feat: task-2 中 arrow 也默认采用 ai，同时 img-raw 默认返回 rgb，适配 line 相关需求。

main.py

@@ -23,24 +23,19 @@ from utils.base_msg import BaseMsg
 from utils.speech_demo import speak
 # from utils.marker_client import MarkerRunner
 
-from task_1.task_1 import run_task_1
-from task_2_5.task_2_5 import run_task_2_5
-from task_3.task_3 import run_task_3, run_task_3_back, pass_up_down
 from task_1.task_1 import run_task_1, run_task_1_back
 from task_2.task_2 import run_task_2, run_task_2_back, run_task_2_demo
 from task_2_5.task_2_5 import run_task_2_5, run_task_2_5_back
+from task_3.task_3 import run_task_3, run_task_3_back, pass_up_down
 from task_4.task_4 import run_task_4, run_task_4_back, go_straight_with_enhanced_calibration
-from task_4.pass_bar import pass_bar
-from task_test.task_left_line import run_task_test
 from task_5.task_5 import run_task_5
 from base_move.turn_degree import turn_degree, turn_degree_v2
-from base_move.center_on_dual_tracks import center_on_dual_tracks
 from base_move.go_to_xy import go_to_x_v2, go_to_y_v2
 
 from utils.log_helper import info
 
 pass_marker = True
-TIME_SLEEP = 3000
+TIME_SLEEP = 3000  # TODO 比赛时改成 5000
 
 def main():
     rclpy.init()  # 新增：在主程序中统一初始化 ROS 2 上下文
@@ -50,27 +45,28 @@ def main():
     msg = robot_control_cmd_lcmt()
     print('2')
     try:
-        info("Recovery stand", "info")
+        # print('yuyin')
-        # Ctrl.base_msg.stand_up()
+        # cv_image = Ctrl.image_processor.get_current_image('ai')
-        print('yuyin')
+        # print('111')
-        cv_image = Ctrl.image_processor.get_current_image('ai')
+        # cv2.imwrite(f"saved_images/firstai.jpg", cv_image)
-        print('111')
-        cv2.imwrite(f"saved_images/firstai.jpg", cv_image)
 
-        print('try out')
+        # print('try out')
         # speak('nihao')
-        # Ctrl.base_msg.stop()  # BUG 垃圾指令 for eat
+        info("Recovery stand", "info")
-        # run_task_1(Ctrl, msg, time_sleep=TIME_SLEEP)
+        Ctrl.base_msg.stand_up()
+        Ctrl.base_msg.stop()  # BUG 垃圾指令 for eat # INFO 但是正式比赛或许也有用
+
+        # TAG task - 1
+        run_task_1(Ctrl, msg, time_sleep=TIME_SLEEP)
+        
         # go_straight_with_enhanced_calibration(Ctrl, msg, distance = 5, speed=0.5, observe=False, mode=11, gait_id=3, step_height=[0.21, 0.21])
-        # run_task_2(Ctrl, msg)
         # pass_up_down(Ctrl, msg)
         # pass_bar(Ctrl, msg)
-        # Ctrl.base_msg.stand_up()
+        # run_task_2(Ctrl, msg)
 
-        # time.sleep(100) # TEST,
 
-        # run_task_1(Ctrl, msg, time_sleep=TIME_SLEEP)
+        # TAG task - 2
-        # arrow_direction = run_task_2_demo(Ctrl, msg, xy_flag=False)
+        arrow_direction = run_task_2_demo(Ctrl, msg, xy_flag=False)
         # print(arrow_direction)
         # arrow_direction = run_task_2(Ctrl, msg, xy_flag=False)
         # arrow_direction = 'right' # TEST

task_2/task_2.py

@@ -95,7 +95,7 @@ class AsyncArrowDetector:
             
             # 按指定间隔检测
             if current_time - last_detection_time >= interval:
-                img = self.image_processor.get_current_image()
+                img = self.image_processor.get_current_image('ai')
                 if img is not None:
                     try:
                         # 保存最后处理的图像
@@ -207,7 +207,7 @@ def run_task_2(ctrl, msg, xy_flag=False):
             arrow_detector.start_detection(interval=0.3)
             arrow_detection_started = True
         
-        cv_image = ctrl.image_processor.get_current_image()
+        cv_image = ctrl.image_processor.get_current_image('ai')
         print('111')
         cv2.imwrite(f"saved_images/first{i}.jpg", cv_image)
 
@@ -258,7 +258,7 @@ def run_task_2(ctrl, msg, xy_flag=False):
                 info("异步检测未得到确定结果，尝试在当前图像上直接检测", "箭头检测")
                 
                 # 获取当前图像
-                image = ctrl.image_processor.get_current_image()
+                image = ctrl.image_processor.get_current_image('ai')
                 if image is not None:
                     # 直接在当前图像上检测
                     arrow_direction = detect_arrow_direction(image, observe=False)
@@ -425,8 +425,6 @@ def test_crawl_transition_only(ctrl, msg):
     return False
 
 
-
-
 def run_task_2_demo(ctrl, msg, xy_flag=False):
     # 微调 xy 和角度
     go_to_xy_v2(ctrl, msg, 0.9, 0.25, speed=0.5, observe=True)
@@ -506,7 +504,7 @@ def run_task_2_demo(ctrl, msg, xy_flag=False):
                 info("异步检测未得到确定结果，尝试在当前图像上直接检测", "箭头检测")
                 
                 # 获取当前图像
-                image = ctrl.image_processor.get_current_image()
+                image = ctrl.image_processor.get_current_image('ai')
 
                 print(image)
 

task_4/task_4.py

@@ -366,7 +366,7 @@ def go_straight_with_enhanced_calibration(ctrl, msg, distance, speed=0.5, observ
             # 更新检查时间
             last_check_time = current_time
         
-        # 定期进行视觉检查和修正
+        # 定期进行视觉检查和修正  # TODO 这个函数如果用于 上下坡的话，感觉或许就不需要了，如果能保证 task 2-5 的效果。
         if hasattr(ctrl, 'image_processor') and current_time - last_vision_check >= vision_check_interval:
             try:
                 # 获取当前相机帧

utils/image_raw.py

@@ -245,17 +245,17 @@ class ImageProcessor:
         self.image_subscriber.stop_camera()
         self.image_subscriber.destroy_node()
 
-    def get_current_image(self, text):
+    def get_current_image(self, text = 'rgb'):
+        # INFO 默认返回 rgb 图像
         if text=='ai':
             return self.image_subscriber.cv_image_ai
-        if text=='left':
+        elif text=='left':
             return self.image_subscriber.cv_image_left
-        if text=='right':
+        elif text=='right':
             return self.image_subscriber.cv_image_right
-        if text=='rgb':
+        else: # text=='rgb':
             return self.image_subscriber.cv_image_rgb
 
-    
     def decode_all_qrcodes(self, img=None):
         """使用pyzbar解码QR码"""
         if img is None: