391 lines
16 KiB
Python
391 lines
16 KiB
Python
# hls_service_kadian.py
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# 基于HLS TS分片的卡点检测服务
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# 支持从本地TS分片读取帧，按照PTS时间间隔模拟实时流
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import av
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import os
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import time
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import threading
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import queue
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import yaml
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import glob
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from dataclasses import dataclass
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from biz.checkpoint.checkpoint_biz import KadianDetector, RTSP_TARGET_FPS, ALERT_PUSH_INTERVAL, FrameProcessorWorker
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from utils.web_socket_sender import WebSocketSender
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from utils.logger import get_logger
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logger = get_logger(__name__)
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WS_HOST = "0.0.0.0"
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WS_PORT = 8765
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# HLS配置
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HLS_SEGMENT_DIR = "D:\\ProjectDoc\\Police\\data\\hls" # TS分片存储目录
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HLS_SEGMENT_PATTERN = "segment_%09d.ts" # TS文件命名模式
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# ========================= 数据结构 =========================
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@dataclass
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class CameraConfig:
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id: int
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name: str
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index: str
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# ========================= TS 文件读取线程 =========================
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class TSReaderWorker(threading.Thread):
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def __init__(self, camera_cfg: CameraConfig, frame_queue: queue.Queue, stop_event: threading.Event):
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super().__init__(daemon=True)
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self.camera_cfg = camera_cfg
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self.frame_queue = frame_queue
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self.stop_event = stop_event
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# HLS状态变量
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self.current_segment_num = -1 # 当前处理的TS分片序号
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self.start_time = None # 播放开始时间
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self.base_pts = None # 第一个帧的PTS基准
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# 队列阈值控制
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self.queue_threshold = 150 # 队列中帧数量阈值
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def find_segment_files(self):
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"""查找TS分片文件，返回排序后的文件名列表"""
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pattern = os.path.join(HLS_SEGMENT_DIR, "segment_*.ts")
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files = glob.glob(pattern)
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# 按文件名中的数字排序
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files.sort(key=lambda x: int(x.split('_')[-1].split('.')[0]))
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return files
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def get_segment_number(self, filename):
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"""从文件名中提取序号"""
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return int(filename.split('_')[-1].split('.')[0])
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def find_nth_largest_segment(self, n):
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"""查找第n大的TS分片"""
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files = self.find_segment_files()
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if len(files) < n:
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return None
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# 返回第n大的文件（从大到小排序）
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files_sorted = sorted(files, key=self.get_segment_number, reverse=True)
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return files_sorted[n-1] if n-1 < len(files_sorted) else None
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def read_ts_frames(self, ts_file):
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"""读取TS文件中的所有帧，返回帧列表和PTS信息"""
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frames_with_pts = []
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try:
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container = av.open(ts_file)
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video_stream = container.streams.video[0]
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for packet in container.demux(video_stream):
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for frame in packet.decode():
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if frame.pts is not None:
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# 计算PTS时间（毫秒）
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pts_ms = frame.pts * video_stream.time_base * 1000
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# 转换为numpy数组
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frame_np = frame.to_ndarray(format='bgr24')
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frames_with_pts.append({
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'frame': frame_np,
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'pts_ms': pts_ms,
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'timestamp': time.time() # 当前系统时间
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})
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container.close()
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return frames_with_pts
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except Exception as e:
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logger.error(f"[ERROR] Failed to read TS file {ts_file}: {e}")
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return []
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def initialize_playback(self):
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"""初始化播放：找到第3大的TS分片，建立时间基准"""
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while not self.stop_event.is_set():
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# 查找第3大的TS分片
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third_largest = self.find_nth_largest_segment(3)
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if third_largest is not None:
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segment_num = self.get_segment_number(third_largest)
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logger.info(f"[INFO] Found segment {segment_num}, starting playback")
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# 读取该分片的所有帧
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frames = self.read_ts_frames(third_largest)
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if frames:
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# 设置基准时间
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self.current_segment_num = segment_num
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self.start_time = time.time()
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self.base_pts = frames[0]['pts_ms']
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return frames
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else:
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logger.warning(f"[WARN] No frames found in segment {segment_num}")
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# 等待0.5秒后重试
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time.sleep(0.5)
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logger.warning(f"[WARN] No frames found, waiting...")
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return []
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def find_next_segment(self):
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"""查找下一个TS分片"""
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next_segment_num = self.current_segment_num + 1
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next_segment_path = os.path.join(HLS_SEGMENT_DIR, f"segment_{next_segment_num:09d}.ts")
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# 检查+1, +2, +3是否存在
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check_segments = [
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next_segment_num + 0, # +1
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next_segment_num + 1, # +2
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next_segment_num + 2 # +3
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]
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for seg_num in check_segments:
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seg_path = os.path.join(HLS_SEGMENT_DIR, f"segment_{seg_num:09d}.ts")
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if not os.path.exists(seg_path):
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return None
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# 所有检查的分片都存在，返回下一个分片
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return next_segment_path
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def run(self):
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"""主循环：读取TS文件并将帧放入队列"""
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try:
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# 初始化播放
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current_frames = self.initialize_playback()
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if not current_frames:
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logger.error("[ERROR] Failed to initialize playback")
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return
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while not self.stop_event.is_set():
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try:
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# 检查队列大小，如果超过阈值则等待
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if self.frame_queue.qsize() >= self.queue_threshold:
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time.sleep(0.2)
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continue
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# 当前分片播放完毕，查找下一个分片
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next_segment = self.find_next_segment()
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if next_segment is not None:
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# 读取下一个分片
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logger.info(f"[INFO] Starting to read TS segment: {next_segment}")
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start_time = time.time()
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current_frames = self.read_ts_frames(next_segment)
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elapsed_time = (time.time() - start_time) * 1000 # 转换为毫秒
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logger.info(f"[INFO] Finished reading TS segment, took {elapsed_time:.1f}ms")
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if current_frames:
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self.current_segment_num += 1
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frame_index = 0
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logger.info(f"[INFO] Switching to segment {self.current_segment_num}")
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else:
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logger.warning(f"[WARN] Failed to read next segment, waiting...")
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time.sleep(0.5)
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continue
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else:
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# 下一个分片不存在，等待
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logger.warning(f"[WARN] No next segment found, waiting...")
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time.sleep(0.5)
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continue
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# 一次性将所有帧放入队列
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for frame_data in current_frames:
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item = {
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"frame": frame_data['frame'],
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"pts_ms": frame_data['pts_ms']
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}
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try:
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# 队列满时处理
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if self.frame_queue.full():
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try:
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self.frame_queue.get_nowait()
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except queue.Empty:
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pass
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self.frame_queue.put(item, timeout=0.5)
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except queue.Full:
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logger.warning(f"[WARN] Queue full, dropping frame from {self.camera_cfg.name}")
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break # 如果队列满，停止放入更多帧
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except Exception as e:
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logger.error(f"[ERROR] TSReaderWorker loop error: {e}")
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time.sleep(1) # 出错后等待1秒再继续
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except Exception as e:
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logger.error(f"[ERROR] TSReaderWorker main error: {e}")
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logger.info("[INFO] TSReaderWorker will restart in 3 seconds...")
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time.sleep(3)
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# 重新启动线程
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self.run()
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# ========================= 帧处理线程 =========================
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class HLSFrameProcessor(threading.Thread):
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def __init__(self, camera_cfg: CameraConfig, frame_queue: queue.Queue, raw_queue: queue.Queue, stop_event: threading.Event):
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super().__init__(daemon=True)
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self.camera_cfg = camera_cfg
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self.frame_queue = frame_queue
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self.raw_queue = raw_queue
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self.stop_event = stop_event
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# 时间同步相关
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self.start_time = None
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self.base_pts = None
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self.last_process_time = None # 上次处理时间
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def run(self):
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"""主循环：从帧队列获取帧，按照PTS时间间隔放入raw_queue"""
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try:
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while not self.stop_event.is_set():
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try:
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# 从帧队列获取帧数据（阻塞等待）
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frame_data = self.frame_queue.get(timeout=1.0)
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# 初始化时间基准
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if self.start_time is None:
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self.start_time = time.time()
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self.base_pts = frame_data['pts_ms']
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logger.info("[INFO] Frame processor initialized time base")
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# 计算预期的播放时间
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expected_play_time = self.start_time + (frame_data['pts_ms'] - self.base_pts) / 1000.0
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current_time = time.time()
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# 计算时间差
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time_diff = current_time - expected_play_time
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# 打印距离上次处理过去的时间
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current_time = time.time()
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if self.last_process_time is not None:
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time_since_last = (current_time - self.last_process_time) * 1000 # 转换为毫秒
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logger.info(f"[INFO] Time since last frame: {time_since_last:.1f}ms, pts: {frame_data['pts_ms']} ms")
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self.last_process_time = current_time
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# 时间同步策略
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if time_diff > 0.06: # 超过60ms，播放落后 （3帧）
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# 跳过这一帧追赶
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logger.info(f"[DEBUG] Lagging behind by {time_diff*1000:.1f}ms, skipping frame")
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self.frame_queue.task_done()
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continue
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elif time_diff < -0.06: # 超前60ms，需要等待 （3帧）
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# 等待到正确的时间点
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wait_time = -time_diff
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if wait_time > 0.1: # 如果等待时间过长，重置时间基准
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logger.info(f"[WARN] Too far ahead, resetting time base")
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self.start_time = current_time
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self.base_pts = frame_data['pts_ms']
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else:
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time.sleep(wait_time)
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logger.info(f"[DEBUG] Waiting for {wait_time*1000:.1f}ms")
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# 时间同步良好，放入raw_queue
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item = {
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"camera_id": self.camera_cfg.id,
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"camera_name": self.camera_cfg.name,
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"timestamp": current_time,
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"frame": frame_data["frame"],
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}
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try:
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# raw_queue满时处理
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if self.raw_queue.full():
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try:
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self.raw_queue.get_nowait()
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self.raw_queue.task_done()
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except queue.Empty:
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pass
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self.raw_queue.put(item, timeout=0.5)
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except queue.Full:
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logger.warning(f"[WARN] Raw queue full, dropping frame from {self.camera_cfg.name}")
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# 标记帧处理完成
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self.frame_queue.task_done()
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time.sleep(0.02)
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except queue.Empty:
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# 队列为空，继续等待
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time.sleep(0.02)
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continue
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except Exception as e:
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logger.error(f"[ERROR] HLSFrameProcessor loop error: {e}")
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time.sleep(1) # 出错后等待1秒再继续
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except Exception as e:
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logger.error(f"[ERROR] HLSFrameProcessor main error: {e}")
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logger.info("[INFO] HLSFrameProcessor will restart in 3 seconds...")
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time.sleep(3)
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# 重新启动线程
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self.run()
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# ========================= 服务主类 =========================
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class HLSKadianService:
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def __init__(self, config_path: str = "config.yaml"):
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with open(config_path, "r", encoding="utf-8") as f:
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cfg = yaml.safe_load(f)
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self.cameras = [CameraConfig(id=c["id"], name=c.get("name", f"cam_{c['id']}"), index=c["index"])
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for c in cfg.get("cameras", [])]
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self.stop_event = threading.Event()
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self.frame_queue = queue.Queue(maxsize=2000) # 帧队列，容量较大
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self.raw_queue = queue.Queue(maxsize=3) # 原始队列，容量较小
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self.ws_queue = queue.Queue(maxsize=1000) # WebSocket队列
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self.ts_reader_workers = []
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self.frame_processor_workers = []
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self.biz_processor = FrameProcessorWorker(self.raw_queue, self.ws_queue, self.stop_event)
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self.ws_sender = WebSocketSender(self.ws_queue, self.stop_event, WS_HOST, WS_PORT)
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def start(self):
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# 确保TS分片目录存在
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os.makedirs(HLS_SEGMENT_DIR, exist_ok=True)
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self.ws_sender.start()
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self.biz_processor.start()
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# 为每个摄像头启动TS读取线程和帧处理线程
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for cam in self.cameras:
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# 启动TS读取线程
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ts_reader = TSReaderWorker(cam, self.frame_queue, self.stop_event)
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ts_reader.start()
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self.ts_reader_workers.append(ts_reader)
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# 启动帧处理线程
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frame_processor = HLSFrameProcessor(cam, self.frame_queue, self.raw_queue, self.stop_event)
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frame_processor.start()
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self.frame_processor_workers.append(frame_processor)
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logger.info("[INFO] HLS Kadian Service started")
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def stop(self):
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self.stop_event.set()
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self.frame_queue.join()
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self.raw_queue.join()
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self.ws_queue.join()
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for w in self.ts_reader_workers:
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w.join(timeout=2.0)
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for w in self.frame_processor_workers:
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w.join(timeout=2.0)
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self.biz_processor.join(timeout=2.0)
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self.ws_sender.join(timeout=2.0)
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logger.info("[INFO] Service stopped")
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if __name__ == "__main__":
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service = HLSKadianService("config.yaml")
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service.start()
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try:
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while True:
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time.sleep(1)
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except KeyboardInterrupt:
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service.stop() |