Spaces:
Runtime error
Runtime error
File size: 9,155 Bytes
ff271bf |
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 |
import gradio as gr
import numpy as np
import torch
from pulid import attention_processor as attention
from pulid.pipeline import PuLIDPipeline
from pulid.utils import resize_numpy_image_long, seed_everything
torch.set_grad_enabled(False)
pipeline = PuLIDPipeline()
# 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'
)
def run(*args):
id_image = args[0]
supp_images = args[1:4]
prompt, neg_prompt, scale, n_samples, seed, steps, H, W, id_scale, mode, id_mix = args[4:]
pipeline.debug_img_list = []
if mode == 'fidelity':
attention.NUM_ZERO = 8
attention.ORTHO = False
attention.ORTHO_v2 = True
elif mode == 'extremely style':
attention.NUM_ZERO = 16
attention.ORTHO = True
attention.ORTHO_v2 = False
else:
raise ValueError
if id_image is not None:
id_image = resize_numpy_image_long(id_image, 1024)
id_embeddings = pipeline.get_id_embedding(id_image)
for supp_id_image in supp_images:
if supp_id_image is not None:
supp_id_image = resize_numpy_image_long(supp_id_image, 1024)
supp_id_embeddings = pipeline.get_id_embedding(supp_id_image)
id_embeddings = torch.cat(
(id_embeddings, supp_id_embeddings if id_mix else supp_id_embeddings[:, :5]), dim=1
)
else:
id_embeddings = None
seed_everything(seed)
ims = []
for _ in range(n_samples):
img = pipeline.inference(prompt, (1, H, W), neg_prompt, id_embeddings, id_scale, scale, steps)[0]
ims.append(np.array(img))
return ims, 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>. Techenical report: <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
- We offer two modes: fidelity mode and extremely style mode. In most cases, the default fidelity mode should suffice. If you find that the generated results are not stylized enough, you can choose the extremely style mode.
''' # 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)
---
🚀 **Share**
If you have generated satisfying or interesting images with PuLID, please share them with us or your friends!
📝 **Citation**
If you find our work useful for your research or applications, please cite using this bibtex:
```bibtex
@article{guo2024pulid,
title={PuLID: Pure and Lightning ID Customization via Contrastive Alignment},
author={Guo, Zinan and Wu, Yanze and Chen, Zhuowei and Chen, Lang and He, Qian},
journal={arXiv preprint arXiv:2404.16022},
year={2024}
}
```
📋 **License**
Apache-2.0 LICENSE. Please refer to the [LICENSE file](placeholder) for details.
📧 **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)", sources="upload", type="numpy", height=256)
supp_image1 = gr.Image(
label="Additional ID image (auxiliary)", sources="upload", type="numpy", height=256
)
supp_image2 = gr.Image(
label="Additional ID image (auxiliary)", sources="upload", type="numpy", height=256
)
supp_image3 = gr.Image(
label="Additional ID image (auxiliary)", sources="upload", type="numpy", 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 value range [1, 1.5], 1 will be faster ",
value=1.2,
minimum=1,
maximum=1.5,
step=0.1,
)
n_samples = gr.Slider(label="Num samples", value=4, minimum=1, maximum=8, step=1)
seed = gr.Slider(
label="Seed", value=42, minimum=np.iinfo(np.uint32).min, maximum=np.iinfo(np.uint32).max, step=1
)
steps = gr.Slider(label="Steps", value=4, minimum=1, maximum=100, step=1)
with gr.Row():
H = gr.Slider(label="Height", value=1024, minimum=512, maximum=2024, step=64)
W = gr.Slider(label="Width", value=768, minimum=512, maximum=2024, step=64)
with gr.Row():
id_scale = gr.Slider(label="ID scale", minimum=0, maximum=5, step=0.05, value=0.8, interactive=True)
mode = gr.Dropdown(label="mode", choices=['fidelity', 'extremely style'], value='fidelity')
id_mix = gr.Checkbox(
label="ID Mix (if you want to mix two ID image, please turn this on, otherwise, turn this off)",
value=False,
)
gr.Markdown("## Examples")
example_inps = [
[
'portrait,cinematic,wolf ears,white hair',
'example_inputs/liuyifei.png',
'fidelity',
]
]
gr.Examples(examples=example_inps, inputs=[prompt, face_image, mode], label='realistic')
example_inps = [
[
'portrait, impressionist painting, loose brushwork, vibrant color, light and shadow play',
'example_inputs/zcy.webp',
'fidelity',
]
]
gr.Examples(examples=example_inps, inputs=[prompt, face_image, mode], label='painting style')
example_inps = [
[
'portrait, flat papercut style, silhouette, clean cuts, paper, sharp edges, minimalist,color block,man', # noqa E501
'example_inputs/lecun.jpg',
'fidelity',
]
]
gr.Examples(examples=example_inps, inputs=[prompt, face_image, mode], label='papercut style')
example_inps = [
[
'woman,cartoon,solo,Popmart Blind Box, Super Mario, 3d',
'example_inputs/rihanna.webp',
'fidelity',
]
]
gr.Examples(examples=example_inps, inputs=[prompt, face_image, mode], label='3d style')
example_inps = [
[
'portrait, the legend of zelda, anime',
'example_inputs/liuyifei.png',
'extremely style',
]
]
gr.Examples(examples=example_inps, inputs=[prompt, face_image, mode], label='anime style')
example_inps = [
[
'portrait, superman',
'example_inputs/lecun.jpg',
'example_inputs/lifeifei.jpg',
'fidelity',
True,
]
]
gr.Examples(examples=example_inps, inputs=[prompt, face_image, supp_image1, mode, id_mix], label='id mix')
with gr.Column():
output = gr.Gallery(label='Output', elem_id="gallery")
intermediate_output = gr.Gallery(label='DebugImage', elem_id="gallery", visible=False)
gr.Markdown(_CITE_)
inps = [
face_image,
supp_image1,
supp_image2,
supp_image3,
prompt,
neg_prompt,
scale,
n_samples,
seed,
steps,
H,
W,
id_scale,
mode,
id_mix,
]
submit.click(fn=run, inputs=inps, outputs=[output, intermediate_output])
demo.queue(max_size=3)
demo.launch(server_name='0.0.0.0')
|