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from PIL import Image |
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import streamlit as st |
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from pix2text import set_logger, Pix2Text |
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logger = set_logger() |
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st.set_page_config(layout="wide") |
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@st.cache(allow_output_mutation=True) |
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def get_model(): |
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return Pix2Text() |
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def main(): |
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p2t = get_model() |
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title = '开源工具 <a href="https://github.com/breezedeus/pix2text">Pix2Text</a> Demo' |
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st.markdown(f"<h1 style='text-align: center;'>{title}</h1>", unsafe_allow_html=True) |
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subtitle = '作者：<a href="https://github.com/breezedeus">breezedeus</a>； ' \ |
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'欢迎加入 <a href="https://cnocr.readthedocs.io/zh-cn/stable/contact/">交流群</a>' |
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st.markdown(f"<div style='text-align: center;'>{subtitle}</div>", unsafe_allow_html=True) |
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st.markdown('') |
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st.subheader('选择待识别图片') |
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content_file = st.file_uploader('', type=["png", "jpg", "jpeg", "webp"]) |
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if content_file is None: |
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st.stop() |
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try: |
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img = Image.open(content_file).convert('RGB') |
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img.save('ori.jpg') |
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out = p2t(img) |
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logger.info(out) |
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st.markdown('##### 原始图片：') |
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cols = st.columns([1, 3, 1]) |
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with cols[1]: |
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st.image(content_file) |
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st.subheader('识别结果：') |
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st.markdown(f"* **图片类型**：{out['image_type']}") |
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st.markdown("* **识别内容**：") |
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cols = st.columns([1, 3, 1]) |
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with cols[1]: |
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st.text(out['text']) |
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if out['image_type'] == 'formula': |
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st.markdown(f"$${out['text']}$$") |
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except Exception as e: |
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st.error(e) |
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if __name__ == '__main__': |
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main() |
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