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| #!/usr/bin/env python | |
| from __future__ import annotations | |
| import argparse | |
| import pathlib | |
| import gradio as gr | |
| from model import Model | |
| DESCRIPTION = '''# CBNetV2 | |
| This is an unofficial demo for [https://github.com/VDIGPKU/CBNetV2](https://github.com/VDIGPKU/CBNetV2).''' | |
| FOOTER = '<img id="visitor-badge" alt="visitor badge" src="https://visitor-badge.glitch.me/badge?page_id=hysts.cbnetv2" />' | |
| 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 main(): | |
| args = parse_args() | |
| model = Model(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(): | |
| input_image = gr.Image(label='Input Image', type='numpy') | |
| with gr.Row(): | |
| detector_name = gr.Dropdown(list(model.models.keys()), | |
| value=model.model_name, | |
| label='Detector') | |
| with gr.Row(): | |
| detect_button = gr.Button(value='Detect') | |
| detection_results = gr.Variable() | |
| with gr.Column(): | |
| with gr.Row(): | |
| detection_visualization = gr.Image( | |
| label='Detection Result', type='numpy') | |
| with gr.Row(): | |
| visualization_score_threshold = gr.Slider( | |
| 0, | |
| 1, | |
| step=0.05, | |
| value=0.3, | |
| label='Visualization Score Threshold') | |
| with gr.Row(): | |
| redraw_button = gr.Button(value='Redraw') | |
| with gr.Row(): | |
| paths = sorted(pathlib.Path('images').rglob('*.jpg')) | |
| example_images = gr.Dataset(components=[input_image], | |
| samples=[[path.as_posix()] | |
| for path in paths]) | |
| gr.Markdown(FOOTER) | |
| detector_name.change(fn=model.set_model_name, | |
| inputs=[detector_name], | |
| outputs=None) | |
| detect_button.click(fn=model.detect_and_visualize, | |
| inputs=[ | |
| input_image, | |
| visualization_score_threshold, | |
| ], | |
| outputs=[ | |
| detection_results, | |
| detection_visualization, | |
| ]) | |
| redraw_button.click(fn=model.visualize_detection_results, | |
| inputs=[ | |
| input_image, | |
| detection_results, | |
| visualization_score_threshold, | |
| ], | |
| outputs=[detection_visualization]) | |
| example_images.click(fn=set_example_image, | |
| inputs=[example_images], | |
| outputs=[input_image]) | |
| demo.launch( | |
| enable_queue=args.enable_queue, | |
| server_port=args.port, | |
| share=args.share, | |
| ) | |
| if __name__ == '__main__': | |
| main() | |