#!/usr/bin/env python from __future__ import annotations import argparse import gradio as gr from huggingface_hub import hf_hub_download from model import Model DESCRIPTION = '''# StyleGAN-Human This is an unofficial demo for [https://github.com/stylegan-human/StyleGAN-Human](https://github.com/stylegan-human/StyleGAN-Human). ''' FOOTER = '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 main(): args = parse_args() app = Model(device=args.device) with gr.Blocks(theme=args.theme, css='style.css') as demo: gr.Markdown(DESCRIPTION) with gr.Row(): with gr.Column(): with gr.Row(): seed1 = gr.Number(value=6876, label='Seed 1') psi1 = gr.Slider(0, 2, value=0.7, step=0.05, label='Truncation psi 1') with gr.Row(): generate_button1 = gr.Button('Generate') with gr.Row(): generated_image1 = gr.Image(type='numpy', label='Generated Image 1') with gr.Column(): with gr.Row(): seed2 = gr.Number(value=6886, label='Seed 2') psi2 = gr.Slider(0, 2, value=0.7, step=0.05, label='Truncation psi 2') with gr.Row(): generate_button2 = gr.Button('Generate') with gr.Row(): generated_image2 = gr.Image(type='numpy', label='Generated Image 2') with gr.Row(): with gr.Column(): with gr.Row(): num_frames = gr.Slider( 0, 41, value=7, step=1, label='Number of Intermediate Frames') with gr.Row(): interpolate_button = gr.Button('Interpolate') with gr.Row(): interpolated_images = gr.Gallery(label='Output Images') gr.Markdown(FOOTER) generate_button1.click(app.generate_single_image, inputs=[seed1, psi1], outputs=generated_image1) generate_button2.click(app.generate_single_image, inputs=[seed2, psi2], outputs=generated_image2) interpolate_button.click(app.generate_interpolated_images, inputs=[seed1, psi1, seed2, psi2, num_frames], outputs=interpolated_images) demo.launch( enable_queue=args.enable_queue, server_port=args.port, share=args.share, ) if __name__ == '__main__': main()