修改rtsp获取帧相关代码，使得减少数据丢失，测试有效

rtsp_service_ws_0108.py

@@ -42,7 +42,7 @@ police_prisoner_input_size = 1280
 
 # RTSP 服务配置
 RTSP_TARGET_FPS = 30.0
-FRAMES_PER_SEGMENT = 1800
+FRAMES_PER_SEGMENT = 300
 VIDEO_OUTPUT_DIR = "./videos"
 WS_HOST = "0.0.0.0"
 WS_PORT = 8765
@@ -412,30 +412,91 @@ class RTSPCaptureWorker(threading.Thread):
         self.camera_cfg = camera_cfg
         self.raw_queue = raw_queue
         self.stop_event = stop_event
+        # 添加重连计数器
+        self.reconnect_count = 0
+        self.max_reconnects = 10
 
     def run(self):
-        cap = cv2.VideoCapture(self.camera_cfg.rtsp_url, cv2.CAP_FFMPEG)
+        while not self.stop_event.is_set() and self.reconnect_count < self.max_reconnects:
+            try:
+                # 方法1：使用TCP传输（更稳定）
+                rtsp_url = self.camera_cfg.rtsp_url
+                if "?" not in rtsp_url:
+                    rtsp_url += "?transport=tcp"  # 强制TCP传输
+                else:
+                    rtsp_url += "&transport=tcp"
+
+                # 方法2：添加更多FFmpeg参数
+                cap = cv2.VideoCapture(rtsp_url, cv2.CAP_FFMPEG)
+
+                # 方法3：设置缓冲区大小
+                cap.set(cv2.CAP_PROP_BUFFERSIZE, 10)  # 增加缓冲区
+
+                # 方法4：设置超时和重连参数
+                os.environ["OPENCV_FFMPEG_CAPTURE_OPTIONS"] = \
+                    "rtsp_transport;tcp|buffer_size;1024000|max_delay;500000|stimeout;2000000"
+
+                # 方法5：设置解码器flags，忽略解码错误
+                # cap.set(cv2.CAP_PROP_HW_ACCELERATION, cv2.VIDEO_ACCELERATION_ANY)
+
                 if not cap.isOpened():
                     print(f"[ERROR] Cannot open RTSP: {self.camera_cfg.rtsp_url}")
-            return
-        print(f"[INFO] Capturing {self.camera_cfg.name} (ID:{self.camera_cfg.id})")
+                    time.sleep(2)
+                    self.reconnect_count += 1
+                    continue
+
+                print(f"[INFO] Successfully opened RTSP: {self.camera_cfg.name}")
+                self.reconnect_count = 0  # 重置重连计数
+
+                # # 设置帧率（可选）
+                # cap.set(cv2.CAP_PROP_FPS, 25)
+
                 while not self.stop_event.is_set():
                     ret, frame = cap.read()
                     if not ret:
-                time.sleep(0.2)
-                continue
+                        # 检查流是否结束
+                        print(f"[WARN] Failed to read frame from {self.camera_cfg.name}")
+
+                        # 检查是否还有数据
+                        time.sleep(0.1)
+                        # 尝试几次后重连
+                        break
+
                     item = {
                         "camera_id": self.camera_cfg.id,
                         "camera_name": self.camera_cfg.name,
                         "timestamp": time.time(),
                         "frame": frame,
                     }
+
                     try:
-                self.raw_queue.put(item, timeout=1.0)
-            except queue.Full:
+                        # 添加队列满时的处理
+                        if self.raw_queue.full():
+                            # 丢弃最旧的一帧
+                            try:
+                                self.raw_queue.get_nowait()
+                                self.raw_queue.task_done()
+                            except queue.Empty:
                                 pass
+
+                        self.raw_queue.put(item, timeout=0.5)
+                    except queue.Full:
+                        print(f"[WARN] Queue full, dropping frame from {self.camera_cfg.name}")
+                        continue
+
+                    # 控制读取速度，避免过快
+                    time.sleep(0.02)  # 约50ms间隔
+
                 cap.release()
 
+            except Exception as e:
+                print(f"[ERROR] Error in RTSP capture for {self.camera_cfg.name}: {e}")
+                time.sleep(2)
+                self.reconnect_count += 1
+
+        if self.reconnect_count >= self.max_reconnects:
+            print(f"[ERROR] Max reconnects reached for {self.camera_cfg.name}, stopping.")
+
 
 # ========================= 帧处理线程 =========================
 class FrameProcessorWorker(threading.Thread):
@@ -495,6 +556,7 @@ class FrameProcessorWorker(threading.Thread):
 
     def run(self):
         target_interval = 1.0 / RTSP_TARGET_FPS
+        # last_processed_time = {}  # 记录每个摄像头上次处理时间
         while not self.stop_event.is_set():
             try:
                 item = self.raw_queue.get(timeout=0.5)
@@ -516,6 +578,16 @@ class FrameProcessorWorker(threading.Thread):
                 self.kadian_detectors[cam_id] = KadianDetector()
             detector = self.kadian_detectors[cam_id]
 
+            # # 计算距离上次处理的时间间隔
+            # current_time = time.time()
+            # time_since_last = 0
+            # if cam_id in last_processed_time:
+            #     time_since_last = (current_time - last_processed_time[cam_id]) * 1000  # 转换为毫秒
+            # last_processed_time[cam_id] = current_time
+            #
+            # if time_since_last > 0:
+            #     print(f"[DEBUG] 摄像头{cam_id} - 距离上次处理间隔: {time_since_last:.1f}ms")
+
             # 2) 进行人脸识别（如果启用）
             current_face_alert = None
             face_results = []