482 lines
18 KiB
Python
482 lines
18 KiB
Python
# base_frame_processor.py
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# 通用帧处理工作线程基类
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# 统一异步POST、告警去重、抽帧控制等公共逻辑
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import cv2
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import base64
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import json
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import os
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import subprocess
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import time
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import threading
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import queue
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import requests
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from typing import Dict, Any, Callable
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from concurrent.futures import ThreadPoolExecutor
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from common import constants
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from common.type_mapping import get_alert_label
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from utils.logger import get_logger
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from utils.hls_utils import get_segments_before_current, parse_segment_info
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logger = get_logger(__name__)
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# 告警推送频率限制（秒）
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ALERT_PUSH_INTERVAL = 5.0
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class BaseFrameProcessorWorker(threading.Thread):
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"""
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通用帧处理工作线程基类
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功能：
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- 统一异步POST（线程池）
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- 统一告警去重逻辑
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- 统一抽帧控制
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- 统一异常处理
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子类仅需提供：
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- DETECTOR_FACTORY: 检测器工厂函数
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- POST_TYPE: POST请求的type值
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- TARGET_FPS: 目标帧率
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"""
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# ========== 子类必须重写的类常量 ==========
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DETECTOR_FACTORY: Callable = None # 检测器工厂函数
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POST_TYPE: int = 2 # POST type
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TARGET_FPS: float = 10.0 # 目标帧率
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def __init__(self,
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raw_queue: queue.Queue,
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ws_queue: queue.Queue,
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stop_event: threading.Event,
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cameras=None,
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post_workers: int = 4):
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super().__init__(daemon=True)
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self.raw_queue = raw_queue
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self.ws_queue = ws_queue
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self.stop_event = stop_event
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# 将摄像头列表转换为字典，key为id，方便通过camera_id快速查找
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self.cameras = {cam.id: cam for cam in cameras} if cameras is not None else {}
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self.last_ts: Dict[int, float] = {}
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# 检测器实例缓存
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self.detectors: Dict[int, Any] = {}
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# 告警去重记录 {camera_id: {action: last_push_time}}
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self.last_alert_push_time: Dict[int, Dict[str, float]] = {}
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# 异步POST线程池
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self.post_executor = ThreadPoolExecutor(
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max_workers=post_workers,
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thread_name_prefix="alert_post"
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)
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# MP4缓存 {segment_path: mp4_path}
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self._mp4_cache: Dict[str, str] = {}
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# 启动视频文件清理线程
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self._start_cleanup_thread()
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def _encode_image_to_base64(self, img) -> str:
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"""图像编码为 Base64"""
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ok, buf = cv2.imencode(".jpg", img)
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if not ok:
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raise RuntimeError("Failed to encode image to JPEG")
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return base64.b64encode(buf.tobytes()).decode("ascii")
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def _expand_msg_by_ori_alert(self, msg: dict) -> list:
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"""
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将 msg 中的 ori_alert 数组展开为多个独立的 msg
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Args:
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msg: 原始消息，包含 ori_alert 数组
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original_image_b64: 原始图像的 base64 编码（作为后备）
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Returns:
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msg 列表，每个 msg 的 result_type 为包含 action_code 和 action_name 的对象
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"""
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ori_alerts = msg.get("ori_alert", [])
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# 如果没有 ori_alert 或为空，直接返回原消息
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if not ori_alerts:
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new_msg = msg.copy()
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new_msg.pop("ori_alert", None)
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return [new_msg]
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result = []
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for alert_item in ori_alerts:
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action_code = alert_item.get("action")
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if not action_code:
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continue
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new_msg = msg.copy()
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# 处理 image：优先使用 ori_alert 中的 image，否则使用原来的
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alert_image = alert_item.get("image")
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if alert_image is not None:
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try:
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new_msg["image_base64"] = self._encode_image_to_base64(alert_image)
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except Exception as e:
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logger.warning(f"[WARN] Failed to encode alert image: {e}, using original")
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# 设置 result_type
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new_msg["result_type"] = {
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"action_code": action_code,
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"action_name": get_alert_label(action_code)
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}
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# 移除 ori_alert
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new_msg.pop("ori_alert", None)
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result.append(new_msg)
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return result
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def _post_alert(self, msg: dict):
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"""异步发送告警 POST 请求（在线程池中执行）- 旧接口，保留备用"""
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try:
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response = requests.post(constants.ALERT_PUSH_URL, json=msg, timeout=5.0)
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if response.status_code == 200:
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print(f"[INFO] POST alert sent successfully for actions: {msg.get('result_type')}")
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else:
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print(f"[WARN] POST alert failed with status: {response.status_code}")
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except Exception as e:
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print(f"[ERROR] POST alert request failed: {e}")
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def _post_alert_with_video(self, msg: dict, video_path: str = None):
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"""
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异步发送告警 POST 请求（带视频，multipart/form-data）
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Args:
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msg: 消息内容
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video_path: 视频文件路径（可选）
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"""
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try:
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if video_path and os.path.exists(video_path):
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# 有视频，使用 multipart/form-data 上传
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with open(video_path, 'rb') as f:
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files = {
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'video': f,
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'metadata': (None, json.dumps(msg))
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}
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response = requests.post(constants.ALERT_PUSH_URL, files=files, timeout=10.0)
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else:
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# 无视频，也使用 multipart/form-data
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files = {
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'metadata': (None, json.dumps(msg))
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}
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response = requests.post(constants.ALERT_PUSH_URL, files=files, timeout=5.0)
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if response.status_code == 200:
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logger.info(f"[INFO] POST alert sent successfully for actions: {msg.get('result_type')}")
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else:
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logger.warning(f"[WARN] POST alert failed with status: {response.status_code}")
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except Exception as e:
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logger.error(f"[ERROR] POST alert request failed: {e}")
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def _start_cleanup_thread(self):
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"""启动视频文件清理线程"""
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def cleanup_loop():
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while not self.stop_event.is_set():
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try:
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self._cleanup_expired_files()
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except Exception as e:
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logger.error(f"[ERROR] Cleanup thread error: {e}")
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# 每10分钟检查一次
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self.stop_event.wait(600)
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thread = threading.Thread(target=cleanup_loop, daemon=True, name="video_cleanup")
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thread.start()
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logger.info("[INFO] Video cleanup thread started")
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def _cleanup_expired_files(self):
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"""清理过期的视频文件"""
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output_dir = constants.VIDEO_CLIP_OUTPUT_DIR
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if not output_dir or not os.path.exists(output_dir):
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return
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retention_seconds = constants.VIDEO_CLIP_RETENTION_SECONDS
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current_time = time.time()
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try:
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for filename in os.listdir(output_dir):
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if not filename.endswith('.mp4'):
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continue
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filepath = os.path.join(output_dir, filename)
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if os.path.isfile(filepath):
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file_mtime = os.path.getmtime(filepath)
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if current_time - file_mtime > retention_seconds:
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try:
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os.remove(filepath)
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logger.info(f"[INFO] Cleaned up expired video: {filename}")
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except Exception as e:
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logger.error(f"[ERROR] Failed to delete {filename}: {e}")
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except Exception as e:
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logger.error(f"[ERROR] Cleanup expired files error: {e}")
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def _create_or_get_video_clip(self, segment_path: str, segment_duration: float = None) -> str | None:
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"""
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创建或获取视频剪辑
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Args:
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segment_path: 当前TS分片路径
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segment_duration: 当前分片时长（秒）
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Returns:
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MP4文件路径，失败返回 None
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"""
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if not segment_path:
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return None
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# 检查缓存
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if segment_path in self._mp4_cache:
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cached_path = self._mp4_cache[segment_path]
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if os.path.exists(cached_path):
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return cached_path
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else:
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# 缓存失效，移除
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del self._mp4_cache[segment_path]
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# 解析分片信息，构建MP4路径
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camera_id, timestamp, seq = parse_segment_info(segment_path)
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if not camera_id:
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logger.warning(f"[WARN] Failed to parse segment info: {segment_path}")
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return None
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output_dir = constants.VIDEO_CLIP_OUTPUT_DIR
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if not output_dir:
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logger.warning("[WARN] VIDEO_CLIP_OUTPUT_DIR not configured")
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return None
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# 确保输出目录存在
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os.makedirs(output_dir, exist_ok=True)
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# MP4文件名
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mp4_filename = f"{camera_id}_{timestamp}_{seq}.mp4"
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mp4_path = os.path.join(output_dir, mp4_filename)
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# 检查是否已存在
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if os.path.exists(mp4_path):
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self._mp4_cache[segment_path] = mp4_path
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return mp4_path
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# 计算需要回溯的分片数量
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clip_duration = constants.VIDEO_CLIP_DURATION_SECONDS
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default_segment_duration = constants.VIDEO_CLIP_DEFAULT_SEGMENT_DURATION
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effective_duration = segment_duration if segment_duration else default_segment_duration
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if effective_duration <= 0:
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effective_duration = default_segment_duration
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n_segments = int(clip_duration / effective_duration) + 1
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# 获取需要合并的分片
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ts_files = get_segments_before_current(segment_path, n_segments)
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if not ts_files:
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logger.warning(f"[WARN] No segments found for clip: {segment_path}")
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return None
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# 合并TS为MP4
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if self._merge_ts_to_mp4(ts_files, mp4_path):
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self._mp4_cache[segment_path] = mp4_path
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return mp4_path
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return None
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def _merge_ts_to_mp4(self, ts_files: list, output_path: str) -> bool:
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"""
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使用 ffmpeg 合并 TS 分片为 MP4
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Args:
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ts_files: TS文件路径列表（按时间顺序）
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output_path: 输出MP4路径
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Returns:
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是否成功
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"""
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if not ts_files:
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return False
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try:
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# 构建 concat 字符串
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concat_str = "|".join(ts_files)
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# ffmpeg 命令
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cmd = [
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'ffmpeg',
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'-i', f'concat:{concat_str}',
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'-c', 'copy',
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'-y', # 覆盖输出文件
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output_path
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]
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# 执行命令
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result = subprocess.run(
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cmd,
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capture_output=True,
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timeout=60 # 60秒超时
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)
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if result.returncode == 0:
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logger.info(f"[INFO] Created video clip: {output_path}")
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return True
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else:
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logger.error(f"[ERROR] ffmpeg failed: {result.stderr.decode()}")
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return False
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except subprocess.TimeoutExpired:
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logger.error(f"[ERROR] ffmpeg timeout for {output_path}")
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return False
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except FileNotFoundError:
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logger.error("[ERROR] ffmpeg not found, please install ffmpeg")
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return False
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except Exception as e:
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logger.error(f"[ERROR] Failed to merge TS files: {e}")
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return False
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def _process_alert_with_video(self, msg: dict, segment_path: str, segment_duration: float):
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"""
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处理告警（含视频剪辑）- 在线程池中执行
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Args:
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msg: 基础消息
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segment_path: 当前TS分片路径
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segment_duration: 当前分片时长
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"""
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# 尝试创建/获取视频剪辑
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mp4_path = None
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if segment_path:
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mp4_path = self._create_or_get_video_clip(segment_path, segment_duration)
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# 展开 ori_alert
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expanded_msgs = self._expand_msg_by_ori_alert(msg)
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# 发送每个展开后的消息
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for expanded_msg in expanded_msgs:
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self._post_alert_with_video(expanded_msg, mp4_path)
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def _create_detector(self, params):
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"""创建检测器实例"""
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# 使用 type(self) 访问类属性，避免 lambda 被绑定 self 参数
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factory = type(self).DETECTOR_FACTORY
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if factory is None:
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raise NotImplementedError("子类必须提供 DETECTOR_FACTORY")
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return factory(params)
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def _filter_duplicate_alerts(self, cam_id: int, alerts: list, current_time: float) -> list:
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"""
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过滤5秒内重复的告警
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Args:
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cam_id: 摄像头ID
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alerts: 当前帧的告警列表
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current_time: 当前时间戳
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Returns:
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符合推送条件的action列表
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"""
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if cam_id not in self.last_alert_push_time:
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self.last_alert_push_time[cam_id] = {}
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push_actions = []
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for alert in alerts:
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action = alert['action']
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last_push = self.last_alert_push_time[cam_id].get(action, 0)
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# 检查是否超过推送间隔
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if current_time - last_push >= ALERT_PUSH_INTERVAL:
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push_actions.append(action)
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# 更新该action的最后推送时间
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self.last_alert_push_time[cam_id][action] = current_time
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return push_actions
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def run(self):
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"""主循环 - 模板方法"""
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target_interval = 1.0 / self.TARGET_FPS
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while not self.stop_event.is_set():
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try:
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item = self.raw_queue.get(timeout=0.5)
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except queue.Empty:
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continue
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try:
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cam_id = item["camera_id"]
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ts = item["timestamp"]
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frame = item["frame"]
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# 抽帧控制
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if ts - self.last_ts.get(cam_id, 0) < target_interval:
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continue
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self.last_ts[cam_id] = ts
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# 获取或创建检测器实例
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if cam_id not in self.detectors:
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camera_config = self.cameras.get(cam_id)
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params = camera_config.params if camera_config else None
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self.detectors[cam_id] = self._create_detector(params)
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detector = self.detectors[cam_id]
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# 执行检测
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result = detector.process_frame(frame.copy(), cam_id, ts)
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result_img = result["image"]
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result_alerts = result["alerts"]
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# 过滤重复告警
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push_actions = self._filter_duplicate_alerts(
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cam_id, result_alerts, time.time()
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)
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# 编码图像
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try:
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img_b64 = self._encode_image_to_base64(result_img)
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except Exception as e:
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logger.error(f"[ERROR] Encode image failed: {e}")
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img_b64 = None
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# 推送结果
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if img_b64 is not None:
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msg = {
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"msg_type": "frame",
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"camera_id": item["camera_index"],
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"timestamp": ts,
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"result_type": push_actions,
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"image_base64": img_b64
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}
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try:
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self.ws_queue.put(msg, timeout=1.0)
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if push_actions and len(push_actions) > 0:
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# 构建消息
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post_msg = msg.copy()
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post_msg['type'] = self.POST_TYPE
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post_msg['ori_alert']: result_alerts
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#备用backup
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#self.post_executor.submit(self._post_alert, post_msg)
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# 获取视频相关信息（仅HLS模式有）
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segment_path = item.get("segment_path")
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segment_duration = item.get("segment_duration")
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# 提交到线程池执行（包含视频剪辑和POST）
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self.post_executor.submit(
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self._process_alert_with_video,
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post_msg,
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segment_path,
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segment_duration
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)
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except queue.Full:
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logger.warning("[WARN] ws_send_queue full, drop frame message")
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except Exception as e:
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logger.error(
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f"[ERROR] Frame processing failed for camera {cam_id if 'cam_id' in locals() else 'unknown'}: {e}")
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logger.exception("Exception details:")
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finally:
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self.raw_queue.task_done()
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# 线程退出时关闭线程池
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self.post_executor.shutdown(wait=False)
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