JETSON AGX XAVIER GMSL2接口相机驱动

环境：opencv 3.4.15、 ROS melodic

ros中使用usb相机

首先创建一个工作空间：

$ mkdir -p ~/ros_ws/src
$ cd ~/ros_ws/
$ catkin_make
$ source devel/setup.bash

再建立一个功能包：

$ cd ~/ros_ws/src
$ catkin_create_pkg learning_image_transport roscpp std_msgs cv_bridge image_transport sensor_msgs 

然后在功能包learning_image_transport下的src目录中建立两个cpp文件：

$ cd ~/ros_ws/src/learning_image_transport/src/
$ gedit my_publisher.cpp

将下列代码复制进去：

#include   
#include   
#include   
#include   
#include  // for converting the command line parameter to integer  

int main(int argc, char** argv)  
{  
    // Check if video source has been passed as a parameter  
    if(argv[1] == NULL)   
    {  
        ROS_INFO("argv[1]=NULL\n");  
        return 1;  
    }  

    ros::init(argc, argv, "image_publisher");  
    ros::NodeHandle nh;  
    image_transport::ImageTransport it(nh);  
    image_transport::Publisher pub = it.advertise("camera/image", 1);  

    // Convert the passed as command line parameter index for the video device to an integer  
    std::istringstream video_sourceCmd(argv[1]);  
    int video_source;  
    // Check if it is indeed a number  
    if(!(video_sourceCmd >> video_source))   
    {  
        ROS_INFO("video_sourceCmd is %d\n",video_source);  
        return 1;  
    }  

    cv::VideoCapture cap(video_source);  
    // Check if video device can be opened with the given index  
    if(!cap.isOpened())   
    {  
        ROS_INFO("can not opencv video device\n");  
        return 1;  
    }  
    cv::Mat frame;  
    sensor_msgs::ImagePtr msg;  

    ros::Rate loop_rate(5);  
    while (nh.ok()) 
    {  
        cap >> frame;  
        // Check if grabbed frame is actually full with some content  
        if(!frame.empty()) 
        {  
            msg = cv_bridge::CvImage(std_msgs::Header(), "bgr8", frame).toImageMsg();  
            pub.publish(msg);  
            //cv::Wait(1);  
    	}  
    }
    
    ros::spinOnce();  
    loop_rate.sleep();  
}  

保存以后，继续创建my_subscriber.cpp：

$ gedit my_subscriber.cpp

复制下列代码：

#include   
#include   
#include   
#include   

void imageCallback(const sensor_msgs::ImageConstPtr& msg)  
{  
	try  
	{  
		cv::imshow("view", cv_bridge::toCvShare(msg, "bgr8")->image); 
		// cv::waitKey(30);  
	}  
	catch (cv_bridge::Exception& e)  
	{  
		ROS_ERROR("Could not convert from '%s' to 'bgr8'.", msg->encoding.c_str());  
	}  
}  

int main(int argc, char **argv)  
{  
	ros::init(argc, argv, "image_listener");  
	ros::NodeHandle nh;  
	cv::namedWindow("view");  
	cv::startWindowThread();  
	image_transport::ImageTransport it(nh);  
	image_transport::Subscriber sub = it.subscribe("camera/image", 1,imageCallback);  
	ros::spin();  
	cv::destroyWindow("view");  
}  

接下来要把涉及到的各种包和opencv在CMakeList中声明一下，回到程序包目录下。

$ cd ~/ros_ws/src/learning_image_transport/
$ gedit CMakeLists.txt

添加以下语句：

find_package(OpenCV REQUIRED)  
# add the publisher example  
add_executable(my_publisher src/my_publisher.cpp)  

target_link_libraries(my_publisher ${catkin_LIBRARIES} ${OpenCV_LIBRARIES})  

# add the subscriber example  
add_executable(my_subscriber src/my_subscriber.cpp)  
target_link_libraries(my_subscriber ${catkin_LIBRARIES} ${OpenCV_LIBRARIES}) 

将这个包进行编译：

$ cd ~/ros_ws/
$ catkin_make  

接下来开始运行程序,首先启动ROS。

$ roscore 

运行my_publisher节点.(如果运行不起来,需要先source devel/setup.bash)。

$ rosrun learning_image_transport my_publisher 0 

这时候会看到我们的摄像头灯已经亮起来了,0代表默认摄像头,如果有多个摄像头,则第二个是1,依次类推。

接下来运行my_subscriber节点来接收图像。

$ rosrun learning_image_transport my_subscriber

ros订阅图像

ros编写发布/接收图片的结点(Python)

新建py文件 /AGV/src/image_processing/scripts/image_process.py

#!/usr/bin/env python2.7
#coding:utf-8

import rospy
import cv2
from sensor_msgs.msg import Image
from cv_bridge import CvBridge,CvBridgeError

def callback(data):         	
	cv_image=CvBridge().imgmsg_to_cv2(data,"bgr8")
	cv2.imshow("view",cv_image)
	cv2.waitKey(1)

if __name__ == '__main__':
    rospy.init_node('image_acquistion')
    rospy.Subscriber('camera/image', Image, callback)
    rospy.spin()
    cv2.destoryAllWindows()
    

rosrun image_processing image_process.py