mirror of
https://github.com/yejinlei/pdf-ocr-skill.git
synced 2026-09-19 06:03:41 +08:00
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653 lines
23 KiB
Python
653 lines
23 KiB
Python
#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""
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PDF OCR处理脚本
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支持两种OCR引擎：
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1. 硅基流动大模型API（云端）
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2. RapidOCR（本地，无需API）
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支持自动安装缺失的依赖
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"""
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import os
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import sys
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import base64
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import requests
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import subprocess
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from typing import Dict, Any, List, Optional
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from dotenv import load_dotenv
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# 加载环境变量
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load_dotenv()
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def install_dependency(package):
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"""自动安装缺失的依赖"""
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print(f"正在安装依赖: {package}")
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try:
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subprocess.check_call([sys.executable, "-m", "pip", "install", package])
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print(f"依赖 {package} 安装成功")
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return True
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except subprocess.CalledProcessError as e:
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print(f"依赖 {package} 安装失败: {e}")
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return False
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class RapidOCREngine:
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"""RapidOCR本地OCR引擎"""
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def __init__(self):
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self.ocr = None
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self._init_engine()
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def _init_engine(self):
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"""初始化RapidOCR引擎"""
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try:
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from rapidocr_onnxruntime import RapidOCR
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self.ocr = RapidOCR()
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except ImportError:
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print("RapidOCR依赖未安装，正在尝试自动安装...")
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if install_dependency("rapidocr_onnxruntime"):
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try:
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from rapidocr_onnxruntime import RapidOCR
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self.ocr = RapidOCR()
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except ImportError:
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raise Exception("RapidOCR依赖安装失败，请手动安装: pip install rapidocr_onnxruntime")
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else:
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raise Exception("RapidOCR依赖安装失败，请手动安装: pip install rapidocr_onnxruntime")
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def recognize(self, image_path: str) -> str:
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"""识别单张图片"""
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if self.ocr is None:
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raise Exception("RapidOCR引擎未初始化")
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result, _ = self.ocr(image_path)
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if not result:
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return ""
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# 提取文本
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texts = []
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for line in result:
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if len(line) >= 2:
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texts.append(line[1])
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return "\n".join(texts)
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class PaddleOCREngine:
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"""PaddleOCR本地OCR引擎"""
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def __init__(self):
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self.ocr = None
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self._init_engine()
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def _init_engine(self):
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"""初始化PaddleOCR引擎"""
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try:
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from paddleocr import PaddleOCR
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# 使用PP-OCRv5模型
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print("正在初始化PaddleOCR引擎...")
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self.ocr = PaddleOCR(use_textline_orientation=True, lang='ch')
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print("PaddleOCR引擎初始化成功")
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except ImportError as e:
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print(f"PaddleOCR导入失败: {e}")
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print("PaddleOCR依赖未安装，正在尝试自动安装...")
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if install_dependency("paddleocr"):
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try:
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from paddleocr import PaddleOCR
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# 使用PP-OCRv5模型
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print("正在初始化PaddleOCR引擎...")
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self.ocr = PaddleOCR(use_textline_orientation=True, lang='ch')
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print("PaddleOCR引擎初始化成功")
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except ImportError as e:
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print(f"PaddleOCR导入失败: {e}")
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raise Exception("PaddleOCR依赖安装失败，请手动安装: pip install paddleocr")
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else:
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raise Exception("PaddleOCR依赖安装失败，请手动安装: pip install paddleocr")
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except Exception as e:
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print(f"PaddleOCR初始化失败: {e}")
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raise
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def recognize(self, image_path: str) -> str:
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"""识别单张图片"""
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if self.ocr is None:
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raise Exception("PaddleOCR引擎未初始化")
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result = self.ocr.predict(image_path)
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if not result:
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return ""
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# 提取文本
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texts = []
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for page in result:
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for line in page:
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if len(line) >= 2:
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texts.append(line[1][0])
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return "\n".join(texts)
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class SiliconFlowOCREngine:
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"""硅基流动API OCR引擎"""
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def __init__(self, api_key: str = "", model: str = "deepseek-ai/DeepSeek-OCR"):
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self.api_key = api_key or os.getenv("SILICON_FLOW_API_KEY", "")
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self.model = model or os.getenv("SILICON_FLOW_OCR_MODEL", "deepseek-ai/DeepSeek-OCR")
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self.base_url = "https://api.siliconflow.cn/v1/chat/completions"
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self.headers = {
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"Content-Type": "application/json",
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"Authorization": f"Bearer {self.api_key}"
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}
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def recognize(self, image_base64: str, page_num: int = 1) -> str:
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"""使用硅基流动大模型识别单张图片"""
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prompt = f"""请仔细识别这张图片中的所有文字内容。
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这是第 {page_num} 页的内容。
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要求：
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1. 完整提取所有可见文字
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2. 保持文字的顺序和结构
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3. 识别中文和英文
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4. 输出纯文本格式，不要添加任何额外说明
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请直接输出识别的文字内容："""
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payload = {
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"model": self.model,
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"messages": [
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{
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"role": "user",
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"content": [
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{
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"type": "text",
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"text": prompt
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},
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{
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"type": "image_url",
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"image_url": {
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"url": f"data:image/png;base64,{image_base64}"
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}
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}
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]
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}
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],
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"temperature": 0.1,
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"max_tokens": 4000
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}
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try:
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response = requests.post(
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self.base_url,
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headers=self.headers,
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json=payload,
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timeout=120
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)
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response.raise_for_status()
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return response.json()["choices"][0]["message"]["content"].strip()
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except Exception as e:
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return f"【OCR识别失败: {str(e)}】"
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class RapidDocEngine:
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"""RapidDoc增强OCR引擎"""
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def __init__(self):
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self.doc = None
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self._init_engine()
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def _init_engine(self):
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"""初始化RapidDoc引擎"""
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try:
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from rapid_doc import RapidDoc
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self.doc = RapidDoc()
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except ImportError:
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print("RapidDoc依赖未安装，正在尝试自动安装...")
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if install_dependency("rapid-doc"):
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try:
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from rapid_doc import RapidDoc
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self.doc = RapidDoc()
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except ImportError:
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raise Exception("RapidDoc依赖安装失败，请手动安装: pip install rapid-doc")
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else:
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raise Exception("RapidDoc依赖安装失败，请手动安装: pip install rapid-doc")
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def recognize(self, file_path: str) -> Dict[str, Any]:
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"""识别PDF或图片文件
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Args:
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file_path: PDF或图片文件路径
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Returns:
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包含text和markdown的字典
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"""
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if self.doc is None:
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raise Exception("RapidDoc引擎未初始化")
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# 处理文件
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result = self.doc(file_path)
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# 提取文本内容（去除Markdown格式）
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import re
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text_content = re.sub(r'!\[.*?\]\(.*?\)', '', result.markdown) # 移除图片
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text_content = re.sub(r'\|.*?\|', '', text_content) # 移除表格
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text_content = re.sub(r'#+', '', text_content) # 移除标题
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text_content = '\n'.join([line.strip() for line in text_content.split('\n') if line.strip()]) # 清理空行
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return {
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"text": text_content,
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"markdown": result.markdown,
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"images_count": len(result.images)
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}
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class PDFOCRProcessor:
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"""PDF OCR处理器 - 支持多种OCR引擎"""
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def __init__(self, engine: Optional[str] = None):
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"""
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初始化PDF OCR处理器
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Args:
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engine: OCR引擎类型，可选值：
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- "rapid": 使用RapidOCR本地引擎（默认，无需API）
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- "rapidoc": 使用RapidDoc增强引擎
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- "paddle": 使用PaddleOCR本地引擎
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- "siliconflow": 使用硅基流动API引擎
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- None: 从环境变量 OCR_ENGINE 读取，默认为 "rapid"
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"""
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self.engine_type = engine or os.getenv("OCR_ENGINE", "rapid")
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self.rapid_engine: Optional[RapidOCREngine] = None
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self.rapidoc_engine: Optional[RapidDocEngine] = None
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self.paddle_engine: Optional[PaddleOCREngine] = None
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self.siliconflow_engine: Optional[SiliconFlowOCREngine] = None
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# 初始化选定的引擎
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self._init_engine()
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def _init_engine(self):
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"""初始化OCR引擎"""
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if self.engine_type == "rapid":
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try:
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self.rapid_engine = RapidOCREngine()
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except Exception as e:
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print(f"RapidOCR初始化失败: {e}")
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print("将尝试使用硅基流动API引擎...")
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self.engine_type = "siliconflow"
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self.siliconflow_engine = SiliconFlowOCREngine()
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elif self.engine_type == "rapidoc":
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try:
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self.rapidoc_engine = RapidDocEngine()
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except Exception as e:
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print(f"RapidDoc初始化失败: {e}")
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print("将尝试使用RapidOCR引擎...")
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self.engine_type = "rapid"
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self.rapid_engine = RapidOCREngine()
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elif self.engine_type == "paddle":
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try:
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self.paddle_engine = PaddleOCREngine()
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except Exception as e:
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print(f"PaddleOCR初始化失败: {e}")
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print("将尝试使用RapidOCR引擎...")
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self.engine_type = "rapid"
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self.rapid_engine = RapidOCREngine()
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elif self.engine_type == "siliconflow":
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self.siliconflow_engine = SiliconFlowOCREngine()
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else:
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raise ValueError(f"不支持的OCR引擎类型: {self.engine_type}")
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def pdf_to_images(self, pdf_path: str, output_dir: Optional[str] = None) -> List[str]:
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"""
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将PDF转换为图片列表
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Args:
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pdf_path: PDF文件路径
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output_dir: 图片输出目录，如果为None则返回base64编码列表
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Returns:
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如果output_dir为None，返回base64编码列表；否则返回图片文件路径列表
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"""
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try:
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import fitz # PyMuPDF
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from PIL import Image
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import io
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doc = fitz.open(pdf_path)
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images = []
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for page_num in range(len(doc)):
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page = doc[page_num]
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# 将PDF页面转换为图片
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zoom = 2 # 放大倍数
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mat = fitz.Matrix(zoom, zoom)
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pix = page.get_pixmap(matrix=mat)
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# 转换为PIL Image
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img = Image.frombytes("RGB", [pix.width, pix.height], pix.samples)
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if output_dir:
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# 保存到文件
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os.makedirs(output_dir, exist_ok=True)
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img_path = os.path.join(output_dir, f"page_{page_num + 1}.png")
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img.save(img_path, "PNG")
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images.append(img_path)
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else:
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# 转换为base64
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buffered = io.BytesIO()
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img.save(buffered, format="PNG")
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img_base64 = base64.b64encode(buffered.getvalue()).decode()
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images.append(img_base64)
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doc.close()
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return images
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except ImportError:
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print("PDF处理依赖未安装，正在尝试自动安装...")
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if install_dependency("pymupdf") and install_dependency("pillow"):
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try:
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import fitz # PyMuPDF
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from PIL import Image
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import io
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doc = fitz.open(pdf_path)
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images = []
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for page_num in range(len(doc)):
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page = doc[page_num]
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# 将PDF页面转换为图片
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zoom = 2 # 放大倍数
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mat = fitz.Matrix(zoom, zoom)
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pix = page.get_pixmap(matrix=mat)
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# 转换为PIL Image
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img = Image.frombytes("RGB", [pix.width, pix.height], pix.samples)
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if output_dir:
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# 保存到文件
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os.makedirs(output_dir, exist_ok=True)
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img_path = os.path.join(output_dir, f"page_{page_num + 1}.png")
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img.save(img_path, "PNG")
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images.append(img_path)
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else:
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# 转换为base64
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buffered = io.BytesIO()
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img.save(buffered, format="PNG")
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img_base64 = base64.b64encode(buffered.getvalue()).decode()
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images.append(img_base64)
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doc.close()
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return images
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except ImportError:
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raise Exception("PDF处理依赖安装失败，请手动安装: pip install pymupdf pillow")
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else:
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raise Exception("PDF处理依赖安装失败，请手动安装: pip install pymupdf pillow")
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except Exception as e:
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raise Exception(f"PDF转图片失败: {str(e)}")
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def ocr_pdf(self, pdf_path: str, save_images: bool = False) -> Dict[str, Any]:
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"""
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OCR识别整个PDF
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Args:
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pdf_path: PDF文件路径
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save_images: 是否保存中间图片文件（RapidOCR和PaddleOCR模式下）
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Returns:
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包含text和page_count的字典
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"""
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result = {
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"text": "",
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"page_count": 0,
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"engine": self.engine_type
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}
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try:
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if self.engine_type == "rapid":
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# 使用RapidOCR本地识别
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result = self._ocr_with_rapid(pdf_path, save_images)
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elif self.engine_type == "rapidoc":
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# 使用RapidDoc增强识别
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result = self._ocr_with_rapidoc(pdf_path)
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elif self.engine_type == "paddle":
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# 使用PaddleOCR本地识别
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result = self._ocr_with_paddle(pdf_path, save_images)
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else:
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# 使用硅基流动API识别
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result = self._ocr_with_siliconflow(pdf_path)
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except Exception as e:
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raise Exception(f"OCR识别失败: {str(e)}")
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return result
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def _ocr_with_rapid(self, pdf_path: str, save_images: bool = False) -> Dict[str, Any]:
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"""使用RapidOCR识别PDF"""
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import tempfile
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import shutil
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# 创建临时目录存放图片
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if save_images:
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temp_dir = os.path.join(os.path.dirname(pdf_path), "pdf_images")
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else:
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temp_dir = tempfile.mkdtemp()
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try:
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# 转换PDF为图片
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image_paths = self.pdf_to_images(pdf_path, output_dir=temp_dir)
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text_parts = []
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for idx, img_path in enumerate(image_paths, 1):
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page_text = self.rapid_engine.recognize(img_path)
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text_parts.append(f"=== 第 {idx} 页 ===\n{page_text}")
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return {
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"text": "\n\n".join(text_parts),
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"page_count": len(image_paths),
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"engine": "rapid",
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"images_dir": temp_dir if save_images else None
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}
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finally:
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# 清理临时文件
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if not save_images and os.path.exists(temp_dir):
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shutil.rmtree(temp_dir)
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def _ocr_with_paddle(self, pdf_path: str, save_images: bool = False) -> Dict[str, Any]:
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"""使用PaddleOCR识别PDF"""
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import tempfile
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import shutil
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# 创建临时目录存放图片
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if save_images:
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temp_dir = os.path.join(os.path.dirname(pdf_path), "pdf_images")
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else:
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temp_dir = tempfile.mkdtemp()
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try:
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# 转换PDF为图片
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image_paths = self.pdf_to_images(pdf_path, output_dir=temp_dir)
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text_parts = []
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for idx, img_path in enumerate(image_paths, 1):
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page_text = self.paddle_engine.recognize(img_path)
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text_parts.append(f"=== 第 {idx} 页 ===\n{page_text}")
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return {
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"text": "\n\n".join(text_parts),
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"page_count": len(image_paths),
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"engine": "paddle",
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"images_dir": temp_dir if save_images else None
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}
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finally:
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# 清理临时文件
|
||
if not save_images and os.path.exists(temp_dir):
|
||
shutil.rmtree(temp_dir)
|
||
|
||
def _ocr_with_rapidoc(self, pdf_path: str) -> Dict[str, Any]:
|
||
"""使用RapidDoc识别PDF"""
|
||
try:
|
||
# 直接使用RapidDoc处理PDF
|
||
result = self.rapidoc_engine.recognize(pdf_path)
|
||
|
||
# 计算页数
|
||
page_count = 1
|
||
try:
|
||
import fitz # PyMuPDF
|
||
doc = fitz.open(pdf_path)
|
||
page_count = len(doc)
|
||
doc.close()
|
||
except:
|
||
pass
|
||
|
||
return {
|
||
"text": result["text"],
|
||
"page_count": page_count,
|
||
"engine": "rapidoc",
|
||
"markdown": result["markdown"],
|
||
"images_count": result["images_count"]
|
||
}
|
||
except Exception as e:
|
||
raise Exception(f"RapidDoc识别失败: {str(e)}")
|
||
|
||
def _ocr_with_siliconflow(self, pdf_path: str) -> Dict[str, Any]:
|
||
"""使用硅基流动API识别PDF"""
|
||
images = self.pdf_to_images(pdf_path)
|
||
|
||
text_parts = []
|
||
for idx, img_base64 in enumerate(images, 1):
|
||
page_text = self.siliconflow_engine.recognize(img_base64, idx)
|
||
text_parts.append(f"=== 第 {idx} 页 ===\n{page_text}")
|
||
|
||
return {
|
||
"text": "\n\n".join(text_parts),
|
||
"page_count": len(images),
|
||
"engine": "siliconflow"
|
||
}
|
||
|
||
def process(self, input_data: Dict[str, Any]) -> Dict[str, Any]:
|
||
"""
|
||
处理入口点（供skill-loader调用）
|
||
|
||
Args:
|
||
input_data: 包含file_path和可选engine的字典
|
||
|
||
Returns:
|
||
包含success、text、page_count和engine的字典
|
||
"""
|
||
pdf_path = input_data.get('file_path', '')
|
||
engine = input_data.get('engine', None)
|
||
|
||
if not pdf_path:
|
||
return {"success": False, "error": "PDF file path is required"}
|
||
|
||
return process_pdf_ocr(pdf_path, engine=engine)
|
||
|
||
def ocr_image_file(self, image_path: str) -> Dict[str, Any]:
|
||
"""OCR识别单个图片文件"""
|
||
result = {
|
||
"text": "",
|
||
"page_count": 1,
|
||
"engine": self.engine_type
|
||
}
|
||
|
||
try:
|
||
if self.engine_type == "rapid":
|
||
result["text"] = self.rapid_engine.recognize(image_path)
|
||
elif self.engine_type == "rapidoc":
|
||
# 使用RapidDoc识别图片
|
||
rapidoc_result = self.rapidoc_engine.recognize(image_path)
|
||
result["text"] = rapidoc_result["text"]
|
||
result["markdown"] = rapidoc_result["markdown"]
|
||
result["images_count"] = rapidoc_result["images_count"]
|
||
elif self.engine_type == "paddle":
|
||
# 使用PaddleOCR识别图片
|
||
result["text"] = self.paddle_engine.recognize(image_path)
|
||
else:
|
||
# 将图片转换为base64
|
||
try:
|
||
from PIL import Image
|
||
import io
|
||
except ImportError:
|
||
print("图片处理依赖未安装，正在尝试自动安装...")
|
||
if install_dependency("pillow"):
|
||
from PIL import Image
|
||
import io
|
||
else:
|
||
raise Exception("图片处理依赖安装失败，请手动安装: pip install pillow")
|
||
|
||
img = Image.open(image_path)
|
||
if img.mode != 'RGB':
|
||
img = img.convert('RGB')
|
||
|
||
buffered = io.BytesIO()
|
||
img.save(buffered, format="PNG")
|
||
img_base64 = base64.b64encode(buffered.getvalue()).decode()
|
||
|
||
result["text"] = self.siliconflow_engine.recognize(img_base64, 1)
|
||
|
||
except Exception as e:
|
||
raise Exception(f"图片OCR识别失败: {str(e)}")
|
||
|
||
return result
|
||
|
||
|
||
def process_pdf_ocr(pdf_path: str, engine: Optional[str] = None) -> Dict[str, Any]:
|
||
"""
|
||
处理PDF OCR的主函数
|
||
|
||
Args:
|
||
pdf_path: PDF文件路径
|
||
engine: OCR引擎类型，可选 "rapid" 或 "siliconflow"
|
||
|
||
Returns:
|
||
包含success、text、page_count和engine的字典
|
||
"""
|
||
processor = PDFOCRProcessor(engine=engine)
|
||
result = processor.ocr_pdf(pdf_path)
|
||
result['success'] = True
|
||
return result
|
||
|
||
|
||
def main(input_data: Dict[str, Any] = None) -> Dict[str, Any]:
|
||
"""SKILL 入口点"""
|
||
if input_data is None:
|
||
input_data = {}
|
||
pdf_path = input_data.get('file_path', '')
|
||
engine = input_data.get('engine', None)
|
||
if not pdf_path:
|
||
return {"success": False, "error": "PDF file path is required"}
|
||
return process_pdf_ocr(pdf_path, engine=engine)
|
||
|
||
|
||
if __name__ == "__main__":
|
||
# 测试代码
|
||
if len(sys.argv) > 1:
|
||
pdf_path = sys.argv[1]
|
||
engine = sys.argv[2] if len(sys.argv) > 2 else None
|
||
else:
|
||
print("使用方法: python pdf_ocr_processor.py <pdf_file_path> [engine]")
|
||
print("engine可选值: rapid (默认) | rapidoc | paddle | siliconflow")
|
||
sys.exit(1)
|
||
|
||
if not os.path.exists(pdf_path):
|
||
print(f"文件不存在: {pdf_path}")
|
||
sys.exit(1)
|
||
|
||
try:
|
||
result = process_pdf_ocr(pdf_path, engine=engine)
|
||
print(f"OCR识别完成，共 {result['page_count']} 页")
|
||
print(f"使用引擎: {result['engine']}")
|
||
if 'images_count' in result:
|
||
print(f"提取的图片数量: {result['images_count']}")
|
||
print("\n识别结果:")
|
||
print(result['text'])
|
||
if 'markdown' in result and len(result['markdown']) > 500:
|
||
print("\nMarkdown结果预览:")
|
||
print(result['markdown'][:500] + "...")
|
||
except Exception as e:
|
||
print(f"处理失败: {e}")
|
||
sys.exit(1)
|