关于发布订阅模型订阅者回调函数里放发布者，无 .publish功能的问题

[熵]

#!/usr/bin/env python
# -*- coding: utf-8 -*-
import rclpy
from rclpy import Node
import cv2
import numpy as np
from sensor_msgs.msg import Image
from geometry_msgs.msg import PoseStamped
from cv_bridge import CvBridge,CvBridgeError
import message_filters 
import time
import math
import pickle

#dis_pub = rclpy.Publisher('/dis',PoseStamped,queue_size=10)
#time_pub = rclpy.Publisher('/time',PoseStamped,queue_size=10)
dis_pub = rclpy.Node.create_publisher(PoseStamped,'/dis',10)
time_pub = rclpy.Node.create_publisher(PoseStamped,'/time',10)

frame_count = 1 
class templatematching(Node):
    def __init__(self,name):
        super().__init__(name)
        #rospy.on_shutdown(self.cleanup)
        self.bridge = CvBridge()
        self.image_pub = self.create_publisher(Image, "cv_bridge_image", queue_size=1)
        self.image_sub = self.create_subscription(Image, "/usb_cam/image_raw", self.image_callback,   queue_size=1)
        self.firstFrame = None
        self.template = None
    def image_callback(self, data):
        global frame_count 
        focal_length_x = 446.6          #相机x，y方向的焦距
        focal_length_y = 445.8
        camera_height = 255
        w = 240  # 模板宽度
        h = 240  # 模板长度
        w_2 = int(w / 2)  # 模板宽度一半
        h_2 = int(h / 2)  # 模板长度一半
        offset_x = 30
        offset_y_up = 100  # 上侧
        offset_y_down = 100  # control search field
        cumulative_u = 0.0
        cumulative_v = 0.0
        cumulative_pixel = 0.0
        last_time = rclpy.get_time()
    
        try:
            cv_image = self.bridge.imgmsg_to_cv2(data, "bgr8")
            frame = np.array(cv_image, dtype=np.uint8)
        except CvBridgeError as e:
            print(e) 

        if self.firstFrame is None:
            self.firstFrame = frame
            return

        
        if frame_count == 1:
             self.template = self.firstFrame[240 - h_2: 240 + h_2 + 1,320 - w_2: 320 + w_2 + 1]  #选取模板240*240
             frame_count += 1
             return
        y = np.shape(frame)[0]  # Current frame  行数  图像长度  ?
        x = np.shape(frame)[1]  #列数     图像宽度   ?
        cv2.circle(frame, (320 - w_2, 240 - h_2), 5, (0, 0, 255), 2)
     
        search_field = frame[240 - h_2 - offset_y_up: 240 + h_2 + offset_y_down + 1, 320 - w_2 - offset_x: 320 + w_2 + offset_x + 1]
        #search_field = frame[320 - w_2 - offset_x : 320 + w_2 + offset_x  + 1, 240 - h_2 - offset_y_up: 240 + h_2 + offset_y_down + 1]
         
        cv2.rectangle(frame, (320 - w_2 - offset_x, 240 - h_2 - offset_y_up), (320 + w_2 + offset_x, 240 + h_2 + offset_y_down), (0, 0, 128), 2)
        match_start_time = rclpy.get_time()
        match_score = cv2.matchTemplate(search_field, self.template, method=cv2.TM_CCOEFF_NORMED)
        match_end_time = rclpy.get_time()
        match_time = match_end_time - match_start_time
        #rospy.loginfo(match_time)
        min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(match_score) 
        top_left = (max_loc[0] + 320 - w_2 - offset_x, max_loc[1] + 240 - h_2 - offset_y_up)  # 转换成全局坐标(缩小搜索区域时需要改动)
        bottom_right = (top_left[0] + w, top_left[1] + h)
        cv2.rectangle(frame, top_left, bottom_right, 255, 2) 
        last_frame_top_left = (int(x / 2 - w / 2), int(y / 2 - h / 2))
        cv2.line(frame, top_left, last_frame_top_left, (0, 255, 0), 2)
      
        cv2.imshow("Image window",frame)
        cv2.waitKey(3)

        diff_u = top_left[0] - last_frame_top_left[0]   #水平，竖直方向位移
        diff_v = top_left[1] - last_frame_top_left[1]
        diff_pixel = (diff_u ** 2 + diff_v ** 2) ** 0.5  # **表示乘方
        cumulative_u = cumulative_u + diff_u
        cumulative_v = cumulative_v + diff_v
        cumulative_pixel = cumulative_pixel + diff_pixel

        diff_x_c = (diff_u) / focal_length_x * camera_height
        diff_y_c = (diff_v) / focal_length_y * camera_height
        diff_x_u = -diff_x_c   #图像坐标系转相机坐标系
        diff_y_v = diff_y_c    #相机坐标系转机器人坐标系


        
        #self.template = frame[320 - w_2: 320 + w_2 + 1,240 - h_2: 240 + h_2 + 1]  #选取模板240*240
        self.template = frame[240 - h_2: 240 + h_2 + 1, 320 - w_2: 320 + w_2 + 1]
        self.image_pub.publish(self.bridge.cv2_to_imgmsg(frame, "bgr8"))
        current_time = rclpy.get_time()
        dt =  current_time - last_time
        #rospy.loginfo(dt)
         
        dis_msg = PoseStamped()
        dis_msg.header.frame_id = "displacement"
        dis_msg.header.stamp = rclpy.Time.now()
        dis_msg.pose.position.x = diff_x_u
        dis_msg.pose.position.y = diff_y_v
        dis_pub.publish(dis_msg)

        time_msg = PoseStamped()
        time_msg.header.frame_id = "time"
        time_msg.header.stamp = rclpy.Time.now()
        time_msg.pose.position.x = dt
        time_msg.pose.position.y = match_time
        time_pub.publish(time_msg) 


#if __name__ == '__main__':
def main(args =None):
    try:
        # 初始化ros节点
     #   rclpy.init_node("templatematching")
      #  rclpy.loginfo("templatematching node is started...")
      #  rclpy.loginfo("Please subscribe the ROS image.")
       rclpy.init(args=args)
       node = rclpy.create_node("templatematching")      
       node.get_logger().info("templatematching node is started...")
       node.get_logger().info("Please subscribe the ROS image.")
       rclpy.spin(node)
       rclpy.shutdown()
    except KeyboardInterrupt:  
       print ("Shutting down motion detector node.")
       cv2.destroyAllWindows()


if __name__ == '__main__':
     main()

!

[小鱼]

@熵 ROS1里可以这样做，但是ros2不行，ros1在设计的时候开了多个线程，对使用规范要求很低，ros2的代码做了很多优化，比如同一个节点默认只开了一个线程，所以无法像ros1那样可以随便写。你的回调函数写了太多的内容，估计要用多线程回调组才行，我简单针对你的问题改了下，你还需要加上一个回调组的设置。

在回调函数中发布数据方式参考代码如下：

import rclpy
from rclpy.node import Node
from std_msgs.msg import String,UInt32
from village_interfaces.srv import SellNovel
from queue import Queue,LifoQueue,PriorityQueue
from rclpy.executors import MultiThreadedExecutor
from rclpy.callback_groups import MutuallyExclusiveCallbackGroup

class TestNode(Node):
    """
    对象编写
    """
    def __init__(self,name):
        super().__init__(name)
        self.get_logger().info("大家好，我是%s,我是一名订阅者！" % name)
        self.pub_money = self.create_publisher(UInt32,"sexy_girl_money", 10) 
        # 声明回调组
        self.sell_novel_callback_group = MutuallyExclusiveCallbackGroup()
        self.sell_service = self.create_subscription(String,"sexy_girl", self.recv_msg_callback, 10,callback_group=self.sell_novel_callback_group) 

    def recv_msg_callback(self,msg):
        self.msg = msg.data
        self.get_logger().info('穷汉王五：我已经收到了李四的稿子，%s' % self.msg)
        # 组装发布数据
        money = UInt32()
        money.data = 10
        self.pub_money.publish(money)  #将金钱发给李四
        self.queue_list.put(self.msg)


def main(args=None):
    rclpy.init(args=args) # 初始化rclpy
    node = TestNode("wangwu")  # 新建一个节点
    executor = MultiThreadedExecutor()
    executor.add_node(node)
    executor.spin()
    rclpy.shutdown() # 关闭rclpy

[熵]

@小鱼
鱼哥，我看了下官方文档后，简单加了回调组的声明，并改了一下有关time的部分。不知怎么的
self.image_pub.publish
self.time_pub.publish(time_msg)
self.dis_pub.publish(dis_msg)
这三个中,self.image_pub.publish的 .publish是黄色，正常调用，另两个是白色。
我编译运行后，果然报错了，不过我看报的错误和.publish貌似没啥关系，我注释掉回调组，问题没有任何变化。修改后代码和编译报错如下

#!/usr/bin/env python
# -*- coding: utf-8 -*-
import rclpy
from rclpy import Node
import cv2
import numpy as np
from sensor_msgs.msg import Image
from geometry_msgs.msg import PoseStamped
from cv_bridge import CvBridge,CvBridgeError
from rclpy.executors import MultiThreadedExecutor
from rclpy.callback_groups import MutuallyExclusiveCallbackGroup
import message_filters 
import time
import math
import pickle

#dis_pub = rclpy.Publisher('/dis',PoseStamped,queue_size=10)
#time_pub = rclpy.Publisher('/time',PoseStamped,queue_size=10)


frame_count = 1 
class templatematching(Node):
   def __init__(self):
      # super().__init__(name)
       #rospy.on_shutdown(self.cleanup)
       self.bridge = CvBridge()
       #声明发布者
       self.dis_pub = rclpy.Node.create_publisher(PoseStamped,'/dis',10)
       self.time_pub = rclpy.Node.create_publisher(PoseStamped,'/time',10)
       self.image_pub = self.create_publisher(Image, "cv_bridge_image", 1)
       #声明回调组
       self.image_sub_callback_group = MutuallyExclusiveCallbackGroup()
       self.image_sub = self.create_subscription(Image, "/usb_cam/image_raw", self.image_callback,   1,callback_group=self.image_sub_callback_group)
       
       self.firstFrame = None
       self.template = None
   def image_callback(self, data):
       global frame_count 
       focal_length_x = 446.6          #相机x，y方向的焦距
       focal_length_y = 445.8
       camera_height = 255
       w = 240  # 模板宽度
       h = 240  # 模板长度
       w_2 = int(w / 2)  # 模板宽度一半
       h_2 = int(h / 2)  # 模板长度一半
       offset_x = 30
       offset_y_up = 100  # 上侧
       offset_y_down = 100  # control search field
       cumulative_u = 0.0
       cumulative_v = 0.0
       cumulative_pixel = 0.0
    #  last_time = rclpy.get_time()
       last_time = time.time()
       
       try:
           cv_image = self.bridge.imgmsg_to_cv2(data, "bgr8")
           frame = np.array(cv_image, dtype=np.uint8)
       except CvBridgeError as e:
           print(e) 

       if self.firstFrame is None:
           self.firstFrame = frame
           return

       
       if frame_count == 1:
            self.template = self.firstFrame[240 - h_2: 240 + h_2 + 1,320 - w_2: 320 + w_2 + 1]  #选取模板240*240
            frame_count += 1
            return
       y = np.shape(frame)[0]  # Current frame  行数  图像长度  ?
       x = np.shape(frame)[1]  #列数     图像宽度   ?
       cv2.circle(frame, (320 - w_2, 240 - h_2), 5, (0, 0, 255), 2)
    
       search_field = frame[240 - h_2 - offset_y_up: 240 + h_2 + offset_y_down + 1, 320 - w_2 - offset_x: 320 + w_2 + offset_x + 1]
       #search_field = frame[320 - w_2 - offset_x : 320 + w_2 + offset_x  + 1, 240 - h_2 - offset_y_up: 240 + h_2 + offset_y_down + 1]
        
       cv2.rectangle(frame, (320 - w_2 - offset_x, 240 - h_2 - offset_y_up), (320 + w_2 + offset_x, 240 + h_2 + offset_y_down), (0, 0, 128), 2)
   #    match_start_time = rclpy.get_time()
       match_start_time = time.time()
       match_score = cv2.matchTemplate(search_field, self.template, method=cv2.TM_CCOEFF_NORMED)
   #   match_end_time = rclpy.get_time()
       match_end_time = time.time()
       match_time = match_end_time - match_start_time
       #rospy.loginfo(match_time)
       min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(match_score) 
       top_left = (max_loc[0] + 320 - w_2 - offset_x, max_loc[1] + 240 - h_2 - offset_y_up)  # 转换成全局坐标(缩小搜索区域时需要改动)
       bottom_right = (top_left[0] + w, top_left[1] + h)
       cv2.rectangle(frame, top_left, bottom_right, 255, 2) 
       last_frame_top_left = (int(x / 2 - w / 2), int(y / 2 - h / 2))
       cv2.line(frame, top_left, last_frame_top_left, (0, 255, 0), 2)
     
       cv2.imshow("Image window",frame)
       cv2.waitKey(3)

       diff_u = top_left[0] - last_frame_top_left[0]   #水平，竖直方向位移
       diff_v = top_left[1] - last_frame_top_left[1]
       diff_pixel = (diff_u ** 2 + diff_v ** 2) ** 0.5  # **表示乘方
       cumulative_u = cumulative_u + diff_u
       cumulative_v = cumulative_v + diff_v
       cumulative_pixel = cumulative_pixel + diff_pixel

       diff_x_c = (diff_u) / focal_length_x * camera_height
       diff_y_c = (diff_v) / focal_length_y * camera_height
       diff_x_u = -diff_x_c   #图像坐标系转相机坐标系
       diff_y_v = diff_y_c    #相机坐标系转机器人坐标系


       
       #self.template = frame[320 - w_2: 320 + w_2 + 1,240 - h_2: 240 + h_2 + 1]  #选取模板240*240
       self.template = frame[240 - h_2: 240 + h_2 + 1, 320 - w_2: 320 + w_2 + 1]
       self.image_pub.publish(self.bridge.cv2_to_imgmsg(frame, "bgr8"))
    #   current_time = rclpy.get_time()
       current_time = time.time()
       dt =  current_time - last_time
       #rospy.loginfo(dt)
       
       dis_msg = PoseStamped()
       dis_msg.header.frame_id = "displacement"
    #   dis_msg.header.stamp = rclpy.Time.now()
       dis_msg.header.stamp = time.time()
       dis_msg.pose.position.x = diff_x_u
       dis_msg.pose.position.y = diff_y_v
       self.dis_pub.publish(dis_msg)
     
       time_msg = PoseStamped()
       time_msg.header.frame_id = "time"
    #   time_msg.header.stamp = rclpy.Time.now()
       time_msg.header.stamp = time.time()
       time_msg.pose.position.x = dt
       time_msg.pose.position.y = match_time
       self.time_pub.publish(time_msg) 

#if __name__ == '__main__':
def main(args =None):
   try:
       # 初始化ros节点
    #   rclpy.init_node("templatematching")
     #  rclpy.loginfo("templatematching node is started...")
     #  rclpy.loginfo("Please subscribe the ROS image.")
      rclpy.init(args=args)
      node = rclpy.create_node("templatematching")      
      node.get_logger().info("templatematching node is started...")
      node.get_logger().info("Please subscribe the ROS image.")
      rclpy.spin(node)
      rclpy.shutdown()
   except KeyboardInterrupt:  
      print ("Shutting down motion detector node.")
      cv2.destroyAllWindows()


if __name__ == '__main__':
    main()

rr@rr-TM1709:~/d2lros2/chapt2/photo_ws$ colcon build
Starting >>> example_py
--- stderr: example_py                   
/usr/lib/python3/dist-packages/setuptools/command/install.py:34: SetuptoolsDeprecationWarning: setup.py install is deprecated. Use build and pip and other standards-based tools.
  warnings.warn(
---
Finished <<< example_py [1.08s]

Summary: 1 package finished [1.39s]
  1 package had stderr output: example_py
rr@rr-TM1709:~/d2lros2/chapt2/photo_ws$ source install/setup.bash
rr@rr-TM1709:~/d2lros2/chapt2/photo_ws$ ros2 run example_py node_01
Traceback (most recent call last):
  File "/home/rr/d2lros2/chapt2/photo_ws/install/example_py/lib/example_py/node_01", line 33, in <module>
    sys.exit(load_entry_point('example-py==0.0.0', 'console_scripts', 'node_01')())
  File "/home/rr/d2lros2/chapt2/photo_ws/install/example_py/lib/example_py/node_01", line 25, in importlib_load_entry_point
    return next(matches).load()
  File "/usr/lib/python3.10/importlib/metadata/__init__.py", line 171, in load
    module = import_module(match.group('module'))
  File "/usr/lib/python3.10/importlib/__init__.py", line 126, in import_module
    return _bootstrap._gcd_import(name[level:], package, level)
  File "<frozen importlib._bootstrap>", line 1050, in _gcd_import
  File "<frozen importlib._bootstrap>", line 1027, in _find_and_load
  File "<frozen importlib._bootstrap>", line 1006, in _find_and_load_unlocked
  File "<frozen importlib._bootstrap>", line 688, in _load_unlocked
  File "<frozen importlib._bootstrap_external>", line 883, in exec_module
  File "<frozen importlib._bootstrap>", line 241, in _call_with_frames_removed
  File "/home/rr/d2lros2/chapt2/photo_ws/install/example_py/lib/python3.10/site-packages/example_py/node_01.py", line 4, in <module>
    from rclpy import Node
ImportError: cannot import name 'Node' from 'rclpy' (/opt/ros/humble/local/lib/python3.10/dist-packages/rclpy/__init__.py)
[ros2run]: Process exited with failure 1

[小鱼]

@熵 在 关于发布订阅模型订阅者回调函数里放发布者，无 .publish功能的问题 中说：

self.dis_pub = rclpy.Node.create_publisher(PoseStamped,'/dis',10)
self.time_pub = rclpy.Node.create_publisher(PoseStamped,'/time',10)
self.image_pub = self.create_publisher(Image, "cv_bridge_image", 1)

正确创建发布者的方式是第三行，使用self.create_publisher,而不是rclpy.Node.create_publisher

[熵]

@小鱼 嗯嗯，哥，改了后变黄了。
果然，编译的报错和发布者一点关系没有....难难难，我去搜搜

[小鱼]

@小鱼 在 关于发布订阅模型订阅者回调函数里放发布者，无 .publish功能的问题 中说：

from rclpy.node import Node

正确的导入node方式是这样的，要细心些，仔细对比即可发现

[熵]

@小鱼 谢谢鱼哥，我好粗心

[熵]

最新代码，能够正常编译，运行时没报错。
但好像无法与相机发布者连接，正在查找原因

#!/usr/bin/env python
# -*- coding: utf-8 -*-
import rclpy
from rclpy.node import Node
import cv2
import numpy as np
from sensor_msgs.msg import Image
from geometry_msgs.msg import PoseStamped
from cv_bridge import CvBridge,CvBridgeError
from rclpy.executors import MultiThreadedExecutor
from rclpy.callback_groups import MutuallyExclusiveCallbackGroup
import message_filters 
import time
import math
import pickle

#dis_pub = rclpy.Publisher('/dis',PoseStamped,queue_size=10)
#time_pub = rclpy.Publisher('/time',PoseStamped,queue_size=10)


frame_count = 1 
class templatematching(Node):
    def __init__(self):
        print("02")
        self.get_logger().info("01")
       # super().__init__(name)
        #rospy.on_shutdown(self.cleanup)
        self.bridge = CvBridge()
        #声明发布者
        self.dis_pub = self.create_publisher(PoseStamped,'/dis',10)
        self.time_pub = self.create_publisher(PoseStamped,'/time',10)
        self.image_pub = self.create_publisher(Image, "cv_bridge_image", 1)
        #声明回调组
        self.image_sub_callback_group = MutuallyExclusiveCallbackGroup()
        self.image_sub = self.create_subscription(Image, "/usb_cam/image_raw", self.image_callback,   1,callback_group=self.image_sub_callback_group)
        
        self.firstFrame = None
        self.template = None
    def image_callback(self, data):
        global frame_count 
        focal_length_x = 446.6          #相机x，y方向的焦距
        focal_length_y = 445.8
        camera_height = 255
        w = 240  # 模板宽度
        h = 240  # 模板长度
        w_2 = int(w / 2)  # 模板宽度一半
        h_2 = int(h / 2)  # 模板长度一半
        offset_x = 30
        offset_y_up = 100  # 上侧
        offset_y_down = 100  # control search field
        cumulative_u = 0.0
        cumulative_v = 0.0
        cumulative_pixel = 0.0
     #  last_time = rclpy.get_time()
        last_time = time.time()
        
        try:
            cv_image = self.bridge.imgmsg_to_cv2(data, "bgr8")
            frame = np.array(cv_image, dtype=np.uint8)
        except CvBridgeError as e:
            print(e) 

        if self.firstFrame is None:
            self.firstFrame = frame
            return

        
        if frame_count == 1:
             self.template = self.firstFrame[240 - h_2: 240 + h_2 + 1,320 - w_2: 320 + w_2 + 1]  #选取模板240*240
             frame_count += 1
             return
        y = np.shape(frame)[0]  # Current frame  行数  图像长度  ?
        x = np.shape(frame)[1]  #列数     图像宽度   ?
        cv2.circle(frame, (320 - w_2, 240 - h_2), 5, (0, 0, 255), 2)
     
        search_field = frame[240 - h_2 - offset_y_up: 240 + h_2 + offset_y_down + 1, 320 - w_2 - offset_x: 320 + w_2 + offset_x + 1]
        #search_field = frame[320 - w_2 - offset_x : 320 + w_2 + offset_x  + 1, 240 - h_2 - offset_y_up: 240 + h_2 + offset_y_down + 1]
         
        cv2.rectangle(frame, (320 - w_2 - offset_x, 240 - h_2 - offset_y_up), (320 + w_2 + offset_x, 240 + h_2 + offset_y_down), (0, 0, 128), 2)
    #    match_start_time = rclpy.get_time()
        match_start_time = time.time()
        match_score = cv2.matchTemplate(search_field, self.template, method=cv2.TM_CCOEFF_NORMED)
    #   match_end_time = rclpy.get_time()
        match_end_time = time.time()
        match_time = match_end_time - match_start_time
        #rospy.loginfo(match_time)
        min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(match_score) 
        top_left = (max_loc[0] + 320 - w_2 - offset_x, max_loc[1] + 240 - h_2 - offset_y_up)  # 转换成全局坐标(缩小搜索区域时需要改动)
        bottom_right = (top_left[0] + w, top_left[1] + h)
        cv2.rectangle(frame, top_left, bottom_right, 255, 2) 
        last_frame_top_left = (int(x / 2 - w / 2), int(y / 2 - h / 2))
        cv2.line(frame, top_left, last_frame_top_left, (0, 255, 0), 2)
      
        cv2.imshow("Image window",frame)
        cv2.waitKey(3)

        diff_u = top_left[0] - last_frame_top_left[0]   #水平，竖直方向位移
        diff_v = top_left[1] - last_frame_top_left[1]
        diff_pixel = (diff_u ** 2 + diff_v ** 2) ** 0.5  # **表示乘方
        cumulative_u = cumulative_u + diff_u
        cumulative_v = cumulative_v + diff_v
        cumulative_pixel = cumulative_pixel + diff_pixel

        diff_x_c = (diff_u) / focal_length_x * camera_height
        diff_y_c = (diff_v) / focal_length_y * camera_height
        diff_x_u = -diff_x_c   #图像坐标系转相机坐标系
        diff_y_v = diff_y_c    #相机坐标系转机器人坐标系


        
        #self.template = frame[320 - w_2: 320 + w_2 + 1,240 - h_2: 240 + h_2 + 1]  #选取模板240*240
        self.template = frame[240 - h_2: 240 + h_2 + 1, 320 - w_2: 320 + w_2 + 1]
        self.image_pub.publish(self.bridge.cv2_to_imgmsg(frame, "bgr8"))
     #   current_time = rclpy.get_time()
        current_time = time.time()
        dt =  current_time - last_time
        #rospy.loginfo(dt)
        
        dis_msg = PoseStamped()
        dis_msg.header.frame_id = "displacement"
     #   dis_msg.header.stamp = rclpy.Time.now()
        dis_msg.header.stamp = time.time()
        dis_msg.pose.position.x = diff_x_u
        dis_msg.pose.position.y = diff_y_v
        self.dis_pub.publish(dis_msg)
      
        time_msg = PoseStamped()
        time_msg.header.frame_id = "time"
     #   time_msg.header.stamp = rclpy.Time.now()
        time_msg.header.stamp = time.time()
        time_msg.pose.position.x = dt
        time_msg.pose.position.y = match_time
        self.time_pub.publish(time_msg) 

#if __name__ == '__main__':
def main(args =None):
    try:
        # 初始化ros节点
     #   rclpy.init_node("templatematching")
      #  rclpy.loginfo("templatematching node is started...")
      #  rclpy.loginfo("Please subscribe the ROS image.")
       rclpy.init(args=args)
       node = rclpy.create_node("templatematching")      
       node.get_logger().info("templatematching node is started...")
       node.get_logger().info("Please subscribe the ROS image.")
       print("01")
       rclpy.spin(node)
       rclpy.shutdown()
    except KeyboardInterrupt:  
       print ("Shutting down motion detector node.")
       cv2.destroyAllWindows()


if __name__ == '__main__':
     main()