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Update: release PhotoMaker code, demo, and model

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release_results/
civitai_models/
gradio_cached_examples/
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__pycache__/
*.bin
*.safetensors
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Tencent is pleased to support the open source community by making PhotoMaker available.
Copyright (C) 2024 THL A29 Limited, a Tencent company. All rights reserved.
PhotoMaker is licensed under the Apache License Version 2.0 except for the third-party components listed below.
Terms of the Apache License Version 2.0:
---------------------------------------------
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README.md 100644 → 100755
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<p align="center">
<img src="https://photo-maker.github.io/assets/logo.png" height=100>
</p>
<!-- ## <div align="center"><b>PhotoMaker</b></div> -->
<div align="center">
## PhotoMaker: Customizing Realistic Human Photos via Stacked ID Embedding
[[Paper](https://arxiv.org/abs/2312.04461)] &emsp; [[Project Page](https://photo-maker.github.io)] &emsp; [Demo] <be>
</div>
We are currently organizing the code and demo to ensure that everyone can enjoy the wonderful journey that PhotoMaker may bring as soon as possible.
If you want to support and cheer for us, please star ⭐ our project.
<br>
<p align="center">
<img src="https://photo-maker.github.io/assets/teaser.jpg">
</p>
### Recontextualization
<p align="center">
<img src="https://photo-maker.github.io/assets/website_recontext_lowres.jpg">
</p>
### Bringing a person in artwork/old photo into reality
<p align="center">
<img src="https://photo-maker.github.io/assets/website_oldphoto_lowres.jpg">
</p>
### Stylization
<p align="center">
<img src="https://photo-maker.github.io/assets/stylization.jpg">
</p>
### Citation
```
@article{li2023photomaker,
title={PhotoMaker: Customizing Realistic Human Photos via Stacked ID Embedding},
author={Li, Zhen and Cao, Mingdeng and Wang, Xintao and Qi, Zhongang and Cheng, Ming-Ming and Shan, Ying},
booktitle={arXiv preprint arxiv:2312.04461},
year={2023}
}
```
<p align="center">
<img src="https://photo-maker.github.io/assets/logo.png" height=100>
</p>
<!-- ## <div align="center"><b>PhotoMaker</b></div> -->
<div align="center">
## PhotoMaker: Customizing Realistic Human Photos via Stacked ID Embedding
[[Paper](https://huggingface.co/papers/2312.04461)] &emsp; [[Project Page](https://photo-maker.github.io)] &emsp; [[Model Card](https://huggingface.co/TencentARC/PhotoMaker)] <br>
[[🤗 Demo (Realistic)](https://huggingface.co/spaces/TencentARC/PhotoMaker)] &emsp; [[🤗 Demo (Stylization)](https://huggingface.co/spaces/TencentARC/PhotoMaker-Style)] <br>
</div>
---
Official implementation of **[PhotoMaker: Customizing Realistic Human Photos via Stacked ID Embedding](https://huggingface.co/papers/2312.04461)**.
### 🌠 **Key Features:**
1. Rapid customization **within seconds**, with no additional LoRA training.
2. Ensures impressive ID fidelity, offering diversity, promising text controllability, and high-quality generation.
3. Can serve as an **Adapter** to collaborate with other Base Models alongside LoRA modules in community.
---
<div align="center">
![photomaker_demo_fast](https://github.com/TencentARC/PhotoMaker/assets/21050959/e72cbf4d-938f-417d-b308-55e76a4bc5c8)
</div>
## 🚩 **New Features/Updates**
- ✅ Jan. 15, 2024. We release PhotoMaker.
---
## 🔥 **Examples**
### Realistic generation
- [![Huggingface PhotoMaker](https://img.shields.io/static/v1?label=Demo&message=Huggingface%20Gradio&color=orange)](https://huggingface.co/spaces/TencentARC/PhotoMaker)
- [**PhotoMaker notebook demo**](photomaker_demo.ipynb)
<p align="center">
<img src="https://cdn-uploads.huggingface.co/production/uploads/6285a9133ab6642179158944/BYBZNyfmN4jBKBxxt4uxz.jpeg" height=450>
</p>
<p align="center">
<img src="https://cdn-uploads.huggingface.co/production/uploads/6285a9133ab6642179158944/9KYqoDxfbNVLzVKZzSzwo.jpeg" height=450>
</p>
### Stylization generation
Note: only change the base model and add the LoRA modules for better stylization
- [![Huggingface PhotoMaker-Style](https://img.shields.io/static/v1?label=Demo&message=Huggingface%20Gradio&color=orange)](https://huggingface.co/spaces/TencentARC/PhotoMaker-Style)
- [**PhotoMaker-Style notebook demo**](photomaker_style_demo.ipynb)
<p align="center">
<img src="https://cdn-uploads.huggingface.co/production/uploads/6285a9133ab6642179158944/du884lcjpqqjnJIxpATM2.jpeg" height=450>
</p>
<p align="center">
<img src="https://cdn-uploads.huggingface.co/production/uploads/6285a9133ab6642179158944/-AC7Hr5YL4yW1zXGe_Izl.jpeg" height=450>
</p>
# 🔧 Dependencies and Installation
- Python >= 3.8 (Recommend to use [Anaconda](https://www.anaconda.com/download/#linux) or [Miniconda](https://docs.conda.io/en/latest/miniconda.html))
- [PyTorch >= 2.0.0](https://pytorch.org/)
```bash
pip install -r requirements.txt
```
# ⏬ Download Models
The model will be automatically downloaded through following two lines:
```python
from huggingface_hub import hf_hub_download
photomaker_path = hf_hub_download(repo_id="TencentARC/PhotoMaker", filename="photomaker-v1.bin", repo_type="model")
```
You can also choose to download manually from this [url](https://huggingface.co/TencentARC/PhotoMaker).
# 💻 How to Test
## Use like [diffusers](https://github.com/huggingface/diffusers)
- Dependency
```py
import torch
import os
from diffusers.utils import load_image
from diffusers import EulerDiscreteScheduler
from photomaker.pipeline import PhotoMakerStableDiffusionXLPipeline
### Load base model
pipe = PhotoMakerStableDiffusionXLPipeline.from_pretrained(
base_model_path, # can change to any base model based on SDXL
torch_dtype=torch.bfloat16,
use_safetensors=True,
variant="fp16"
).to(device)
### Load PhotoMaker checkpoint
pipe.load_photomaker_adapter(
os.path.dirname(photomaker_path),
subfolder="",
weight_name=os.path.basename(photomaker_path),
trigger_word="img" # define the trigger word
)
pipe.scheduler = EulerDiscreteScheduler.from_config(pipe.scheduler.config)
### Also can cooperate with other LoRA modules
# pipe.load_lora_weights(os.path.dirname(lora_path), weight_name=lora_model_name, adapter_name="xl_more_art-full")
# pipe.set_adapters(["photomaker", "xl_more_art-full"], adapter_weights=[1.0, 0.5])
pipe.fuse_lora()
```
- Input ID Images
```py
### define the input ID images
input_folder_name = './examples/newton_man'
image_basename_list = os.listdir(input_folder_name)
image_path_list = sorted([os.path.join(input_folder_name, basename) for basename in image_basename_list])
input_id_images = []
for image_path in image_path_list:
input_id_images.append(load_image(image_path))
```
<div align="center">
<a href="https://github.com/TencentARC/PhotoMaker/assets/21050959/01d53dfa-7528-4f09-a1a5-96b349ae7800" align="center"><img style="margin:0;padding:0;" src="https://github.com/TencentARC/PhotoMaker/assets/21050959/01d53dfa-7528-4f09-a1a5-96b349ae7800"/></a>
</div>
- Generation
```py
# Note that the trigger word `img` must follow the class word for personalization
prompt = "a half-body portrait of a man img wearing the sunglasses in Iron man suit, best quality"
negative_prompt = "(asymmetry, worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch), open mouth, grayscale"
generator = torch.Generator(device=device).manual_seed(42)
images = pipe(
prompt=prompt,
input_id_images=input_id_images,
negative_prompt=negative_prompt,
num_images_per_prompt=1,
num_inference_steps=num_steps,
start_merge_step=10,
generator=generator,
).images[0]
gen_images.save('out_photomaker.png')
```
<div align="center">
<a href="https://github.com/TencentARC/PhotoMaker/assets/21050959/703c00e1-5e50-4c19-899e-25ee682d2c06" align="center"><img width=400 style="margin:0;padding:0;" src="https://github.com/TencentARC/PhotoMaker/assets/21050959/703c00e1-5e50-4c19-899e-25ee682d2c06"/></a>
</div>
## Start a local gradio demo
Run the following command:
```python
python gradio_demo/app.py
```
You could customize this script in [this file](gradio_demo/app.py).
## Usage Tips:
- Upload more photos of the person to be customized to improve ID fidelty. If the input is Asian face(s), maybe consider adding 'asian' before the class word, e.g., `asian woman img`
- When stylizing, does the generated face look too realistic? Adjust the Style strength to 30-50, the larger the number, the less ID fidelty, but the stylization ability will be better. You could also try out other base models or LoRAs with good stylization effects.
- For faster speed, reduce the number of generated images and sampling steps. However, please note that reducing the sampling steps may compromise the ID fidelity.
# 🤗 Acknowledgements
- T2I-Adapter is co-hosted by Tencent ARC Lab and Nankai University [MCG-NKU](https://mmcheng.net/cmm/).
- Inspired from many excellent demos and repos, including [IP-Adapter](https://github.com/tencent-ailab/IP-Adapter), [multimodalart/Ip-Adapter-FaceID](https://huggingface.co/spaces/multimodalart/Ip-Adapter-FaceID), [FastComposer](https://github.com/mit-han-lab/fastcomposer), and [T2I-Adapter](https://github.com/TencentARC/T2I-Adapter). Thanks for their great works!
# Disclaimer
This project strives to positively impact the domain of AI-driven image generation. Users are granted the freedom to create images using this tool, but they are expected to comply with local laws and utilize it in a responsible manner. The developers do not assume any responsibility for potential misuse by users.
# BibTeX
If you find PhotoMaker useful for your research and applications, please cite using this BibTeX:
```bibtex
@article{li2023photomaker,
title={PhotoMaker: Customizing Realistic Human Photos via Stacked ID Embedding},
author={Li, Zhen and Cao, Mingdeng and Wang, Xintao and Qi, Zhongang and Cheng, Ming-Ming and Shan, Ying},
booktitle={arXiv preprint arxiv:2312.04461},
year={2023}
}
\ No newline at end of file
gradio_demo/app.py 0 → 100755
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import torch
import numpy as np
import random
import os
from diffusers.utils import load_image
from diffusers import EulerDiscreteScheduler
from huggingface_hub import hf_hub_download
import spaces
import gradio as gr
from photomaker.pipeline import PhotoMakerStableDiffusionXLPipeline
from style_template import styles
# global variable
base_model_path = 'SG161222/RealVisXL_V3.0'
device = "cuda" if torch.cuda.is_available() else "cpu"
MAX_SEED = np.iinfo(np.int32).max
STYLE_NAMES = list(styles.keys())
DEFAULT_STYLE_NAME = "Photographic (Default)"
# download PhotoMaker checkpoint to cache
photomaker_ckpt = hf_hub_download(repo_id="TencentARC/PhotoMaker", filename="photomaker-v1.bin", repo_type="model")
pipe = PhotoMakerStableDiffusionXLPipeline.from_pretrained(
base_model_path,
torch_dtype=torch.bfloat16,
use_safetensors=True,
variant="fp16",
).to(device)
pipe.load_photomaker_adapter(
os.path.dirname(photomaker_ckpt),
subfolder="",
weight_name=os.path.basename(photomaker_ckpt),
trigger_word="img"
)
pipe.scheduler = EulerDiscreteScheduler.from_config(pipe.scheduler.config)
# pipe.set_adapters(["photomaker"], adapter_weights=[1.0])
pipe.fuse_lora()
@spaces.GPU(enable_queue=True)
def generate_image(upload_images, prompt, negative_prompt, style_name, num_steps, style_strength_ratio, num_outputs, guidance_scale, seed, progress=gr.Progress(track_tqdm=True)):
# check the trigger word
image_token_id = pipe.tokenizer.convert_tokens_to_ids(pipe.trigger_word)
input_ids = pipe.tokenizer.encode(prompt)
if image_token_id not in input_ids:
raise gr.Error(f"Cannot find the trigger word '{pipe.trigger_word}' in text prompt! Please refer to step 2️⃣")
if input_ids.count(image_token_id) > 1:
raise gr.Error(f"Cannot use multiple trigger words '{pipe.trigger_word}' in text prompt!")
# apply the style template
prompt, negative_prompt = apply_style(style_name, prompt, negative_prompt)
if upload_images is None:
raise gr.Error(f"Cannot find any input face image! Please refer to step 1️⃣")
input_id_images = []
for img in upload_images:
input_id_images.append(load_image(img))
generator = torch.Generator(device=device).manual_seed(seed)
print("Start inference...")
print(f"[Debug] Prompt: {prompt}, \n[Debug] Neg Prompt: {negative_prompt}")
start_merge_step = int(float(style_strength_ratio) / 100 * num_steps)
if start_merge_step > 30:
start_merge_step = 30
print(start_merge_step)
images = pipe(
prompt=prompt,
input_id_images=input_id_images,
negative_prompt=negative_prompt,
num_images_per_prompt=num_outputs,
num_inference_steps=num_steps,
start_merge_step=start_merge_step,
generator=generator,
guidance_scale=guidance_scale,
).images
return images, gr.update(visible=True)
def swap_to_gallery(images):
return gr.update(value=images, visible=True), gr.update(visible=True), gr.update(visible=False)
def upload_example_to_gallery(images, prompt, style, negative_prompt):
return gr.update(value=images, visible=True), gr.update(visible=True), gr.update(visible=False)
def remove_back_to_files():
return gr.update(visible=False), gr.update(visible=False), gr.update(visible=True)
def remove_tips():
return gr.update(visible=False)
def randomize_seed_fn(seed: int, randomize_seed: bool) -> int:
if randomize_seed:
seed = random.randint(0, MAX_SEED)
return seed
def apply_style(style_name: str, positive: str, negative: str = "") -> tuple[str, str]:
p, n = styles.get(style_name, styles[DEFAULT_STYLE_NAME])
return p.replace("{prompt}", positive), n + ' ' + negative
def get_image_path_list(folder_name):
image_basename_list = os.listdir(folder_name)
image_path_list = sorted([os.path.join(folder_name, basename) for basename in image_basename_list])
return image_path_list
def get_example():
case = [
[
get_image_path_list('./examples/scarletthead_woman'),
"instagram photo, portrait photo of a woman img, colorful, perfect face, natural skin, hard shadows, film grain",
"(No style)",
"(asymmetry, worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch), open mouth",
],
[
get_image_path_list('./examples/newton_man'),
"sci-fi, closeup portrait photo of a man img wearing the sunglasses in Iron man suit, face, slim body, high quality, film grain",
"(No style)",
"(asymmetry, worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch), open mouth",
],
]
return case
### Description and style
logo = r"""
<center><img src='https://photo-maker.github.io/assets/logo.png' alt='PhotoMaker logo' style="width:80px; margin-bottom:10px"></center>
"""
title = r"""
<h1 align="center">PhotoMaker: Customizing Realistic Human Photos via Stacked ID Embedding</h1>
"""
description = r"""
<b>Official 🤗 Gradio demo</b> for <a href='https://github.com/TencentARC/PhotoMaker' target='_blank'><b>PhotoMaker: Customizing Realistic Human Photos via Stacked ID Embedding</b></a>.<br>
<br>
For stylization, you could use our other gradio demo [PhotoMaker-Style](https://huggingface.co/spaces/TencentARC/PhotoMaker-Style).
<br>
❗️❗️❗️[<b>Important</b>] Personalization steps:<br>
1️⃣ Upload images of someone you want to customize. One image is ok, but more is better. Although we do not perform face detection, the face in the uploaded image should <b>occupy the majority of the image</b>.<br>
2️⃣ Enter a text prompt, making sure to <b>follow the class word</b> you want to customize with the <b>trigger word</b>: `img`, such as: `man img` or `woman img` or `girl img`.<br>
3️⃣ Choose your preferred style template.<br>
4️⃣ Click the <b>Submit</b> button to start customizing.
"""
article = r"""
If PhotoMaker is helpful, please help to ⭐ the <a href='https://github.com/TencentARC/PhotoMaker' target='_blank'>Github Repo</a>. Thanks!
[![GitHub Stars](https://img.shields.io/github/stars/TencentARC/PhotoMaker?style=social)](https://github.com/TencentARC/PhotoMaker)
---
📝 **Citation**
<br>
If our work is useful for your research, please consider citing:
```bibtex
@article{li2023photomaker,
title={PhotoMaker: Customizing Realistic Human Photos via Stacked ID Embedding},
author={Li, Zhen and Cao, Mingdeng and Wang, Xintao and Qi, Zhongang and Cheng, Ming-Ming and Shan, Ying},
booktitle={arXiv preprint arxiv:2312.04461},
year={2023}
}
```
📋 **License**
<br>
Apache-2.0 LICENSE. Please refer to the [LICENSE file](https://huggingface.co/TencentARC/PhotoMaker/blob/main/LICENSE) for details.
📧 **Contact**
<br>
If you have any questions, please feel free to reach me out at <b>zhenli1031@gmail.com</b>.
"""
tips = r"""
### Usage tips of PhotoMaker
1. Upload more photos of the person to be customized to **improve ID fidelty**. If the input is Asian face(s), maybe consider adding 'asian' before the class word, e.g., `asian woman img`
2. When stylizing, does the generated face look too realistic? Try switching to our **other gradio demo** [PhotoMaker-Style](https://huggingface.co/spaces/TencentARC/PhotoMaker-Style). Adjust the **Style strength** to 30-50, the larger the number, the less ID fidelty, but the stylization ability will be better.
3. For **faster** speed, reduce the number of generated images and sampling steps. However, please note that reducing the sampling steps may compromise the ID fidelity.
"""
# We have provided some generate examples and comparisons at: [this website]().
# 3. Don't make the prompt too long, as we will trim it if it exceeds 77 tokens.
# 4. When generating realistic photos, if it's not real enough, try switching to our other gradio application [PhotoMaker-Realistic]().
css = '''
.gradio-container {width: 85% !important}
'''
with gr.Blocks(css=css) as demo:
gr.Markdown(logo)
gr.Markdown(title)
gr.Markdown(description)
# gr.DuplicateButton(
# value="Duplicate Space for private use ",
# elem_id="duplicate-button",
# visible=os.getenv("SHOW_DUPLICATE_BUTTON") == "1",
# )
with gr.Row():
with gr.Column():
files = gr.Files(
label="Drag (Select) 1 or more photos of your face",
file_types=["image"]
)
uploaded_files = gr.Gallery(label="Your images", visible=False, columns=5, rows=1, height=200)
with gr.Column(visible=False) as clear_button:
remove_and_reupload = gr.ClearButton(value="Remove and upload new ones", components=files, size="sm")
prompt = gr.Textbox(label="Prompt",
info="Try something like 'a photo of a man/woman img', 'img' is the trigger word.",
placeholder="A photo of a [man/woman img]...")
style = gr.Dropdown(label="Style template", choices=STYLE_NAMES, value=DEFAULT_STYLE_NAME)
submit = gr.Button("Submit")
with gr.Accordion(open=False, label="Advanced Options"):
negative_prompt = gr.Textbox(
label="Negative Prompt",
placeholder="low quality",
value="nsfw, lowres, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature, watermark, username, blurry",
)
num_steps = gr.Slider(
label="Number of sample steps",
minimum=20,
maximum=100,
step=1,
value=50,
)
style_strength_ratio = gr.Slider(
label="Style strength (%)",
minimum=15,
maximum=50,
step=1,
value=20,
)
num_outputs = gr.Slider(
label="Number of output images",
minimum=1,
maximum=4,
step=1,
value=2,
)
guidance_scale = gr.Slider(
label="Guidance scale",
minimum=0.1,
maximum=10.0,
step=0.1,
value=5,
)
seed = gr.Slider(
label="Seed",
minimum=0,
maximum=MAX_SEED,
step=1,
value=0,
)
randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
with gr.Column():
gallery = gr.Gallery(label="Generated Images")
usage_tips = gr.Markdown(label="Usage tips of PhotoMaker", value=tips ,visible=False)
files.upload(fn=swap_to_gallery, inputs=files, outputs=[uploaded_files, clear_button, files])
remove_and_reupload.click(fn=remove_back_to_files, outputs=[uploaded_files, clear_button, files])
submit.click(
fn=remove_tips,
outputs=usage_tips,
).then(
fn=randomize_seed_fn,
inputs=[seed, randomize_seed],
outputs=seed,
queue=False,
api_name=False,
).then(
fn=generate_image,
inputs=[files, prompt, negative_prompt, style, num_steps, style_strength_ratio, num_outputs, guidance_scale, seed],
outputs=[gallery, usage_tips]
)
gr.Examples(
examples=get_example(),
inputs=[files, prompt, style, negative_prompt],
run_on_click=True,
fn=upload_example_to_gallery,
outputs=[uploaded_files, clear_button, files],
)
gr.Markdown(article)
demo.launch()
\ No newline at end of file
gradio_demo/style_template.py 0 → 100755
View file @ fb4d1b7b
style_list = [
{
"name": "(No style)",
"prompt": "{prompt}",
"negative_prompt": "",
},
{
"name": "Cinematic",
"prompt": "cinematic still {prompt} . emotional, harmonious, vignette, highly detailed, high budget, bokeh, cinemascope, moody, epic, gorgeous, film grain, grainy",
"negative_prompt": "anime, cartoon, graphic, text, painting, crayon, graphite, abstract, glitch, deformed, mutated, ugly, disfigured",
},
{
"name": "Disney Charactor",
"prompt": "A Pixar animation character of {prompt} . pixar-style, studio anime, Disney, high-quality",
"negative_prompt": "lowres, bad anatomy, bad hands, text, bad eyes, bad arms, bad legs, error, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature, watermark, blurry, grayscale, noisy, sloppy, messy, grainy, highly detailed, ultra textured, photo",
},
{
"name": "Digital Art",
"prompt": "concept art {prompt} . digital artwork, illustrative, painterly, matte painting, highly detailed",
"negative_prompt": "photo, photorealistic, realism, ugly",
},
{
"name": "Photographic (Default)",
"prompt": "cinematic photo {prompt} . 35mm photograph, film, bokeh, professional, 4k, highly detailed",
"negative_prompt": "drawing, painting, crayon, sketch, graphite, impressionist, noisy, blurry, soft, deformed, ugly",
},
{
"name": "Fantasy art",
"prompt": "ethereal fantasy concept art of {prompt} . magnificent, celestial, ethereal, painterly, epic, majestic, magical, fantasy art, cover art, dreamy",
"negative_prompt": "photographic, realistic, realism, 35mm film, dslr, cropped, frame, text, deformed, glitch, noise, noisy, off-center, deformed, cross-eyed, closed eyes, bad anatomy, ugly, disfigured, sloppy, duplicate, mutated, black and white",
},
{
"name": "Neonpunk",
"prompt": "neonpunk style {prompt} . cyberpunk, vaporwave, neon, vibes, vibrant, stunningly beautiful, crisp, detailed, sleek, ultramodern, magenta highlights, dark purple shadows, high contrast, cinematic, ultra detailed, intricate, professional",
"negative_prompt": "painting, drawing, illustration, glitch, deformed, mutated, cross-eyed, ugly, disfigured",
},
{
"name": "Enhance",
"prompt": "breathtaking {prompt} . award-winning, professional, highly detailed",
"negative_prompt": "ugly, deformed, noisy, blurry, distorted, grainy",
},
{
"name": "Comic book",
"prompt": "comic {prompt} . graphic illustration, comic art, graphic novel art, vibrant, highly detailed",
"negative_prompt": "photograph, deformed, glitch, noisy, realistic, stock photo",
},
{
"name": "Lowpoly",
"prompt": "low-poly style {prompt} . low-poly game art, polygon mesh, jagged, blocky, wireframe edges, centered composition",
"negative_prompt": "noisy, sloppy, messy, grainy, highly detailed, ultra textured, photo",
},
{
"name": "Line art",
"prompt": "line art drawing {prompt} . professional, sleek, modern, minimalist, graphic, line art, vector graphics",
"negative_prompt": "anime, photorealistic, 35mm film, deformed, glitch, blurry, noisy, off-center, deformed, cross-eyed, closed eyes, bad anatomy, ugly, disfigured, mutated, realism, realistic, impressionism, expressionism, oil, acrylic",
}
]
styles = {k["name"]: (k["prompt"], k["negative_prompt"]) for k in style_list}
\ No newline at end of file
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