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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':
subprocess.call('pip uninstall -y mmcv-full'.split())
subprocess.call('pip install mmcv-full==1.5.2'.split())
subprocess.call('git apply ../patch'.split(), cwd='Text2Human')
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 set_example_image(example: list) -> dict:
return gr.Image.update(value=example[0])
def set_example_text(example: list) -> dict:
return gr.Textbox.update(value=example[0])
def main():
args = parse_args()
model = Model(args.device)
css = '''
h1#title {
text-align: center;
}
#input-image {
max-height: 300px;
}
#label-image {
height: 300px;
}
#result-image {
height: 300px;
}
'''
with gr.Blocks(theme=args.theme, css=css) as demo:
gr.Markdown('''<h1 id="title">Text2Human</h1>
This is an unofficial demo for <a href="https://github.com/yumingj/Text2Human">https://github.com/yumingj/Text2Human</a>.
''')
with gr.Row():
with gr.Column():
with gr.Row():
input_image = gr.Image(label='Input Pose Image',
type='pil',
elem_id='input-image')
with gr.Row():
paths = sorted(pathlib.Path('pose_images').glob('*.png'))
example_images = gr.Dataset(components=[input_image],
samples=[[path.as_posix()]
for path in paths])
with gr.Column():
with gr.Row():
label_image = gr.Image(label='Label Image',
type='numpy',
elem_id='label-image')
with gr.Row():
shape_text = gr.Textbox(
label='Shape Description',
placeholder=
'''<gender>, <sleeve length>, <length of lower clothing>, <outer clothing type>, <other accessories1>, ...
Note: The outer clothing type and accessories can be omitted.''')
with gr.Row():
shape_example_texts = gr.Dataset(
components=[shape_text],
samples=[['man, sleeveless T-shirt, long pants'],
['woman, short-sleeve T-shirt, short jeans']])
with gr.Row():
generate_label_button = gr.Button('Generate Label Image')
with gr.Column():
with gr.Row():
result = gr.Image(label='Result',
type='numpy',
elem_id='result-image')
with gr.Row():
texture_text = gr.Textbox(
label='Texture Description',
placeholder=
'''<upper clothing texture>, <lower clothing texture>, <outer clothing texture>
Note: Currently, only 5 types of textures are supported, i.e., pure color, stripe/spline, plaid/lattice, floral, denim.'''
)
with gr.Row():
texture_example_texts = gr.Dataset(
components=[texture_text],
samples=[['pure color, denim'], ['floral, stripe']])
with gr.Row():
sample_steps = gr.Slider(10,
300,
value=10,
step=10,
label='Sample Steps')
with gr.Row():
seed = gr.Slider(0, 1000000, value=0, step=1, label='Seed')
with gr.Row():
generate_human_button = gr.Button('Generate Human')
gr.Markdown(
'<center><img src="https://visitor-badge.glitch.me/badge?page_id=hysts.text2human" alt="visitor badge"/></center>'
)
input_image.change(fn=model.process_pose_image,
inputs=[input_image],
outputs=None)
generate_label_button.click(fn=model.generate_label_image,
inputs=[shape_text],
outputs=[label_image])
generate_human_button.click(fn=model.generate_human,
inputs=[
texture_text,
sample_steps,
seed,
],
outputs=[result])
example_images.click(fn=set_example_image,
inputs=example_images,
outputs=example_images.components)
shape_example_texts.click(fn=set_example_text,
inputs=shape_example_texts,
outputs=shape_example_texts.components)
texture_example_texts.click(fn=set_example_text,
inputs=texture_example_texts,
outputs=texture_example_texts.components)
demo.launch(
enable_queue=args.enable_queue,
server_port=args.port,
share=args.share,
)
if __name__ == '__main__':
main()
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