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| #!/usr/bin/env python | |
| from __future__ import annotations | |
| import gradio as gr | |
| from model import AppModel | |
| DESCRIPTION = '''# <a href="https://github.com/THUDM/CogView2">CogView2</a> (text2image) | |
| This application accepts English or Chinese as input. | |
| In general, Chinese input produces better results than English input. | |
| If you check the "Translate to Chinese" checkbox, the app will use the English to Chinese translation results with [this Space](https://huggingface.co/spaces/chinhon/translation_eng2ch) as input. | |
| But the translation model may mistranslate and the results could be poor. | |
| So, it is also a good idea to input the translation results from other translation services. | |
| ''' | |
| NOTES = ''' | |
| - This app is adapted from <a href="https://github.com/hysts/CogView2_demo">https://github.com/hysts/CogView2_demo</a>. It would be recommended to use the repo if you want to run the app yourself. | |
| ''' | |
| FOOTER = '<img id="visitor-badge" alt="visitor badge" src="https://visitor-badge.glitch.me/badge?page_id=THUDM.CogView2" />' | |
| def set_example_text(example: list) -> list[dict]: | |
| return [ | |
| gr.Textbox.update(value=example[0]), | |
| gr.Dropdown.update(value=example[1]), | |
| ] | |
| def main(): | |
| only_first_stage = True | |
| max_inference_batch_size = 8 | |
| model = AppModel(max_inference_batch_size, only_first_stage) | |
| with gr.Blocks(css='style.css') as demo: | |
| gr.Markdown(DESCRIPTION) | |
| with gr.Row(): | |
| with gr.Column(): | |
| with gr.Group(): | |
| text = gr.Textbox(label='Input Text') | |
| translate = gr.Checkbox(label='Translate to Chinese', | |
| value=False) | |
| style = gr.Dropdown(choices=[ | |
| 'none', | |
| 'mainbody', | |
| 'photo', | |
| 'flat', | |
| 'comics', | |
| 'oil', | |
| 'sketch', | |
| 'isometric', | |
| 'chinese', | |
| 'watercolor', | |
| ], | |
| value='mainbody', | |
| label='Style') | |
| seed = gr.Slider(0, | |
| 100000, | |
| step=1, | |
| value=1234, | |
| label='Seed') | |
| only_first_stage = gr.Checkbox( | |
| label='Only First Stage', | |
| value=only_first_stage, | |
| visible=not only_first_stage) | |
| num_images = gr.Slider(1, | |
| 16, | |
| step=1, | |
| value=4, | |
| label='Number of Images') | |
| run_button = gr.Button('Run') | |
| with open('samples.txt') as f: | |
| samples = [ | |
| line.strip().split('\t') for line in f.readlines() | |
| ] | |
| examples = gr.Dataset(components=[text, style], | |
| samples=samples) | |
| with gr.Column(): | |
| with gr.Group(): | |
| translated_text = gr.Textbox(label='Translated Text') | |
| with gr.Tabs(): | |
| with gr.TabItem('Output (Grid View)'): | |
| result_grid = gr.Image(show_label=False) | |
| with gr.TabItem('Output (Gallery)'): | |
| result_gallery = gr.Gallery(show_label=False) | |
| gr.Markdown(NOTES) | |
| gr.Markdown(FOOTER) | |
| run_button.click(fn=model.run_with_translation, | |
| inputs=[ | |
| text, | |
| translate, | |
| style, | |
| seed, | |
| only_first_stage, | |
| num_images, | |
| ], | |
| outputs=[ | |
| translated_text, | |
| result_grid, | |
| result_gallery, | |
| ]) | |
| examples.click(fn=set_example_text, | |
| inputs=examples, | |
| outputs=examples.components) | |
| demo.launch(enable_queue=True) | |
| if __name__ == '__main__': | |
| main() | |