app.py

#!/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()