ROS-release camera node and write opencv image processing node (python)

Article Directory

Software and hardware environment

hardware

Lower computer: Raspberry Pi 4B (4G)
Host computer: PC
USB camera

software

Both upper and lower computers are Ubuntu 18.04 systems
ROS melodic

Opencv and ROS

Conversion between OpenCV format pictures (or video frames) and ROS data format pictures (or video frames). Or be straightforward and send a message of the image data type through ROS.

We only need to define the following data to publish the image data.
Insert picture description here

Publish camera data node

#!/usr/bin/env python
# coding:utf-8

import cv2
import numpy as np
import rospy
from std_msgs.msg import Header
from sensor_msgs.msg import Image
from cv_bridge import CvBridge , CvBridgeError
import time

if __name__=="__main__":
    capture = cv2.VideoCapture(0) # 定义摄像头
    rospy.init_node('camera_node', anonymous=True) #定义节点
    image_pub=rospy.Publisher('/image_view/image_raw', Image, queue_size = 1) #定义话题

    while not rospy.is_shutdown():    # Ctrl C正常退出，如果异常退出会报错device busy！
        start = time.time()
        ret, frame = capture.read()
        if ret: # 如果有画面再执行
            # frame = cv2.flip(frame,0)   #垂直镜像操作
            frame = cv2.flip(frame,1)   #水平镜像操作   
    
            ros_frame = Image()
            header = Header(stamp = rospy.Time.now())
            header.frame_id = "Camera"
            ros_frame.header=header
            ros_frame.width = 640
            ros_frame.height = 480
            ros_frame.encoding = "bgr8"
            ros_frame.step = 1920
            ros_frame.data = np.array(frame).tostring() #图片格式转换
            image_pub.publish(ros_frame) #发布消息
            end = time.time()  
            print("cost time:", end-start ) # 看一下每一帧的执行时间，从而确定合适的rate
            rate = rospy.Rate(25) # 10hz 

    capture.release()
    cv2.destroyAllWindows() 
    print("quit successfully!")

Image receiving and processing node

I only wrote a simple code for receiving images and displaying it, which can be expanded on the basis of the basic code.

#!/usr/bin/env python
# coding:utf-8

import rospy
import numpy as np
from sensor_msgs.msg import Image
from cv_bridge import CvBridge, CvBridgeError
import cv2
 
def callback(data):
    global bridge
    cv_img = bridge.imgmsg_to_cv2(data, "bgr8")
    cv2.imshow("frame" , cv_img)
    cv2.waitKey(1)

if __name__ == '__main__':
    rospy.init_node('img_process_node', anonymous=True)
    bridge = CvBridge()
    rospy.Subscriber('/image_view/image_raw', Image, callback)
    rospy.spin()

Show results:
Insert picture description here

Reference article: