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Running
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CPU Upgrade
| #!/usr/bin/env python | |
| import pathlib | |
| import gradio as gr | |
| from model import run_model | |
| DESCRIPTION = '# [CutLER](https://github.com/facebookresearch/CutLER)' | |
| paths = sorted(pathlib.Path('CutLER/cutler/demo/imgs').glob('*.jpg')) | |
| with gr.Blocks(css='style.css') as demo: | |
| gr.Markdown(DESCRIPTION) | |
| with gr.Row(): | |
| with gr.Column(): | |
| image = gr.Image(label='Input image', type='filepath') | |
| score_threshold = gr.Slider(label='Score threshold', | |
| minimum=0, | |
| maximum=1, | |
| value=0.5, | |
| step=0.05) | |
| run_button = gr.Button('Run') | |
| with gr.Column(): | |
| result = gr.Image(label='Result', type='numpy') | |
| with gr.Row(): | |
| gr.Examples(examples=[[path.as_posix()] for path in paths], | |
| inputs=image) | |
| run_button.click(fn=run_model, | |
| inputs=[ | |
| image, | |
| score_threshold, | |
| ], | |
| outputs=result, | |
| api_name='run') | |
| demo.queue(max_size=20).launch() | |