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#!/usr/bin/env python
from __future__ import annotations
import argparse
import os
import pathlib
import subprocess
import gradio as gr
if os.getenv('SYSTEM') == 'spaces':
with open('patch.e4e') as f:
subprocess.run('patch -p1'.split(), cwd='encoder4editing', stdin=f)
with open('patch.hairclip') as f:
subprocess.run('patch -p1'.split(), cwd='HairCLIP', stdin=f)
from model import Model
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 load_hairstyle_list() -> list[str]:
with open('HairCLIP/mapper/hairstyle_list.txt') as f:
lines = [line.strip() for line in f.readlines()]
lines = [line[:-10] for line in lines]
return lines
def set_example_image(example: list) -> dict:
return gr.Image.update(value=example[0])
def update_step2_components(choice: str) -> tuple[dict, dict]:
return (
gr.Dropdown.update(visible=choice in ['hairstyle', 'both']),
gr.Textbox.update(visible=choice in ['color', 'both']),
)
def main():
args = parse_args()
model = Model(device=args.device)
css = '''
h1#title {
text-align: center;
}
img#teaser {
max-width: 1000px;
max-height: 600px;
}
'''
with gr.Blocks(theme=args.theme, css=css) as demo:
gr.Markdown('''<h1 id="title">HairCLIP</h1>
This is an unofficial demo for <a href="https://github.com/wty-ustc/HairCLIP">https://github.com/wty-ustc/HairCLIP</a>.
<center><img id="teaser" src="https://raw.githubusercontent.com/wty-ustc/HairCLIP/main/assets/teaser.png" alt="teaser"></center>
''')
with gr.Box():
gr.Markdown('## Step 1')
with gr.Row():
with gr.Column():
with gr.Row():
input_image = gr.Image(label='Input Image',
type='file')
with gr.Row():
preprocess_button = gr.Button('Preprocess')
with gr.Column():
aligned_face = gr.Image(label='Aligned Face',
type='pil',
interactive=False)
with gr.Column():
reconstructed_face = gr.Image(label='Reconstructed Face',
type='numpy')
latent = gr.Variable()
with gr.Row():
paths = sorted(pathlib.Path('images').glob('*.jpg'))
example_images = gr.Dataset(components=[input_image],
samples=[[path.as_posix()]
for path in paths])
with gr.Box():
gr.Markdown('## Step 2')
with gr.Row():
with gr.Column():
with gr.Row():
editing_type = gr.Radio(['hairstyle', 'color', 'both'],
value='both',
type='value',
label='Editing Type')
with gr.Row():
hairstyles = load_hairstyle_list()
hairstyle_index = gr.Dropdown(hairstyles,
value='afro',
type='index',
label='Hairstyle')
with gr.Row():
color_description = gr.Textbox(value='red',
label='Color')
with gr.Row():
run_button = gr.Button('Run')
with gr.Column():
result = gr.Image(label='Result')
gr.Markdown(
'<center><img src="https://visitor-badge.glitch.me/badge?page_id=gradio-blocks.hairclip" alt="visitor badge"/></center>'
)
preprocess_button.click(fn=model.detect_and_align_face,
inputs=[input_image],
outputs=[aligned_face])
aligned_face.change(fn=model.reconstruct_face,
inputs=[aligned_face],
outputs=[reconstructed_face, latent])
editing_type.change(fn=update_step2_components,
inputs=[editing_type],
outputs=[hairstyle_index, color_description])
run_button.click(fn=model.generate,
inputs=[
editing_type,
hairstyle_index,
color_description,
latent,
],
outputs=[result])
example_images.click(fn=set_example_image,
inputs=example_images,
outputs=example_images.components)
demo.launch(
enable_queue=args.enable_queue,
server_port=args.port,
share=args.share,
)
if __name__ == '__main__':
main()
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