File size: 20,404 Bytes
92a699d |
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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 |
import argparse
import gradio as gr
import numpy as np
import torch
from pulid import attention_processor as attention
from pulid.pipeline_v1_1 import PuLIDPipeline
from pulid.utils import resize_numpy_image_long
torch.set_grad_enabled(False)
parser = argparse.ArgumentParser()
parser.add_argument(
'--base',
type=str,
default='RunDiffusion/Juggernaut-XL-v9',
choices=[
'Lykon/dreamshaper-xl-lightning',
# 'SG161222/RealVisXL_V4.0', will add it later
'RunDiffusion/Juggernaut-XL-v9',
],
)
# parser.add_argument('--sampler', type=str, default='dpmpp_2m', choices=['dpmpp_sde', 'dpmpp_2m'])
parser.add_argument('--port', type=int, default=7860)
args = parser.parse_args()
use_lightning_model = 'lightning' in args.base.lower()
# currently we only support two commonly used sampler
args.sampler = 'dpmpp_sde' if use_lightning_model else 'dpmpp_2m'
if use_lightning_model:
default_cfg = 2.0
default_steps = 5
else:
default_cfg = 7.0
default_steps = 25
pipeline = PuLIDPipeline(sdxl_repo=args.base, sampler=args.sampler)
# other params
DEFAULT_NEGATIVE_PROMPT = (
'flaws in the eyes, flaws in the face, flaws, lowres, non-HDRi, low quality, worst quality,'
'artifacts noise, text, watermark, glitch, deformed, mutated, ugly, disfigured, hands, '
'low resolution, partially rendered objects, deformed or partially rendered eyes, '
'deformed, deformed eyeballs, cross-eyed,blurry'
)
dreamshaper_example_inps = [
['portrait, blacklight', 'example_inputs/liuyifei.png', 42, 0.8, 10],
['pixel art, 1boy', 'example_inputs/lecun.jpg', 42, 0.8, 10],
[
'cinematic film still, close up, photo of redheaded girl near grasses, fictional landscapes, (intense sunlight:1.4), realist detail, brooding mood, ue5, detailed character expressions, light amber and red, amazing quality, wallpaper, analog film grain',
'example_inputs/liuyifei.png',
42,
0.8,
10,
],
[
'A minimalist line art depiction of an Artificial Intelligence being\'s thought process, lines and nodes forming intricate patterns.',
'example_inputs/hinton.jpeg',
42,
0.8,
10,
],
[
'instagram photo, photo of 23 y.o man in black sweater, pale skin, (smile:0.4), hard shadows',
'example_inputs/pengwei.jpg',
42,
0.8,
10,
],
[
'by Tsutomu Nihei,(strange but extremely beautiful:1.4),(masterpiece, best quality:1.4),in the style of nicola samori,The Joker,',
'example_inputs/lecun.jpg',
1675432759740519133,
0.8,
10,
],
]
jugger_example_inps = [
[
'robot,simple robot,robot with glass face,ellipse head robot,(made partially out of glass),hexagonal shapes,ferns growing inside head,butterflies on head,butterflies flying around',
'example_inputs/hinton.jpeg',
15022214902832471291,
0.8,
20,
],
['sticker art, 1girl', 'example_inputs/liuyifei.png', 42, 0.8, 20],
[
'1girl, cute model, Long thick Maxi Skirt, Knit sweater, swept back hair, alluring smile, working at a clothing store, perfect eyes, highly detailed beautiful expressive eyes, detailed eyes, 35mm photograph, film, bokeh, professional, 4k, highly detailed dynamic lighting, photorealistic, 8k, raw, rich, intricate details,',
'example_inputs/liuyifei.png',
42,
0.8,
20,
],
['Chinese paper-cut, 1girl', 'example_inputs/liuyifei.png', 42, 0.8, 20],
['Studio Ghibli, 1boy', 'example_inputs/hinton.jpeg', 42, 0.8, 20],
['1man made of ice sculpture', 'example_inputs/lecun.jpg', 42, 0.8, 20],
['portrait of green-skinned shrek, wearing lacoste purple sweater', 'example_inputs/lecun.jpg', 42, 0.8, 20],
['1990s Japanese anime, 1girl', 'example_inputs/liuyifei.png', 42, 0.8, 20],
['made of little stones, portrait', 'example_inputs/hinton.jpeg', 42, 0.8, 20],
]
@torch.inference_mode()
def run(*args):
id_image = args[0]
supp_images = args[1:4]
prompt, neg_prompt, scale, seed, steps, H, W, id_scale, num_zero, ortho = args[4:]
seed = int(seed)
if seed == -1:
seed = torch.Generator(device="cpu").seed()
pipeline.debug_img_list = []
attention.NUM_ZERO = num_zero
if ortho == 'v2':
attention.ORTHO = False
attention.ORTHO_v2 = True
elif ortho == 'v1':
attention.ORTHO = True
attention.ORTHO_v2 = False
else:
attention.ORTHO = False
attention.ORTHO_v2 = False
if id_image is not None:
id_image = resize_numpy_image_long(id_image, 1024)
supp_id_image_list = [
resize_numpy_image_long(supp_id_image, 1024) for supp_id_image in supp_images if supp_id_image is not None
]
id_image_list = [id_image] + supp_id_image_list
uncond_id_embedding, id_embedding = pipeline.get_id_embedding(id_image_list)
else:
uncond_id_embedding = None
id_embedding = None
img = pipeline.inference(
prompt, (1, H, W), neg_prompt, id_embedding, uncond_id_embedding, id_scale, scale, steps, seed
)[0]
return np.array(img), str(seed), pipeline.debug_img_list
_HEADER_ = '''
<h2><b>Official Gradio Demo</b></h2><h2><a href='https://github.com/ToTheBeginning/PuLID' target='_blank'><b>PuLID: Pure and Lightning ID Customization via Contrastive Alignment</b></a></h2>
**PuLID** is a tuning-free ID customization approach. PuLID maintains high ID fidelity while effectively reducing interference with the original model’s behavior.
Code: <a href='https://github.com/ToTheBeginning/PuLID' target='_blank'>GitHub</a>. Paper: <a href='https://arxiv.org/abs/2404.16022' target='_blank'>ArXiv</a>.
❗️❗️❗️**Tips:**
- we provide some examples in the bottom, you can try these example prompts first
- a single ID image is usually sufficient, you can also supplement with additional auxiliary images
- You can adjust the trade-off between ID fidelity and editability in the advanced options, but generally, the default settings are good enough.
''' # noqa E501
_CITE_ = r"""
If PuLID is helpful, please help to ⭐ the <a href='https://github.com/ToTheBeginning/PuLID' target='_blank'>Github Repo</a>. Thanks! [](https://github.com/ToTheBeginning/PuLID)
---
📧 **Contact**
If you have any questions, feel free to open a discussion or contact us at <b>[email protected]</b> or <b>[email protected]</b>.
""" # noqa E501
with gr.Blocks(title="PuLID", css=".gr-box {border-color: #8136e2}") as demo:
gr.Markdown(_HEADER_)
with gr.Row():
with gr.Column():
with gr.Row():
face_image = gr.Image(label="ID image (main)", height=256)
supp_image1 = gr.Image(label="Additional ID image (auxiliary)", height=256)
supp_image2 = gr.Image(label="Additional ID image (auxiliary)", height=256)
supp_image3 = gr.Image(label="Additional ID image (auxiliary)", height=256)
prompt = gr.Textbox(label="Prompt", value='portrait,color,cinematic,in garden,soft light,detailed face')
submit = gr.Button("Generate")
neg_prompt = gr.Textbox(label="Negative Prompt", value=DEFAULT_NEGATIVE_PROMPT)
scale = gr.Slider(
label="CFG (recommend 2 for lightning model and 7 for non-accelerated model)",
value=default_cfg,
minimum=1,
maximum=10,
step=0.1,
)
seed = gr.Textbox(-1, label="Seed (-1 for random)")
steps = gr.Slider(label="Steps", value=default_steps, minimum=1, maximum=30, step=1)
with gr.Row():
H = gr.Slider(label="Height", value=1152, minimum=512, maximum=2024, step=64)
W = gr.Slider(label="Width", value=896, minimum=512, maximum=2024, step=64)
with gr.Row(), gr.Accordion(
"Advanced Options (adjust the trade-off between ID fidelity and editability)", open=False
):
id_scale = gr.Slider(
label="ID scale (Increasing it enhances ID similarity but reduces editability)",
minimum=0,
maximum=5,
step=0.05,
value=0.8,
interactive=True,
)
num_zero = gr.Slider(
label="num zero (Increasing it enhances ID editability but reduces similarity)",
minimum=0,
maximum=80,
step=1,
value=20,
interactive=True,
)
ortho = gr.Dropdown(label="ortho", choices=['off', 'v1', 'v2'], value='v2', visible=False)
with gr.Column():
output = gr.Image(label="Generated Image")
seed_output = gr.Textbox(label="Used Seed")
intermediate_output = gr.Gallery(label='DebugImage', elem_id="gallery", visible=False)
gr.Markdown(_CITE_)
with gr.Row(), gr.Column():
gr.Markdown("## Examples")
if args.base == 'Lykon/dreamshaper-xl-lightning':
gr.Examples(
examples=dreamshaper_example_inps,
inputs=[prompt, face_image, seed, id_scale, num_zero],
label='dreamshaper-xl-lightning examples',
)
elif args.base == 'RunDiffusion/Juggernaut-XL-v9':
gr.Examples(
examples=jugger_example_inps,
inputs=[prompt, face_image, seed, id_scale, num_zero],
label='Juggernaut-XL-v9 examples',
)
inps = [
face_image,
supp_image1,
supp_image2,
supp_image3,
prompt,
neg_prompt,
scale,
seed,
steps,
H,
W,
id_scale,
num_zero,
ortho,
]
submit.click(fn=run, inputs=inps, outputs=[output, seed_output, intermediate_output])
import argparse
import gradio as gr
import numpy as np
import torch
from pulid import attention_processor as attention
from pulid.pipeline_v1_1 import PuLIDPipeline
from pulid.utils import resize_numpy_image_long
torch.set_grad_enabled(False)
parser = argparse.ArgumentParser()
parser.add_argument(
'--base',
type=str,
default='RunDiffusion/Juggernaut-XL-v9',
choices=[
'Lykon/dreamshaper-xl-lightning',
# 'SG161222/RealVisXL_V4.0', will add it later
'RunDiffusion/Juggernaut-XL-v9',
],
)
# parser.add_argument('--sampler', type=str, default='dpmpp_2m', choices=['dpmpp_sde', 'dpmpp_2m'])
parser.add_argument('--port', type=int, default=7860)
args = parser.parse_args()
use_lightning_model = 'lightning' in args.base.lower()
# currently we only support two commonly used sampler
args.sampler = 'dpmpp_sde' if use_lightning_model else 'dpmpp_2m'
if use_lightning_model:
default_cfg = 2.0
default_steps = 5
else:
default_cfg = 7.0
default_steps = 25
pipeline = PuLIDPipeline(sdxl_repo=args.base, sampler=args.sampler)
# other params
DEFAULT_NEGATIVE_PROMPT = (
'flaws in the eyes, flaws in the face, flaws, lowres, non-HDRi, low quality, worst quality,'
'artifacts noise, text, watermark, glitch, deformed, mutated, ugly, disfigured, hands, '
'low resolution, partially rendered objects, deformed or partially rendered eyes, '
'deformed, deformed eyeballs, cross-eyed,blurry'
)
dreamshaper_example_inps = [
['portrait, blacklight', 'example_inputs/liuyifei.png', 42, 0.8, 10],
['pixel art, 1boy', 'example_inputs/lecun.jpg', 42, 0.8, 10],
[
'cinematic film still, close up, photo of redheaded girl near grasses, fictional landscapes, (intense sunlight:1.4), realist detail, brooding mood, ue5, detailed character expressions, light amber and red, amazing quality, wallpaper, analog film grain',
'example_inputs/liuyifei.png',
42,
0.8,
10,
],
[
'A minimalist line art depiction of an Artificial Intelligence being\'s thought process, lines and nodes forming intricate patterns.',
'example_inputs/hinton.jpeg',
42,
0.8,
10,
],
[
'instagram photo, photo of 23 y.o man in black sweater, pale skin, (smile:0.4), hard shadows',
'example_inputs/pengwei.jpg',
42,
0.8,
10,
],
[
'by Tsutomu Nihei,(strange but extremely beautiful:1.4),(masterpiece, best quality:1.4),in the style of nicola samori,The Joker,',
'example_inputs/lecun.jpg',
1675432759740519133,
0.8,
10,
],
]
jugger_example_inps = [
[
'robot,simple robot,robot with glass face,ellipse head robot,(made partially out of glass),hexagonal shapes,ferns growing inside head,butterflies on head,butterflies flying around',
'example_inputs/hinton.jpeg',
15022214902832471291,
0.8,
20,
],
['sticker art, 1girl', 'example_inputs/liuyifei.png', 42, 0.8, 20],
[
'1girl, cute model, Long thick Maxi Skirt, Knit sweater, swept back hair, alluring smile, working at a clothing store, perfect eyes, highly detailed beautiful expressive eyes, detailed eyes, 35mm photograph, film, bokeh, professional, 4k, highly detailed dynamic lighting, photorealistic, 8k, raw, rich, intricate details,',
'example_inputs/liuyifei.png',
42,
0.8,
20,
],
['Chinese paper-cut, 1girl', 'example_inputs/liuyifei.png', 42, 0.8, 20],
['Studio Ghibli, 1boy', 'example_inputs/hinton.jpeg', 42, 0.8, 20],
['1man made of ice sculpture', 'example_inputs/lecun.jpg', 42, 0.8, 20],
['portrait of green-skinned shrek, wearing lacoste purple sweater', 'example_inputs/lecun.jpg', 42, 0.8, 20],
['1990s Japanese anime, 1girl', 'example_inputs/liuyifei.png', 42, 0.8, 20],
['made of little stones, portrait', 'example_inputs/hinton.jpeg', 42, 0.8, 20],
]
@torch.inference_mode()
def run(*args):
id_image = args[0]
supp_images = args[1:4]
prompt, neg_prompt, scale, seed, steps, H, W, id_scale, num_zero, ortho = args[4:]
seed = int(seed)
if seed == -1:
seed = torch.Generator(device="cpu").seed()
pipeline.debug_img_list = []
attention.NUM_ZERO = num_zero
if ortho == 'v2':
attention.ORTHO = False
attention.ORTHO_v2 = True
elif ortho == 'v1':
attention.ORTHO = True
attention.ORTHO_v2 = False
else:
attention.ORTHO = False
attention.ORTHO_v2 = False
if id_image is not None:
id_image = resize_numpy_image_long(id_image, 1024)
supp_id_image_list = [
resize_numpy_image_long(supp_id_image, 1024) for supp_id_image in supp_images if supp_id_image is not None
]
id_image_list = [id_image] + supp_id_image_list
uncond_id_embedding, id_embedding = pipeline.get_id_embedding(id_image_list)
else:
uncond_id_embedding = None
id_embedding = None
img = pipeline.inference(
prompt, (1, H, W), neg_prompt, id_embedding, uncond_id_embedding, id_scale, scale, steps, seed
)[0]
return np.array(img), str(seed), pipeline.debug_img_list
_HEADER_ = '''
<h2><b>Official Gradio Demo</b></h2><h2><a href='https://github.com/ToTheBeginning/PuLID' target='_blank'><b>PuLID: Pure and Lightning ID Customization via Contrastive Alignment</b></a></h2>
**PuLID** is a tuning-free ID customization approach. PuLID maintains high ID fidelity while effectively reducing interference with the original model’s behavior.
Code: <a href='https://github.com/ToTheBeginning/PuLID' target='_blank'>GitHub</a>. Paper: <a href='https://arxiv.org/abs/2404.16022' target='_blank'>ArXiv</a>.
❗️❗️❗️**Tips:**
- we provide some examples in the bottom, you can try these example prompts first
- a single ID image is usually sufficient, you can also supplement with additional auxiliary images
- You can adjust the trade-off between ID fidelity and editability in the advanced options, but generally, the default settings are good enough.
''' # noqa E501
_CITE_ = r"""
If PuLID is helpful, please help to ⭐ the <a href='https://github.com/ToTheBeginning/PuLID' target='_blank'>Github Repo</a>. Thanks! [](https://github.com/ToTheBeginning/PuLID)
---
📧 **Contact**
If you have any questions, feel free to open a discussion or contact us at <b>[email protected]</b> or <b>[email protected]</b>.
""" # noqa E501
with gr.Blocks(title="PuLID", css=".gr-box {border-color: #8136e2}") as demo:
gr.Markdown(_HEADER_)
with gr.Row():
with gr.Column():
with gr.Row():
face_image = gr.Image(label="ID image (main)", height=256)
supp_image1 = gr.Image(label="Additional ID image (auxiliary)", height=256)
supp_image2 = gr.Image(label="Additional ID image (auxiliary)", height=256)
supp_image3 = gr.Image(label="Additional ID image (auxiliary)", height=256)
prompt = gr.Textbox(label="Prompt", value='portrait,color,cinematic,in garden,soft light,detailed face')
submit = gr.Button("Generate")
neg_prompt = gr.Textbox(label="Negative Prompt", value=DEFAULT_NEGATIVE_PROMPT)
scale = gr.Slider(
label="CFG (recommend 2 for lightning model and 7 for non-accelerated model)",
value=default_cfg,
minimum=1,
maximum=10,
step=0.1,
)
seed = gr.Textbox(-1, label="Seed (-1 for random)")
steps = gr.Slider(label="Steps", value=default_steps, minimum=1, maximum=30, step=1)
with gr.Row():
H = gr.Slider(label="Height", value=1152, minimum=512, maximum=2024, step=64)
W = gr.Slider(label="Width", value=896, minimum=512, maximum=2024, step=64)
with gr.Row(), gr.Accordion(
"Advanced Options (adjust the trade-off between ID fidelity and editability)", open=False
):
id_scale = gr.Slider(
label="ID scale (Increasing it enhances ID similarity but reduces editability)",
minimum=0,
maximum=5,
step=0.05,
value=0.8,
interactive=True,
)
num_zero = gr.Slider(
label="num zero (Increasing it enhances ID editability but reduces similarity)",
minimum=0,
maximum=80,
step=1,
value=20,
interactive=True,
)
ortho = gr.Dropdown(label="ortho", choices=['off', 'v1', 'v2'], value='v2', visible=False)
with gr.Column():
output = gr.Image(label="Generated Image")
seed_output = gr.Textbox(label="Used Seed")
intermediate_output = gr.Gallery(label='DebugImage', elem_id="gallery", visible=False)
gr.Markdown(_CITE_)
with gr.Row(), gr.Column():
gr.Markdown("## Examples")
if args.base == 'Lykon/dreamshaper-xl-lightning':
gr.Examples(
examples=dreamshaper_example_inps,
inputs=[prompt, face_image, seed, id_scale, num_zero],
label='dreamshaper-xl-lightning examples',
)
elif args.base == 'RunDiffusion/Juggernaut-XL-v9':
gr.Examples(
examples=jugger_example_inps,
inputs=[prompt, face_image, seed, id_scale, num_zero],
label='Juggernaut-XL-v9 examples',
)
inps = [
face_image,
supp_image1,
supp_image2,
supp_image3,
prompt,
neg_prompt,
scale,
seed,
steps,
H,
W,
id_scale,
num_zero,
ortho,
]
submit.click(fn=run, inputs=inps, outputs=[output, seed_output, intermediate_output])
demo.launch(server_name='0.0.0.0', server_port=args.port)
demo.launch(server_name='0.0.0.0', server_port=args.port)
|