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@@ -369,20 +369,130 @@ class StreamlitOCRValidator:
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return wrapped_content
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- def display_html_table_as_dataframe(self, html_content: str):
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+ def display_html_table_as_dataframe(self, html_content: str, enable_editing: bool = False):
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"""将HTML表格解析为DataFrame显示"""
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import pandas as pd
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- from io import StringIO
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+ from io import StringIO, BytesIO
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try:
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# 使用pandas直接读取HTML表格
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tables = pd.read_html(StringIO(html_content))
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if tables:
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for i, table in enumerate(tables):
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- st.subheader(f"表格 {i+1}")
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- st.dataframe(table, use_container_width=True)
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+ st.subheader(f"📊 表格 {i+1}")
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+
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+ # 创建表格操作按钮
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+ col1, col2, col3, col4 = st.columns(4)
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+ with col1:
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+ show_info = st.checkbox(f"显示表格信息", key=f"info_{i}")
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+ with col2:
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+ show_stats = st.checkbox(f"显示统计信息", key=f"stats_{i}")
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+ with col3:
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+ enable_filter = st.checkbox(f"启用过滤", key=f"filter_{i}")
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+ with col4:
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+ enable_sort = st.checkbox(f"启用排序", key=f"sort_{i}")
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+
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+ # 数据过滤
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+ filtered_table = table.copy()
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+ if enable_filter and not table.empty:
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+ filter_col = st.selectbox(
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+ f"选择过滤列 (表格 {i+1})",
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+ options=['无'] + list(table.columns),
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+ key=f"filter_col_{i}"
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+ )
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+
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+ if filter_col != '无':
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+ filter_value = st.text_input(
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+ f"过滤值 (表格 {i+1})",
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+ key=f"filter_value_{i}"
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+ )
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+ if filter_value:
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+ filtered_table = table[
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+ table[filter_col].astype(str).str.contains(filter_value, na=False)
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+ ]
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+
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+ # 数据排序
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+ if enable_sort and not filtered_table.empty:
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+ sort_col = st.selectbox(
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+ f"选择排序列 (表格 {i+1})",
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+ options=['无'] + list(filtered_table.columns),
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+ key=f"sort_col_{i}"
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+ )
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+
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+ if sort_col != '无':
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+ sort_order = st.radio(
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+ f"排序方式 (表格 {i+1})",
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+ options=['升序', '降序'],
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+ horizontal=True,
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+ key=f"sort_order_{i}"
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+ )
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+ ascending = (sort_order == '升序')
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+ filtered_table = filtered_table.sort_values(sort_col, ascending=ascending)
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+
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+ # 显示表格
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+ if enable_editing:
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+ # 可编辑表格
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+ edited_table = st.data_editor(
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+ filtered_table,
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+ use_container_width=True,
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+ key=f"editor_{i}"
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+ )
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+
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+ # 检查是否有编辑
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+ if not edited_table.equals(filtered_table):
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+ st.success("✏️ 表格已编辑，可以导出修改后的数据")
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+
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+ else:
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+ # 只读表格
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+ st.dataframe(filtered_table, use_container_width=True)
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+
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+ # 显示表格信息
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+ if show_info:
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+ st.write(f"**表格信息:**")
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+ st.write(f"- 原始行数: {len(table)}")
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+ st.write(f"- 过滤后行数: {len(filtered_table)}")
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+ st.write(f"- 列数: {len(table.columns)}")
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+ st.write(f"- 列名: {', '.join(table.columns)}")
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+
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+ # 显示统计信息
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+ if show_stats:
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+ st.write(f"**统计信息:**")
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+ numeric_cols = filtered_table.select_dtypes(include=[np.number]).columns
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+ if len(numeric_cols) > 0:
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+ st.dataframe(filtered_table[numeric_cols].describe())
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+ else:
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+ st.info("表格中没有数值列")
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+
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+ # 导出功能
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+ if st.button(f"📥 导出表格 {i+1}", key=f"export_{i}"):
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+ # 创建CSV数据
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+ csv_data = filtered_table.to_csv(index=False)
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+ st.download_button(
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+ label=f"下载CSV (表格 {i+1})",
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+ data=csv_data,
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+ file_name=f"table_{i+1}.csv",
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+ mime="text/csv",
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+ key=f"download_csv_{i}"
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+ )
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+
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+ # 创建Excel数据
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+ excel_buffer = BytesIO()
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+ filtered_table.to_excel(excel_buffer, index=False)
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+ st.download_button(
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+ label=f"下载Excel (表格 {i+1})",
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+ data=excel_buffer.getvalue(),
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+ file_name=f"table_{i+1}.xlsx",
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+ mime="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
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+ key=f"download_excel_{i}"
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+ )
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+
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+ st.markdown("---")
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+ else:
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+ st.warning("未找到可解析的表格")
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+
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except Exception as e:
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st.error(f"表格解析失败: {e}")
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+ st.info("尝试使用HTML渲染模式查看表格")
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# 回退到HTML渲染
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st.markdown(html_content, unsafe_allow_html=True)
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@@ -486,154 +596,221 @@ def main():
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st.error(f"❌ 统计信息计算失败: {e}")
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return
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- # 主要布局 - 左右分栏
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- left_col, right_col = st.columns([1, 1])
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+ # 创建标签页
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+ tab1, tab2, tab3 = st.tabs(["📄 文本校验", "📊 表格分析", "📈 数据统计"])
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- # 左侧 - OCR文本内容
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- with left_col:
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- st.header("📄 OCR识别内容")
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-
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- # 文本选择器
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- if st.session_state.validator.text_bbox_mapping:
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- text_options = ["请选择文本..."] + list(st.session_state.validator.text_bbox_mapping.keys())
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- selected_index = st.selectbox(
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- "选择要校验的文本",
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- range(len(text_options)),
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- format_func=lambda x: text_options[x],
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- key="text_selector"
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- )
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-
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- if selected_index > 0:
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- st.session_state.selected_text = text_options[selected_index]
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- else:
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- st.warning("没有找到可点击的文本")
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+ with tab1:
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+ # 原有的左右分栏内容
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+ left_col, right_col = st.columns([1, 1])
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- # 显示MD内容（可搜索和过滤）
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- if st.session_state.validator.md_content:
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- search_term = st.text_input("🔍 搜索文本内容", placeholder="输入关键词搜索...")
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+ # 左侧 - OCR文本内容
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+ with left_col:
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+ st.header("📄 OCR识别内容")
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- display_content = st.session_state.validator.md_content
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- if search_term:
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- lines = display_content.split('\n')
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- filtered_lines = [line for line in lines if search_term.lower() in line.lower()]
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- display_content = '\n'.join(filtered_lines)
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- if filtered_lines:
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- st.success(f"找到 {len(filtered_lines)} 行包含 '{search_term}'")
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- else:
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- st.warning(f"未找到包含 '{search_term}' 的内容")
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-
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- # 渲染方式选择
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- render_mode = st.radio(
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- "选择渲染方式",
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- ["HTML渲染", "Markdown渲染", "DataFrame表格", "原始文本"], # 添加DataFrame选项
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- horizontal=True
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- )
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-
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- if render_mode == "HTML渲染":
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- # 使用unsafe_allow_html=True来渲染HTML表格
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- st.markdown(display_content, unsafe_allow_html=True)
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- elif render_mode == "Markdown渲染":
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- # 转换HTML表格为Markdown格式
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- converted_content = st.session_state.validator.convert_html_table_to_markdown(display_content)
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- st.markdown(converted_content)
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- elif render_mode == "DataFrame表格":
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- # 新增：使用DataFrame显示表格
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- if '<table>' in display_content.lower():
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- st.session_state.validator.display_html_table_as_dataframe(display_content)
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- else:
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- st.info("当前内容中没有检测到HTML表格")
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- st.markdown(display_content)
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- else:
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- # 原始文本显示
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- st.text_area(
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- "MD内容预览",
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- display_content,
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- height=300,
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- help="OCR识别的文本内容"
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+ # 文本选择器
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+ if st.session_state.validator.text_bbox_mapping:
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+ text_options = ["请选择文本..."] + list(st.session_state.validator.text_bbox_mapping.keys())
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+ selected_index = st.selectbox(
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+ "选择要校验的文本",
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+ range(len(text_options)),
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+ format_func=lambda x: text_options[x],
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+ key="text_selector"
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)
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-
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- # 可点击文本列表
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- st.subheader("🎯 可点击文本列表")
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-
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- if st.session_state.validator.text_bbox_mapping:
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- for text, info_list in st.session_state.validator.text_bbox_mapping.items():
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- info = info_list[0] # 使用第一个bbox信息
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-
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- # 确定显示样式
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- is_selected = (text == st.session_state.selected_text)
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- is_error = (text in st.session_state.marked_errors)
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- # 创建按钮行
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- button_col, error_col = st.columns([4, 1])
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+ if selected_index > 0:
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+ st.session_state.selected_text = text_options[selected_index]
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+ else:
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+ st.warning("没有找到可点击的文本")
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+
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+ # 显示MD内容（可搜索和过滤）
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+ if st.session_state.validator.md_content:
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+ search_term = st.text_input("🔍 搜索文本内容", placeholder="输入关键词搜索...")
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- with button_col:
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- button_type = "primary" if is_selected else "secondary"
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- if st.button(f"📍 {text}", key=f"btn_{text}", type=button_type):
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- st.session_state.selected_text = text
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- st.rerun()
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+ display_content = st.session_state.validator.md_content
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+ if search_term:
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+ lines = display_content.split('\n')
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+ filtered_lines = [line for line in lines if search_term.lower() in line.lower()]
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+ display_content = '\n'.join(filtered_lines)
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+ if filtered_lines:
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+ st.success(f"找到 {len(filtered_lines)} 行包含 '{search_term}'")
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+ else:
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+ st.warning(f"未找到包含 '{search_term}' 的内容")
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- with error_col:
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- if is_error:
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- if st.button("✅", key=f"fix_{text}", help="取消错误标记"):
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- st.session_state.marked_errors.discard(text)
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- st.rerun()
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+ # 渲染方式选择
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+ render_mode = st.radio(
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+ "选择渲染方式",
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+ ["HTML渲染", "Markdown渲染", "DataFrame表格", "原始文本"], # 添加DataFrame选项
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+ horizontal=True
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+ )
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+
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+ if render_mode == "HTML渲染":
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+ # 使用unsafe_allow_html=True来渲染HTML表格
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+ st.markdown(display_content, unsafe_allow_html=True)
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+ elif render_mode == "Markdown渲染":
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+ # 转换HTML表格为Markdown格式
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+ converted_content = st.session_state.validator.convert_html_table_to_markdown(display_content)
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+ st.markdown(converted_content)
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+ elif render_mode == "DataFrame表格":
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+ # 新增：使用DataFrame显示表格
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+ if '<table>' in display_content.lower():
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+ st.session_state.validator.display_html_table_as_dataframe(display_content)
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else:
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- if st.button("❌", key=f"error_{text}", help="标记为错误"):
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- st.session_state.marked_errors.add(text)
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+ st.info("当前内容中没有检测到HTML表格")
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+ st.markdown(display_content)
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+ else:
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+ # 原始文本显示
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+ st.text_area(
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+ "MD内容预览",
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+ display_content,
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+ height=300,
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+ help="OCR识别的文本内容"
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+ )
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+
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+ # 可点击文本列表
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+ st.subheader("🎯 可点击文本列表")
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+
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+ if st.session_state.validator.text_bbox_mapping:
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+ for text, info_list in st.session_state.validator.text_bbox_mapping.items():
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+ info = info_list[0] # 使用第一个bbox信息
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+
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+ # 确定显示样式
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+ is_selected = (text == st.session_state.selected_text)
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+ is_error = (text in st.session_state.marked_errors)
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+
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+ # 创建按钮行
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+ button_col, error_col = st.columns([4, 1])
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+
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+ with button_col:
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+ button_type = "primary" if is_selected else "secondary"
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+ if st.button(f"📍 {text}", key=f"btn_{text}", type=button_type):
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+ st.session_state.selected_text = text
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st.rerun()
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- else:
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- st.info("没有可点击的文本项目")
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+
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+ with error_col:
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+ if is_error:
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+ if st.button("✅", key=f"fix_{text}", help="取消错误标记"):
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+ st.session_state.marked_errors.discard(text)
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+ st.rerun()
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+ else:
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+ if st.button("❌", key=f"error_{text}", help="标记为错误"):
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+ st.session_state.marked_errors.add(text)
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+ st.rerun()
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+ else:
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+ st.info("没有可点击的文本项目")
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+
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+ # 右侧 - 图像显示
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+ with right_col:
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+ st.header("🖼️ 原图标注")
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+
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+ if st.session_state.validator.image_path and Path(st.session_state.validator.image_path).exists():
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+ try:
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+ # 加载图片
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+ image = Image.open(st.session_state.validator.image_path)
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+
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+ # 创建交互式图片
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+ selected_bbox = None
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+ if st.session_state.selected_text and st.session_state.selected_text in st.session_state.validator.text_bbox_mapping:
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+ info = st.session_state.validator.text_bbox_mapping[st.session_state.selected_text][0]
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+ selected_bbox = info['bbox']
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+
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+ fig = st.session_state.validator.create_interactive_plot(image, selected_bbox)
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+ st.plotly_chart(fig, use_container_width=True)
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+
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+ # 显示选中文本的详细信息
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+ if st.session_state.selected_text:
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+ st.subheader("📍 选中文本详情")
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+
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+ if st.session_state.selected_text in st.session_state.validator.text_bbox_mapping:
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+ info = st.session_state.validator.text_bbox_mapping[st.session_state.selected_text][0]
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+ bbox = info['bbox']
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+
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+ info_col1, info_col2 = st.columns(2)
|
|
|
+ with info_col1:
|
|
|
+ st.write(f"**文本内容:** {st.session_state.selected_text}")
|
|
|
+ st.write(f"**类别:** {info['category']}")
|
|
|
+ st.write(f"**置信度:** {info.get('confidence', 'N/A')}")
|
|
|
+
|
|
|
+ with info_col2:
|
|
|
+ st.write(f"**位置:** [{', '.join(map(str, bbox))}]")
|
|
|
+ if len(bbox) >= 4:
|
|
|
+ st.write(f"**宽度:** {bbox[2] - bbox[0]} px")
|
|
|
+ st.write(f"**高度:** {bbox[3] - bbox[1]} px")
|
|
|
+
|
|
|
+ # 标记状态
|
|
|
+ is_error = st.session_state.selected_text in st.session_state.marked_errors
|
|
|
+ if is_error:
|
|
|
+ st.error("⚠️ 此文本已标记为错误")
|
|
|
+ else:
|
|
|
+ st.success("✅ 此文本未标记错误")
|
|
|
+ except Exception as e:
|
|
|
+ st.error(f"❌ 图片处理失败: {e}")
|
|
|
+ else:
|
|
|
+ st.error("未找到对应的图片文件")
|
|
|
+ if st.session_state.validator.image_path:
|
|
|
+ st.write(f"期望路径: {st.session_state.validator.image_path}")
|
|
|
|
|
|
- # 右侧 - 图像显示
|
|
|
- with right_col:
|
|
|
- st.header("🖼️ 原图标注")
|
|
|
-
|
|
|
- if st.session_state.validator.image_path and Path(st.session_state.validator.image_path).exists():
|
|
|
- try:
|
|
|
- # 加载图片
|
|
|
- image = Image.open(st.session_state.validator.image_path)
|
|
|
-
|
|
|
- # 创建交互式图片
|
|
|
- selected_bbox = None
|
|
|
- if st.session_state.selected_text and st.session_state.selected_text in st.session_state.validator.text_bbox_mapping:
|
|
|
- info = st.session_state.validator.text_bbox_mapping[st.session_state.selected_text][0]
|
|
|
- selected_bbox = info['bbox']
|
|
|
+ with tab2:
|
|
|
+ # 新增：专门的表格分析页面
|
|
|
+ st.header("📊 表格数据分析")
|
|
|
+
|
|
|
+ if st.session_state.validator.md_content:
|
|
|
+ # 检查是否包含表格
|
|
|
+ if '<table' in st.session_state.validator.md_content.lower():
|
|
|
+ col1, col2 = st.columns([2, 1])
|
|
|
|
|
|
- fig = st.session_state.validator.create_interactive_plot(image, selected_bbox)
|
|
|
- st.plotly_chart(fig, use_container_width=True)
|
|
|
+ with col1:
|
|
|
+ st.subheader("🔍 表格数据预览")
|
|
|
+ st.session_state.validator.display_html_table_as_dataframe(
|
|
|
+ st.session_state.validator.md_content
|
|
|
+ )
|
|
|
|
|
|
- # 显示选中文本的详细信息
|
|
|
- if st.session_state.selected_text:
|
|
|
- st.subheader("📍 选中文本详情")
|
|
|
+ with col2:
|
|
|
+ st.subheader("⚙️ 表格操作")
|
|
|
|
|
|
- if st.session_state.selected_text in st.session_state.validator.text_bbox_mapping:
|
|
|
- info = st.session_state.validator.text_bbox_mapping[st.session_state.selected_text][0]
|
|
|
- bbox = info['bbox']
|
|
|
-
|
|
|
- info_col1, info_col2 = st.columns(2)
|
|
|
- with info_col1:
|
|
|
- st.write(f"**文本内容:** {st.session_state.selected_text}")
|
|
|
- st.write(f"**类别:** {info['category']}")
|
|
|
- st.write(f"**置信度:** {info.get('confidence', 'N/A')}")
|
|
|
-
|
|
|
- with info_col2:
|
|
|
- st.write(f"**位置:** [{', '.join(map(str, bbox))}]")
|
|
|
- if len(bbox) >= 4:
|
|
|
- st.write(f"**宽度:** {bbox[2] - bbox[0]} px")
|
|
|
- st.write(f"**高度:** {bbox[3] - bbox[1]} px")
|
|
|
-
|
|
|
- # 标记状态
|
|
|
- is_error = st.session_state.selected_text in st.session_state.marked_errors
|
|
|
- if is_error:
|
|
|
- st.error("⚠️ 此文本已标记为错误")
|
|
|
- else:
|
|
|
- st.success("✅ 此文本未标记错误")
|
|
|
- except Exception as e:
|
|
|
- st.error(f"❌ 图片处理失败: {e}")
|
|
|
+ if st.button("📥 导出表格数据", type="primary"):
|
|
|
+ try:
|
|
|
+ import pandas as pd
|
|
|
+ from io import StringIO
|
|
|
+ tables = pd.read_html(StringIO(st.session_state.validator.md_content))
|
|
|
+ if tables:
|
|
|
+ # 创建Excel文件
|
|
|
+ output = BytesIO()
|
|
|
+ with pd.ExcelWriter(output, engine='openpyxl') as writer:
|
|
|
+ for i, table in enumerate(tables):
|
|
|
+ table.to_excel(writer, sheet_name=f'Table_{i+1}', index=False)
|
|
|
+
|
|
|
+ st.download_button(
|
|
|
+ label="📥 下载Excel文件",
|
|
|
+ data=output.getvalue(),
|
|
|
+ file_name="ocr_tables.xlsx",
|
|
|
+ mime="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
|
|
|
+ )
|
|
|
+ except Exception as e:
|
|
|
+ st.error(f"导出失败: {e}")
|
|
|
+
|
|
|
+ if st.button("🔍 表格统计分析"):
|
|
|
+ try:
|
|
|
+ import pandas as pd
|
|
|
+ from io import StringIO
|
|
|
+ tables = pd.read_html(StringIO(st.session_state.validator.md_content))
|
|
|
+ if tables:
|
|
|
+ st.write("**表格统计信息:**")
|
|
|
+ for i, table in enumerate(tables):
|
|
|
+ st.write(f"表格 {i+1}:")
|
|
|
+ st.write(f"- 行数: {len(table)}")
|
|
|
+ st.write(f"- 列数: {len(table.columns)}")
|
|
|
+ st.write(f"- 数值列数: {len(table.select_dtypes(include=[np.number]).columns)}")
|
|
|
+ except Exception as e:
|
|
|
+ st.error(f"统计分析失败: {e}")
|
|
|
+ else:
|
|
|
+ st.info("当前OCR结果中没有检测到表格数据")
|
|
|
else:
|
|
|
- st.error("未找到对应的图片文件")
|
|
|
- if st.session_state.validator.image_path:
|
|
|
- st.write(f"期望路径: {st.session_state.validator.image_path}")
|
|
|
+ st.warning("请先加载OCR数据")
|
|
|
+
|
|
|
+ with tab3:
|
|
|
+ # 数据统计页面
|
|
|
+ st.header("📈 OCR数据统计")
|
|
|
+ # ...现有的统计代码...
|
|
|
|
|
|
if __name__ == "__main__":
|
|
|
main()
|
