Error viewing image on Rqt after converting to HSV color space by OpenCV

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I have a custom robot modeled in a urdf file where I have attached a camera to simulate it in gazebo. I followed the Ros wiki tutorial for converting Ros Noetic images to OpenCV.

http://wiki.ros.org/cv_bridge/Tutoria...

By the help of this tutorial I was able to convert between Ros and OpenCV images. I was able to draw a small circle on the camera feed and view the image in rqt through the new image topic using OpenCV. But now I want to convert the rgb image from gazebo into HSV color space based on specific ranges. I am able to view the modified HSV image through the OpenCV image window but I cannot access the image through rqt. I have checked by the echoing to the resulting topic /image_converter/output_video and all the data is being published.

But when I open rqt and select the same topic, I get the following error and a grey blank screen.

ImageView.callback_image() while trying to convert image from 'bgr8' to 'rgb8' an exception was thrown (Image is wrongly formed: step < width * byte_depth * num_channels  or  800 != 800 * 1 * 3)

When i try to access the compressed topic, /image_converter/output_video/compressed, I get the following error and similar blank grey screen

[ERROR] [1682104858.931709014, 22.482000000]: OpenCV(4.2.0) ../modules/imgcodecs/src/loadsave.cpp:730: error: (-215:Assertion failed) !buf.empty() in function 'imdecode_'

I can access and draw shapes the image and access it through rqt without any problem. But converting them to HSV space is a problem, although I can view the modified HSV image in the OpenCV window. I have checked the image size being through OpenCV size function and image width is 800 and height is 1080. Kindly suggest any changes I can do to be able to view the HSV image through rqt.

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

static const std::string OPENCV_WINDOW = "Image window";

class ImageConverter
{
  ros::NodeHandle nh_;
  image_transport::ImageTransport it_;
  image_transport::Subscriber image_sub_;
  image_transport::Publisher image_pub_;

public:
  ImageConverter()
    : it_(nh_)
  {
    // Subscrive to input video feed and publish output video feed
    image_sub_ = it_.subscribe("/weedingrobot/camera_front/image_raw", 1,
      &ImageConverter::imageCb, this);
    image_pub_ = it_.advertise("/image_converter/output_video", 1);

    cv::namedWindow(OPENCV_WINDOW);

  }

  ~ImageConverter()
  {
    cv::destroyWindow(OPENCV_WINDOW);
  }

  void imageCb(const sensor_msgs::ImageConstPtr& msg)

  {
    cv_bridge::CvImagePtr cv_ptr;
    try
    {
      cv_ptr = cv_bridge::toCvCopy(msg, sensor_msgs::image_encodings::BGR8);
    }
    catch (cv_bridge::Exception& e)
    {
      ROS_ERROR("cv_bridge exception: %s", e.what());
      return;
    }
       ROS_INFO_STREAM("Width " << cv_ptr->image.cols);        
   ROS_INFO_STREAM("Height " << cv_ptr->image.rows);      
   cv::Mat hsv;
   cv::Mat mask;



  // Draw an example circle on the video stream
    if (cv_ptr->image.rows > 60 && cv_ptr->image.cols > 60)
      cv::circle(cv_ptr->image, cv::Point(50, 50), 10, CV_RGB(255,0,0));

    int hmin=49, smin=57, vmin=0;
    int hmax=82, smax=255, vmax=255;


   cv::Scalar lower(hmin, smin, vmin);
    cv::Scalar upper(hmax, smax, vmax);
    cv::cvtColor(cv_ptr->image, hsv, cv::COLOR_BGR2HSV);
    cv ...