161 lines
4.9 KiB
Python
161 lines
4.9 KiB
Python
# -*- coding: utf-8 -*-
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"""
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并行OCR识别 - 多进程加速
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"""
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import os
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import sqlite3
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import requests
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import base64
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from PIL import Image
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import glob
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import json
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from multiprocessing import Pool, Manager
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import time
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def ocr_image(args):
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"""OCR识别单张图片"""
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image_path, idx, total = args
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try:
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with open(image_path, 'rb') as f:
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image_base64 = base64.b64encode(f.read()).decode('utf-8')
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url = "http://localhost:11434/api/chat"
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payload = {
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"model": "glm-ocr",
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"messages": [{
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"role": "user",
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"content": """识别图片中的所有联系人名称。要求：
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1. 只输出联系人名称，每行一个
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2. 忽略分组标题（如星号、字母A-Z等）
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3. 忽略数字统计
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4. 不要添加任何其他内容""",
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"images": [image_base64]
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}],
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"stream": False
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}
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response = requests.post(url, json=payload, timeout=60)
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result = response.json().get('message', {}).get('content', '')
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contacts = []
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for line in result.strip().split('\n'):
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line = line.strip()
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if line and len(line) >= 2 and len(line) < 50:
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# 简单过滤
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if not any(x in line for x in ['公众号', '服务号', '企业微信', '联系人', '星标朋友', '新的朋友']):
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contacts.append(line.strip('"\'').rstrip(',，。：:'))
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print(f"[{idx+1}/{total}] {os.path.basename(image_path)}: 发现 {len(contacts)} 个联系人")
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return contacts
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except Exception as e:
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print(f"[{idx+1}/{total}] {os.path.basename(image_path)}: 失败 - {e}")
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return []
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def get_existing_contacts():
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"""从数据库获取已存在的联系人"""
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conn = sqlite3.connect(r'D:\夏骥\微信研究\contacts.db')
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cursor = conn.cursor()
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cursor.execute('SELECT name FROM contacts')
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existing = set(row[0] for row in cursor.fetchall())
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conn.close()
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return existing
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def add_new_contacts(new_contacts):
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"""将新联系人添加到数据库"""
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if not new_contacts:
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return 0
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conn = sqlite3.connect(r'D:\夏骥\微信研究\contacts.db')
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cursor = conn.cursor()
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# 获取当前最大ID
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cursor.execute('SELECT MAX(id) FROM contacts')
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max_id = cursor.fetchone()[0] or 0
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added = 0
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for idx, name in enumerate(new_contacts, start=max_id + 1):
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cursor.execute('''
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INSERT INTO contacts (id, name, category, blessing, selected)
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VALUES (?, ?, ?, ?, ?)
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''', (idx, name, '', '马年新春快乐！愿您在新的一年里，事业腾飞，马到成功！', False))
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added += 1
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conn.commit()
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conn.close()
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return added
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def main():
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print("=" * 60)
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print("并行OCR识别")
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print("=" * 60)
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# 获取截图目录
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scroll_dir = r"D:\夏骥\微信研究\scroll_complete"
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screenshots = sorted(glob.glob(os.path.join(scroll_dir, "*.png")))
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if not screenshots:
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print("未找到截图文件！")
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return
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print(f"找到 {len(screenshots)} 张截图")
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# 获取已存在的联系人
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existing_contacts = get_existing_contacts()
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print(f"数据库中已有 {len(existing_contacts)} 个联系人")
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# 准备参数
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args_list = [(path, i, len(screenshots)) for i, path in enumerate(screenshots)]
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# 并行处理 - 使用4个进程
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print("\n开始并行OCR识别...")
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all_contacts = set()
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with Pool(processes=4) as pool:
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results = pool.map(ocr_image, args_list)
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# 收集结果
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for contacts in results:
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for name in contacts:
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if name and len(name) >= 2 and name not in existing_contacts:
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all_contacts.add(name)
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print(f"\n{'='*60}")
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print(f"OCR完成！")
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print(f"发现新联系人: {len(all_contacts)} 个")
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# 入库
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if all_contacts:
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added = add_new_contacts(sorted(all_contacts, key=lambda x: (not x[0].isalpha() if x else True, x.lower() if x and x[0].isalpha() else x)))
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print(f"成功入库: {added} 个")
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# 更新JSON文件
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conn = sqlite3.connect(r'D:\夏骥\微信研究\contacts.db')
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cursor = conn.cursor()
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cursor.execute('SELECT * FROM contacts ORDER BY id')
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all_db_contacts = []
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for row in cursor.fetchall():
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all_db_contacts.append({
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"id": row[0],
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"name": row[1],
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"category": row[2],
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"blessing": row[3],
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"selected": bool(row[4])
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})
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conn.close()
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json_file = r"D:\夏骥\微信研究\contacts_data.json"
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with open(json_file, 'w', encoding='utf-8') as f:
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json.dump(all_db_contacts, f, ensure_ascii=False, indent=2)
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print(f"JSON数据已更新: {json_file}")
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print(f"数据库总联系人: {len(all_db_contacts)} 个")
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if __name__ == '__main__':
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main()
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