Spaces:
Sleeping
Sleeping
| #!/usr/bin/env python | |
| from __future__ import annotations | |
| import pathlib | |
| import gradio as gr | |
| from model import Model | |
| repo_dir = pathlib.Path(__file__).parent | |
| def create_demo(): | |
| TITLE = '# [ELITE Demo](https://github.com/csyxwei/ELITE)' | |
| USAGE='''To run the demo, you should: | |
| 1. Upload your image. | |
| 2. **Draw a mask on the object part.** | |
| 3. Input proper text prompts, such as "A photo of S" or "A S wearing sunglasses", where "S" denotes your customized concept. | |
| 4. Click the Run button. You can also adjust the hyperparameters to improve the results. | |
| ''' | |
| model = Model() | |
| with gr.Blocks(css=repo_dir / 'style.css') as demo: | |
| gr.Markdown(TITLE) | |
| gr.Markdown(USAGE) | |
| with gr.Row(): | |
| with gr.Column(): | |
| with gr.Group(): | |
| # image = gr.Image(label='Input', tool='sketch', type='pil') | |
| image = gr.ImageEditor(label="Input", | |
| type="pil", | |
| brush=gr.Brush(colors=["#FFFFFF"], default_size=20, color_mode="fixed"), | |
| layers=False, | |
| interactive=True) | |
| # gr.Markdown('Draw a mask on your object.') | |
| gr.Markdown('Upload your image and **draw a mask on the object part.** Like [this](https://user-images.githubusercontent.com/23421814/224873479-c4cf44d6-8c99-4ef9-b972-87c25fe923ee.png).') | |
| prompt = gr.Text( | |
| label='Prompt', | |
| placeholder='e.g. "A photo of S", "A S wearing sunglasses"', | |
| info='Use "S" for your concept.') | |
| lambda_ = gr.Slider( | |
| label='Lambda', | |
| minimum=0, | |
| maximum=1.5, | |
| step=0.1, | |
| value=0.6, | |
| info= | |
| 'The larger the lambda, the more consistency between the generated image and the input image, but less editability.' | |
| ) | |
| run_button = gr.Button('Run') | |
| with gr.Accordion(label='Advanced options', open=False): | |
| seed = gr.Slider( | |
| label='Seed', | |
| minimum=-1, | |
| maximum=1000000, | |
| step=1, | |
| value=-1, | |
| info= | |
| 'If set to -1, a different seed will be used each time.' | |
| ) | |
| guidance_scale = gr.Slider(label='Guidance scale', | |
| minimum=0, | |
| maximum=50, | |
| step=0.1, | |
| value=5.0) | |
| num_steps = gr.Slider( | |
| label='Steps', | |
| minimum=1, | |
| maximum=100, | |
| step=1, | |
| value=300, | |
| info= | |
| 'In the paper, the number of steps is set to 100, but in this demo the default value is 20 to reduce inference time.' | |
| ) | |
| with gr.Column(): | |
| result = gr.Image(label='Result') | |
| paths = sorted([ | |
| path.as_posix() | |
| for path in (repo_dir / 'ELITE/test_datasets').glob('*') | |
| if 'bg' not in path.stem | |
| ]) | |
| gr.Examples(examples=paths, inputs=image, examples_per_page=20) | |
| inputs = [ | |
| image, | |
| prompt, | |
| seed, | |
| guidance_scale, | |
| lambda_, | |
| num_steps, | |
| ] | |
| prompt.submit(fn=model.run, inputs=inputs, outputs=result) | |
| run_button.click(fn=model.run, inputs=inputs, outputs=result) | |
| return demo | |
| if __name__ == '__main__': | |
| demo = create_demo() | |
| demo.queue(api_open=False).launch() | |