feat: 添加 Web 界面和项目文档

新增功能：
- 添加 Streamlit Web 界面 (src/app.py)，支持批量上传和在线预览
- 添加 README.md，包含项目介绍、部署方案和配置要求

依赖更新：
- 锁定 PaddleOCR 2.x 版本以确保稳定性
- 新增 streamlit 依赖

部署方案：
- 内网服务器部署
- Docker 容器化部署
- systemd 系统服务

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

src/app.py

@@ -0,0 +1,88 @@
+import os
+import tempfile
+import pandas as pd
+import streamlit as st
+from paddleocr import PaddleOCR
+from processor import extract_info, save_to_excel
+
+os.environ["PADDLE_PDX_DISABLE_MODEL_SOURCE_CHECK"] = "True"
+
+st.set_page_config(page_title="信封信息提取系统", page_icon="📮", layout="wide")
+st.title("📮 信封信息提取系统")
+
+
+@st.cache_resource
+def load_ocr():
+    return PaddleOCR(use_textline_orientation=True, lang="ch", show_log=False)
+
+
+ocr = load_ocr()
+
+
+def process_image(image_file):
+    """处理单张图片"""
+    with tempfile.NamedTemporaryFile(delete=False, suffix=".jpg") as tmp:
+        tmp.write(image_file.getvalue())
+        tmp_path = tmp.name
+
+    try:
+        result = ocr.ocr(tmp_path, cls=False)
+        ocr_texts = []
+        if result and result[0]:
+            for line in result[0]:
+                if line and len(line) >= 2:
+                    ocr_texts.append(line[1][0])
+        return extract_info(ocr_texts), ocr_texts
+    finally:
+        os.unlink(tmp_path)
+
+
+# 文件上传
+uploaded_files = st.file_uploader(
+    "上传信封图片（支持批量）",
+    type=["jpg", "jpeg", "png", "bmp"],
+    accept_multiple_files=True,
+)
+
+if uploaded_files:
+    all_records = []
+
+    progress = st.progress(0)
+    status = st.empty()
+
+    for i, file in enumerate(uploaded_files):
+        status.text(f"正在处理: {file.name}")
+        record, raw_texts = process_image(file)
+        record["文件名"] = file.name
+        all_records.append(record)
+        progress.progress((i + 1) / len(uploaded_files))
+
+    status.text("处理完成！")
+
+    # 显示结果表格
+    df = pd.DataFrame(all_records)
+    cols = ["文件名", "编号", "邮编", "地址", "联系人/单位名", "电话"]
+    df = df.reindex(columns=cols)
+
+    st.subheader("📋 提取结果")
+    st.dataframe(df, use_container_width=True)
+
+    # 下载按钮
+    output_path = tempfile.mktemp(suffix=".xlsx")
+    df.to_excel(output_path, index=False)
+    with open(output_path, "rb") as f:
+        st.download_button(
+            label="📥 下载 Excel",
+            data=f,
+            file_name="信封提取结果.xlsx",
+            mime="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
+        )
+    os.unlink(output_path)
+
+    # 预览图片和识别详情
+    with st.expander("🔍 查看识别详情"):
+        cols = st.columns(min(3, len(uploaded_files)))
+        for i, file in enumerate(uploaded_files):
+            with cols[i % 3]:
+                st.image(file, caption=file.name, use_container_width=True)
+                st.json(all_records[i])