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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) |