优化自适应帧率

src/tracking_car/config.yaml

@@ -4,27 +4,23 @@ port: 2000
 timeout: 20.0
 
 # ======================== 传感器配置 ========================
-# 增大分辨率和视野，提升远距离检测能力
-img_width: 1280          # ↑ 从640提升到1280，让远处车辆更清晰
-img_height: 960          # ↑ 从480提升到960
-fov: 110                 # ↑ 从90提升到110，扩大视野范围
+img_width: 1280
+img_height: 960
+fov: 110
 sensor_tick: 0.05
-use_lidar: true          # 保持LiDAR开启，用于距离验证
+use_lidar: true
 
 # ======================== LiDAR配置 ========================
 lidar_channels: 32
 lidar_range: 100.0
 lidar_points_per_second: 500000
 
 # ======================== 检测模型配置 ========================
-# 关键优化：降低阈值，增大输入尺寸
-yolo_model: "yolov8n.pt"          # 可选：换成 yolov8m.pt 效果更好
-conf_thres: 0.25                  # ↓ 从0.5降低到0.25，检测更多远处目标
-iou_thres: 0.3                    # 保持
-device: "cuda" if torch.cuda.is_available() else "cpu"
-yolo_imgsz_max: 640               # ↑ 从320提升到640，提升小目标检测能力
-yolo_iou: 0.45
-yolo_quantize: false
+yolo_model: "yolov8n.pt"
+conf_thres: 0.25
+iou_thres: 0.3
+device: "cpu"  
+yolo_imgsz_max: 640
 
 # ======================== 跟踪算法配置 ========================
 max_age: 5
@@ -39,63 +35,25 @@ display_fps: 30
 
 # ======================== 轨迹历史配置 ========================
 track_history_len: 20
-track_line_width: 2
-track_alpha: 0.6
 
 # ======================== 行为分析配置 ========================
-# 针对远距离检测调整参数
-stop_speed_thresh: 0.8            # ↓ 降低停车速度阈值
+stop_speed_thresh: 0.8
 stop_frames_thresh: 5
 overtake_speed_ratio: 1.5
-overtake_dist_thresh: 60.0        # ↑ 增大超车距离阈值
+overtake_dist_thresh: 60.0
 lane_change_thresh: 0.4
 brake_accel_thresh: 2.0
 turn_angle_thresh: 15.0
-danger_dist_thresh: 15.0          # ↑ 增大危险距离阈值，适应更远检测
+danger_dist_thresh: 15.0
 predict_frames: 10
 
 # ======================== 天气与NPC配置 ========================
-default_weather: "clear"          # 使用清晰天气，有利于远距离检测
+default_weather: "clear"
 num_npcs: 20
 
-# ======================== 性能优化配置 ========================
-auto_adjust_detection: true       # 自动调整检测参数
-smooth_alpha: 0.2
-fps_window_size: 15
-
-# ======================== 传感器融合配置 ========================
-fuse_lidar_vision: true           # 启用传感器融合
-
-# ======================== 数据记录配置 ========================
-record_data: true
-record_dir: "track_records"
-record_format: "csv"
-record_fps: 10
-save_screenshots: false
-
-# ======================== 3D可视化配置 ========================
-use_3d_visualization: true
-pcd_view_size: 800
-
-# ======================== 检测框样式配置 ========================
-det_box_color: [255, 0, 0]        # 蓝色框
-det_box_thickness: 2
-det_label_bg_color: [0, 0, 0]     # 黑色背景
-det_label_text_color: [255, 255, 255]  # 白色文字
-det_label_font_scale: 0.5
-det_label_padding: 5
-
 # ======================== 视角控制配置 ========================
 view:
-  default_mode: "satellite"       # 默认视角模式
-  satellite_height: 50.0          # 卫星视角高度
-  behind_distance: 10.0           # 后方视角距离
-  first_person_height: 1.6        # 第一人称视角高度
-
-# ======================== 新增：远距离检测专用配置 ========================
-far_detection:
-  enabled: true                   # 启用远距离检测模式
-  min_confidence: 0.2            # 远距离目标最低置信度
-  min_pixel_size: 15             # 最小检测像素尺寸（宽或高）
-  scale_factor: 1.5              # 图像缩放因子用于小目标检测
-  enable_multi_scale: true       # 启用多尺度检测
+  default_mode: "satellite"
+  satellite_height: 50.0
+  behind_distance: 10.0
+  first_person_height: 1.6

src/tracking_car/main.py

@@ -31,7 +31,6 @@
     print("  - tracker.py")
     sys.exit(1)
 
-
 # ======================== Configuration Management ========================
 
 def load_config(config_path=None):
@@ -115,7 +114,6 @@ def load_config(config_path=None):
 
     return default_config
 
-
 def setup_carla_client(config):
     """
     Setup CARLA client
@@ -157,7 +155,6 @@ def setup_carla_client(config):
         logger.error(f"[ERROR] Failed to connect to CARLA server: {e}")
         return None, None
 
-
 def set_weather(world, weather_name):
     """
     Set weather
@@ -182,7 +179,6 @@ def set_weather(world, weather_name):
     else:
         logger.warning(f"Unknown weather: {weather_name}, using clear weather")
 
-
 # ======================== Visualization (Enhanced: Independent stats window) ========================
 
 class Visualizer:
@@ -1117,7 +1113,6 @@ def destroy(self):
         cv2.destroyAllWindows()
         logger.info("[OK] All visualization windows closed")
 
-
 # ======================== Main Program ========================
 
 class CarlaTrackingSystem:
@@ -1534,33 +1529,35 @@ def _handle_keyboard_input(self, key):
                 logger.info(f"[VIEW] 切换到 {mode_name}")
 
     def _control_frame_rate(self, current_fps):
-        """Control frame rate"""
+        """自适应帧率控制（简单版）"""
         import time
-        target_fps = self.config.get('display_fps', 30)
+        import psutil
+
+        # 获取当前系统负载
+        cpu_usage = psutil.cpu_percent()
+
+        # 根据CPU使用率动态调整目标FPS
+        if cpu_usage > 85:  # 非常高负载
+            target_fps = max(10, self.config.get('display_fps', 30) * 0.5)
+        elif cpu_usage > 70:  # 高负载
+            target_fps = max(15, self.config.get('display_fps', 30) * 0.7)
+        elif cpu_usage < 40:  # 低负载，可以尝试更高FPS
+            target_fps = min(60, self.config.get('display_fps', 30) * 1.5)
+        elif cpu_usage < 60:  # 中等负载
+            target_fps = min(45, self.config.get('display_fps', 30) * 1.2)
+        else:  # 正常负载
+            target_fps = self.config.get('display_fps', 30)
+
         if target_fps <= 0:
             return
-        
+
         target_interval = 1.0 / target_fps
-        
-        # If frame rate is too high, sleep appropriately
-        if current_fps > target_fps * 1.2:  # Allow 20% fluctuation
+
+        # 如果帧率过高，适当休眠
+        if current_fps > target_fps * 1.2:  # 允许20%波动
             sleep_time = max(0, target_interval - (1.0 / current_fps))
             time.sleep(sleep_time)
 
-    def _save_screenshot(self):
-        """Save screenshot"""
-        try:
-            import time
-            timestamp = time.strftime("%Y%m%d_%H%M%S")
-            filename = f"screenshot_{timestamp}_{self.frame_count:06d}.png"
-
-            # Get currently displayed image
-            screenshot = self.sensor_manager.get_camera_image()
-            if utils.valid_img(screenshot):
-                utils.save_image(screenshot, filename)
-                logger.info(f"[SCREENSHOT] Screenshot saved: {filename}")
-        except Exception as e:
-            logger.warning(f"Screenshot save failed: {e}")
 
     def _print_status(self, stats_data):
         """Print system status"""
@@ -1613,7 +1610,6 @@ def cleanup(self):
 
         logger.info("[OK] Resource cleanup complete")
 
-
 # ======================== Main Function ========================
 
 def main():
@@ -1692,7 +1688,6 @@ def main():
         logger.info("[END] Program ended")
         logger.info("=" * 50)
 
-
 if __name__ == "__main__":
     # 检查配置
     try:

src/tracking_car/requirements.txt

@@ -1,16 +1,17 @@
 # 核心依赖
+# 可选依赖
+
 carla>=0.9.14
-opencv-python>=4.8.0
+loguru>=0.7.0
+matplotlib>=3.7.0
+numba>=0.57.0
 numpy>=1.24.0
-torch>=2.0.0
-ultralytics>=8.0.0
 open3d>=0.17.0
+opencv-python>=4.8.0
+pandas>=2.0.0
 psutil>=5.9.0
-scipy>=1.10.0
-scikit-learn>=1.2.0
-numba>=0.57.0
-loguru>=0.7.0
 pyyaml>=6.0.0
-# 可选依赖
-matplotlib>=3.7.0
-pandas>=2.0.0
+scikit-learn>=1.2.0
+scipy>=1.10.0
+torch>=2.0.0
+ultralytics>=8.0.0

src/tracking_car/sensors.py

@@ -3,6 +3,7 @@
 包含：相机、LiDAR传感器封装和管理
 """
 
+import random  # 添加随机模块支持
 import carla
 import cv2
 import numpy as np
@@ -23,7 +24,6 @@
 import open3d as o3d
 from sklearn.cluster import DBSCAN
 
-
 class CameraManager:
     """相机管理器"""
 
@@ -147,7 +147,6 @@ def destroy(self):
                 logger.warning(f"销毁相机失败: {e}")
         self.camera = None
 
-
 class LiDARManager:
     """LiDAR管理器"""
 
@@ -368,8 +367,6 @@ def destroy(self):
                 logger.warning(f"销毁LiDAR失败: {e}")
         self.lidar = None
 
-# ======================== 视角管理器 ========================
-
 class SpectatorManager:
     """CARLA视角管理器 - 提供卫星视角跟随"""
 
@@ -681,9 +678,6 @@ def destroy(self):
 
         logger.info("✅ 所有传感器已销毁")
 
-
-# ======================== 工具函数 ========================
-
 def create_ego_vehicle(world, config, spawn_points=None):
     """
     创建自车
@@ -797,7 +791,6 @@ def create_ego_vehicle(world, config, spawn_points=None):
         traceback.print_exc()
         return None
 
-
 def spawn_npc_vehicles(world, config, count=None):
     """
     生成NPC车辆
@@ -848,7 +841,6 @@ def spawn_npc_vehicles(world, config, count=None):
                 continue
 
             # 随机选择车辆蓝图
-            import random
             vehicle_bp = random.choice(vehicle_bps)
 
             # 尝试生成
@@ -874,7 +866,6 @@ def spawn_npc_vehicles(world, config, count=None):
         logger.error(f"生成NPC车辆失败: {e}")
         return 0
 
-
 def clear_all_actors(world, exclude_ids=None):
     """
     清理所有演员（车辆和传感器）
@@ -927,9 +918,6 @@ def clear_all_actors(world, exclude_ids=None):
     except Exception as e:
         logger.warning(f"清理演员时出错: {e}")
 
-
-# ======================== 测试函数 ========================
-
 def test_sensor_manager():
     """测试传感器管理器"""
     print("=" * 50)
@@ -953,6 +941,5 @@ def test_sensor_manager():
 
     return True
 
-
 if __name__ == "__main__":
     test_sensor_manager()