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| #!/usr/bin/env python | |
| from __future__ import annotations | |
| import os | |
| import gradio as gr | |
| from model import Model | |
| DESCRIPTION = '# [UniDiffuser](https://github.com/thu-ml/unidiffuser)' | |
| SPACE_ID = os.getenv('SPACE_ID') | |
| if SPACE_ID is not None: | |
| DESCRIPTION += f'\n<p>For faster inference without waiting in queue, you may duplicate the space and upgrade to GPU in settings. <a href="https://huggingface.co/spaces/{SPACE_ID}?duplicate=true"><img style="display: inline; margin-top: 0em; margin-bottom: 0em" src="https://bit.ly/3gLdBN6" alt="Duplicate Space" /></a></p>' | |
| model = Model() | |
| def create_demo(mode_name: str) -> gr.Blocks: | |
| with gr.Blocks() as demo: | |
| with gr.Row(): | |
| with gr.Column(): | |
| mode = gr.Dropdown(label='Mode', | |
| choices=[ | |
| 't2i', | |
| 'i2t', | |
| 'joint', | |
| 'i', | |
| 't', | |
| 'i2ti2', | |
| 't2i2t', | |
| ], | |
| value=mode_name, | |
| visible=False) | |
| prompt = gr.Text(label='Prompt', | |
| max_lines=1, | |
| visible=mode_name in ['t2i', 't2i2t']) | |
| image = gr.Image(label='Input image', | |
| type='filepath', | |
| visible=mode_name in ['i2t', 'i2t2i']) | |
| run_button = gr.Button('Run') | |
| with gr.Accordion('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.' | |
| ) | |
| num_steps = gr.Slider(label='Steps', | |
| minimum=1, | |
| maximum=100, | |
| value=50, | |
| step=1) | |
| guidance_scale = gr.Slider(label='Guidance Scale', | |
| minimum=0.1, | |
| maximum=30.0, | |
| value=7.0, | |
| step=0.1) | |
| with gr.Column(): | |
| result_image = gr.Image(label='Generated image', | |
| visible=mode_name | |
| in ['t2i', 'i', 'joint', 'i2t2i']) | |
| result_text = gr.Text(label='Generated text', | |
| visible=mode_name | |
| in ['i2t', 't', 'joint', 't2i2t']) | |
| inputs = [ | |
| mode, | |
| prompt, | |
| image, | |
| seed, | |
| num_steps, | |
| guidance_scale, | |
| ] | |
| outputs = [ | |
| result_image, | |
| result_text, | |
| ] | |
| prompt.submit(fn=model.run, inputs=inputs, outputs=outputs) | |
| run_button.click(fn=model.run, inputs=inputs, outputs=outputs) | |
| return demo | |
| with gr.Blocks(css='style.css') as demo: | |
| gr.Markdown(DESCRIPTION) | |
| with gr.Tabs(): | |
| with gr.TabItem('text2image'): | |
| create_demo('t2i') | |
| with gr.TabItem('image2text'): | |
| create_demo('i2t') | |
| with gr.TabItem('image variation'): | |
| create_demo('i2t2i') | |
| with gr.TabItem('joint generation'): | |
| create_demo('joint') | |
| with gr.TabItem('image generation'): | |
| create_demo('i') | |
| with gr.TabItem('text generation'): | |
| create_demo('t') | |
| with gr.TabItem('text variation'): | |
| create_demo('t2i2t') | |
| demo.queue(api_open=False).launch() | |