diff --git a/src/carla_autonomous_driving_perception/carla_model3_spawn_with_spectator.py b/src/carla_autonomous_driving_perception/carla_model3_spawn_with_spectator.py index 8311566eb2..be28081035 100644 --- a/src/carla_autonomous_driving_perception/carla_model3_spawn_with_spectator.py +++ b/src/carla_autonomous_driving_perception/carla_model3_spawn_with_spectator.py @@ -13,29 +13,29 @@ def lerp(a, b, t): # 语义分割调色板（Cityscapes格式，兼容所有CARLA版本） CITYSCAPES_PALETTE = [ - (0, 0, 0), # 0: 未标注 - (70, 70, 70), # 1: 建筑物 - (100, 40, 40), # 2: 围栏 - (55, 90, 80), # 3: 其他 - (220, 20, 60), # 4: 行人 - (153, 153, 153), # 5: 杆子 - (157, 234, 50), # 6: 道路线 - (128, 64, 128), # 7: 道路 - (244, 35, 232), # 8: 人行道 - (107, 142, 35), # 9: 植被 - (0, 0, 142), # 10: 车辆 - (102, 102, 156), # 11: 墙壁 - (220, 220, 0), # 12: 交通灯 - (70, 130, 180), # 13: 交通标志 - (81, 0, 81), # 14: 天 - (150, 100, 100), # 15: 地形 - (230, 150, 140), # 16: 护栏 - (180, 165, 180), # 17: 栅栏 - (250, 170, 30), # 18: 静态 - (110, 190, 160), # 19: 动态 - (170, 120, 50), # 20: 其他 - (45, 60, 150), # 21: 水 - (145, 170, 100) # 22: 路面标记 + (0, 0, 0), # 0: Unlabeled + (70, 70, 70), # 1: Building + (100, 40, 40), # 2: Fence + (55, 90, 80), # 3: Other + (220, 20, 60), # 4: Pedestrian (red) + (153, 153, 153), # 5: Pole + (157, 234, 50), # 6: RoadLine + (128, 64, 128), # 7: Road + (244, 35, 232), # 8: Sidewalk + (107, 142, 35), # 9: Vegetation + (0, 0, 142), # 10: Vehicle (blue) + (102, 102, 156), # 11: Wall + (220, 220, 0), # 12: TrafficLight + (70, 130, 180), # 13: TrafficSign + (81, 0, 81), # 14: Sky + (150, 100, 100), # 15: Terrain + (230, 150, 140), # 16: GuardRail + (180, 165, 180), # 17: Fence + (250, 170, 30), # 18: Static + (110, 190, 160), # 19: Dynamic + (170, 120, 50), # 20: Other + (45, 60, 150), # 21: Water + (145, 170, 100) # 22: RoadMarking ] # 1. 连接CARLA服务器并配置强同步模式 @@ -134,6 +134,66 @@ def init_semantic_camera(vehicle): actual_npc_count = len(all_vehicles) - 1 print(f"NPC生成完成 | 实际数量: {actual_npc_count}辆（总车辆: {len(all_vehicles)}）") +# ==================== 行人生成核心逻辑 ==================== +# 6.1 生成行人（walker） +walker_count = 50 # 生成50个行人（可调整） +walkers = [] # 存储行人actor +walker_controllers = [] # 存储行人控制器（用于移动） +print(f"\n开始生成{walker_count}个行人...") + +# 获取行人蓝图（随机选择不同行人模型） +walker_bps = bp_lib.filter('walker.pedestrian.*') + +# 获取行人生成点（使用地图的行人专用生成点，或随机点） +walker_spawn_points = [] +for _ in range(walker_count * 2): # 生成双倍候选点，避免重叠 + spawn_point = carla.Transform() + # 随机位置（围绕主角车，半径50-200米，避免太近） + spawn_point.location = world.get_random_location_from_navigation() + if spawn_point.location is not None: + # 确保行人不在车辆正前方（避免生成失败） + if spawn_point.location.distance(vehicle.get_location()) > 20: + walker_spawn_points.append(spawn_point) + +# 生成行人 +for i in range(walker_count): + if i >= len(walker_spawn_points): + break # 候选点用完则停止 + walker_bp = random.choice(walker_bps) + # 设置行人为不可碰撞（避免卡死） + walker_bp.set_attribute('is_invincible', 'false') + try: + walker = world.spawn_actor(walker_bp, walker_spawn_points[i]) + walkers.append(walker) + # 每生成10个行人同步一次，避免服务器卡顿 + if i % 10 == 0: + world.tick() + time.sleep(0.05) + except: + continue + +# 6.2 生成行人控制器并启动自主移动 +if walkers: + # 获取行人控制器蓝图 + controller_bp = bp_lib.find('controller.ai.walker') + # 启动交通管理器（行人也需要同步） + tm = client.get_trafficmanager(8000) + tm.set_synchronous_mode(True) + + for walker in walkers: + # 生成控制器并绑定到行人 + controller = world.spawn_actor(controller_bp, carla.Transform(), walker) + walker_controllers.append(controller) + # 启动行人自主行走（随机目标点，速度1-3 m/s） + controller.start() + controller.go_to_location(world.get_random_location_from_navigation()) + controller.set_max_speed(random.uniform(1.0, 3.0)) + +# 统计实际生成的行人数量 +actual_walker_count = len(walkers) +print(f"行人生成完成 | 实际数量: {actual_walker_count}个") +# ================================================================= + # 7. 启动所有车辆自动驾驶 tm = client.get_trafficmanager(8000) tm.set_synchronous_mode(True) @@ -176,7 +236,7 @@ def set_spectator_smooth(last_transform=None): # 9. 主循环（核心：RGB与语义分割图像拼接显示） print("\n程序运行中，按Ctrl+C或窗口按'q'退出...") -print("功能：RGB与语义分割图像拼接显示 + 车辆自动驾驶 + 平滑视角") +print(f"功能：RGB与语义分割图像拼接显示 + {actual_npc_count}辆车辆 + {actual_walker_count}个行人 + 平滑视角") last_spectator_tf = None clock = pygame.time.Clock() @@ -206,12 +266,13 @@ def set_spectator_smooth(last_transform=None): # 横向拼接两张图像（宽度合并，高度不变） combined_img = cv2.hconcat([rgb_img, sem_rgb]) - # 添加标题区分左右区域 - cv2.putText(combined_img, "RGB Image | Semantic Segmentation", + # 添加标题（纯英文，避免中文乱码/问号） + cv2.putText(combined_img, + f"RGB Image | Semantic Segmentation (Vehicles:{actual_npc_count} Pedestrians:{actual_walker_count})", (10, 30), cv2.FONT_HERSHEY_SIMPLEX, 1.0, (0, 255, 0), 2) - # 显示拼接后的图像 - cv2.imshow('RGB + Semantic Segmentation', combined_img) + # 显示拼接后的图像（窗口标题纯英文） + cv2.imshow('CARLA RGB + Semantic Segmentation (with Pedestrians)', combined_img) if cv2.waitKey(1) == ord('q'): break @@ -220,6 +281,19 @@ def set_spectator_smooth(last_transform=None): except KeyboardInterrupt: print("\n用户中断，清理资源...") finally: + # ==================== 清理行人资源 ==================== + # 停止并销毁行人控制器 + for controller in walker_controllers: + if controller.is_alive: + controller.stop() + controller.destroy() + # 销毁行人 + for walker in walkers: + if walker.is_alive: + walker.destroy() + print(f"已销毁{len(walker_controllers)}个行人控制器 + {len(walkers)}个行人") + # ================================================================= + # 清理传感器 rgb_camera.stop() rgb_camera.destroy() @@ -237,4 +311,4 @@ def set_spectator_smooth(last_transform=None): v.destroy() cv2.destroyAllWindows() - print("资源清理完成，同步模式已关闭") \ No newline at end of file + print(f"资源清理完成，同步模式已关闭（销毁{len(all_vehicles)}辆车辆）") \ No newline at end of file