双十二文档识别推荐

import pytesseract
from PIL import Image
import numpy as np

# 使用Tesseract OCR识别图像中的文字
def ocr_recognition(image_path):
    image = Image.open(image_path)
    text = pytesseract.image_to_string(image)
    return text

# 示例：识别文档中的文字
image_path = 'example.jpg'
recognized_text = ocr_recognition(image_path)
print("Recognized Text:", recognized_text)

# 推荐系统示例：基于内容的推荐
def content_based_recommendation(text):
    # 这里可以添加更复杂的逻辑，如关键词提取、相似度计算等
    keywords = text.split()[:5]  # 简单提取前五个词作为关键词
    recommended_items = []  # 根据关键词查找相关推荐项
    # 示例：假设我们有一个预定义的推荐项列表
    predefined_items = {
        "apple": ["Apple iPhone", "Apple MacBook"],
        "python": ["Python Programming Book", "Python Course"]
    }
    for keyword in keywords:
        if keyword in predefined_items:
            recommended_items.extend(predefined_items[keyword])
    return recommended_items

recommended_items = content_based_recommendation(recognized_text)
print("Recommended Items:", recommended_items)