Ubuntu安装usb相机驱动usb_cam

最新推荐文章于 2025-03-05 14:23:04 发布

呆弱木鸡

最新推荐文章于 2025-03-05 14:23:04 发布

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本文链接：https://blog.youkuaiyun.com/supma374686/article/details/139282734

版权

前言

对于一般的USB相机，没有专门的相机驱动供我们使用，利用ros功能包usb_cam可以让我们把相机传感器接收到的图片信息转化为topic供其他程序使用

创建工作空间

mkdir -p usb_ws/src
cd usb_ws/src
catkin_init_workspace

编译工作空间

cd ~/usb_ws/
catkin_make

使得环境变量在所有的终端中都有效

echo "source ~/usb_ws/devel/setup.bash" >> ~/.bashrc
source ~/.bashrc

查看添加的环境变量是否生效：

echo $ROS_PACKAGE_PATH

编译安装USB相机驱动

下载usb_cam压缩包

在网站：usb_cam选择合适的压缩包（我是ubuntu20.04/ros neotic选择的是develop的包)

提取到工作空间/usb_ws/src目录下

编译代码文件

cd usb_ws
catkin_make

报错

No package 'libv4l2' found

再打开一个终端，输入

sudo apt-get install libv4l-dev

然后重新编译即可

修改启动文件

将相机插入电脑，利用指令

ls /dev/video*

查看相机设备号

打开launch文件usb_cam-test.lauch，修改如下：

<launch>
  <arg name="image_view" default="false" />

  <node name="usb_cam" pkg="usb_cam" type="usb_cam_node" output="screen" >
      <rosparam command="load" file="$(find usb_cam)/config/usb_cam.yml"/>
      <param name="video_device" value="/dev/video0" />
    //把/dev/video0修改为自己相机对应的设备号
      <param name="image_width" value="640" />
      <param name="image_height" value="480" />
      <param name="pixel_format" value="yuyv" />
    //usb_cam支持三种图片格式：yuyv，mjpeg，uyvy，可以先设置为yuyv，移动摄像头，如果画面很卡顿那就轮流试试mjpeg和uyuv
      <param name="camera_frame_id" value="usb_cam" />
      <param name="io_method" value="mmap" />
  </node>
  <node if="$(arg image_view)" name="image_view" pkg="image_view" type="image_view"
        respawn="false" output="screen">
    <remap from="image" to="/usb_cam/image_raw"/>
    <param name="autosize" value="true" />
  </node>
</launch>

如果需要运行双目单usb端口摄像头，launch文件单目的大体相同，只是改第四第五行分辨率640*480为2560*720，如果不改分辨率640*480只有双目其中一个摄像头的画面，2560*720是两个1280*720的图像，改完分辨率运行步骤与单目相同

编译usb_cam相机驱动

cd usb_ws
catkin_make

使工作空间的环境变量永久有效

 source devel/setup.bash  
 echo "source ~/usb_ws/devel/setup.sh" >> ~/.bashrc          //永久生效环境

启动相机节点接收信息

使用指令：

roslaunch usb_cam usb_cam-test.launch

启动相机，再打开rviz选择相应的topic即可查看图像信息

分割双目图像

1.创建工作空间并添加依赖

mkdir -p cut_ws/src 
cd cut_ws 
catkin_make
cd src
catkin_create_pkg camera_split cv_bridge image_transport roscpp sensor_msgs std_msgs camera_info_manager

2.修改CMakeList.txt文件

find_package(OpenCV REQUIRED)
#修改include_directories:
include_directories (
    ${catkin_INCLUDE_DIRS}
    ${OpenCV_INCLUDE_DIRS}
)
#添加可执行文件
add_executable(camera_split_node src/camera_split.cpp )
#指定链接库
target_link_libraries(camera_split_node
    ${catkin_LIBRARIES}
    ${OpenCV_LIBRARIES}
)

3.创建源代码文件camera_split.cpp

//
// Created by daybeha on 2022/1/27.
//

#include <ros/ros.h>
#include <iostream>
#include <image_transport/image_transport.h>
#include <cv_bridge/cv_bridge.h>
#include <sensor_msgs/image_encodings.h>
#include <camera_info_manager/camera_info_manager.h>

#include <opencv2/opencv.hpp>
//#include <opencv2/imgproc/imgproc.hpp>
//#include <opencv2/highgui/highgui.hpp>

using namespace std;

class CameraSplitter
{
public:
    CameraSplitter():nh_("~"),it_(nh_)
    {
        image_sub_ = it_.subscribe("/usb_cam/image_raw", 1, &CameraSplitter::imageCallback, this);
        image_pub_left_ = it_.advertiseCamera("/left_cam/image_raw", 1);
        image_pub_right_ = it_.advertiseCamera("/right_cam/image_raw", 1);
        cinfo_ =boost::shared_ptr<camera_info_manager::CameraInfoManager>(new camera_info_manager::CameraInfoManager(nh_));

        //读取参数服务器参数，得到左右相机参数文件的位置
        string left_cal_file = nh_.param<std::string>("left_cam_file", "");
        string right_cal_file = nh_.param<std::string>("right_cam_file", "");
        if(!left_cal_file.empty())
        {
            if(cinfo_->validateURL(left_cal_file)) {
                cout<<"Load left camera info file: "<<left_cal_file<<endl;
                cinfo_->loadCameraInfo(left_cal_file);
                ci_left_ = sensor_msgs::CameraInfoPtr(new sensor_msgs::CameraInfo(cinfo_->getCameraInfo()));
            }
            else {
                cout<<"Can't load left camera info file: "<<left_cal_file<<endl;
                ros::shutdown();
            }
        }
        else {
            cout<<"Did not specify left camera info file." <<endl;
            ci_left_=sensor_msgs::CameraInfoPtr(new sensor_msgs::CameraInfo());
        }
        if(!right_cal_file.empty())
        {
            if(cinfo_->validateURL(right_cal_file)) {
                cout<<"Load right camera info file: "<<right_cal_file<<endl;
                cinfo_->loadCameraInfo(right_cal_file);
                ci_right_ = sensor_msgs::CameraInfoPtr(new sensor_msgs::CameraInfo(cinfo_->getCameraInfo()));
            }
            else {
                cout<<"Can't load right camera info file: "<<left_cal_file<<endl;
                ros::shutdown();
            }
        }
        else {
            cout<<"Did not specify right camera info file." <<endl;
            ci_right_=sensor_msgs::CameraInfoPtr(new sensor_msgs::CameraInfo());
        }
    }

    void imageCallback(const sensor_msgs::ImageConstPtr& msg)
    {
        cv_bridge::CvImageConstPtr cv_ptr;
        namespace enc= sensor_msgs::image_encodings;
        cv_ptr= cv_bridge::toCvShare(msg, enc::BGR8);
        //截取ROI(Region Of Interest)，即左右图像，会将原图像数据拷贝出来。
        leftImgROI_=cv_ptr->image(cv::Rect(0,0,cv_ptr->image.cols/2, cv_ptr->image.rows));
        rightImgROI_=cv_ptr->image(cv::Rect(cv_ptr->image.cols/2,0, cv_ptr->image.cols/2, cv_ptr->image.rows ));
        //创建两个CvImage, 用于存放原始图像的左右部分。CvImage创建时是对Mat进行引用的,不会进行数据拷贝
        leftImgPtr_=cv_bridge::CvImagePtr(new cv_bridge::CvImage(cv_ptr->header, cv_ptr->encoding,leftImgROI_) );
        rightImgPtr_=cv_bridge::CvImagePtr(new cv_bridge::CvImage(cv_ptr->header, cv_ptr->encoding,rightImgROI_) );

        //发布到/left_cam/image_raw和/right_cam/image_raw
        ci_left_->header = cv_ptr->header; 	//很重要，不然会提示不同步导致无法去畸变
        ci_right_->header = cv_ptr->header;
        sensor_msgs::ImagePtr leftPtr =leftImgPtr_->toImageMsg();
        sensor_msgs::ImagePtr rightPtr =rightImgPtr_->toImageMsg();
        leftPtr->header=msg->header; 		//很重要，不然输出的图象没有时间戳
        rightPtr->header=msg->header;
        image_pub_left_.publish(leftPtr,ci_left_);
        image_pub_right_.publish(rightPtr,ci_right_);
    }

private:
    ros::NodeHandle nh_;
    image_transport::ImageTransport it_;
    image_transport::Subscriber image_sub_;
    image_transport::CameraPublisher image_pub_left_;
    image_transport::CameraPublisher image_pub_right_;
    boost::shared_ptr<camera_info_manager::CameraInfoManager> cinfo_;
    sensor_msgs::CameraInfoPtr ci_left_;
    sensor_msgs::CameraInfoPtr ci_right_;

    cv::Mat leftImgROI_;
    cv::Mat rightImgROI_;
    cv_bridge::CvImagePtr leftImgPtr_=NULL;
    cv_bridge::CvImagePtr rightImgPtr_=NULL;
};

int main(int argc,char** argv)
{
    ros::init(argc,argv, "camera_split");
    CameraSplitter cameraSplitter;
    ros::spin();
    return 0;
}

5.创建launch文件camera_split_no_calibration.launch

<launch>
    <node pkg="camera_split" type="camera_split_node" name="camera_split_node" output="screen" />
    <node pkg="image_view" type="image_view" name="image_view_left" respawn="false" output="screen">
        <remap from="image" to="/left_cam/image_raw"/>
        <param name="autosize" value="true" />
    </node>
    <node pkg="image_view" type="image_view" name="image_view_right" respawn="false" output="screen">
        <remap from="image" to="/right_cam/image_raw"/>
        <param name="autosize" value="true" />
    </node>
</launch>

6.运行查看效果：

cd cut_ws
catkin_make
source ./devel/setup.bash
roslaunch camera_split camera_split_no_calibration.launch