import numpy as np import gradio as gr import paddlehub as hub model = hub.Module(name='ernie_vilg') def inference(text_prompts, style): try: results = model.generate_image( text_prompts=text_prompts, style=style, visualization=False) return 'Success', results[:6] except Exception as e: error_text = str(e) return error_text, None return title="ERNIE-ViLG" description="ERNIE-ViLG model, which supports text-to-image task." css = """ .gradio-container { font-family: 'IBM Plex Sans', sans-serif; } .gr-button { color: white; border-color: black; background: black; } input[type='range'] { accent-color: black; } .dark input[type='range'] { accent-color: #dfdfdf; } .container { max-width: 730px; margin: auto; padding-top: 1.5rem; } #gallery { min-height: 22rem; margin-bottom: 15px; margin-left: auto; margin-right: auto; border-bottom-right-radius: .5rem !important; border-bottom-left-radius: .5rem !important; } #gallery>div>.h-full { min-height: 20rem; } .details:hover { text-decoration: underline; } .gr-button { white-space: nowrap; } .gr-button:focus { border-color: rgb(147 197 253 / var(--tw-border-opacity)); outline: none; box-shadow: var(--tw-ring-offset-shadow), var(--tw-ring-shadow), var(--tw-shadow, 0 0 #0000); --tw-border-opacity: 1; --tw-ring-offset-shadow: var(--tw-ring-inset) 0 0 0 var(--tw-ring-offset-width) var(--tw-ring-offset-color); --tw-ring-shadow: var(--tw-ring-inset) 0 0 0 calc(3px var(--tw-ring-offset-width)) var(--tw-ring-color); --tw-ring-color: rgb(191 219 254 / var(--tw-ring-opacity)); --tw-ring-opacity: .5; } .footer { margin-bottom: 45px; margin-top: 35px; text-align: center; border-bottom: 1px solid #e5e5e5; } .footer>p { font-size: .8rem; display: inline-block; padding: 0 10px; transform: translateY(10px); background: white; } .dark .footer { border-color: #303030; } .dark .footer>p { background: #0b0f19; } .prompt h4{ margin: 1.25em 0 .25em 0; font-weight: bold; font-size: 115%; } """ block = gr.Blocks(css=css) examples = [ [ '戴着眼镜的猫', '油画' ], [ '日落时的城市天际线,史前遗迹风格', '油画' ], [ '一只猫坐在椅子上,戴着一副墨镜, low poly 风格', '卡通' ], ] with block: gr.HTML( """
Paddlehub

ERNIE-ViLG Demo

ERNIE-ViLG is a state-of-the-art text-to-image model that generates images from Chinese text.

""" ) with gr.Group(): with gr.Box(): with gr.Row().style(mobile_collapse=False, equal_height=True): text = gr.Textbox( label="Prompt (Chinese)", show_label=False, max_lines=1, placeholder="Enter your Chinese prompt", ).style( border=(True, False, True, True), rounded=(True, False, False, True), container=False, ) btn = gr.Button("Generate image").style( margin=False, rounded=(False, True, True, False), ) styles = gr.Dropdown(label="style", choices=['水彩','油画', '粉笔画', '卡通', '蜡笔画', '儿童画', '探索无限'], value='油画') gallery = gr.Gallery( label="Generated images", show_label=False, elem_id="gallery" ).style(grid=[2, 3], height="auto") status_text = gr.Textbox( label="Process status", show_label=True, max_lines=1, interactive=False ) ex = gr.Examples(examples=examples, fn=inference, inputs=[text, styles], outputs=gallery, cache_examples=False) ex.dataset.headers = [""] text.submit(inference, inputs=[text, styles], outputs=[status_text, gallery]) btn.click(inference, inputs=[text, styles], outputs=[status_text, gallery]) gr.HTML( """

Prompt公式

Prompt = [形容词] [主语] ,[细节设定], [修饰语或者艺术家]。 关于各部分的构造方式和效果,可以参考YouPromptMe指南

""" ) block.queue(concurrency_count=100).launch()