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Running on Zero
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6d3d2e5 978bbab 1e166a2 2574268 1e166a2 6d3d2e5 83a2290 6d3d2e5 ed6bd68 83a2290 f28667e 6d3d2e5 83a2290 6d3d2e5 cd4f0c3 2574268 83a2290 f28667e 22f7727 83a2290 978bbab fc5875c 978bbab fc5875c 978bbab bb106a4 5c44a43 d250056 8fc474a 978bbab 83a2290 22f7727 6d3d2e5 22f7727 83a2290 22f7727 6d3d2e5 1e166a2 1f4ff16 978bbab 1e166a2 22f7727 83a2290 22f7727 1e166a2 22f7727 1e166a2 22f7727 6d3d2e5 22f7727 1e166a2 22f7727 ed6bd68 22f7727 ed6bd68 6d3d2e5 bb106a4 978bbab bb106a4 5c44a43 2574268 d250056 8fc474a 6d3d2e5 2574268 6d3d2e5 cd4f0c3 1e166a2 1f4ff16 978bbab 1e166a2 bb106a4 978bbab d250056 8fc474a 6d3d2e5 1e166a2 6d3d2e5 978bbab bb106a4 5c44a43 d250056 8fc474a 81ad766 3169c9c 1e166a2 e665f99 3169c9c 74c91d3 81ad766 3169c9c 1e166a2 e665f99 3169c9c 6d3d2e5 83a2290 5056f16 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 | import os
import random
import tempfile
import uuid
from datetime import datetime, timezone
from pathlib import Path
from typing import Optional
import gradio as gr
import spaces
import torch
from diffusers import StableDiffusionPipeline
MODEL_ID = os.getenv("MODEL_ID", "stabilityai/sd-turbo")
MAX_STEPS = int(os.getenv("MAX_STEPS", "12"))
GPU_DURATION = max(10, min(int(os.getenv("GPU_DURATION", "20")), 30))
BUILD_TAG = os.getenv("SPACE_BUILD_TAG", datetime.now(timezone.utc).strftime("%Y-%m-%d %H:%M:%S UTC"))
_pipe: Optional[StableDiffusionPipeline] = None
_pipe_cpu: Optional[StableDiffusionPipeline] = None
SAFE_RANDOM_PROMPTS = [
"cinematic forest path at golden hour, ultra detailed, soft volumetric light",
"futuristic neon city street in rain, reflections, moody atmosphere, photoreal",
"cozy mountain cabin in winter, warm lights, snowfall, realistic texture",
"epic fantasy castle on a cliff, dramatic sky, matte painting style",
"macro photo of a dew-covered leaf, shallow depth of field, 8k",
"anime style girl in cyberpunk tokyo, dynamic lighting, highly detailed",
"astronaut walking on alien planet, cinematic composition, ultra wide shot",
"vintage film noir detective in old city alley, monochrome, grain",
"luxury sports car in studio, rim light, glossy reflections, product photo",
"majestic dragon flying over snowy mountains, fantasy concept art",
]
ADULT_RANDOM_PROMPTS = [
"tasteful sensual portrait, studio soft light, high detail skin, fine art",
"boudoir fashion photo, cinematic shadows, elegant pose, photoreal",
"romantic intimate couple portrait, warm light, shallow depth of field",
"glamour portrait, beauty lighting, ultra realistic details, 85mm lens",
"artistic nude silhouette, dramatic rim light, black background, fine art",
"editorial lingerie photoshoot, luxury hotel room, cinematic color grading",
"pin-up style portrait, retro lighting, detailed makeup, high contrast",
"moody bedroom portrait, neon accent light, realistic skin texture",
"high-fashion sensual photoshoot, magazine style, sharp focus",
"tasteful body portrait, soft shadows, museum-grade fine art photography",
]
STYLE_TAGS = {
"Cinematic": ["cinematic", "film", "volumetric", "dramatic"],
"Photo": ["photo", "photoreal", "lens", "realistic", "macro", "studio soft light"],
"Anime": ["anime", "manga"],
"Fantasy": ["fantasy", "dragon", "castle", "matte painting", "alien"],
"Studio": ["studio", "product", "rim light", "beauty lighting", "editorial", "fashion"],
}
STYLE_NEGATIVE_PROMPTS = {
"Mix": "blurry, low quality, worst quality, jpeg artifacts, watermark",
"Cinematic": "blurry, low quality, flat lighting, overexposed, underexposed, watermark",
"Photo": "blurry, low quality, cartoon, cgi, plastic skin, overprocessed, watermark",
"Anime": "blurry, low quality, bad anatomy, extra fingers, deformed face, watermark, text",
"Fantasy": "blurry, low quality, low detail, muddy colors, watermark",
"Studio": "blurry, low quality, bad skin texture, harsh shadows, watermark",
}
PHOTOREAL_PRO_NEGATIVE = (
"blurry, low quality, worst quality, cartoon, anime, illustration, cgi,"
" plastic skin, overprocessed skin, deformed face, extra fingers, watermark, text"
)
PORTRAIT_PRO_NEGATIVE = (
"blurry, low quality, worst quality, cartoon, anime, illustration, cgi,"
" deformed face, malformed face, asymmetrical eyes, extra eyes, duplicate face,"
" multiple faces, twin face, cloned face, extra limbs, bad anatomy, watermark, text"
)
HUMAN_KEYWORDS = {
"woman",
"man",
"girl",
"boy",
"female",
"male",
"person",
"portrait",
"face",
"frau",
"mann",
"gesicht",
"nackt",
"nude",
}
ADULT_KEYWORDS = {
"nude",
"nudity",
"nsfw",
"explicit",
"sex",
"sexual",
"erotic",
"porn",
"boobs",
"breasts",
"nipples",
"penis",
"vagina",
"fetish",
"lingerie",
"naked",
}
def get_pipe(force_cpu: bool = False) -> StableDiffusionPipeline:
global _pipe, _pipe_cpu
use_gpu = torch.cuda.is_available() and not force_cpu
if use_gpu:
if _pipe is not None:
return _pipe
load_kwargs = {"torch_dtype": torch.float16, "variant": "fp16"}
_pipe = StableDiffusionPipeline.from_pretrained(MODEL_ID, **load_kwargs)
_pipe = _pipe.to("cuda")
return _pipe
if _pipe_cpu is not None:
return _pipe_cpu
load_kwargs = {"torch_dtype": torch.float32}
_pipe_cpu = StableDiffusionPipeline.from_pretrained(MODEL_ID, **load_kwargs)
_pipe_cpu = _pipe_cpu.to("cpu")
return _pipe_cpu
def _generate_core(
prompt: str,
negative_prompt: str,
steps: int,
guidance: float,
width: int,
height: int,
seed: str,
adult_enabled: bool,
realism_boost: bool,
force_cpu: bool,
):
if not prompt.strip():
raise gr.Error("Prompt darf nicht leer sein.")
prompt_text = prompt.strip()
lowered_prompt = prompt_text.lower()
if not adult_enabled and any(keyword in lowered_prompt for keyword in ADULT_KEYWORDS):
raise gr.Error("Adult-Inhalte sind deaktiviert. Aktiviere den Adult-Schalter, um diesen Prompt zu nutzen.")
pipe = get_pipe(force_cpu=force_cpu)
steps = max(1, min(int(steps), MAX_STEPS))
width = max(256, min(int(width), 1024))
height = max(256, min(int(height), 1024))
width = max(64, (width // 64) * 64)
height = max(64, (height // 64) * 64)
prompt_for_generation = prompt_text
negative_for_generation = negative_prompt.strip() or ""
lowered_prompt = prompt_for_generation.lower()
is_human_prompt = any(keyword in lowered_prompt for keyword in HUMAN_KEYWORDS)
if realism_boost:
prompt_for_generation = (
f"{prompt_for_generation}, photorealistic, ultra detailed, realistic lighting, natural skin texture,"
" sharp focus, high dynamic range"
)
realism_negative = "cartoon, anime, illustration, lowres, deformed, oversaturated"
negative_for_generation = f"{negative_for_generation}, {realism_negative}".strip(", ")
if is_human_prompt:
prompt_for_generation = (
f"{prompt_for_generation}, single subject, one person, one face, centered composition,"
" anatomically correct face, symmetrical eyes"
)
human_negative = (
"multiple faces, duplicate face, extra eyes, extra nose, cloned face, bad facial anatomy"
)
negative_for_generation = f"{negative_for_generation}, {human_negative}".strip(", ")
seed_text = "" if seed is None else str(seed).strip()
seed_value = int(seed_text) if seed_text else 42
generator_device = "cpu" if force_cpu else ("cuda" if torch.cuda.is_available() else "cpu")
generator = torch.Generator(device=generator_device)
generator.manual_seed(seed_value)
result = pipe(
prompt=prompt_for_generation,
negative_prompt=negative_for_generation or None,
num_inference_steps=steps,
guidance_scale=float(guidance),
width=width,
height=height,
generator=generator,
)
image = result.images[0]
temp_dir = Path(tempfile.gettempdir()) / "pixelforge_downloads"
temp_dir.mkdir(parents=True, exist_ok=True)
download_path = temp_dir / f"pixelforge_{uuid.uuid4().hex[:12]}.png"
image.save(download_path)
return image, str(download_path)
@spaces.GPU(duration=GPU_DURATION)
def generate_image_gpu(
prompt: str,
negative_prompt: str,
steps: int,
guidance: float,
width: int,
height: int,
seed: str,
adult_enabled: bool,
realism_boost: bool,
):
return _generate_core(
prompt,
negative_prompt,
steps,
guidance,
width,
height,
seed,
adult_enabled,
realism_boost,
force_cpu=False,
)
def generate_image(
prompt: str,
negative_prompt: str,
steps: int,
guidance: float,
width: int,
height: int,
seed: str,
adult_enabled: bool,
realism_boost: bool,
):
try:
return generate_image_gpu(
prompt,
negative_prompt,
steps,
guidance,
width,
height,
seed,
adult_enabled,
realism_boost,
)
except Exception as exc:
message = str(exc)
if "quota" in message.lower() or "zerogpu" in message.lower():
return _generate_core(
prompt,
negative_prompt,
steps,
guidance,
width,
height,
seed,
adult_enabled,
realism_boost,
force_cpu=True,
)
if isinstance(exc, gr.Error):
raise
raise gr.Error(f"Generierung fehlgeschlagen: {exc}") from exc
def random_prompt(adult_enabled: bool, style: str):
prompts = ADULT_RANDOM_PROMPTS if adult_enabled else SAFE_RANDOM_PROMPTS
selected_style = style if style in STYLE_TAGS else "Mix"
if selected_style == "Mix":
filtered_prompts = prompts
else:
tags = STYLE_TAGS[selected_style]
filtered_prompts = [
prompt_text
for prompt_text in prompts
if any(tag in prompt_text.lower() for tag in tags)
]
if not filtered_prompts:
filtered_prompts = prompts
selected_prompt = random.choice(filtered_prompts)
negative_prompt = STYLE_NEGATIVE_PROMPTS.get(selected_style, STYLE_NEGATIVE_PROMPTS["Mix"])
if adult_enabled:
negative_prompt = f"{negative_prompt}, child, young, underage, teen, loli"
return selected_prompt, negative_prompt
def apply_photoreal_pro_preset(adult_enabled: bool):
base_negative = PHOTOREAL_PRO_NEGATIVE
if adult_enabled:
base_negative = f"{base_negative}, child, young, underage, teen, loli"
return base_negative, 2.4, 896, 896, "Photo", True
def apply_portrait_pro_preset(adult_enabled: bool):
base_negative = PORTRAIT_PRO_NEGATIVE
if adult_enabled:
base_negative = f"{base_negative}, child, young, underage, teen, loli"
return base_negative, 2.8, 704, 960, "Photo", True
with gr.Blocks(title="PixelForge ZeroGPU") as demo:
gr.Markdown("## PixelForge ZeroGPU")
gr.Markdown("Leichte ZeroGPU-App für Text-zu-Bild mit SD-Turbo.")
gr.Markdown(f"Build: {BUILD_TAG}")
with gr.Row():
with gr.Column(scale=1):
prompt = gr.Textbox(label="Prompt", placeholder="z. B. cinematic cyberpunk city at night", lines=3)
negative_prompt = gr.Textbox(label="Negative Prompt", value="blurry, low quality", lines=2)
steps = gr.Slider(1, MAX_STEPS, value=min(8, MAX_STEPS), step=1, label="Steps")
guidance = gr.Slider(0.0, 8.0, value=2.4, step=0.1, label="Guidance")
width = gr.Slider(256, 1024, value=768, step=64, label="Bildbreite")
height = gr.Slider(256, 1024, value=768, step=64, label="Bildhöhe")
seed = gr.Textbox(label="Seed", value="42")
adult_enabled = gr.Checkbox(label="Adult-Generierung erlauben (18+)", value=False)
realism_boost = gr.Checkbox(label="Realismus Boost", value=True)
style_select = gr.Dropdown(
label="Random Style",
choices=["Mix", "Cinematic", "Photo", "Anime", "Fantasy", "Studio"],
value="Mix",
)
random_btn = gr.Button("Random Prompt", variant="secondary")
photoreal_btn = gr.Button("Photoreal Pro Preset", variant="secondary")
portrait_btn = gr.Button("Portrait Pro Preset", variant="secondary")
run_btn = gr.Button("Bild erzeugen", variant="primary")
with gr.Column(scale=1):
image_out = gr.Image(label="Ergebnis", type="pil", elem_id="result-image", height=720)
download_out = gr.File(label="Download", file_count="single")
random_btn.click(
fn=random_prompt,
inputs=[adult_enabled, style_select],
outputs=[prompt, negative_prompt],
queue=False,
api_name=False,
)
photoreal_btn.click(
fn=apply_photoreal_pro_preset,
inputs=[adult_enabled],
outputs=[negative_prompt, guidance, width, height, style_select, realism_boost],
queue=False,
api_name=False,
)
portrait_btn.click(
fn=apply_portrait_pro_preset,
inputs=[adult_enabled],
outputs=[negative_prompt, guidance, width, height, style_select, realism_boost],
queue=False,
api_name=False,
)
run_btn.click(
fn=generate_image,
inputs=[prompt, negative_prompt, steps, guidance, width, height, seed, adult_enabled, realism_boost],
outputs=[image_out, download_out],
queue=False,
api_name=False,
)
prompt.submit(
fn=generate_image,
inputs=[prompt, negative_prompt, steps, guidance, width, height, seed, adult_enabled, realism_boost],
outputs=[image_out, download_out],
queue=False,
api_name=False,
)
if __name__ == "__main__":
demo.launch(
server_name="0.0.0.0",
server_port=int(os.getenv("PORT", "7860")),
show_error=True,
show_api=False,
) |