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@@ -0,0 +1,639 @@
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+#!/usr/bin/env python3
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+"""
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+基于Streamlit的OCR可视化校验工具（修复版）
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+提供丰富的交互组件和更好的用户体验
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+"""
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+
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+import streamlit as st
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+import json
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+import pandas as pd
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+from pathlib import Path
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+import numpy as np
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+from PIL import Image, ImageDraw, ImageFont
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+import cv2
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+import base64
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+from typing import Dict, List, Optional, Tuple
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+import plotly.express as px
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+import plotly.graph_objects as go
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+from plotly.subplots import make_subplots
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+
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+# 设置页面配置
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+st.set_page_config(
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+ page_title="OCR可视化校验工具",
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+ page_icon="🔍",
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+ layout="wide",
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+ initial_sidebar_state="expanded"
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+)
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+
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+# 自定义CSS样式
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+st.markdown("""
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+<style>
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+ .main > div {
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+ padding-top: 2rem;
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+ }
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+
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+ .stSelectbox > div > div > div {
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+ background-color: #f0f2f6;
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+ }
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+
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+ .clickable-text {
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+ background-color: #e1f5fe;
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+ padding: 2px 6px;
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+ border-radius: 4px;
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+ border: 1px solid #0288d1;
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+ cursor: pointer;
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+ margin: 2px;
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+ display: inline-block;
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+ }
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+
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+ .selected-text {
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+ background-color: #fff3e0;
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+ border-color: #ff9800;
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+ font-weight: bold;
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+ }
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+
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+ .error-text {
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+ background-color: #ffebee;
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+ border-color: #f44336;
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+ color: #d32f2f;
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+ }
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+
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+ .stats-container {
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+ background-color: #f8f9fa;
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+ padding: 1rem;
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+ border-radius: 8px;
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+ border-left: 4px solid #28a745;
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+ }
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+</style>
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+""", unsafe_allow_html=True)
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+
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+class StreamlitOCRValidator:
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+ def __init__(self):
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+ self.ocr_data = []
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+ self.md_content = ""
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+ self.image_path = ""
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+ self.text_bbox_mapping = {}
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+ self.selected_text = None
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+ self.marked_errors = set()
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+
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+ def load_ocr_data(self, json_path: str, md_path: Optional[str] = None, image_path: Optional[str] = None):
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+ """加载OCR相关数据"""
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+ json_file = Path(json_path)
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+
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+ # 加载JSON数据
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+ try:
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+ with open(json_file, 'r', encoding='utf-8') as f:
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+ data = json.load(f)
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+ # 确保数据是列表格式
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+ if isinstance(data, list):
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+ self.ocr_data = data
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+ elif isinstance(data, dict) and 'results' in data:
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+ self.ocr_data = data['results']
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+ else:
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+ st.error(f"❌ 不支持的JSON格式: {json_path}")
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+ return
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+ except Exception as e:
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+ st.error(f"❌ 加载JSON文件失败: {e}")
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+ return
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+
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+ # 推断MD文件路径
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+ if md_path is None:
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+ md_file = json_file.with_suffix('.md')
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+ else:
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+ md_file = Path(md_path)
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+
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+ if md_file.exists():
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+ with open(md_file, 'r', encoding='utf-8') as f:
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+ self.md_content = f.read()
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+
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+ # 推断图片路径
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+ if image_path is None:
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+ image_name = json_file.stem
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+ sample_data_dir = Path("./sample_data")
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+
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+ image_candidates = [
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+ sample_data_dir / f"{image_name}.png",
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+ sample_data_dir / f"{image_name}.jpg",
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+ json_file.parent / f"{image_name}.png",
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+ json_file.parent / f"{image_name}.jpg",
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+ ]
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+
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+ for candidate in image_candidates:
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+ if candidate.exists():
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+ self.image_path = str(candidate)
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+ break
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+ else:
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+ self.image_path = image_path
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+
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+ # 处理数据
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+ self.process_data()
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+
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+ def process_data(self):
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+ """处理OCR数据，建立文本到bbox的映射"""
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+ self.text_bbox_mapping = {}
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+
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+ # 确保 ocr_data 是列表
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+ if not isinstance(self.ocr_data, list):
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+ st.warning("⚠️ OCR数据格式不正确，期望列表格式")
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+ return
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+
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+ for i, item in enumerate(self.ocr_data):
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+ # 确保 item 是字典类型
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+ if not isinstance(item, dict):
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+ continue
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+
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+ if 'text' in item and 'bbox' in item:
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+ text = str(item['text']).strip()
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+ if text and text not in ['Picture', '']:
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+ bbox = item['bbox']
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+ # 确保bbox是4个数字的列表
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+ if isinstance(bbox, list) and len(bbox) == 4:
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+ if text not in self.text_bbox_mapping:
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+ self.text_bbox_mapping[text] = []
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+ self.text_bbox_mapping[text].append({
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+ 'bbox': bbox,
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+ 'category': item.get('category', 'Text'),
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+ 'index': i,
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+ 'confidence': item.get('confidence', 1.0)
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+ })
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+
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+ def draw_bbox_on_image(self, image: Image.Image, bbox: List[int], color: str = "red", width: int = 3) -> Image.Image:
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+ """在图片上绘制bbox框"""
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+ img_copy = image.copy()
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+ draw = ImageDraw.Draw(img_copy)
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+
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+ x1, y1, x2, y2 = bbox
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+
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+ # 绘制矩形框
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+ draw.rectangle([x1, y1, x2, y2], outline=color, width=width)
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+
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+ # 添加半透明填充
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+ overlay = Image.new('RGBA', img_copy.size, (0, 0, 0, 0))
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+ overlay_draw = ImageDraw.Draw(overlay)
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+
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+ if color == "red":
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+ fill_color = (255, 0, 0, 30)
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+ elif color == "blue":
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+ fill_color = (0, 0, 255, 30)
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+ elif color == "green":
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+ fill_color = (0, 255, 0, 30)
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+ else:
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+ fill_color = (255, 255, 0, 30)
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+
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+ overlay_draw.rectangle([x1, y1, x2, y2], fill=fill_color)
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+ img_copy = Image.alpha_composite(img_copy.convert('RGBA'), overlay).convert('RGB')
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+
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+ return img_copy
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+
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+ def create_interactive_plot(self, image: Image.Image, selected_bbox: Optional[List[int]] = None) -> go.Figure:
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+ """创建交互式图片显示"""
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+ fig = go.Figure()
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+
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+ # 添加图片
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+ fig.add_layout_image(
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+ dict(
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+ source=image,
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+ xref="x",
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+ yref="y",
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+ x=0,
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+ y=image.height,
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+ sizex=image.width,
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+ sizey=image.height,
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+ sizing="stretch",
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+ opacity=1.0,
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+ layer="below"
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+ )
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+ )
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+
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+ # 添加所有bbox（浅色显示）
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+ for text, info_list in self.text_bbox_mapping.items():
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+ for info in info_list:
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+ bbox = info['bbox']
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+ if len(bbox) >= 4: # 确保bbox有足够的坐标
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+ x1, y1, x2, y2 = bbox[:4]
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+
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+ color = "rgba(0, 100, 200, 0.2)" # 默认浅蓝色
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+ if text in self.marked_errors:
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+ color = "rgba(255, 0, 0, 0.3)" # 错误标记为红色
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+
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+ fig.add_shape(
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+ type="rect",
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+ x0=x1, y0=image.height-y2,
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+ x1=x2, y1=image.height-y1,
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+ line=dict(color=color.replace('0.2', '0.8').replace('0.3', '1.0'), width=1),
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+ fillcolor=color,
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+ )
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+
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+ # 高亮显示选中的bbox
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+ if selected_bbox and len(selected_bbox) >= 4:
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+ x1, y1, x2, y2 = selected_bbox[:4]
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+ fig.add_shape(
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+ type="rect",
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+ x0=x1, y0=image.height-y2,
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+ x1=x2, y1=image.height-y1,
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+ line=dict(color="red", width=3),
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+ fillcolor="rgba(255, 0, 0, 0.2)",
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+ )
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+
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+ # 设置布局
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+ fig.update_xaxes(
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+ visible=False,
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+ range=[0, image.width]
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+ )
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+
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+ fig.update_yaxes(
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+ visible=False,
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+ range=[0, image.height],
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+ scaleanchor="x"
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+ )
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+
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+ fig.update_layout(
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+ width=800,
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+ height=600,
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+ margin=dict(l=0, r=0, t=0, b=0),
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+ xaxis_showgrid=False,
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+ yaxis_showgrid=False,
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+ plot_bgcolor='white'
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+ )
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+
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+ return fig
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+
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+ def get_statistics(self) -> Dict:
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+ """获取统计信息"""
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+ # 先确保 ocr_data 不为空且是列表
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+ if not isinstance(self.ocr_data, list) or not self.ocr_data:
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+ return {
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+ 'total_texts': 0,
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+ 'clickable_texts': 0,
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+ 'marked_errors': 0,
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+ 'categories': {},
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+ 'accuracy_rate': 0
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+ }
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+
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+ total_texts = len(self.ocr_data)
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+ clickable_texts = len(self.text_bbox_mapping)
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+ marked_errors = len(self.marked_errors)
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+
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+ # 按类别统计 - 添加类型检查
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+ categories = {}
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+ for item in self.ocr_data:
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+ # 确保 item 是字典类型
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+ if isinstance(item, dict):
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+ category = item.get('category', 'Unknown')
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+ elif isinstance(item, str):
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+ category = 'Text' # 字符串类型默认为 Text 类别
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+ else:
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+ category = 'Unknown'
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+
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+ categories[category] = categories.get(category, 0) + 1
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+
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+ return {
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+ 'total_texts': total_texts,
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+ 'clickable_texts': clickable_texts,
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+ 'marked_errors': marked_errors,
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+ 'categories': categories,
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+ 'accuracy_rate': (clickable_texts - marked_errors) / clickable_texts * 100 if clickable_texts > 0 else 0
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+ }
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+
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+ def convert_html_table_to_markdown(self, content: str) -> str:
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+ """将HTML表格转换为Markdown表格格式"""
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+ import re
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+ from html import unescape
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+
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+ # 简单的HTML表格到Markdown转换
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+ def replace_table(match):
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+ table_html = match.group(0)
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+
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+ # 提取所有行
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+ rows = re.findall(r'<tr>(.*?)</tr>', table_html, re.DOTALL | re.IGNORECASE)
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+ if not rows:
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+ return table_html # 如果没有找到行，返回原始内容
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+
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+ markdown_rows = []
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+ for i, row in enumerate(rows):
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+ # 提取单元格
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+ cells = re.findall(r'<td[^>]*>(.*?)</td>', row, re.DOTALL | re.IGNORECASE)
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+ if cells:
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+ # 清理单元格内容
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+ clean_cells = []
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+ for cell in cells:
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+ # 移除HTML标签，保留文本
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+ cell_text = re.sub(r'<[^>]+>', '', cell).strip()
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+ cell_text = unescape(cell_text) # 解码HTML实体
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+ clean_cells.append(cell_text)
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+
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+ # 构建Markdown行
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+ markdown_row = '| ' + ' | '.join(clean_cells) + ' |'
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+ markdown_rows.append(markdown_row)
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+
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+ # 在第一行后添加分隔符
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+ if i == 0:
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+ separator = '| ' + ' | '.join(['---'] * len(clean_cells)) + ' |'
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+ markdown_rows.append(separator)
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+
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+ return '\n'.join(markdown_rows) if markdown_rows else table_html
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+
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+ # 替换所有HTML表格
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+ converted = re.sub(r'<table[^>]*>.*?</table>', replace_table, content, flags=re.DOTALL | re.IGNORECASE)
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+ return converted
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+
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+ def render_markdown_with_options(self, markdown_content: str, table_format: str = "grid", escape_html: bool = True):
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+ """自定义Markdown渲染方法，支持多种选项"""
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+ import markdown
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+
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+ # 处理HTML表格
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+ if escape_html:
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+ markdown_content = self.convert_html_table_to_markdown(markdown_content)
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+
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+ # 渲染Markdown
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+ html_content = markdown.markdown(markdown_content)
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+
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+ # 根据选项包裹在特定的HTML结构中
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+ if table_format == "grid":
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+ # 网格布局
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+ wrapped_content = f"""
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+ <div class="markdown-grid">
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+ {html_content}
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+ </div>
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+ """
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+ elif table_format == "list":
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+ # 列表布局
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+ wrapped_content = f"""
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+ <div class="markdown-list">
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+ {html_content}
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+ </div>
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+ """
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+ else:
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+ # 默认直接返回
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+ wrapped_content = html_content
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+
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+ return wrapped_content
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+
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+ def display_html_table_as_dataframe(self, html_content: str):
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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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+
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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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+ except Exception as e:
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+ st.error(f"表格解析失败: {e}")
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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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+
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+def main():
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+ """主应用"""
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+ st.title("🔍 OCR可视化校验工具")
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+ st.markdown("---")
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+
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+ # 初始化session state
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+ if 'validator' not in st.session_state:
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+ st.session_state.validator = StreamlitOCRValidator()
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+
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+ if 'selected_text' not in st.session_state:
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+ st.session_state.selected_text = None
|
|
|
+
|
|
|
+ if 'marked_errors' not in st.session_state:
|
|
|
+ st.session_state.marked_errors = set()
|
|
|
+
|
|
|
+ # 同步标记的错误到validator
|
|
|
+ st.session_state.validator.marked_errors = st.session_state.marked_errors
|
|
|
+
|
|
|
+ # 侧边栏 - 文件选择和控制
|
|
|
+ with st.sidebar:
|
|
|
+ st.header("📁 文件选择")
|
|
|
+
|
|
|
+ # 查找可用的OCR文件
|
|
|
+ output_dir = Path("output")
|
|
|
+ available_files = []
|
|
|
+
|
|
|
+ if output_dir.exists():
|
|
|
+ for json_file in output_dir.rglob("*.json"):
|
|
|
+ available_files.append(str(json_file))
|
|
|
+
|
|
|
+ if available_files:
|
|
|
+ selected_file = st.selectbox(
|
|
|
+ "选择OCR结果文件",
|
|
|
+ available_files,
|
|
|
+ index=0
|
|
|
+ )
|
|
|
+
|
|
|
+ if st.button("🔄 加载文件", type="primary") and selected_file:
|
|
|
+ try:
|
|
|
+ st.session_state.validator.load_ocr_data(selected_file)
|
|
|
+ st.success("✅ 文件加载成功！")
|
|
|
+ st.rerun() # 重新运行应用以更新界面
|
|
|
+ except Exception as e:
|
|
|
+ st.error(f"❌ 加载失败: {e}")
|
|
|
+ else:
|
|
|
+ st.warning("未找到OCR结果文件")
|
|
|
+ st.info("请确保output目录下有OCR结果文件")
|
|
|
+
|
|
|
+ st.markdown("---")
|
|
|
+
|
|
|
+ # 控制面板
|
|
|
+ st.header("🎛️ 控制面板")
|
|
|
+
|
|
|
+ if st.button("🧹 清除选择"):
|
|
|
+ st.session_state.selected_text = None
|
|
|
+ st.rerun()
|
|
|
+
|
|
|
+ if st.button("❌ 清除错误标记"):
|
|
|
+ st.session_state.marked_errors = set()
|
|
|
+ st.rerun()
|
|
|
+
|
|
|
+ # 显示调试信息
|
|
|
+ if st.checkbox("🔧 调试信息"):
|
|
|
+ st.write("**当前状态:**")
|
|
|
+ st.write(f"- OCR数据项数: {len(st.session_state.validator.ocr_data)}")
|
|
|
+ st.write(f"- 可点击文本: {len(st.session_state.validator.text_bbox_mapping)}")
|
|
|
+ st.write(f"- 选中文本: {st.session_state.selected_text}")
|
|
|
+ st.write(f"- 标记错误数: {len(st.session_state.marked_errors)}")
|
|
|
+
|
|
|
+ if st.session_state.validator.ocr_data:
|
|
|
+ st.write("**数据类型检查:**")
|
|
|
+ sample_item = st.session_state.validator.ocr_data[0] if st.session_state.validator.ocr_data else None
|
|
|
+ st.write(f"- 第一项类型: {type(sample_item)}")
|
|
|
+ if isinstance(sample_item, dict):
|
|
|
+ st.write(f"- 第一项键: {list(sample_item.keys())}")
|
|
|
+
|
|
|
+ # 主内容区域
|
|
|
+ if not st.session_state.validator.ocr_data:
|
|
|
+ st.info("👈 请在左侧选择并加载OCR结果文件")
|
|
|
+ return
|
|
|
+
|
|
|
+ # 显示统计信息
|
|
|
+ try:
|
|
|
+ stats = st.session_state.validator.get_statistics()
|
|
|
+
|
|
|
+ col1, col2, col3, col4 = st.columns(4)
|
|
|
+ with col1:
|
|
|
+ st.metric("📊 总文本块", stats['total_texts'])
|
|
|
+ with col2:
|
|
|
+ st.metric("🔗 可点击文本", stats['clickable_texts'])
|
|
|
+ with col3:
|
|
|
+ st.metric("❌ 标记错误", stats['marked_errors'])
|
|
|
+ with col4:
|
|
|
+ st.metric("✅ 准确率", f"{stats['accuracy_rate']:.1f}%")
|
|
|
+
|
|
|
+ st.markdown("---")
|
|
|
+ except Exception as e:
|
|
|
+ st.error(f"❌ 统计信息计算失败: {e}")
|
|
|
+ return
|
|
|
+
|
|
|
+ # 主要布局 - 左右分栏
|
|
|
+ left_col, right_col = st.columns([1, 1])
|
|
|
+
|
|
|
+ # 左侧 - OCR文本内容
|
|
|
+ with left_col:
|
|
|
+ st.header("📄 OCR识别内容")
|
|
|
+
|
|
|
+ # 文本选择器
|
|
|
+ if st.session_state.validator.text_bbox_mapping:
|
|
|
+ text_options = ["请选择文本..."] + list(st.session_state.validator.text_bbox_mapping.keys())
|
|
|
+ selected_index = st.selectbox(
|
|
|
+ "选择要校验的文本",
|
|
|
+ range(len(text_options)),
|
|
|
+ format_func=lambda x: text_options[x],
|
|
|
+ key="text_selector"
|
|
|
+ )
|
|
|
+
|
|
|
+ if selected_index > 0:
|
|
|
+ st.session_state.selected_text = text_options[selected_index]
|
|
|
+ else:
|
|
|
+ st.warning("没有找到可点击的文本")
|
|
|
+
|
|
|
+ # 显示MD内容（可搜索和过滤）
|
|
|
+ if st.session_state.validator.md_content:
|
|
|
+ search_term = st.text_input("🔍 搜索文本内容", placeholder="输入关键词搜索...")
|
|
|
+
|
|
|
+ display_content = st.session_state.validator.md_content
|
|
|
+ if search_term:
|
|
|
+ lines = display_content.split('\n')
|
|
|
+ filtered_lines = [line for line in lines if search_term.lower() in line.lower()]
|
|
|
+ display_content = '\n'.join(filtered_lines)
|
|
|
+ if filtered_lines:
|
|
|
+ st.success(f"找到 {len(filtered_lines)} 行包含 '{search_term}'")
|
|
|
+ else:
|
|
|
+ st.warning(f"未找到包含 '{search_term}' 的内容")
|
|
|
+
|
|
|
+ # 渲染方式选择
|
|
|
+ render_mode = st.radio(
|
|
|
+ "选择渲染方式",
|
|
|
+ ["HTML渲染", "Markdown渲染", "DataFrame表格", "原始文本"], # 添加DataFrame选项
|
|
|
+ horizontal=True
|
|
|
+ )
|
|
|
+
|
|
|
+ if render_mode == "HTML渲染":
|
|
|
+ # 使用unsafe_allow_html=True来渲染HTML表格
|
|
|
+ st.markdown(display_content, unsafe_allow_html=True)
|
|
|
+ elif render_mode == "Markdown渲染":
|
|
|
+ # 转换HTML表格为Markdown格式
|
|
|
+ converted_content = st.session_state.validator.convert_html_table_to_markdown(display_content)
|
|
|
+ st.markdown(converted_content)
|
|
|
+ elif render_mode == "DataFrame表格":
|
|
|
+ # 新增：使用DataFrame显示表格
|
|
|
+ if '<table>' in display_content.lower():
|
|
|
+ st.session_state.validator.display_html_table_as_dataframe(display_content)
|
|
|
+ else:
|
|
|
+ st.info("当前内容中没有检测到HTML表格")
|
|
|
+ st.markdown(display_content)
|
|
|
+ else:
|
|
|
+ # 原始文本显示
|
|
|
+ st.text_area(
|
|
|
+ "MD内容预览",
|
|
|
+ display_content,
|
|
|
+ height=300,
|
|
|
+ help="OCR识别的文本内容"
|
|
|
+ )
|
|
|
+
|
|
|
+ # 可点击文本列表
|
|
|
+ st.subheader("🎯 可点击文本列表")
|
|
|
+
|
|
|
+ if st.session_state.validator.text_bbox_mapping:
|
|
|
+ for text, info_list in st.session_state.validator.text_bbox_mapping.items():
|
|
|
+ info = info_list[0] # 使用第一个bbox信息
|
|
|
+
|
|
|
+ # 确定显示样式
|
|
|
+ is_selected = (text == st.session_state.selected_text)
|
|
|
+ is_error = (text in st.session_state.marked_errors)
|
|
|
+
|
|
|
+ # 创建按钮行
|
|
|
+ button_col, error_col = st.columns([4, 1])
|
|
|
+
|
|
|
+ with button_col:
|
|
|
+ button_type = "primary" if is_selected else "secondary"
|
|
|
+ if st.button(f"📍 {text}", key=f"btn_{text}", type=button_type):
|
|
|
+ st.session_state.selected_text = text
|
|
|
+ st.rerun()
|
|
|
+
|
|
|
+ with error_col:
|
|
|
+ if is_error:
|
|
|
+ if st.button("✅", key=f"fix_{text}", help="取消错误标记"):
|
|
|
+ st.session_state.marked_errors.discard(text)
|
|
|
+ st.rerun()
|
|
|
+ else:
|
|
|
+ if st.button("❌", key=f"error_{text}", help="标记为错误"):
|
|
|
+ st.session_state.marked_errors.add(text)
|
|
|
+ st.rerun()
|
|
|
+ else:
|
|
|
+ st.info("没有可点击的文本项目")
|
|
|
+
|
|
|
+ # 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']
|
|
|
+
|
|
|
+ fig = st.session_state.validator.create_interactive_plot(image, selected_bbox)
|
|
|
+ st.plotly_chart(fig, use_container_width=True)
|
|
|
+
|
|
|
+ # 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")
|
|
|
+
|
|
|
+ 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}")
|
|
|
+ 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}")
|
|
|
+
|
|
|
+if __name__ == "__main__":
|
|
|
+ main()
|
