import json
import re

from mysql.connector import Error as MySQLError

from ds.config import BUSINESS_CONFIG
from ds.db import db
from service.face_service import detect as faceDetect,init_insightface
from service.model_service import load_yolo_model,detect as yoloDetect
from service.ocr_service import detect as ocrDetect,init_ocr_engine
from service.file_service import save_detect_file, save_detect_yolo_file, save_detect_face_file
import asyncio
from concurrent.futures import ThreadPoolExecutor


# 创建线程池执行器
executor = ThreadPoolExecutor(max_workers=10)
def init():
    # # 人脸相关
    init_insightface()
    # # 初始化OCR引擎
    init_ocr_engine()
    #初始化YOLO模型
    load_yolo_model()

def save_db(model_type, client_ip, result):
    conn = None
    cursor = None
    try:
        # 连接数据库
        conn = db.get_connection()
        # 往表插入数据
        cursor = conn.cursor(dictionary=True)  # 返回字典格式结果
        insert_query = """
            INSERT INTO device_danger (client_ip, type, result)
            VALUES (%s, %s, %s)
        """
        cursor.execute(insert_query, (client_ip, model_type, result))
        conn.commit()
    except MySQLError as e:
        raise Exception(f"获取设备列表失败: {str(e)}") from e
    finally:
        db.close_connection(conn, cursor)


def detectFrame(client_ip, frame):
    # YOLO检测
    yolo_flag, yolo_result = yoloDetect(frame, float(BUSINESS_CONFIG["yolo_conf"]))
    if yolo_flag:
        print(f"❌ 检测到违规内容，保存图片,YOLO")
        danger_handler(client_ip)
        path = save_detect_yolo_file(client_ip, frame, yolo_result, "yolo")
        save_db(model_type="色情", client_ip=client_ip, result=str(path))

    # 人脸检测
    face_flag, face_result = faceDetect(frame, float(BUSINESS_CONFIG["face_conf"]))
    if face_flag:
        print(f"❌ 检测到违规内容，保存图片,FACE")
        print("人脸识别内容:", face_result)
        model_type = extract_face_names(face_result)
        danger_handler(client_ip)
        path = save_detect_face_file(client_ip, frame, face_result, "face")
        save_db(model_type=model_type, client_ip=client_ip, result=str(path))

    # OCR检测部分（使用修正后的提取函数）
    ocr_flag, ocr_result = ocrDetect(frame, float(BUSINESS_CONFIG["ocr_conf"]))
    if ocr_flag:
        print(f"❌ 检测到违规内容，保存图片,OCR")
        print("ocr识别内容:", ocr_result)
        danger_handler(client_ip)
        path = save_detect_file(client_ip, frame, "ocr")
        save_db(model_type=str(ocr_result), client_ip=client_ip, result=str(path))

    # 仅当所有检测均未发现违规时才提示
    if not (face_flag or yolo_flag or ocr_flag):
        print(f"所有模型未检测到任何违规内容")

def danger_handler(client_ip):
    from ws.ws import send_message_to_client, get_current_time_str
    from service.device_service import increment_alarm_count_by_ip
    from service.device_service import update_is_need_handler_by_client_ip

    danger_msg = {
        "type": "danger",
        "timestamp": get_current_time_str(),
        "client_ip": client_ip,
    }
    asyncio.run(
        send_message_to_client(
            client_ip=client_ip,
            json_data=json.dumps(danger_msg)
        )
    )
    lock_msg = {
        "type": "lock",
        "timestamp": get_current_time_str(),
        "client_ip": client_ip
    }
    asyncio.run(
        send_message_to_client(
            client_ip=client_ip,
            json_data=json.dumps(lock_msg)
        )
    )
    # 增加危险记录次数
    increment_alarm_count_by_ip(client_ip)
    # 更新设备状态为未处理
    update_is_need_handler_by_client_ip(client_ip, 1)

def extract_face_names(face_result: str) -> str:
    pattern = r"匹配: (.*?) \("
    all_names = re.findall(pattern, face_result)
    unique_names = list(set([name.strip() for name in all_names if name.strip()]))
    return ",".join(unique_names)