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@@ -1,16 +1,90 @@
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import re
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import os
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from pathlib import Path
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+from decimal import Decimal, InvalidOperation
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+
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+
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+def _normalize_amount_token(token: str) -> str:
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+ """
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+ 规范单个金额 token 中逗号/小数点的用法。
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+ 仅在形态明显为金额时进行纠错，其他情况原样返回。
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+ """
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+ if not token:
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+ return token
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+
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+ # 只处理包含数字的简单 token，避免带字母/其他符号的误改
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+ if not re.fullmatch(r"[+-]?\d[\d,\.]*\d", token):
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+ return token
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+
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+ sign = ""
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+ core = token
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+ if core[0] in "+-":
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+ sign, core = core[0], core[1:]
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+
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+ has_dot = "." in core
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+ has_comma = "," in core
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+
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+ # 辅助: 尝试解析为 Decimal；失败则认为不安全，回退原值
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+ def _safe_decimal(s: str) -> bool:
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+ try:
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+ Decimal(s.replace(",", ""))
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+ return True
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+ except (InvalidOperation, ValueError):
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+ return False
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+
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+ # 规则A：同时包含 . 和 ,，最后一个分隔符是逗号，且其后为 1-2 位数字
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+ if has_dot and has_comma:
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+ last_comma = core.rfind(",")
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+ last_dot = core.rfind(".")
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+ if last_comma > last_dot and last_comma != -1:
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+ frac = core[last_comma + 1 :]
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+ if 1 <= len(frac) <= 2 and frac.isdigit():
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+ # 先把所有点当作千分位逗号，再把最后一个逗号当作小数点
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+ temp = core.replace(".", ",")
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+ idx = temp.rfind(",")
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+ if idx != -1:
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+ candidate = temp[:idx] + "." + temp[idx + 1 :]
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+ if _safe_decimal(candidate):
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+ return sign + candidate
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+
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+ # 规则B：只有 .，多个点，最后一段视为小数，其余为千分位
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+ if has_dot and not has_comma:
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+ parts = core.split(".")
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+ if len(parts) >= 3:
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+ last = parts[-1]
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+ ints = parts[:-1]
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+ if 1 <= len(last) <= 2 and all(len(p) == 3 for p in ints[1:]):
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+ candidate = ",".join(ints) + "." + last
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+ if _safe_decimal(candidate):
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+ return sign + candidate
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+
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+ # 规则C：只有 ,，多个逗号，最后一段长度为 1-2 且前面为 3 位分组
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+ if has_comma and not has_dot:
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+ parts = core.split(",")
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+ if len(parts) >= 3:
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+ last = parts[-1]
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+ ints = parts[:-1]
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+ if 1 <= len(last) <= 2 and all(len(p) == 3 for p in ints[1:]):
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+ # 将最后一个逗号视为小数点
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+ idx = core.rfind(",")
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+ candidate = core[:idx] + "." + core[idx + 1 :]
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+ if _safe_decimal(candidate):
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+ return sign + candidate
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+ # 规则D：只有 ,，且仅有一个逗号、逗号后 1-2 位数字 → 欧洲格式小数，如 301,55 → 301.55
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+ elif len(parts) == 2:
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+ left, right = parts[0], parts[1]
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+ if 1 <= len(right) <= 2 and right.isdigit() and left.isdigit():
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+ candidate = left + "." + right
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+ if _safe_decimal(candidate):
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+ return sign + candidate
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+
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+ # 没有需要纠错的典型形态，直接返回原 token
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+ return token
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+
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def normalize_financial_numbers(text: str) -> str:
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"""
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- 标准化财务数字：将全角字符转换为半角字符
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-
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- Args:
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- text: 原始文本
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-
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- Returns:
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- 标准化后的文本
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+ 标准化财务数字：将全角字符转换为半角字符，并纠正常见的逗号/小数点错用。
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"""
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if not text:
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return text
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@@ -31,30 +105,30 @@ def normalize_financial_numbers(text: str) -> str:
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'％': '%', # 全角百分号转半角百分号
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}
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- # 第一步：执行基础字符替换
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+ # 第一步：执行基础字符替换（全角 -> 半角）
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normalized_text = text
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for fullwidth, halfwidth in fullwidth_to_halfwidth.items():
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normalized_text = normalized_text.replace(fullwidth, halfwidth)
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- # 第二步：处理数字序列中的空格和分隔符
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- # 修改正则表达式以匹配完整的数字序列，包括空格
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- # 匹配模式：数字 + (空格? + 逗号 + 空格? + 数字)* + (空格? + 小数点 + 数字+)?
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+ # 第二步：处理数字序列中的空格和分隔符（保留原有逻辑）
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number_sequence_pattern = r'(\d+(?:\s*[，,]\s*\d+)*(?:\s*[。．.]\s*\d+)?)'
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def normalize_number_sequence(match):
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sequence = match.group(1)
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-
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- # 处理千分位分隔符周围的空格
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- # 将 "数字 + 空格 + 逗号 + 空格 + 数字" 标准化为 "数字,数字"
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sequence = re.sub(r'(\d)\s*[，,]\s*(\d)', r'\1,\2', sequence)
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-
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- # 处理小数点周围的空格
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- # 将 "数字 + 空格 + 小数点 + 空格 + 数字" 标准化为 "数字.数字"
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sequence = re.sub(r'(\d)\s*[。．.]\s*(\d)', r'\1.\2', sequence)
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-
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return sequence
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normalized_text = re.sub(number_sequence_pattern, normalize_number_sequence, normalized_text)
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+
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+ # 第三步：对疑似金额 token 做逗号/小数点纠错
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+ amount_pattern = r'(?P<tok>[+-]?\d[\d,\.]*\d)'
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+
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+ def _amount_sub(m: re.Match) -> str:
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+ tok = m.group('tok')
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+ return _normalize_amount_token(tok)
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+
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+ normalized_text = re.sub(amount_pattern, _amount_sub, normalized_text)
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return normalized_text
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def normalize_markdown_table(markdown_content: str) -> str:
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@@ -78,7 +152,7 @@ def normalize_markdown_table(markdown_content: str) -> str:
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table_pattern = r'(<table[^>]*>.*?</table>)'
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def normalize_table_match(match):
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- """处理单个表格匹配，保留原始格式"""
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+ """处理单个表格匹配，保留原始格式，并追加数字标准化说明注释。"""
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table_html = match.group(1)
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original_table_html = table_html # 保存原始HTML用于比较
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@@ -86,133 +160,163 @@ def normalize_markdown_table(markdown_content: str) -> str:
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soup = BeautifulSoup(table_html, 'html.parser')
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tables = soup.find_all('table')
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- # 记录所有需要替换的文本（原始文本 -> 标准化文本）
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- replacements = []
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+ # 记录本表格中所有数值修改
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+ changes: list[dict] = []
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for table in tables:
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- if isinstance(table, Tag):
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- cells = table.find_all(['td', 'th'])
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- for cell in cells:
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- if isinstance(cell, Tag):
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- # 获取单元格的纯文本内容
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- original_text = cell.get_text()
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- normalized_text = normalize_financial_numbers(original_text)
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-
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- # 如果内容发生了变化，记录替换
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- if original_text != normalized_text:
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- # 找到单元格中所有文本节点并替换
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- from bs4.element import NavigableString
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- for text_node in cell.find_all(string=True, recursive=True):
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- if isinstance(text_node, NavigableString):
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- text_str = str(text_node)
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- if text_str.strip():
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- normalized = normalize_financial_numbers(text_str.strip())
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- if normalized != text_str.strip():
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- # 保留原始文本节点的前后空白
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- if text_str.strip() == text_str:
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- # 纯文本节点，直接替换
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- text_node.replace_with(normalized)
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- else:
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- # 有前后空白，需要保留
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- leading_ws = text_str[:len(text_str) - len(text_str.lstrip())]
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- trailing_ws = text_str[len(text_str.rstrip()):]
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- text_node.replace_with(leading_ws + normalized + trailing_ws)
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+ if not isinstance(table, Tag):
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+ continue
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+ # 通过 tr / td(th) 计算行列位置
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+ for row_idx, tr in enumerate(table.find_all('tr')): # type: ignore[reportAttributeAccessIssue]
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+ cells = tr.find_all(['td', 'th']) # type: ignore[reportAttributeAccessIssue]
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+ for col_idx, cell in enumerate(cells):
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+ if not isinstance(cell, Tag):
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+ continue
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+ # 与 normalize_json_table 一致：整格取文本、只标准化一次、再写回
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+ original_text = cell.get_text()
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+ normalized_text = normalize_financial_numbers(original_text)
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+ if original_text == normalized_text:
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+ continue
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+ # 记录一条修改
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+ changes.append(
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+ {
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+ "row": row_idx,
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+ "col": col_idx,
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+ "old": original_text,
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+ "new": normalized_text,
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+ }
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+ )
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+ # 整格替换为标准化后的文本（与 normalize_json_table 的 cell.string = normalized_text 一致）
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+ cell.string = normalized_text
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+
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+ # 如果没有任何数值修改，直接返回原始 HTML
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+ if not changes:
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+ return original_table_html
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# 获取修改后的HTML
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modified_html = str(soup)
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- # 如果内容没有变化，返回原始HTML（保持原始格式）
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- # 检查是否只是格式变化（换行、空格等）
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- original_text_only = re.sub(r'\s+', '', original_table_html)
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- modified_text_only = re.sub(r'\s+', '', modified_html)
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+ # 在表格后追加注释，说明哪些单元格被修改
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+ lines = ["<!-- 数字标准化说明："]
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+ for ch in changes:
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+ lines.append(
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+ f" - [row={ch['row']},col={ch['col']}] {ch['old']} -> {ch['new']}"
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+ )
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+ lines.append("-->")
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+ comment = "\n".join(lines)
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- if original_text_only == modified_text_only:
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- # 只有格式变化，返回原始HTML以保留换行符
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- return original_table_html
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-
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- # 有实际内容变化，返回修改后的HTML
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- return modified_html
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+ return modified_html + "\n\n" + comment
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# 使用正则替换，只替换表格内容，保留其他部分（包括换行符）不变
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normalized_content = re.sub(table_pattern, normalize_table_match, markdown_content, flags=re.DOTALL)
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return normalized_content
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-def normalize_json_table(json_content: str) -> str:
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+def normalize_json_table(
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+ json_content: str,
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+ *,
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+ table_type_key: str = "category",
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+ table_type_value: str = "Table",
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+ html_key: str = "text",
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+ cells_key: str | None = None,
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+) -> str:
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"""
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- 专门处理JSON格式OCR结果中表格的数字标准化
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-
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+ 专门处理JSON格式OCR结果中表格的数字标准化。
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+ 通过参数指定提取用的 key，以兼容不同 OCR 工具的 JSON 结构。
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+
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Args:
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- json_content: JSON格式的OCR结果内容
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-
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+ json_content: JSON格式的OCR结果内容（字符串或已解析的 list）
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+ table_type_key: 用于判断“是否为表格”的字段名，如 "type" 或 "category"
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+ table_type_value: 上述字段等于该值时视为表格，如 "table" 或 "Table"
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+ html_key: 存放表格 HTML 的字段名，如 "table_body" 或 "text"
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+ cells_key: 存放单元格列表的字段名，如 "table_cells"；为 None 则不处理 cells，
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+ 仅标准化 html_key 中的表格
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+
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Returns:
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- 标准化后的JSON内容
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- """
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- """
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- json_content 示例:
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- [
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- {
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- "category": "Table",
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- "text": "<table>...</table>"
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- },
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- {
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- "category": "Text",
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- "text": "Some other text"
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- }
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- ]
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+ 标准化后的JSON内容（字符串）
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+
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+ 常见格式示例:
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+ - 旧格式: category="Table", html 在 "text"
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+ normalize_json_table(s) # 默认即此
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+ - mineru_vllm_results_cell_bbox: type="table", html 在 "table_body", cells 在 "table_cells"
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+ normalize_json_table(s, table_type_key="type", table_type_value="table",
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+ html_key="table_body", cells_key="table_cells")
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"""
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import json
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-
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+ from ast import literal_eval
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+
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try:
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- # 解析JSON内容
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data = json.loads(json_content) if isinstance(json_content, str) else json_content
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-
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- # 确保data是列表格式
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if not isinstance(data, list):
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return json_content
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-
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- # 遍历所有OCR结果项
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+
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for item in data:
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if not isinstance(item, dict):
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continue
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-
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- # 检查是否是表格类型
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- if item.get('category') == 'Table' and 'text' in item:
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- table_html = item['text']
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-
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- # 使用BeautifulSoup处理HTML表格
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- from bs4 import BeautifulSoup, Tag
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-
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- soup = BeautifulSoup(table_html, 'html.parser')
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- tables = soup.find_all('table')
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-
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- for table in tables:
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- if isinstance(table, Tag):
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- cells = table.find_all(['td', 'th'])
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- for cell in cells:
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- if isinstance(cell, Tag):
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- original_text = cell.get_text()
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-
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- # 应用数字标准化
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- normalized_text = normalize_financial_numbers(original_text)
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-
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- # 如果内容发生了变化，更新单元格内容
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- if original_text != normalized_text:
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- cell.string = normalized_text
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-
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- # 更新item中的表格内容
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- item['text'] = str(soup)
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-
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- # 同时标准化普通文本中的数字（如果需要）
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- # elif 'text' in item:
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- # original_text = item['text']
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- # normalized_text = normalize_financial_numbers(original_text)
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- # if original_text != normalized_text:
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- # item['text'] = normalized_text
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-
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- # 返回标准化后的JSON字符串
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+ # 按参数判断是否为表格项，且包含 HTML
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+ if item.get(table_type_key) != table_type_value or html_key not in item:
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+ continue
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+
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+ table_html = item[html_key]
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+ if not table_html or not isinstance(table_html, str):
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+ continue
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+
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+ from bs4 import BeautifulSoup, Tag
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+
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+ soup = BeautifulSoup(table_html, "html.parser")
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+ tables = soup.find_all("table")
|
|
|
+ table_changes: list[dict] = []
|
|
|
+
|
|
|
+ for table in tables:
|
|
|
+ if not isinstance(table, Tag):
|
|
|
+ continue
|
|
|
+ for row_idx, tr in enumerate(table.find_all("tr")): # type: ignore[reportAttributeAccessIssue]
|
|
|
+ cells_tag = tr.find_all(["td", "th"]) # type: ignore[reportAttributeAccessIssue]
|
|
|
+ for col_idx, cell in enumerate(cells_tag):
|
|
|
+ if not isinstance(cell, Tag):
|
|
|
+ continue
|
|
|
+ original_text = cell.get_text()
|
|
|
+ normalized_text = normalize_financial_numbers(original_text)
|
|
|
+ if original_text == normalized_text:
|
|
|
+ continue
|
|
|
+ change: dict[str, object] = {
|
|
|
+ "row": row_idx,
|
|
|
+ "col": col_idx,
|
|
|
+ "old": original_text,
|
|
|
+ "new": normalized_text,
|
|
|
+ }
|
|
|
+ bbox_attr = cell.get("data-bbox")
|
|
|
+ if isinstance(bbox_attr, str):
|
|
|
+ try:
|
|
|
+ change["bbox"] = literal_eval(bbox_attr)
|
|
|
+ except Exception:
|
|
|
+ change["bbox"] = bbox_attr
|
|
|
+ table_changes.append(change)
|
|
|
+ cell.string = normalized_text
|
|
|
+
|
|
|
+ # 写回 HTML
|
|
|
+ item[html_key] = str(soup)
|
|
|
+ if table_changes:
|
|
|
+ item["number_normalization_changes"] = table_changes
|
|
|
+
|
|
|
+ # 若指定了 cells_key，同时标准化 cells 中每格的 text（及 matched_text）
|
|
|
+ # for key in ("text", "matched_text"):
|
|
|
+ table_cell_text_keys = ["text"]
|
|
|
+ if cells_key and cells_key in item and isinstance(item[cells_key], list):
|
|
|
+ for cell in item[cells_key]:
|
|
|
+ if not isinstance(cell, dict):
|
|
|
+ continue
|
|
|
+
|
|
|
+ for key in table_cell_text_keys:
|
|
|
+ if key not in cell or not isinstance(cell[key], str):
|
|
|
+ continue
|
|
|
+ orig = cell[key]
|
|
|
+ norm = normalize_financial_numbers(orig)
|
|
|
+ if norm != orig:
|
|
|
+ cell[key] = norm
|
|
|
+
|
|
|
return json.dumps(data, ensure_ascii=False, indent=2)
|
|
|
-
|
|
|
+
|
|
|
except json.JSONDecodeError as e:
|
|
|
print(f"⚠️ JSON解析失败: {e}")
|
|
|
return json_content
|
|
|
@@ -220,31 +324,48 @@ def normalize_json_table(json_content: str) -> str:
|
|
|
print(f"⚠️ JSON表格标准化失败: {e}")
|
|
|
return json_content
|
|
|
|
|
|
-def normalize_json_file(file_path: str, output_path: str | None = None) -> str:
|
|
|
+def normalize_json_file(
|
|
|
+ file_path: str,
|
|
|
+ output_path: str | None = None,
|
|
|
+ *,
|
|
|
+ table_type_key: str = "category",
|
|
|
+ table_type_value: str = "Table",
|
|
|
+ html_key: str = "text",
|
|
|
+ cells_key: str | None = None,
|
|
|
+) -> str:
|
|
|
"""
|
|
|
- 标准化JSON文件中的表格数字
|
|
|
-
|
|
|
+ 标准化JSON文件中的表格数字。
|
|
|
+ 提取表格时使用的 key 可通过参数指定，以兼容不同 OCR 工具。
|
|
|
+
|
|
|
Args:
|
|
|
file_path: 输入JSON文件路径
|
|
|
output_path: 输出文件路径，如果为None则覆盖原文件
|
|
|
-
|
|
|
+ table_type_key: 判断表格的字段名（见 normalize_json_table）
|
|
|
+ table_type_value: 判断表格的字段值
|
|
|
+ html_key: 表格 HTML 所在字段名
|
|
|
+ cells_key: 单元格列表所在字段名，None 表示不处理 cells
|
|
|
+
|
|
|
Returns:
|
|
|
标准化后的JSON内容
|
|
|
"""
|
|
|
input_file = Path(file_path)
|
|
|
output_file = Path(output_path) if output_path else input_file
|
|
|
-
|
|
|
+
|
|
|
if not input_file.exists():
|
|
|
raise FileNotFoundError(f"找不到文件: {file_path}")
|
|
|
-
|
|
|
- # 读取原始JSON文件
|
|
|
- with open(input_file, 'r', encoding='utf-8') as f:
|
|
|
+
|
|
|
+ with open(input_file, "r", encoding="utf-8") as f:
|
|
|
original_content = f.read()
|
|
|
-
|
|
|
+
|
|
|
print(f"🔧 正在标准化JSON文件: {input_file.name}")
|
|
|
-
|
|
|
- # 标准化内容
|
|
|
- normalized_content = normalize_json_table(original_content)
|
|
|
+
|
|
|
+ normalized_content = normalize_json_table(
|
|
|
+ original_content,
|
|
|
+ table_type_key=table_type_key,
|
|
|
+ table_type_value=table_type_value,
|
|
|
+ html_key=html_key,
|
|
|
+ cells_key=cells_key,
|
|
|
+ )
|
|
|
|
|
|
# 保存标准化后的文件
|
|
|
with open(output_file, 'w', encoding='utf-8') as f:
|
|
|
@@ -266,4 +387,51 @@ def normalize_json_file(file_path: str, output_path: str | None = None) -> str:
|
|
|
|
|
|
print(f"📄 标准化结果已保存到: {output_file}")
|
|
|
return normalized_content
|
|
|
+
|
|
|
+
|
|
|
+if __name__ == "__main__":
|
|
|
+ """
|
|
|
+ 简单验证：构造一份“故意打乱逗号/小数点”的 JSON / Markdown 示例，
|
|
|
+ 并打印标准化前后的差异。
|
|
|
+ """
|
|
|
+ import json
|
|
|
+
|
|
|
+ print("=== JSON 示例：金额格式纠错 + 变更记录 ===")
|
|
|
+ demo_json_data = [
|
|
|
+ {
|
|
|
+ "category": "Table",
|
|
|
+ "text": (
|
|
|
+ "<table><tbody>"
|
|
|
+ "<tr><td data-bbox=\"[0,0,10,10]\">项目</td>"
|
|
|
+ "<td data-bbox=\"[10,0,20,10]\">2023 年12 月31 日</td></tr>"
|
|
|
+ # 故意打乱的数字：应为 12,123,456.00 和 1,234,567.89
|
|
|
+ "<tr><td data-bbox=\"[0,10,10,20]\">测试金额A</td>"
|
|
|
+ "<td data-bbox=\"[10,10,20,20]\">12.123,456,00</td></tr>"
|
|
|
+ "<tr><td data-bbox=\"[0,20,10,30]\">测试金额B</td>"
|
|
|
+ "<td data-bbox=\"[10,20,20,30]\">1,234,567,89</td></tr>"
|
|
|
+ "<tr><td data-bbox=\"[0,20,10,40]\">测试金额C</td>"
|
|
|
+ "<td data-bbox=\"[10,20,20,40]\">301,55</td></tr>"
|
|
|
+ "</tbody></table>"
|
|
|
+ ),
|
|
|
+ }
|
|
|
+ ]
|
|
|
+ demo_json_str = json.dumps(demo_json_data, ensure_ascii=False, indent=2)
|
|
|
+ print("原始 JSON：")
|
|
|
+ print(demo_json_str)
|
|
|
+ normalized_json_str = normalize_json_table(demo_json_str)
|
|
|
+ print("\n标准化后 JSON：")
|
|
|
+ print(normalized_json_str)
|
|
|
|
|
|
+ print("\n=== Markdown 示例：金额格式纠错 + 注释说明 ===")
|
|
|
+ demo_md = """<table><tbody>
|
|
|
+<tr><td>项目</td><td>2023 年12 月31 日</td></tr>
|
|
|
+<tr><td>测试金额A</td><td>12.123,456,00</td></tr>
|
|
|
+<tr><td>测试金额B</td><td>1,234,567,89</td></tr>
|
|
|
+<tr><td>测试金额C</td><td>301,55</td></tr>
|
|
|
+</tbody></table>
|
|
|
+"""
|
|
|
+ print("原始 Markdown：")
|
|
|
+ print(demo_md)
|
|
|
+ normalized_md = normalize_markdown_table(demo_md)
|
|
|
+ print("\n标准化后 Markdown：")
|
|
|
+ print(normalized_md)
|
zhch158_admin