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import gradio as gr
from all_models import models
from externalmod import gr_Interface_load, save_image, randomize_seed
import asyncio
import os
from threading import RLock
from datetime import datetime
preSetPrompt = "cute tall slender athletic 20+ caucasian woman. gorgeous face. perky tits. sensual expression. lifting shirt. photorealistic. cinematic. f1.4"
negPreSetPrompt = "[deformed | disfigured], poorly drawn, [bad : wrong] anatomy, [extra | missing | floating | disconnected] limb, (mutated hands and fingers), blurry, text, fuzziness"
lock = RLock()
HF_TOKEN = os.environ.get("HF_TOKEN") if os.environ.get("HF_TOKEN") else None
def get_current_time():
now = datetime.now()
now2 = now
current_time = now2.strftime("%y-%m-%d %H:%M:%S")
return current_time
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_images = 6
inference_timeout = 400
default_models = models[:num_models]
MAX_SEED = 2**32-1
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 random_choices():
import random
random.seed()
return random.choices(models, k=num_models)
async def infer(model_str, prompt, nprompt="", height=0, width=0, steps=0, cfg=0, seed=-1, timeout=inference_timeout):
kwargs = {}
if height > 0: kwargs["height"] = height
if width > 0: kwargs["width"] = width
if steps > 0: kwargs["num_inference_steps"] = steps
if cfg > 0: cfg = kwargs["guidance_scale"] = cfg
if seed == -1:
theSeed = randomize_seed()
kwargs["seed"] = theSeed
else:
kwargs["seed"] = seed
theSeed = seed
task = asyncio.create_task(asyncio.to_thread(models_load[model_str].fn, prompt=prompt, negative_prompt=nprompt, **kwargs, token=HF_TOKEN))
await asyncio.sleep(0)
try:
result = await asyncio.wait_for(task, timeout=timeout)
except asyncio.TimeoutError as e:
print(e)
print(f"Task timed out: {model_str}")
if not task.done(): task.cancel()
result = None
raise Exception(f"Task timed out: {model_str}") from e
except Exception as e:
print(e)
if not task.done(): task.cancel()
result = None
raise Exception() from e
if task.done() and result is not None and not isinstance(result, tuple):
with lock:
png_path = model_str.replace("/", "_") + " - " + get_current_time() + "_" + str(theSeed) + ".png"
image = save_image(result, png_path, model_str, prompt, nprompt, height, width, steps, cfg, seed)
return image
return None
def gen_fn(model_str, prompt, nprompt="", height=0, width=0, steps=0, cfg=0, seed=-1):
if model_str == 'NA':
return None
try:
loop = asyncio.new_event_loop()
result = loop.run_until_complete(infer(model_str, prompt, nprompt,
height, width, steps, cfg, seed, inference_timeout))
except (Exception, asyncio.CancelledError) as e:
print(e)
print(f"Task aborted: {model_str}")
result = None
raise gr.Error(f"Task aborted: {model_str}, Error: {e}")
finally:
loop.close()
return result
def add_gallery(image, model_str, gallery):
if gallery is None:
gallery = []
if model_str == 'NA':
return gallery
with lock:
if image is not None:
gallery.insert(0, (image, model_str))
return gallery
js_func = """
function refresh() {
const url = new URL(window.location);
if (url.searchParams.get('__theme') !== 'dark') {
url.searchParams.set('__theme', 'dark');
window.location.href = url.href;
}
}
"""
js_AutoSave="""
console.log("Yo");
var img1 = document.querySelector("div#component-355 .svelte-1kpcxni button.svelte-1kpcxni .svelte-1kpcxni img"),
observer = new MutationObserver((changes) => {
changes.forEach(change => {
if(change.attributeName.includes('src')){
console.log(img1.src);
document.querySelector("div#component-355 .svelte-1kpcxni .svelte-sr71km a.svelte-1s8vnbx button").click();
}
});
});
observer.observe(img1, {attributes : true});
"""
CSS="""
.gradio-container { max-width: 1200px; margin: 0 auto; background: linear-gradient(to bottom, #1a1a1a, #2d2d2d); !important; }
.output {
width: 112px;
height: 112px;
border-radius: 10px;
box-shadow: 0 4px 8px rgba(0,0,0,0.2);
transition: transform 0.2s;
!important;
}
.output:hover {
transform: scale(1.05);
}
.gallery {
min-width: 512px;
min-height: 512px;
max-height: 512px;
border-radius: 15px;
box-shadow: 0 6px 12px rgba(0,0,0,0.3);
!important;
}
.guide { text-align: center; color: #e0e0e0; !important; }
.primary-btn {
background: linear-gradient(45deg, #4a90e2, #357abd);
border-radius: 8px;
transition: all 0.3s ease;
}
.primary-btn:hover {
transform: translateY(-2px);
box-shadow: 0 5px 15px rgba(74,144,226,0.3);
}
"""
with gr.Blocks(theme='NoCrypt/miku@>=1.2.2', fill_width=True, css=CSS) as demo:
gr.HTML("""<a href="https://visitorbadge.io/status?path=https%3A%2F%2Fgunship999-SexyImages.hf.space">
<img src="https://api.visitorbadge.io/api/visitors?path=https%3A%2F%2Fgunship999-SexyImages.hf.space&countColor=%23263759" />
</a>""")
with gr.Column(scale=2):
with gr.Accordion("Model Selection", open=True):
model_choice = gr.CheckboxGroup(
models,
label=f'Choose up to {int(num_models)} models',
value=default_models,
interactive=True
)
with gr.Group():
txt_input = gr.Textbox(
label='Your prompt:',
value=preSetPrompt,
lines=3,
autofocus=1
)
neg_input = gr.Textbox(
label='Negative prompt:',
value=negPreSetPrompt,
lines=1
)
with gr.Accordion("Advanced Settings", open=False):
with gr.Row():
width = gr.Slider(label="Width", maximum=1216, step=32, value=0)
height = gr.Slider(label="Height", maximum=1216, step=32, value=0)
with gr.Row():
steps = gr.Slider(label="Steps", maximum=100, step=1, value=0)
cfg = gr.Slider(label="Guidance Scale", maximum=30.0, step=0.1, value=0)
seed = gr.Slider(label="Seed", minimum=-1, maximum=MAX_SEED, step=1, value=-1)
seed_rand = gr.Button("🎲", size="sm", elem_classes="primary-btn")
seed_rand.click(randomize_seed, None, [seed], queue=False)
with gr.Row():
gen_button = gr.Button(
f'Generate {int(num_models)} Images',
variant='primary',
scale=3,
elem_classes="primary-btn"
)
random_button = gr.Button(
'Randomize Models',
variant='secondary',
scale=1
)
with gr.Column(scale=1):
with gr.Group():
with gr.Row():
output = [gr.Image(label=m, show_download_button=True,
elem_classes="output",
interactive=False, width=112, height=112,
show_share_button=False, format="png",
visible=True) for m in default_models]
current_models = [gr.Textbox(m, visible=False)
for m in default_models]
with gr.Column(scale=2):
gallery = gr.Gallery(
label="Generated Images",
show_download_button=True,
elem_classes="gallery",
interactive=False,
show_share_button=False,
container=True,
format="png",
preview=True,
object_fit="cover",
columns=2,
rows=2
)
model_choice.change(update_imgbox, model_choice, output)
model_choice.change(extend_choices, model_choice, current_models)
random_button.click(random_choices, None, model_choice)
for m, o in zip(current_models, output):
gen_event = gr.on(
triggers=[gen_button.click, txt_input.submit],
# 수정: 입력값을 실제 텍스트로 처리
fn=lambda txt, neg, h, w, s, c, seed, m=m: gen_fn(
m,
str(txt) if txt is not None else "",
str(neg) if neg is not None else "",
h, w, s, c, seed
) if m != 'NA' else None,
inputs=[txt_input, neg_input, height, width, steps, cfg, seed],
outputs=[o],
concurrency_limit=None,
queue=False
)
o.change(
fn=lambda img, g, m=m: add_gallery(img, m, g) if m != 'NA' else g,
inputs=[o, gallery],
outputs=[gallery]
)
demo.launch(show_api=False, max_threads=400) |