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import argparse | ||
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import gradio as gr | ||
import numpy as np | ||
import torch | ||
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from pulid import attention_processor as attention | ||
from pulid.pipeline_v1_1 import PuLIDPipeline | ||
from pulid.utils import resize_numpy_image_long | ||
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torch.set_grad_enabled(False) | ||
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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() | ||
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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 | ||
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pipeline = PuLIDPipeline(sdxl_repo=args.base, sampler=args.sampler) | ||
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# 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' | ||
) | ||
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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, | ||
], | ||
] | ||
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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], | ||
] | ||
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@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() | ||
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pipeline.debug_img_list = [] | ||
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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 | ||
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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 | ||
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img = pipeline.inference( | ||
prompt, (1, H, W), neg_prompt, id_embedding, uncond_id_embedding, id_scale, scale, steps, seed | ||
)[0] | ||
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return np.array(img), str(seed), pipeline.debug_img_list | ||
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_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 | ||
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_CITE_ = r""" | ||
If PuLID is helpful, please help to ⭐ the <a href='https://github.com/ToTheBeginning/PuLID' target='_blank'>Github Repo</a>. Thanks! [![GitHub Stars](https://img.shields.io/github/stars/ToTheBeginning/PuLID?style=social)](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 | ||
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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) | ||
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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_) | ||
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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', | ||
) | ||
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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]) | ||
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demo.launch(server_name='0.0.0.0', server_port=args.port) |
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# PuLID v1.1 | ||
Following are some examples generated by PuLID-v1.1, you can reproduce these results from our Gradio demo. | ||
![release_v1 1](https://github.com/user-attachments/assets/d5bf3865-5147-428d-bb98-80812c680900) | ||
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## How to use | ||
### Online demo | ||
We plan to upgrade the PuLID demo to v1.1 soon, please stay tuned. | ||
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### Local demo | ||
```bash | ||
python app_v1.1.py --base BASE_MODEL | ||
Usage: | ||
-base: can be RunDiffusion/Juggernaut-XL-v9 or Lykon/dreamshaper-xl-lightning | ||
``` | ||
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