淘到一個雙目攝像頭,輸出是左右鏡頭合到一起的影象.
最大2560*[email protected]
pixel format mjpeg

接入ros下執行有資訊提示:

deprecated pixel format used, make sure you did set range correctly
使用了否決的畫素格式,確認設定了範圍?


看了這篇
http://www.ffmpeg-archive.org/MJPEG-Deprecated-pixel-format-warning-td4663994.html
說
警告主要是針對庫使用者的，ffmpeg的使用者應該不會受到影響。
不知ros下使用會不會受影響,先忽略之.




問題:
攝像頭校正需要左右影象分別輸入.
需想辦法把影象切分,釋出到兩個主題上去.

解決:
檢視攝像頭驅動原始碼是把cv::Mat轉成影象訊息然後釋出到相應主題.

影象訊息和cv::Mat相互轉換.

void publish_test_img(){
    cv::Mat image = cv::imread("/home/zzz/20170415095236604.png", CV_LOAD_IMAGE_COLOR);
    if(image.empty()){
     printf("open error\n");
    }else{
    msg = cv_bridge::CvImage(std_msgs::Header(), "bgr8", image).toImageMsg();
    pub_left.publish(msg);
    ros::spinOnce();
    }
  }
 

 void convert_callback(const sensor_msgs::ImageConstPtr& msg)
  {
    cv_bridge::CvImagePtr cv_ptr; // 宣告一個CvImage指標的例項

    try
    {
        cv_ptr =  cv_bridge::toCvCopy(msg, sensor_msgs::image_encodings::BGR8); //將ROS訊息中的圖象資訊提取，生成新cv型別的圖象，複製給CvImage指標
    }
    catch(cv_bridge::Exception& e)  //異常處理
    {
        ROS_ERROR("cv_bridge exception: %s", e.what());
        return;
    }

    image_process(cv_ptr->image); //得到了cv::Mat型別的圖象，在CvImage指標的image中，將結果傳送給處理函式
  }
 

  cv::Mat image_split(cv::Mat img,CvRect rect){
    // 獲取影象
    int crop_x1 = cv::max(0,rect.x);
    int crop_y1 = cv::max(0,rect.y);
    int crop_x2 = cv::min(img.cols - 1, rect.x + rect.width - 1); // 影象範圍 0到cols-1, 0到rows-1
    int crop_y2 = cv::min(img.rows - 1, rect.y + rect.height - 1);

    return img(cv::Range(crop_y1,crop_y2 + 1),cv::Range(crop_x1,crop_x2 + 1));// 左包含，右不包含

  }

校正效果圖:

launch

<launch>
<node name="imgpub" pkg="zzz_opencv_test" type="rosopencv" output="screen">
<remap from="/camera/image_raw" to="/usb_cam/image_raw"/>
</node>
<node  name="cameracalibrator"
      pkg="camera_calibration" type="cameracalibrator.py"
      args="--size 8x6 --square 0.028778" output="screen">
  <remap from="left" to="camera/image/lefteye"/>
  <remap from="right" to="camera/image/righteye"/>

  <remap from="left_camera" to="usb_cam"/>
  <remap from="right_camera" to="usb_cam"/>

</node>
<!--
<node name="rviz"  pkg="rviz" type="rviz" respawn="false"
       output="screen">
</node>
-->
</launch>

彙總原始碼:

#include <ros/ros.h>
#include <image_transport/image_transport.h>
//#include <opencv2/highgui/highgui.hpp>
#include <cv_bridge/cv_bridge.h>

#include <stdio.h>



//OpenCV2標準標頭檔案
#include<opencv2/core/core.hpp>
#include<opencv2/highgui/highgui.hpp>
#include<opencv2/imgproc/imgproc.hpp>
static const std::string INPUT = "Input"; //定義輸入視窗名稱
static const std::string OUTPUT_LEFT = "OUTPUT_LEFT"; //定義輸出視窗名稱
static const std::string OUTPUT_RIGHT = "OUTPUT_RIGHT"; //定義輸出視窗名稱
class shuangmu2LeftRight
{
private:
  ros::NodeHandle nh; //定義ROS控制代碼
  sensor_msgs::ImagePtr msg ;
  image_transport::ImageTransport it;
  image_transport::Publisher pub_left;
  image_transport::Publisher pub_right;
  image_transport::Subscriber shuangmu_image_sub_;//定義ROS圖象接收器
public:
  shuangmu2LeftRight()
  :it(nh) //建構函式
  {

    pub_left = it.advertise("camera/image/lefteye", 1);
    pub_right = it.advertise("camera/image/righteye", 1);
    shuangmu_image_sub_ = it.subscribe("camera/image_raw", 1, &shuangmu2LeftRight::convert_callback,this);

    //初始化輸入輸出視窗
    cv::namedWindow(INPUT);
    cv::namedWindow(OUTPUT_LEFT);
    cv::namedWindow(OUTPUT_RIGHT);
    publish_test_img();
  }
  ~shuangmu2LeftRight() //解構函式
  {
    cv::destroyWindow(INPUT);
    cv::destroyWindow(OUTPUT_LEFT);
    cv::destroyWindow(OUTPUT_RIGHT);
  }
  void publish_test_img(){
    cv::Mat image = cv::imread("/home/zzz/20170415095236604.png", CV_LOAD_IMAGE_COLOR);
    if(image.empty()){
     printf("open error\n");
    }else{
    msg = cv_bridge::CvImage(std_msgs::Header(), "bgr8", image).toImageMsg();
    pub_left.publish(msg);
    ros::spinOnce();
    }
  }

  /*
        這是一個ROS和OpenCV的格式轉換回調函式，將圖象格式從sensor_msgs/Image  --->  cv::Mat
      */
  void convert_callback(const sensor_msgs::ImageConstPtr& msg)
  {
    cv_bridge::CvImagePtr cv_ptr; // 宣告一個CvImage指標的例項

    try
    {
        cv_ptr =  cv_bridge::toCvCopy(msg, sensor_msgs::image_encodings::BGR8); //將ROS訊息中的圖象資訊提取，生成新cv型別的圖象，複製給CvImage指標
    }
    catch(cv_bridge::Exception& e)  //異常處理
    {
        ROS_ERROR("cv_bridge exception: %s", e.what());
        return;
    }

    image_process(cv_ptr->image); //得到了cv::Mat型別的圖象，在CvImage指標的image中，將結果傳送給處理函式
  }

  cv::Mat image_split(cv::Mat img,CvRect rect){
    // 獲取影象
    int crop_x1 = cv::max(0,rect.x);
    int crop_y1 = cv::max(0,rect.y);
    int crop_x2 = cv::min(img.cols - 1, rect.x + rect.width - 1); // 影象範圍 0到cols-1, 0到rows-1
    int crop_y2 = cv::min(img.rows - 1, rect.y + rect.height - 1);

    return img(cv::Range(crop_y1,crop_y2 + 1),cv::Range(crop_x1,crop_x2 + 1));// 左包含，右不包含

  }
  void image_process(cv::Mat img)
  {

    CvRect rect;

    rect.x        = 0;
    rect.y        = 0;
    rect.width    = img.cols/2;
    rect.height = img.rows;

    //cv::Mat I = cv::Mat::zeros(rect.height, rect.width, 0);// 目標影象
    cv::Mat roi_img=image_split(img,rect);
    msg = cv_bridge::CvImage(std_msgs::Header(), "bgr8", roi_img).toImageMsg();
    pub_left.publish(msg);
    cv::imshow(INPUT, img);
    cv::imshow(OUTPUT_LEFT, roi_img);
    rect.x        = img.cols/2;
    roi_img=image_split(img,rect);
    msg = cv_bridge::CvImage(std_msgs::Header(), "bgr8", roi_img).toImageMsg();
    pub_right.publish(msg);
    cv::imshow(OUTPUT_RIGHT, roi_img);
    cv::waitKey(5);

  }
};

int main(int argc, char** argv)
{
  //初始化節點
  ros::init(argc, argv, "rosopencv");
  shuangmu2LeftRight obj;
  ros::spin();

}