python pdf转图片再OCR

1. 先pdf转图片

import os
from pdf2image import convert_from_path# PDF文件路径
pdf_path = '/Users/xxx/2022.pdf'
# 输出图片的文件夹
output_folder = './output_images2022'
# 输出图片的命名格式
output_name = 'page'# 如果输出文件夹不存在，创建它
if not os.path.exists(output_folder):os.makedirs(output_folder)# 将PDF转换为图像列表，设置分辨率为300 DPI
images = convert_from_path(pdf_path, dpi=300)# 保存每一页为PNG图片
for i, image in enumerate(images):image.save(f'{output_folder}/{output_name}_{i+1}.png', 'PNG')

2. OCR

from PIL import ImageEnhance
import pytesseract
from PIL import Image
from openpyxl import Workbook# 配置 Tesseract 的路径（如果需要）
# pytesseract.pytesseract.tesseract_cmd = r'/usr/local/bin/tesseract'  # Mac 的路径
# pytesseract.pytesseract.tesseract_cmd = r'C:\Program Files\Tesseract-OCR\tesseract.exe'  # Windows 的路径# 打开图片
# image_path = "/Users/xxx/page_3.png"  # 替换为你的图片路径def enhance_image(img):img = img.convert('L')  # 转灰度img = ImageEnhance.Contrast(img).enhance(2.0)return imgdef allimngs(image_path):image = Image.open(image_path)image = enhance_image(image)# 使用 pytesseract 进行 OCRtext = pytesseract.image_to_string(image, lang="chi_sim")  # 中文# # 打印提取的文本# print("提取的文本：")# print(text.replace(' ', ''))return text.replace(' ', '')# 统计子字符串出现次数class TrieNode:def __init__(self):self.children = {}self.keywords = []class Trie:def __init__(self):self.root = TrieNode()def insert(self, keyword):node = self.rootfor char in keyword:if char not in node.children:node.children[char] = TrieNode()node = node.children[char]node.keywords.append(keyword)def count_keywords(text, keywords):# 去重关键词以确保唯一性keywords = list(set(keywords))# 构建Trie树trie = Trie()for kw in keywords:trie.insert(kw)# 初始化计数器counters = {kw: 0 for kw in keywords}i = 0n = len(text)while i < n:current_node = trie.rootmax_len = 0current_len = 0end_pos = i# 寻找从当前位置开始的最长匹配关键词for j in range(i, n):char = text[j]if char in current_node.children:current_node = current_node.children[char]current_len += 1if current_node.keywords:  # 当前节点是某个关键词的结尾max_len = current_lenend_pos = j + 1  # 更新结束位置为当前字符的下一个位置else:break  # 无后续匹配，退出循环if max_len > 0:# 更新所有匹配的关键词计数器for kw in current_node.keywords:counters[kw] += 1i = end_pos  # 跳跃到已匹配部分的末尾else:i += 1  # 无匹配，移动到下一个字符return countersif __name__ == "__main__":keywords = ['矮小','安于现状','暗藏','暗淡','暗黑']all_text = ''workbook = Workbook()sheet = workbook.activefor i in range(108):i = i+1image_path = f"/Users/xxx/output_images2022/page_{i}.png"all_text = all_text + allimngs(image_path)all_text = all_text.replace(' ', '').replace('\n', '')result = count_keywords(all_text, keywords)num = 1for k, v in result.items():sheet[f'A{num}'] = ksheet[f'B{num}'] = vprint(k, v, num)num = num + 1workbook.save(filename='2022.xlsx')