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create app.py
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app.py
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import os
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import requests
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from uuid import uuid4
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from PIL import Image
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import gradio as gr
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def gen_image(prompt: str):
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"""generate the image from the chinese stable diffusion model of paddlenlp server
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Args:
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prompt (str): the source of the prompt
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"""
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if not prompt:
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return
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access_token = os.environ['token']
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url = f"https://aip.baidubce.com/rpc/2.0/nlp-itec/poc/stable_diffusion?access_token={access_token}&text={prompt}"
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content = requests.get(url).content
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cache_dir = 'images'
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os.makedirs(cache_dir, exist_ok=True)
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tempfile = os.path.join(cache_dir, f'{str(uuid4())}.png')
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with open(tempfile, 'wb') as f:
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f.write(content)
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image = Image.open(tempfile)
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os.remove(tempfile)
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return [image]
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def read_content(file_path: str) -> str:
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"""read the content of target file
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"""
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with open(file_path, 'r', encoding='utf-8') as f:
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content = f.read()
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return content
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block = gr.Blocks(css=read_content('assets/style.css'))
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examples = [
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'贝尼·赖特森、丹·蒙福德、亚伦·霍尔基的黑白血腥维多利亚小镇夜景特写街景,恐怖,月亮升起,交叉阴影,高对比度,超精细,极简主义构图,4k',
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'马头雕塑插图印刷,超精细,丹·蒙福德,亚伦·霍基,高对比度,低聚合风格',
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'一只熊从篝火旁的冰箱里偷食物,黑白雕刻版画,交叉影线',
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'厚涂层油画《悲伤男孩的特写肖像》,本·科迪,希卡里·希莫达'
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]
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with block:
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gr.HTML(read_content("assets/header.html"))
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gr.Markdown("[![Stargazers repo roster for @PaddlePaddle/PaddleNLP](https://reporoster.com/stars/PaddlePaddle/PaddleNLP)](https://github.com/PaddlePaddle/PaddleNLP)")
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with gr.Group():
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with gr.Box():
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with gr.Row().style(mobile_collapse=False, equal_height=True):
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text = gr.Textbox(
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label="Prompt",
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show_label=False,
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max_lines=1,
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placeholder="输入中文,生成图片",
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).style(
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border=(True, False, True, True),
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rounded=(True, False, False, True),
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container=False,
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)
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btn = gr.Button("Generate image").style(
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margin=False,
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rounded=(False, True, True, False),
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)
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gallery = gr.Gallery(
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label="Generated images", show_label=False, elem_id="gallery"
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).style(grid=[1, 1], height="auto")
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gr.Examples(examples=examples, fn=gen_image, inputs=text, outputs=gallery)
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text.submit(gen_image, inputs=text, outputs=gallery)
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btn.click(gen_image, inputs=text, outputs=gallery)
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gr.Image('./assets/paddlenlp-preview.jpeg')
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gr.HTML(read_content("assets/footer.html"))
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block.queue(concurrency_count=5).launch(debug=True)
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