hough_lines_nodelet.cpp

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// https://github.com/Itseez/opencv/blob/2.4/samples/cpp/tutorial_code/ImgTrans/HoughLines_Demo.cpp
#include <ros/ros.h>
#include "opencv_apps/nodelet.h"
#include <image_transport/image_transport.h>
#include <cv_bridge/cv_bridge.h>
#include <sensor_msgs/image_encodings.h>

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

#include <dynamic_reconfigure/server.h>
#include "opencv_apps/HoughLinesConfig.h"
#include "opencv_apps/Line.h"
#include "opencv_apps/LineArray.h"
#include "opencv_apps/LineArrayStamped.h"

namespace hough_lines {
class HoughLinesNodelet : public opencv_apps::Nodelet
{
  image_transport::Publisher img_pub_;
  image_transport::Subscriber img_sub_;
  image_transport::CameraSubscriber cam_sub_;
  ros::Publisher msg_pub_;

  boost::shared_ptr<image_transport::ImageTransport> it_;

  typedef hough_lines::HoughLinesConfig Config;
  typedef dynamic_reconfigure::Server<Config> ReconfigureServer;
  Config config_;
  boost::shared_ptr<ReconfigureServer> reconfigure_server_;

  bool debug_view_;
  ros::Time prev_stamp_;

  std::string window_name_;
  static bool need_config_update_;

  int min_threshold_;
  int max_threshold_;
  int threshold_;
  double rho_;
  double theta_;
  double minLineLength_;
  double maxLineGap_;

  void reconfigureCallback(Config &new_config, uint32_t level)
  {
    config_         = new_config;
    rho_            = config_.rho;
    theta_          = config_.theta;
    threshold_      = config_.threshold;
    minLineLength_  = config_.minLineLength;
    maxLineGap_     = config_.maxLineGap;
  }

  const std::string &frameWithDefault(const std::string &frame, const std::string &image_frame)
  {
    if (frame.empty())
      return image_frame;
    return frame;
  }

  void imageCallbackWithInfo(const sensor_msgs::ImageConstPtr& msg, const sensor_msgs::CameraInfoConstPtr& cam_info)
  {
    do_work(msg, cam_info->header.frame_id);
  }

  void imageCallback(const sensor_msgs::ImageConstPtr& msg)
  {
    do_work(msg, msg->header.frame_id);
  }

  static void trackbarCallback( int, void* )
  {
    need_config_update_ = true;
  }

  void do_work(const sensor_msgs::ImageConstPtr& msg, const std::string input_frame_from_msg)
  {
    // Work on the image.
    try
    {
      // Convert the image into something opencv can handle.
      cv::Mat in_image = cv_bridge::toCvShare(msg, sensor_msgs::image_encodings::BGR8)->image;
      cv::Mat src_gray;

      if (in_image.channels() > 1) {
        cv::cvtColor( in_image, src_gray, cv::COLOR_BGR2GRAY );
        Canny( src_gray, in_image, 50, 200, 3 );
      }
      else {
        bool is_filtered = true;
        for(int y=0; y < in_image.rows; ++y) {
          for(int x=0; x < in_image.cols; ++x) {
            if(!(in_image.at<unsigned char>(y, x) == 0
                 || in_image.at<unsigned char>(y, x) == 255)) {
              is_filtered = false;
              break;
            }
            if(!is_filtered) {
              break;
            }
          }
        }

        if(!is_filtered) {
          Canny( in_image, in_image, 50, 200, 3 );
        }
      }

      cv::Mat out_image;
      cv::cvtColor(in_image, out_image, CV_GRAY2BGR);

      // Messages
      opencv_apps::LineArrayStamped lines_msg;
      lines_msg.header = msg->header;

      // Do the work
      std::vector<cv::Rect> faces;

      if( debug_view_) {
        char thresh_label[50];
        sprintf( thresh_label, "Thres: %d + input", min_threshold_ );

        cv::namedWindow( window_name_, cv::WINDOW_AUTOSIZE );
        cv::createTrackbar( thresh_label, window_name_, &threshold_, max_threshold_, trackbarCallback);
        if (need_config_update_) {
          config_.threshold = threshold_;
          reconfigure_server_->updateConfig(config_);
          need_config_update_ = false;
        }
      }

      switch (config_.hough_type) {
        case hough_lines::HoughLines_Standard_Hough_Transform:
          {
            std::vector<cv::Vec2f> s_lines;

            cv::HoughLines( in_image, s_lines, rho_, theta_ * CV_PI/180, threshold_, minLineLength_, maxLineGap_ );

            for( size_t i = 0; i < s_lines.size(); i++ )
            {
              float r = s_lines[i][0], t = s_lines[i][1];
              double cos_t = cos(t), sin_t = sin(t);
              double x0 = r*cos_t, y0 = r*sin_t;
              double alpha = 1000;

              cv::Point pt1( cvRound(x0 + alpha*(-sin_t)), cvRound(y0 + alpha*cos_t) );
              cv::Point pt2( cvRound(x0 - alpha*(-sin_t)), cvRound(y0 - alpha*cos_t) );
#ifndef CV_VERSION_EPOCH
              cv::line( out_image, pt1, pt2, cv::Scalar(255,0,0), 3, cv::LINE_AA);
#else
              cv::line( out_image, pt1, pt2, cv::Scalar(255,0,0), 3, CV_AA);
#endif
              opencv_apps::Line line_msg;
              line_msg.pt1.x = pt1.x;
              line_msg.pt1.y = pt1.y;
              line_msg.pt2.x = pt2.x;
              line_msg.pt2.y = pt2.y;
              lines_msg.lines.push_back(line_msg);
            }

            break;
          }
        case hough_lines::HoughLines_Probabilistic_Hough_Transform:
        default:
          {
            std::vector<cv::Vec4i> p_lines;

            cv::HoughLinesP( in_image, p_lines, rho_, theta_ * CV_PI/180, threshold_, minLineLength_, maxLineGap_ );

            for( size_t i = 0; i < p_lines.size(); i++ )
            {
              cv::Vec4i l = p_lines[i];
#ifndef CV_VERSION_EPOCH
              cv::line( out_image, cv::Point(l[0], l[1]), cv::Point(l[2], l[3]), cv::Scalar(255,0,0), 3, cv::LINE_AA);
#else
              cv::line( out_image, cv::Point(l[0], l[1]), cv::Point(l[2], l[3]), cv::Scalar(255,0,0), 3, CV_AA);
#endif
              opencv_apps::Line line_msg;
              line_msg.pt1.x = l[0];
              line_msg.pt1.y = l[1];
              line_msg.pt2.x = l[2];
              line_msg.pt2.y = l[3];
              lines_msg.lines.push_back(line_msg);
            }

            break;
          }
      }

      //-- Show what you got
      if( debug_view_) {
        cv::imshow( window_name_, out_image );
        int c = cv::waitKey(1);
      }

      // Publish the image.
      sensor_msgs::Image::Ptr out_img = cv_bridge::CvImage(msg->header, "bgr8", out_image).toImageMsg();
      img_pub_.publish(out_img);
      msg_pub_.publish(lines_msg);
    }
    catch (cv::Exception &e)
    {
      NODELET_ERROR("Image processing error: %s %s %s %i", e.err.c_str(), e.func.c_str(), e.file.c_str(), e.line);
    }

    prev_stamp_ = msg->header.stamp;
  }

  void subscribe()
  {
    NODELET_DEBUG("Subscribing to image topic.");
    if (config_.use_camera_info)
      cam_sub_ = it_->subscribeCamera("image", 3, &HoughLinesNodelet::imageCallbackWithInfo, this);
    else
      img_sub_ = it_->subscribe("image", 3, &HoughLinesNodelet::imageCallback, this);
  }

  void unsubscribe()
  {
    NODELET_DEBUG("Unsubscribing from image topic.");
    img_sub_.shutdown();
    cam_sub_.shutdown();
  }

public:
  virtual void onInit()
  {
    Nodelet::onInit();
    it_ = boost::shared_ptr<image_transport::ImageTransport>(new image_transport::ImageTransport(*nh_));

    pnh_->param("debug_view", debug_view_, false);
    if (debug_view_) {
      always_subscribe_ = true;
    }
    prev_stamp_ = ros::Time(0, 0);

    window_name_ = "Hough Lines Demo";
    min_threshold_ = 50;
    max_threshold_ = 150;
    threshold_ = max_threshold_;

    reconfigure_server_ = boost::make_shared<dynamic_reconfigure::Server<Config> >(*pnh_);
    dynamic_reconfigure::Server<Config>::CallbackType f =
      boost::bind(&HoughLinesNodelet::reconfigureCallback, this, _1, _2);
    reconfigure_server_->setCallback(f);

    img_pub_ = advertiseImage(*pnh_, "image", 1);
    msg_pub_ = advertise<opencv_apps::LineArrayStamped>(*pnh_, "lines", 1);

    onInitPostProcess();
  }
};
bool HoughLinesNodelet::need_config_update_ = false;
}

#include <pluginlib/class_list_macros.h>
PLUGINLIB_EXPORT_CLASS(hough_lines::HoughLinesNodelet, nodelet::Nodelet);