StyleGAN-XL / app.py
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#!/usr/bin/env python
from __future__ import annotations
import argparse
import json
import gradio as gr
import numpy as np
from model import Model
TITLE = '# autonomousvision/stylegan_xl'
DESCRIPTION = '''This is an unofficial demo for [https://github.com/autonomousvision/stylegan_xl](https://github.com/autonomousvision/stylegan_xl).
Expected execution time on Hugging Face Spaces: 16s
'''
FOOTER = '<img id="visitor-badge" src="https://visitor-badge.glitch.me/badge?page_id=hysts.stylegan-xl" alt="visitor badge" />'
def parse_args() -> argparse.Namespace:
parser = argparse.ArgumentParser()
parser.add_argument('--device', type=str, default='cpu')
parser.add_argument('--theme', type=str)
parser.add_argument('--share', action='store_true')
parser.add_argument('--port', type=int)
parser.add_argument('--disable-queue',
dest='enable_queue',
action='store_false')
return parser.parse_args()
def update_class_index(name: str) -> dict:
if 'imagenet' in name:
return gr.Slider.update(maximum=999, visible=True)
elif 'cifar' in name:
return gr.Slider.update(maximum=9, visible=True)
else:
return gr.Slider.update(visible=False)
def get_sample_image_url(name: str) -> str:
sample_image_dir = 'https://huggingface.co/spaces/hysts/StyleGAN-XL/resolve/main/samples'
return f'{sample_image_dir}/{name}.jpg'
def get_sample_image_markdown(name: str) -> str:
url = get_sample_image_url(name)
if name == 'imagenet':
size = 128
class_index = '0-999'
seed = '0'
elif name == 'cifar10':
size = 32
class_index = '0-9'
seed = '0'
elif name == 'ffhq':
size = 256
class_index = 'N/A'
seed = '0-99'
elif name == 'pokemon':
size = 256
class_index = 'N/A'
seed = '0-99'
else:
raise ValueError
return f'''
- size: {size}x{size}
- class_index: {class_index}
- seed: {seed}
- truncation: 0.7
![sample images]({url})'''
def load_class_names(name: str) -> list[str]:
with open(f'labels/{name}_classes.json') as f:
names = json.load(f)
return names
def get_class_name_df(name: str) -> list:
names = load_class_names(name)
return list(map(list, enumerate(names))) # type: ignore
IMAGENET_NAMES = load_class_names('imagenet')
CIFAR10_NAMES = load_class_names('cifar10')
def update_class_name(model_name: str, index: int) -> dict:
if 'imagenet' in model_name:
if index < len(IMAGENET_NAMES):
value = IMAGENET_NAMES[index]
else:
value = '-'
return gr.Textbox.update(value=value, visible=True)
elif 'cifar' in model_name:
if index < len(CIFAR10_NAMES):
value = CIFAR10_NAMES[index]
else:
value = '-'
return gr.Textbox.update(value=value, visible=True)
else:
return gr.Textbox.update(visible=False)
def main():
args = parse_args()
model = Model(args.device)
with gr.Blocks(theme=args.theme, css='style.css') as demo:
gr.Markdown(TITLE)
gr.Markdown(DESCRIPTION)
with gr.Tabs():
with gr.TabItem('App'):
with gr.Row():
with gr.Column():
with gr.Group():
model_name = gr.Dropdown(
model.MODEL_NAMES,
value=model.MODEL_NAMES[3],
label='Model')
seed = gr.Slider(0,
np.iinfo(np.uint32).max,
step=1,
value=0,
label='Seed')
psi = gr.Slider(0,
2,
step=0.05,
value=0.7,
label='Truncation psi')
class_index = gr.Slider(0,
999,
step=1,
value=83,
label='Class Index')
class_name = gr.Textbox(
value=IMAGENET_NAMES[class_index.value],
label='Class Label',
interactive=False)
tx = gr.Slider(-1,
1,
step=0.05,
value=0,
label='Translate X')
ty = gr.Slider(-1,
1,
step=0.05,
value=0,
label='Translate Y')
angle = gr.Slider(-180,
180,
step=5,
value=0,
label='Angle')
run_button = gr.Button('Run')
with gr.Column():
result = gr.Image(label='Result', elem_id='result')
with gr.TabItem('Sample Images'):
with gr.Row():
model_name2 = gr.Dropdown([
'imagenet',
'cifar10',
'ffhq',
'pokemon',
],
value='imagenet',
label='Model')
with gr.Row():
text = get_sample_image_markdown(model_name2.value)
sample_images = gr.Markdown(text)
with gr.TabItem('Class Names'):
with gr.Row():
dataset_name = gr.Dropdown([
'imagenet',
'cifar10',
],
value='imagenet',
label='Dataset')
with gr.Row():
df = get_class_name_df('imagenet')
class_names = gr.Dataframe(
df,
col_count=2,
headers=['Class Index', 'Label'],
interactive=False)
gr.Markdown(FOOTER)
model_name.change(fn=model.set_model, inputs=model_name, outputs=None)
model_name.change(fn=update_class_index,
inputs=model_name,
outputs=class_index)
model_name.change(fn=update_class_name,
inputs=[
model_name,
class_index,
],
outputs=class_name)
class_index.change(fn=update_class_name,
inputs=[
model_name,
class_index,
],
outputs=class_name)
run_button.click(fn=model.set_model_and_generate_image,
inputs=[
model_name,
seed,
psi,
class_index,
tx,
ty,
angle,
],
outputs=result)
model_name2.change(fn=get_sample_image_markdown,
inputs=model_name2,
outputs=sample_images)
dataset_name.change(fn=get_class_name_df,
inputs=dataset_name,
outputs=class_names)
demo.launch(
enable_queue=args.enable_queue,
server_port=args.port,
share=args.share,
)
if __name__ == '__main__':
main()