | |
) | |
with gr.Row(): | |
output = [gr.Image(label = m, min_width=480) 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 = gr.on(triggers=[gen_button.click, txt_input.submit], fn=gen_fn, | |
inputs=[m, txt_input], outputs=[o], concurrency_limit=None, queue=False) | |
#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 {int(num_models)} different models from the {len(models)} available!', value=default_models, interactive=True) | |
#model_choice = gr.CheckboxGroup(models, label = f'Choose up to {num_models} different models from the 2 available! Untick them to only use one!', 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/John6666/hfd_test_nostopbutton">Huggingface NoStopButton</a> Space by John6666, <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! For 6 images with the same model check out the <a href="https://huggingface.co/spaces/Yntec/PrintingPress">Printing Press</a>, for the classic UI with prompt enhancer try <a href="https://huggingface.co/spaces/Yntec/blitz_diffusion">Blitz Diffusion!</a> | |
</p> | |
""" | |
) | |
with gr.Tab('🌱 Use seeds!'): | |
txt_inputseed = gr.Textbox(label='Your prompt:', lines=4) | |
gen_buttonseed = gr.Button('Generate up to 6 images with the same seed in up to 3 minutes total') | |
seed = gr.Slider(label="Use a seed to replicate the same image later (maximum 3999999999)", minimum=0, maximum=MAX_SEED, step=1, value=starting_seed, scale=3) | |
#stop_button = gr.Button('Stop', variant = 'secondary', interactive = False) | |
gen_buttonseed.click(lambda s: gr.update(interactive = True), None) | |
gr.HTML( | |
""" | |
<div style="text-align: center; max-width: 1200px; margin: 0 auto;"> | |
<div> | |
<body> | |
<div class="center"><p style="margin-bottom: 10px; color: #000000;">Scroll down to see more images and select models.</p> | |
</div> | |
</body> | |
</div> | |
</div> | |
""" | |
) | |
with gr.Row(): | |
output = [gr.Image(label = m, min_width=480) 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_eventseed = gr.on(triggers=[gen_buttonseed.click, txt_inputseed.submit], fn=gen_fnseed, | |
inputs=[m, txt_inputseed, seed], outputs=[o], concurrency_limit=None, queue=False) | |
#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 {int(num_models)} different models from the {len(models)} available!', value=default_models, interactive=True) | |
#model_choice = gr.CheckboxGroup(models, label = f'Choose up to {num_models} different models from the 2 available! Untick them to only use one!', 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/John6666/hfd_test_nostopbutton">Huggingface NoStopButton</a> Space by John6666, <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! For 6 images with the same model check out the <a href="https://huggingface.co/spaces/Yntec/PrintingPress">Printing Press</a>, for the classic UI with prompt enhancer try <a href="https://huggingface.co/spaces/Yntec/blitz_diffusion">Blitz Diffusion!</a> | |
</p> | |
""" | |
) | |
demo.queue(default_concurrency_limit=200, max_size=200) | |
demo.launch(show_api=False, max_threads=400) |