ROS2之OpenCV基础代码对比foxy~galactic~humble

参考:

automaticaddison.com/getting-started-with-opencv-in-ros-2-galactic-python/

automaticaddison.com/getting-started-with-opencv-in-ros-2-foxy-fitzroy-python/

推荐使用:YOLOX + ROS2 object detection package

也可以参考:github.com/jeffreyttc/opencv_ros2

vision_opencv
ros2 vision_opencv 包含将 ROS 2 与 OpenCV 接口的包,OpenCV 是一个专为计算效率和实时计算机视觉应用程序而设计的库。 该存储库包含:

  1. cv_bridge:ROS 2 图像消息和 OpenCV 图像表示之间的桥梁
  2. image_geometry:处理图像和像素几何的方法集合
  3. opencv_tests:集成测试以使用带有 opencv 的包的功能
  4. vision_opencv:安装 cv_bridge 和 image_geometry 的元包

为了将 ROS 2 与 OpenCV 一起使用,请参阅 cv_bridge 包中的详细信息。

程序适用于foxy/galactic/humble,windows/linux系统通用 

ROS2之OpenCV基础代码对比foxy~galactic~humble

在本教程中,将学习如何将 ROS 2 与流行的计算机视觉库 OpenCV 接口的基础知识。 这些基础知识将提供在机器人应用程序中添加视觉的基础。

我们将创建一个图像发布者节点以将网络摄像头数据(即视频帧)发布到一个主题,我们将创建一个订阅该主题的图像订阅者节点。

pub发布:

foxygalactic

# Basic ROS 2 program to publish real-time streaming

# video from your built-in webcam

# Author:

# - Addison Sears-Collins

  

# Import the necessary libraries

import rclpy # Python Client Library for ROS 2

from rclpy.node import Node # Handles the creation of nodes

from sensor_msgs.msg import Image # Image is the message type

from cv_bridge import CvBridge # Package to convert between ROS and OpenCV Images

import cv2 # OpenCV library

class ImagePublisher(Node):

  """

  Create an ImagePublisher class, which is a subclass of the Node class.

  """

  def __init__(self):

    """

    Class constructor to set up the node

    """

    # Initiate the Node class's constructor and give it a name

    super().__init__('image_publisher')

      

    # Create the publisher. This publisher will publish an Image

    # to the video_frames topic. The queue size is 10 messages.

    self.publisher_ = self.create_publisher(Image, 'video_frames', 10)

      

    # We will publish a message every 0.1 seconds

    timer_period = 0.1  # seconds

      

    # Create the timer

    self.timer = self.create_timer(timer_period, self.timer_callback)

         

    # Create a VideoCapture object

    # The argument '0' gets the default webcam.

    self.cap = cv2.VideoCapture(0)

         

    # Used to convert between ROS and OpenCV images

    self.br = CvBridge()

   

  def timer_callback(self):

    """

    Callback function.

    This function gets called every 0.1 seconds.

    """

    # Capture frame-by-frame

    # This method returns True/False as well

    # as the video frame.

    ret, frame = self.cap.read()

          

    if ret == True:

      # Publish the image.

      # The 'cv2_to_imgmsg' method converts an OpenCV

      # image to a ROS 2 image message

      self.publisher_.publish(self.br.cv2_to_imgmsg(frame))

    # Display the message on the console

    self.get_logger().info('Publishing video frame')

  

def main(args=None):

  

  # Initialize the rclpy library

  rclpy.init(args=args)

  

  # Create the node

  image_publisher = ImagePublisher()

  

  # Spin the node so the callback function is called.

  rclpy.spin(image_publisher)

  

  # Destroy the node explicitly

  # (optional - otherwise it will be done automatically

  # when the garbage collector destroys the node object)

  image_publisher.destroy_node()

  

  # Shutdown the ROS client library for Python

  rclpy.shutdown()

  

if __name__ == '__main__':

  main()

# Basic ROS 2 program to publish real-time streaming

# video from your built-in webcam

# Author:

# - Addison Sears-Collins

   

# Import the necessary libraries

import rclpy # Python Client Library for ROS 2

from rclpy.node import Node # Handles the creation of nodes

from sensor_msgs.msg import Image # Image is the message type

from cv_bridge import CvBridge # Package to convert between ROS and OpenCV Images

import cv2 # OpenCV library

  

class ImagePublisher(Node):

  """

  Create an ImagePublisher class, which is a subclass of the Node class.

  """

  def __init__(self):

    """

    Class constructor to set up the node

    """

    # Initiate the Node class's constructor and give it a name

    super().__init__('image_publisher')

       

    # Create the publisher. This publisher will publish an Image

    # to the video_frames topic. The queue size is 10 messages.

    self.publisher_ = self.create_publisher(Image, 'video_frames', 10)

       

    # We will publish a message every 0.1 seconds

    timer_period = 0.1  # seconds

       

    # Create the timer

    self.timer = self.create_timer(timer_period, self.timer_callback)

          

    # Create a VideoCapture object

    # The argument '0' gets the default webcam.

    self.cap = cv2.VideoCapture(0)

          

    # Used to convert between ROS and OpenCV images

    self.br = CvBridge()

    

  def timer_callback(self):

    """

    Callback function.

    This function gets called every 0.1 seconds.

    """

    # Capture frame-by-frame

    # This method returns True/False as well

    # as the video frame.

    ret, frame = self.cap.read()

           

    if ret == True:

      # Publish the image.

      # The 'cv2_to_imgmsg' method converts an OpenCV

      # image to a ROS 2 image message

      self.publisher_.publish(self.br.cv2_to_imgmsg(frame))

  

    # Display the message on the console

    self.get_logger().info('Publishing video frame')

   

def main(args=None):

   

  # Initialize the rclpy library

  rclpy.init(args=args)

   

  # Create the node

  image_publisher = ImagePublisher()

   

  # Spin the node so the callback function is called.

  rclpy.spin(image_publisher)

   

  # Destroy the node explicitly

  # (optional - otherwise it will be done automatically

  # when the garbage collector destroys the node object)

  image_publisher.destroy_node()

   

  # Shutdown the ROS client library for Python

  rclpy.shutdown()

   

if __name__ == '__main__':

  main()

sub订阅:

foxygalactic

# Basic ROS 2 program to subscribe to real-time streaming

# video from your built-in webcam

# Author:

# - Addison Sears-Collins

  

# Import the necessary libraries

import rclpy # Python library for ROS 2

from rclpy.node import Node # Handles the creation of nodes

from sensor_msgs.msg import Image # Image is the message type

from cv_bridge import CvBridge # Package to convert between ROS and OpenCV Images

import cv2 # OpenCV library

class ImageSubscriber(Node):

  """

  Create an ImageSubscriber class, which is a subclass of the Node class.

  """

  def __init__(self):

    """

    Class constructor to set up the node

    """

    # Initiate the Node class's constructor and give it a name

    super().__init__('image_subscriber')

      

    # Create the subscriber. This subscriber will receive an Image

    # from the video_frames topic. The queue size is 10 messages.

    self.subscription = self.create_subscription(

      Image,

      'video_frames',

      self.listener_callback,

      10)

    self.subscription # prevent unused variable warning

      

    # Used to convert between ROS and OpenCV images

    self.br = CvBridge()

   

  def listener_callback(self, data):

    """

    Callback function.

    """

    # Display the message on the console

    self.get_logger().info('Receiving video frame')

    # Convert ROS Image message to OpenCV image

    current_frame = self.br.imgmsg_to_cv2(data)

    

    # Display image

    cv2.imshow("camera", current_frame)

    

    cv2.waitKey(1)

  

def main(args=None):

  

  # Initialize the rclpy library

  rclpy.init(args=args)

  

  # Create the node

  image_subscriber = ImageSubscriber()

  

  # Spin the node so the callback function is called.

  rclpy.spin(image_subscriber)

  

  # Destroy the node explicitly

  # (optional - otherwise it will be done automatically

  # when the garbage collector destroys the node object)

  image_subscriber.destroy_node()

  

  # Shutdown the ROS client library for Python

  rclpy.shutdown()

  

if __name__ == '__main__':

  main()

# Basic ROS 2 program to subscribe to real-time streaming

# video from your built-in webcam

# Author:

# - Addison Sears-Collins

   

# Import the necessary libraries

import rclpy # Python library for ROS 2

from rclpy.node import Node # Handles the creation of nodes

from sensor_msgs.msg import Image # Image is the message type

from cv_bridge import CvBridge # Package to convert between ROS and OpenCV Images

import cv2 # OpenCV library

  

class ImageSubscriber(Node):

  """

  Create an ImageSubscriber class, which is a subclass of the Node class.

  """

  def __init__(self):

    """

    Class constructor to set up the node

    """

    # Initiate the Node class's constructor and give it a name

    super().__init__('image_subscriber')

       

    # Create the subscriber. This subscriber will receive an Image

    # from the video_frames topic. The queue size is 10 messages.

    self.subscription = self.create_subscription(

      Image,

      'video_frames',

      self.listener_callback,

      10)

    self.subscription # prevent unused variable warning

       

    # Used to convert between ROS and OpenCV images

    self.br = CvBridge()

    

  def listener_callback(self, data):

    """

    Callback function.

    """

    # Display the message on the console

    self.get_logger().info('Receiving video frame')

  

    # Convert ROS Image message to OpenCV image

    current_frame = self.br.imgmsg_to_cv2(data)

     

    # Display image

    cv2.imshow("camera", current_frame)

     

    cv2.waitKey(1)

   

def main(args=None):

   

  # Initialize the rclpy library

  rclpy.init(args=args)

   

  # Create the node

  image_subscriber = ImageSubscriber()

   

  # Spin the node so the callback function is called.

  rclpy.spin(image_subscriber)

   

  # Destroy the node explicitly

  # (optional - otherwise it will be done automatically

  # when the garbage collector destroys the node object)

  image_subscriber.destroy_node()

   

  # Shutdown the ROS client library for Python

  rclpy.shutdown()

   

if __name__ == '__main__':

  main()

humble:

pub

# Basic ROS 2 program to publish real-time streaming

# video from your built-in webcam

# Author:

# - Addison Sears-Collins

   

# Import the necessary libraries

import rclpy # Python Client Library for ROS 2

from rclpy.node import Node # Handles the creation of nodes

from sensor_msgs.msg import Image # Image is the message type

from cv_bridge import CvBridge # Package to convert between ROS and OpenCV Images

import cv2 # OpenCV library

  

class ImagePublisher(Node):

  """

  Create an ImagePublisher class, which is a subclass of the Node class.

  """

  def __init__(self):

    """

    Class constructor to set up the node

    """

    # Initiate the Node class's constructor and give it a name

    super().__init__('image_publisher')

       

    # Create the publisher. This publisher will publish an Image

    # to the video_frames topic. The queue size is 10 messages.

    self.publisher_ = self.create_publisher(Image, 'video_frames', 10)

       

    # We will publish a message every 0.1 seconds

    timer_period = 0.1  # seconds

       

    # Create the timer

    self.timer = self.create_timer(timer_period, self.timer_callback)

          

    # Create a VideoCapture object

    # The argument '0' gets the default webcam.

    self.cap = cv2.VideoCapture(0)

          

    # Used to convert between ROS and OpenCV images

    self.br = CvBridge()

    

  def timer_callback(self):

    """

    Callback function.

    This function gets called every 0.1 seconds.

    """

    # Capture frame-by-frame

    # This method returns True/False as well

    # as the video frame.

    ret, frame = self.cap.read()

           

    if ret == True:

      # Publish the image.

      # The 'cv2_to_imgmsg' method converts an OpenCV

      # image to a ROS 2 image message

      self.publisher_.publish(self.br.cv2_to_imgmsg(frame))

  

    # Display the message on the console

    self.get_logger().info('Publishing video frame')

   

def main(args=None):

   

  # Initialize the rclpy library

  rclpy.init(args=args)

   

  # Create the node

  image_publisher = ImagePublisher()

   

  # Spin the node so the callback function is called.

  rclpy.spin(image_publisher)

   

  # Destroy the node explicitly

  # (optional - otherwise it will be done automatically

  # when the garbage collector destroys the node object)

  image_publisher.destroy_node()

   

  # Shutdown the ROS client library for Python

  rclpy.shutdown()

   

if __name__ == '__main__':

  main()

 sub

# Basic ROS 2 program to subscribe to real-time streaming

# video from your built-in webcam

# Author:

# - Addison Sears-Collins

   

# Import the necessary libraries

import rclpy # Python library for ROS 2

from rclpy.node import Node # Handles the creation of nodes

from sensor_msgs.msg import Image # Image is the message type

from cv_bridge import CvBridge # Package to convert between ROS and OpenCV Images

import cv2 # OpenCV library

  

class ImageSubscriber(Node):

  """

  Create an ImageSubscriber class, which is a subclass of the Node class.

  """

  def __init__(self):

    """

    Class constructor to set up the node

    """

    # Initiate the Node class's constructor and give it a name

    super().__init__('image_subscriber')

       

    # Create the subscriber. This subscriber will receive an Image

    # from the video_frames topic. The queue size is 10 messages.

    self.subscription = self.create_subscription(

      Image,

      'video_frames',

      self.listener_callback,

      10)

    self.subscription # prevent unused variable warning

       

    # Used to convert between ROS and OpenCV images

    self.br = CvBridge()

    

  def listener_callback(self, data):

    """

    Callback function.

    """

    # Display the message on the console

    self.get_logger().info('Receiving video frame')

  

    # Convert ROS Image message to OpenCV image

    current_frame = self.br.imgmsg_to_cv2(data)

     

    # Display image

    cv2.imshow("camera", current_frame)

     

    cv2.waitKey(1)

   

def main(args=None):

   

  # Initialize the rclpy library

  rclpy.init(args=args)

   

  # Create the node

  image_subscriber = ImageSubscriber()

   

  # Spin the node so the callback function is called.

  rclpy.spin(image_subscriber)

   

  # Destroy the node explicitly

  # (optional - otherwise it will be done automatically

  # when the garbage collector destroys the node object)

  image_subscriber.destroy_node()

   

  # Shutdown the ROS client library for Python

  rclpy.shutdown()

   

if __name__ == '__main__':

  main()

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