383 lines
16 KiB
Python
383 lines
16 KiB
Python
import asyncio
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import datetime
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import json
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import os
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from contextlib import asynccontextmanager
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from typing import Dict, Optional, AsyncGenerator
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from service.device_service import update_online_status_by_ip, increment_alarm_count_by_ip
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from service.device_action_service import add_device_action
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from schema.device_action_schema import DeviceActionCreate
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import cv2
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import numpy as np
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from fastapi import WebSocket, APIRouter, WebSocketDisconnect, FastAPI
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from queue import Queue
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from threading import Lock
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from ocr.model_violation_detector import MultiModelViolationDetector
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# 配置文件路径（建议实际部署时改为相对路径或环境变量）
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YOLO_MODEL_PATH = r"D:\Git\bin\video\ocr\models\best.pt"
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OCR_CONFIG_PATH = r"D:\Git\bin\video\ocr\config\1.yaml"
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# 模型池配置（根据GPU显存调整，每个模型约占1G显存）
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MODEL_POOL_SIZE = 3 # 最大并发客户端数
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# 配置常量
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HEARTBEAT_INTERVAL = 30 # 心跳检查间隔（秒）
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HEARTBEAT_TIMEOUT = 600 # 客户端超时阈值（秒）
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WS_ENDPOINT = "/ws" # WebSocket端点路径
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FRAME_QUEUE_SIZE = 1 # 帧队列大小限制
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# 工具函数：获取格式化时间字符串
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def get_current_time_str() -> str:
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return datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
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def get_current_time_file_str() -> str:
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return datetime.datetime.now().strftime("%Y%m%d_%H%M%S_%f")
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# 模型池实现 - 提前初始化固定数量的模型实例
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class ModelPool:
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def __init__(self, pool_size: int = MODEL_POOL_SIZE):
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self.pool = Queue(maxsize=pool_size)
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self.lock = Lock()
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# 提前初始化模型实例（显存会在此阶段预分配）
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for i in range(pool_size):
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detector = MultiModelViolationDetector(
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ocr_config_path=OCR_CONFIG_PATH,
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yolo_model_path=YOLO_MODEL_PATH,
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ocr_confidence_threshold=0.5
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)
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self.pool.put(detector)
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print(f"[{get_current_time_str()}] 模型池初始化：第{i + 1}/{pool_size}个模型加载完成")
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def get_model(self) -> MultiModelViolationDetector:
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"""从池子里获取模型（阻塞直到有可用实例）"""
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with self.lock:
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return self.pool.get()
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def return_model(self, detector: MultiModelViolationDetector):
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"""将模型归还给池子"""
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with self.lock:
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self.pool.put(detector)
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# 初始化模型池（程序启动时加载所有模型，显存会一次性占用 MODEL_POOL_SIZE * 单模型显存）
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model_pool = ModelPool(pool_size=MODEL_POOL_SIZE)
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# 客户端连接封装
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class ClientConnection:
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def __init__(self, websocket: WebSocket, client_ip: str):
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self.websocket = websocket
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self.client_ip = client_ip
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self.last_heartbeat = datetime.datetime.now()
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self.frame_queue = asyncio.Queue(maxsize=FRAME_QUEUE_SIZE)
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self.consumer_task: Optional[asyncio.Task] = None
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# 从模型池获取专属模型（每个客户端独立占用一个模型实例）
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self.detector = model_pool.get_model()
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print(f"[{get_current_time_str()}] 客户端{self.client_ip}：已获取模型池中的模型实例（显存独立）")
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def update_heartbeat(self):
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"""更新心跳时间"""
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self.last_heartbeat = datetime.datetime.now()
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def is_alive(self) -> bool:
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"""判断客户端是否存活"""
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timeout = (datetime.datetime.now() - self.last_heartbeat).total_seconds()
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return timeout < HEARTBEAT_TIMEOUT
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def start_consumer(self):
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"""启动帧消费任务"""
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self.consumer_task = asyncio.create_task(self.consume_frames())
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return self.consumer_task
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def release_model(self):
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"""客户端断开时归还模型到池"""
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model_pool.return_model(self.detector)
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print(f"[{get_current_time_str()}] 客户端{self.client_ip}：模型已归还至模型池（显存可复用）")
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async def send_frame_permit(self):
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"""发送帧发送许可信号"""
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try:
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frame_permit_msg = {
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"type": "frame",
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"timestamp": get_current_time_str(),
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"client_ip": self.client_ip
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}
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await self.websocket.send_json(frame_permit_msg)
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print(f"[{get_current_time_str()}] 客户端{self.client_ip}：已发送帧发送许可信号")
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except Exception as e:
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print(f"[{get_current_time_str()}] 客户端{self.client_ip}：帧许可信号发送失败 - {str(e)}")
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async def consume_frames(self) -> None:
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"""消费队列中的帧并处理（并行执行核心）"""
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try:
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while True:
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# 1. 从队列取出帧
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frame_data = await self.frame_queue.get()
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# 2. 立即发送下一帧许可
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await self.send_frame_permit()
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try:
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# 3. 并行处理帧：用线程池执行AI检测（真正并发）
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await self.process_frame(frame_data)
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finally:
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self.frame_queue.task_done()
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except asyncio.CancelledError:
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print(f"[{get_current_time_str()}] 客户端{self.client_ip}：帧消费任务已取消")
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except Exception as e:
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print(f"[{get_current_time_str()}] 客户端{self.client_ip}：帧消费逻辑错误 - {str(e)}")
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async def process_frame(self, frame_data: bytes) -> None:
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"""处理单帧图像数据（使用客户端专属模型）"""
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# 二进制数据转OpenCV图像
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nparr = np.frombuffer(frame_data, np.uint8)
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img = cv2.imdecode(nparr, cv2.IMREAD_COLOR)
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if img is None:
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print(f"[{get_current_time_str()}] 客户端{self.client_ip}：无法解析图像数据")
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return
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# 确保图像保存目录存在
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os.makedirs('images', exist_ok=True)
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# 保存图像
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filename = f"images/{self.client_ip.replace('.', '_')}_{get_current_time_file_str()}.jpg"
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try:
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cv2.imwrite(filename, img)
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print(f"[{get_current_time_str()}] 图像已保存至：{filename}")
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# 关键修改：使用客户端专属模型 + 线程池并行执行AI检测
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has_violation, violation_type, details = await asyncio.to_thread(
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self.detector.detect_violations, # 客户端独立模型
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img # 输入图像
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)
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if has_violation:
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print(
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f"[{get_current_time_str()}] 客户端{self.client_ip}：检测到违规 - 类型: {violation_type}, 详情: {details}")
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# 调用违规次数加一方法
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try:
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await asyncio.to_thread(increment_alarm_count_by_ip, self.client_ip)
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print(f"[{get_current_time_str()}] 客户端{self.client_ip}：违规次数已+1")
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except Exception as e:
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print(f"[{get_current_time_str()}] 客户端{self.client_ip}：违规次数更新失败 - {str(e)}")
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# 发送危险通知
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danger_msg = {
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"type": "danger",
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"timestamp": get_current_time_str(),
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"client_ip": self.client_ip
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}
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await self.websocket.send_json(danger_msg)
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else:
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print(f"[{get_current_time_str()}] 客户端{self.client_ip}：未检测到违规")
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except Exception as e:
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print(f"[{get_current_time_str()}] 客户端{self.client_ip}：图像处理错误 - {str(e)}")
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# 全局状态管理
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connected_clients: Dict[str, ClientConnection] = {}
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client_lock = asyncio.Lock() # 保护connected_clients的锁
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heartbeat_task: Optional[asyncio.Task] = None
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# 心跳检查
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async def heartbeat_checker():
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while True:
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current_time = get_current_time_str()
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# 加锁保护字典遍历
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async with client_lock:
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timeout_ips = [ip for ip, conn in connected_clients.items() if not conn.is_alive()]
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if timeout_ips:
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print(f"[{current_time}] 心跳检查：{len(timeout_ips)}个客户端超时（IP：{timeout_ips}）")
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for ip in timeout_ips:
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try:
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async with client_lock:
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conn = connected_clients.get(ip)
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if not conn:
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continue
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if conn.consumer_task and not conn.consumer_task.done():
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conn.consumer_task.cancel()
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await conn.websocket.close(code=1008, reason="心跳超时")
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# 归还模型
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conn.release_model()
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# 超时设为离线并记录
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try:
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await asyncio.to_thread(update_online_status_by_ip, ip, 0)
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action_data = DeviceActionCreate(client_ip=ip, action=0)
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await asyncio.to_thread(add_device_action, action_data)
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print(f"[{current_time}] 客户端{ip}：已标记为离线并记录操作")
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except Exception as e:
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print(f"[{current_time}] 客户端{ip}：离线状态更新失败 - {str(e)}")
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finally:
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async with client_lock:
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connected_clients.pop(ip, None)
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else:
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async with client_lock:
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print(f"[{current_time}] 心跳检查：{len(connected_clients)}个客户端在线")
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await asyncio.sleep(HEARTBEAT_INTERVAL)
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# 应用生命周期管理
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@asynccontextmanager
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async def lifespan(app: FastAPI):
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global heartbeat_task
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heartbeat_task = asyncio.create_task(heartbeat_checker())
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print(f"[{get_current_time_str()}] 全局心跳检查任务启动（任务ID：{id(heartbeat_task)}）")
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yield
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if heartbeat_task and not heartbeat_task.done():
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heartbeat_task.cancel()
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try:
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await heartbeat_task
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print(f"[{get_current_time_str()}] 全局心跳检查任务已取消")
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except asyncio.CancelledError:
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pass
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# 消息处理工具函数
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async def send_heartbeat_ack(conn: ClientConnection):
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try:
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heartbeat_ack_msg = {
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"type": "heart",
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"timestamp": get_current_time_str(),
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"client_ip": conn.client_ip
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}
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await conn.websocket.send_json(heartbeat_ack_msg)
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print(f"[{get_current_time_str()}] 客户端{conn.client_ip}：已发送心跳确认")
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return True
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except Exception as e:
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async with client_lock:
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connected_clients.pop(conn.client_ip, None)
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print(f"[{get_current_time_str()}] 客户端{conn.client_ip}：心跳确认发送失败 - {str(e)}")
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return False
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async def handle_text_msg(conn: ClientConnection, text: str):
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try:
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msg = json.loads(text)
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if msg.get("type") == "heart":
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conn.update_heartbeat()
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await send_heartbeat_ack(conn)
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else:
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print(f"[{get_current_time_str()}] 客户端{conn.client_ip}：未知文本消息类型（{msg.get('type')}）")
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except json.JSONDecodeError:
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print(f"[{get_current_time_str()}] 客户端{conn.client_ip}：无效JSON文本消息")
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async def handle_binary_msg(conn: ClientConnection, data: bytes):
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try:
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conn.frame_queue.put_nowait(data)
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print(f"[{get_current_time_str()}] 客户端{conn.client_ip}：图像数据（{len(data)}字节）已加入队列")
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except asyncio.QueueFull:
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print(f"[{get_current_time_str()}] 客户端{conn.client_ip}：帧队列已满，丢弃当前图像数据")
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# WebSocket路由配置
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ws_router = APIRouter()
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@ws_router.websocket(WS_ENDPOINT)
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async def websocket_endpoint(websocket: WebSocket):
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await websocket.accept()
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client_ip = websocket.client.host if websocket.client else "unknown_ip"
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current_time = get_current_time_str()
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print(f"[{current_time}] 客户端{client_ip}：WebSocket连接已建立")
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is_online_updated = False
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new_conn = None
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try:
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# 处理重复连接
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async with client_lock:
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if client_ip in connected_clients:
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old_conn = connected_clients[client_ip]
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if old_conn.consumer_task and not old_conn.consumer_task.done():
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old_conn.consumer_task.cancel()
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await old_conn.websocket.close(code=1008, reason="同一IP新连接建立")
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old_conn.release_model() # 归还旧连接的模型
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connected_clients.pop(client_ip)
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print(f"[{current_time}] 客户端{client_ip}：已关闭旧连接并回收模型")
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# 注册新连接
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new_conn = ClientConnection(websocket, client_ip)
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async with client_lock:
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connected_clients[client_ip] = new_conn
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new_conn.start_consumer()
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# 初始许可：连接建立后立即发一次
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await new_conn.send_frame_permit()
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# 标记上线并记录
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try:
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await asyncio.to_thread(update_online_status_by_ip, client_ip, 1)
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action_data = DeviceActionCreate(client_ip=client_ip, action=1)
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await asyncio.to_thread(add_device_action, action_data)
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print(f"[{current_time}] 客户端{client_ip}：已标记为在线并记录操作")
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is_online_updated = True
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except Exception as e:
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print(f"[{current_time}] 客户端{client_ip}：上线状态更新失败 - {str(e)}")
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async with client_lock:
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print(f"[{current_time}] 客户端{client_ip}：新连接注册成功，在线数：{len(connected_clients)}")
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# 消息循环
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while True:
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data = await websocket.receive()
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if "text" in data:
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await handle_text_msg(new_conn, data["text"])
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elif "bytes" in data:
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await handle_binary_msg(new_conn, data["bytes"])
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except WebSocketDisconnect as e:
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print(f"[{get_current_time_str()}] 客户端{client_ip}：主动断开连接（代码：{e.code}）")
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except Exception as e:
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print(f"[{get_current_time_str()}] 客户端{client_ip}：连接异常 - {str(e)[:50]}")
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finally:
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# 清理资源并标记离线
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if new_conn and client_ip in connected_clients:
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async with client_lock:
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conn = connected_clients.get(client_ip)
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if conn:
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if conn.consumer_task and not conn.consumer_task.done():
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conn.consumer_task.cancel()
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# 归还模型到模型池
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conn.release_model()
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# 主动/异常断开时标记离线
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if is_online_updated:
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try:
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await asyncio.to_thread(update_online_status_by_ip, client_ip, 0)
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action_data = DeviceActionCreate(client_ip=client_ip, action=0)
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await asyncio.to_thread(add_device_action, action_data)
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print(f"[{get_current_time_str()}] 客户端{client_ip}：断开后已标记为离线")
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except Exception as e:
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print(f"[{get_current_time_str()}] 客户端{client_ip}：断开后离线更新失败 - {str(e)}")
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connected_clients.pop(client_ip, None)
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async with client_lock:
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print(f"[{get_current_time_str()}] 客户端{client_ip}：资源已清理，在线数：{len(connected_clients)}")
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# 创建FastAPI应用
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app = FastAPI(lifespan=lifespan)
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app.include_router(ws_router)
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if __name__ == "__main__":
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import uvicorn
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uvicorn.run(app, host="0.0.0.0", port=8000)
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