perf: optimize video playback and detection interval
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@ -85,3 +85,14 @@ logging:
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# 调试图像保存路径
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debug_image_path: "debug/"
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# 性能保护配置
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performance:
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# 处理帧率上限（每秒最多处理多少帧），0 或 null 表示不限制
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max_processing_fps: 0
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# 帧间隔，1 表示每帧处理，2 表示处理 1 帧跳过 1 帧
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frame_stride: 1
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# 检测时间间隔（秒），0 表示每帧都检测
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detection_interval_seconds: 0.1 # 每秒检测10次
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238
main.py
238
main.py
@ -77,6 +77,7 @@ class YantaiVisionXSystem:
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self.alarm_manager = AlarmManager(self.logger)
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self.tech_ui = TechUI()
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self.performance_limiter = PerformanceLimiter()
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self._detection_interval_seconds: float = 0.0
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self._window_internal_name = "YantaiVisionX Monitor"
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self._window_display_name = "烟台蓬莱国际机场低能见度识别软件"
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@ -118,16 +119,24 @@ class YantaiVisionXSystem:
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max_fps = performance_cfg.get("max_processing_fps")
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frame_stride = performance_cfg.get("frame_stride", 1)
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detection_interval = performance_cfg.get("detection_interval_seconds", 0)
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self.performance_limiter.update_settings(max_processing_fps=max_fps, frame_stride=frame_stride)
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try:
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detection_interval_value = float(detection_interval)
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except (TypeError, ValueError):
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detection_interval_value = 0.0
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self._detection_interval_seconds = detection_interval_value if detection_interval_value and detection_interval_value > 0 else 0.0
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self.logger.log_info(
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f"性能限制器配置: max_fps={self.performance_limiter.max_processing_fps}, "
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f"frame_stride={self.performance_limiter.frame_stride}"
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f"frame_stride={self.performance_limiter.frame_stride}, "
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f"detection_interval={self._detection_interval_seconds}s"
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)
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def update_performance_settings(
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self,
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max_processing_fps: Optional[float] = None,
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frame_stride: Optional[int] = None,
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detection_interval_seconds: Optional[float] = None,
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) -> None:
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"""运行中动态调整性能限制参数"""
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@ -135,6 +144,12 @@ class YantaiVisionXSystem:
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max_processing_fps=max_processing_fps,
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frame_stride=frame_stride,
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)
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if detection_interval_seconds is not None:
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try:
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value = float(detection_interval_seconds)
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except (TypeError, ValueError):
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value = 0.0
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self._detection_interval_seconds = value if value > 0 else 0.0
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def initialize_system(self, camera_config=None) -> bool:
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"""
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@ -210,10 +225,24 @@ class YantaiVisionXSystem:
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self.logger.log_error("摄像头打开失败")
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return
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self.logger.log_info("开始 LED 检测...")
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# 获取视频/摄像头帧率，用于控制播放速度
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video_fps = self.camera.get_fps()
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if video_fps <= 0:
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video_fps = 30.0
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frame_interval = 1.0 / video_fps # 每帧间隔（秒）
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self.logger.log_info(f"开始 LED 检测... 帧率: {video_fps:.1f}fps")
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limiter = self.performance_limiter
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frame_index = 0
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last_detection_result = None
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last_detection_time: Optional[float] = None
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display_frame_interval = 5 # 每5帧显示一次，降低UI绑定开销
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# 性能统计
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loop_start = time.perf_counter()
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total_display_time = 0.0
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display_count = 0
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try:
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while self.is_running:
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@ -225,45 +254,77 @@ class YantaiVisionXSystem:
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current_frame_index = frame_index
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frame_index += 1
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current_time = time.perf_counter()
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# 每100帧输出一次性能统计
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if frame_index % 100 == 0:
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elapsed = current_time - loop_start
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actual_fps = frame_index / elapsed if elapsed > 0 else 0
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avg_display = (total_display_time / display_count * 1000) if display_count > 0 else 0
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print(f"[性能] 帧:{frame_index} 实际FPS:{actual_fps:.1f} 显示次数:{display_count} 平均显示耗时:{avg_display:.1f}ms")
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should_process = True
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if limiter and not limiter.should_process_frame(current_frame_index):
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continue
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# 图像预处理
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enhanced_frame = self.image_enhancer.preprocess_frame(
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frame, mode="normal"
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)
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# LED检测
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detection_result = self.led_detector.detect_leds(enhanced_frame)
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# 记录结果
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self.logger.log_detection_result(detection_result)
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should_process = False
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if last_detection_result is None:
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should_process = True
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alarm_result = self.alarm_manager.process_detection(detection_result)
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for event in alarm_result.events:
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self.logger.log_alarm_event(event)
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for roi_name in alarm_result.recoveries:
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self.logger.log_recovery_event(
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roi_name,
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detection_result.frame_count,
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detection_result.timestamp
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if should_process and self._detection_interval_seconds > 0:
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now = time.perf_counter()
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if (
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last_detection_time is not None
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and (now - last_detection_time) < self._detection_interval_seconds
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):
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should_process = False
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else:
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last_detection_time = now
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elif should_process:
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last_detection_time = time.perf_counter()
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detection_result = None
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if should_process:
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# 图像预处理
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enhanced_frame = self.image_enhancer.preprocess_frame(
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frame, mode="normal"
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)
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# 保存结果
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if (
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save_results
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and self.logger.save_results_enabled
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and detection_result.frame_count % self.logger.save_results_interval == 0
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):
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self.logger.save_result_to_file(detection_result)
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# 显示结果
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if self.display_enabled:
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self._display_results(frame, detection_result)
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if limiter:
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limiter.enforce_rate_limit()
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# LED检测
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detection_result = self.led_detector.detect_leds(enhanced_frame)
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last_detection_result = detection_result
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# 记录结果
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self.logger.log_detection_result(detection_result)
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alarm_result = self.alarm_manager.process_detection(detection_result)
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for event in alarm_result.events:
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self.logger.log_alarm_event(event)
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for roi_name in alarm_result.recoveries:
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self.logger.log_recovery_event(
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roi_name,
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detection_result.frame_count,
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detection_result.timestamp
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)
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# 保存结果
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if (
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save_results
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and self.logger.save_results_enabled
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and detection_result.frame_count % self.logger.save_results_interval == 0
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):
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self.logger.save_result_to_file(detection_result)
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display_detection_result = last_detection_result if last_detection_result is not None else detection_result
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# 控制显示帧率：每N帧显示一次，避免UI绑定拖慢速度
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should_display = (current_frame_index % display_frame_interval == 0)
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# 显示结果
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if self.display_enabled and display_detection_result is not None and should_display:
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t0 = time.perf_counter()
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self._display_results(frame, display_detection_result)
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total_display_time += time.perf_counter() - t0
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display_count += 1
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# 检查退出条件
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if cv2.waitKey(1) & 0xFF == ord('q'):
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break
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@ -310,14 +371,23 @@ class YantaiVisionXSystem:
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results = [] if self.logger.save_results_enabled else None
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last_frame = None
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last_detection_result = None
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last_detection_time: Optional[float] = None
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display_frame_interval = 5 # 每5帧显示一次，降低UI绑定开销
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self.logger.log_info(f"开始处理视频: {video_path}")
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limiter = self.performance_limiter
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frame_index = 0
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# 性能统计
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loop_start = time.perf_counter()
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total_display_time = 0.0
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display_count = 0
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try:
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while self.is_running:
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current_time = time.perf_counter()
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success, frame = self.camera.read_frame()
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if not success:
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if self.display_enabled and last_frame is not None:
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@ -326,46 +396,78 @@ class YantaiVisionXSystem:
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current_frame_index = frame_index
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frame_index += 1
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# 每100帧输出一次性能统计
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if frame_index % 100 == 0:
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elapsed = current_time - loop_start
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actual_fps = frame_index / elapsed if elapsed > 0 else 0
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avg_display = (total_display_time / display_count * 1000) if display_count > 0 else 0
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print(f"[性能] 帧:{frame_index} 实际FPS:{actual_fps:.1f} 显示次数:{display_count} 平均显示耗时:{avg_display:.1f}ms")
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should_process = True
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if limiter and not limiter.should_process_frame(current_frame_index):
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continue
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# 图像预处理
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enhanced_frame = self.image_enhancer.preprocess_frame(
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frame, mode="normal"
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)
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# LED检测
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detection_result = self.led_detector.detect_leds(enhanced_frame)
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if results is not None:
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results.append(detection_result)
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should_process = False
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if last_detection_result is None:
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should_process = True
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if should_process and self._detection_interval_seconds > 0:
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now = time.perf_counter()
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if (
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last_detection_time is not None
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and (now - last_detection_time) < self._detection_interval_seconds
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):
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should_process = False
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else:
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last_detection_time = now
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elif should_process:
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last_detection_time = time.perf_counter()
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detection_result = None
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if should_process:
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# 图像预处理
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enhanced_frame = self.image_enhancer.preprocess_frame(
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frame, mode="normal"
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)
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# LED检测
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detection_result = self.led_detector.detect_leds(enhanced_frame)
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last_detection_result = detection_result
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if results is not None:
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results.append(detection_result)
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# 记录结果
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if detection_result.frame_count % 100 == 0:
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self.logger.log_detection_result(detection_result)
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alarm_result = self.alarm_manager.process_detection(detection_result)
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for event in alarm_result.events:
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self.logger.log_alarm_event(event)
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for roi_name in alarm_result.recoveries:
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self.logger.log_recovery_event(
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roi_name,
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detection_result.frame_count,
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detection_result.timestamp
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)
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if self.display_enabled and frame is not None:
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last_frame = frame.copy()
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else:
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last_frame = None
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last_detection_result = detection_result
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# 记录结果
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if detection_result.frame_count % 100 == 0:
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self.logger.log_detection_result(detection_result)
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alarm_result = self.alarm_manager.process_detection(detection_result)
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for event in alarm_result.events:
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self.logger.log_alarm_event(event)
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for roi_name in alarm_result.recoveries:
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self.logger.log_recovery_event(
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roi_name,
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detection_result.frame_count,
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detection_result.timestamp
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)
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display_detection_result = last_detection_result if last_detection_result is not None else detection_result
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# 控制显示帧率：每N帧显示一次，避免UI绑定拖慢速度
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should_display = (current_frame_index % display_frame_interval == 0)
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# 显示结果
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if self.display_enabled:
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self._display_results(frame, detection_result)
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if self.display_enabled and display_detection_result is not None and should_display:
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t0 = time.perf_counter()
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self._display_results(frame, display_detection_result)
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total_display_time += time.perf_counter() - t0
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display_count += 1
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if cv2.waitKey(1) & 0xFF == ord('q'):
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break
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if limiter:
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limiter.enforce_rate_limit()
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# 保存批量结果
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if results:
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