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from __future__ import annotations |
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import argparse |
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import pathlib |
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import gradio as gr |
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from model import Model |
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def parse_args() -> argparse.Namespace: |
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parser = argparse.ArgumentParser() |
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parser.add_argument('--device', type=str, default='cpu') |
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parser.add_argument('--theme', type=str) |
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parser.add_argument('--share', action='store_true') |
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parser.add_argument('--port', type=int) |
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parser.add_argument('--disable-queue', |
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dest='enable_queue', |
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action='store_false') |
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return parser.parse_args() |
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def load_hairstyle_list() -> list[str]: |
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with open('HairCLIP/mapper/hairstyle_list.txt') as f: |
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lines = [line.strip() for line in f.readlines()] |
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lines = [line[:-10] for line in lines] |
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return lines |
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def set_example_image(example: list) -> dict: |
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return gr.Image.update(value=example[0]) |
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def update_step2_components(choice: str) -> tuple[dict, dict]: |
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return ( |
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gr.Dropdown.update(visible=choice in ['hairstyle', 'both']), |
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gr.Textbox.update(visible=choice in ['color', 'both']), |
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) |
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def main(): |
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args = parse_args() |
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model = Model(device=args.device) |
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css = ''' |
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h1#title { |
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text-align: center; |
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} |
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img#teaser { |
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max-width: 1000px; |
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max-height: 600px; |
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} |
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''' |
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with gr.Blocks(theme=args.theme, css=css) as demo: |
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gr.Markdown('''<h1 id="title">HairCLIP</h1> |
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''') |
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with gr.Box(): |
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gr.Markdown('## Step 1') |
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with gr.Row(): |
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with gr.Column(): |
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with gr.Row(): |
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input_image = gr.Image(label='Input Image', |
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type='file') |
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with gr.Row(): |
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preprocess_button = gr.Button('Preprocess') |
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with gr.Column(): |
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aligned_face = gr.Image(label='Aligned Face', |
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type='pil', |
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interactive=False) |
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with gr.Column(): |
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reconstructed_face = gr.Image(label='Reconstructed Face', |
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type='numpy') |
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latent = gr.Variable() |
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with gr.Row(): |
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paths = sorted(pathlib.Path('test').glob('*.jpg')) |
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example_images = gr.Dataset(components=[input_image], |
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samples=[[path.as_posix()] |
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for path in paths]) |
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with gr.Box(): |
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gr.Markdown('## Step 2') |
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with gr.Row(): |
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with gr.Column(): |
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with gr.Row(): |
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editing_type = gr.Radio(['hairstyle', 'color', 'both'], |
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value='both', |
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type='value', |
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label='Editing Type') |
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with gr.Row(): |
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hairstyles = load_hairstyle_list() |
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hairstyle_index = gr.Dropdown(hairstyles, |
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value='afro', |
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type='index', |
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label='Hairstyle') |
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with gr.Row(): |
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color_description = gr.Textbox(value='red', |
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label='Color') |
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with gr.Row(): |
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run_button = gr.Button('Run') |
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with gr.Column(): |
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result = gr.Image(label='Result') |
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gr.Markdown( |
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'<center></center>' |
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) |
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preprocess_button.click(fn=model.detect_and_align_face, |
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inputs=[input_image], |
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outputs=[aligned_face]) |
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aligned_face.change(fn=model.reconstruct_face, |
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inputs=[aligned_face], |
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outputs=[reconstructed_face, latent]) |
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editing_type.change(fn=update_step2_components, |
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inputs=[editing_type], |
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outputs=[hairstyle_index, color_description]) |
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run_button.click(fn=model.generate, |
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inputs=[ |
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editing_type, |
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hairstyle_index, |
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color_description, |
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latent, |
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], |
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outputs=[result]) |
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example_images.click(fn=set_example_image, |
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inputs=example_images, |
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outputs=example_images.components) |
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demo.launch( |
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enable_queue=args.enable_queue, |
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server_port=args.port, |
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share=args.share, |
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) |
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if __name__ == '__main__': |
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main() |
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