point_cloud_xyz_radial.cpp

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#include <ros/ros.h>
#include <nodelet/nodelet.h>
#include <image_transport/image_transport.h>
#include <sensor_msgs/image_encodings.h>
#include <image_geometry/pinhole_camera_model.h>
#include <opencv2/calib3d/calib3d.hpp>
#include <boost/thread.hpp>
#include <depth_image_proc/depth_traits.h>
 
#include <sensor_msgs/point_cloud2_iterator.h>
 
namespace depth_image_proc {
 
    namespace enc = sensor_msgs::image_encodings;
 
    class PointCloudXyzRadialNodelet : public nodelet::Nodelet
    {
        // Subscriptions
        boost::shared_ptr<image_transport::ImageTransport> it_;
        image_transport::CameraSubscriber sub_depth_;
        int queue_size_;
 
        // Publications
        boost::mutex connect_mutex_;
        typedef sensor_msgs::PointCloud2 PointCloud;
        ros::Publisher pub_point_cloud_;
 
        
        std::vector<double> D_;
        boost::array<double, 9> K_;
  
        int width_;
        int height_;
 
        cv::Mat binned;
  
        virtual void onInit();
 
        void connectCb();
 
        void depthCb(const sensor_msgs::ImageConstPtr& depth_msg,
                     const sensor_msgs::CameraInfoConstPtr& info_msg);
 
        // Handles float or uint16 depths
        template<typename T>
        void convert(const sensor_msgs::ImageConstPtr& depth_msg, PointCloud::Ptr& cloud_msg);
    };
 
    cv::Mat initMatrix(cv::Mat cameraMatrix, cv::Mat distCoeffs, int width, int height, bool radial)
    {
        int i,j;
        int totalsize = width*height;
        cv::Mat pixelVectors(1,totalsize,CV_32FC3);
        cv::Mat dst(1,totalsize,CV_32FC3);
 
        cv::Mat sensorPoints(cv::Size(height,width), CV_32FC2);
        cv::Mat undistortedSensorPoints(1,totalsize, CV_32FC2);
 
        std::vector<cv::Mat> ch;
        for(j = 0; j < height; j++)
        {
            for(i = 0; i < width; i++)
            {
                cv::Vec2f &p = sensorPoints.at<cv::Vec2f>(i,j);
                p[0] = i;
                p[1] = j;
            }
        }
 
        sensorPoints = sensorPoints.reshape(2,1);
 
        cv::undistortPoints(sensorPoints, undistortedSensorPoints, cameraMatrix, distCoeffs);
 
        ch.push_back(undistortedSensorPoints);
        ch.push_back(cv::Mat::ones(1,totalsize,CV_32FC1));
        cv::merge(ch,pixelVectors);
 
        if(radial)
        {
            for(i = 0; i < totalsize; i++)
            {
                normalize(pixelVectors.at<cv::Vec3f>(i),
                          dst.at<cv::Vec3f>(i));
            }
            pixelVectors = dst;
        }
        return pixelVectors.reshape(3,width);
    }
  
 
    void PointCloudXyzRadialNodelet::onInit()
    {
        ros::NodeHandle& nh         = getNodeHandle();
        ros::NodeHandle& private_nh = getPrivateNodeHandle();
        it_.reset(new image_transport::ImageTransport(nh));
 
        // Read parameters
        private_nh.param("queue_size", queue_size_, 5);
 
        // Monitor whether anyone is subscribed to the output
        ros::SubscriberStatusCallback connect_cb = 
            boost::bind(&PointCloudXyzRadialNodelet::connectCb, this);
        // Make sure we don't enter connectCb() between advertising and assigning to pub_point_cloud_
        boost::lock_guard<boost::mutex> lock(connect_mutex_);
        pub_point_cloud_ = nh.advertise<PointCloud>("points", 1, connect_cb, connect_cb);
    }
 
    // Handles (un)subscribing when clients (un)subscribe
    void PointCloudXyzRadialNodelet::connectCb()
    {
        boost::lock_guard<boost::mutex> lock(connect_mutex_);
        if (pub_point_cloud_.getNumSubscribers() == 0)
        {
            sub_depth_.shutdown();
        }
        else if (!sub_depth_)
        {
            image_transport::TransportHints hints("raw", ros::TransportHints(), getPrivateNodeHandle());
            sub_depth_ = it_->subscribeCamera("image_raw",
                                              queue_size_,
                                              &PointCloudXyzRadialNodelet::depthCb,
                                              this, hints);
        }
    }
 
    void PointCloudXyzRadialNodelet::depthCb(const sensor_msgs::ImageConstPtr& depth_msg,
                                             const sensor_msgs::CameraInfoConstPtr& info_msg)
    {
        PointCloud::Ptr cloud_msg(new PointCloud);
        cloud_msg->header = depth_msg->header;
        cloud_msg->height = depth_msg->height;
        cloud_msg->width  = depth_msg->width;
        cloud_msg->is_dense = false;
        cloud_msg->is_bigendian = false;
 
        sensor_msgs::PointCloud2Modifier pcd_modifier(*cloud_msg);
        pcd_modifier.setPointCloud2FieldsByString(1, "xyz");
 
        if(info_msg->D != D_ || info_msg->K != K_ || width_ != info_msg->width ||
           height_ != info_msg->height)
        {
            D_ = info_msg->D;
            K_ = info_msg->K;
            width_ = info_msg->width;
            height_ = info_msg->height;
            binned = initMatrix(cv::Mat_<double>(3, 3, &K_[0]),cv::Mat(D_),width_,height_,true);
        }
 
        if (depth_msg->encoding == enc::TYPE_16UC1)
        {
            convert<uint16_t>(depth_msg, cloud_msg);
        }
        else if (depth_msg->encoding == enc::TYPE_32FC1)
        {
            convert<float>(depth_msg, cloud_msg);
        }
        else
        {
            NODELET_ERROR_THROTTLE(5, "Depth image has unsupported encoding [%s]", depth_msg->encoding.c_str());
            return;
        }
 
        pub_point_cloud_.publish (cloud_msg);
    }
 
    template<typename T>
    void PointCloudXyzRadialNodelet::convert(const sensor_msgs::ImageConstPtr& depth_msg, PointCloud::Ptr& cloud_msg)
    {
        // Combine unit conversion (if necessary) with scaling by focal length for computing (X,Y)
        double unit_scaling = DepthTraits<T>::toMeters( T(1) );
        float bad_point = std::numeric_limits<float>::quiet_NaN();
 
        sensor_msgs::PointCloud2Iterator<float> iter_x(*cloud_msg, "x");
        sensor_msgs::PointCloud2Iterator<float> iter_y(*cloud_msg, "y");
        sensor_msgs::PointCloud2Iterator<float> iter_z(*cloud_msg, "z");
        const T* depth_row = reinterpret_cast<const T*>(&depth_msg->data[0]);
        int row_step = depth_msg->step / sizeof(T);
        for (int v = 0; v < (int)cloud_msg->height; ++v, depth_row += row_step)
        {
            for (int u = 0; u < (int)cloud_msg->width; ++u, ++iter_x, ++iter_y, ++iter_z)
            {
                T depth = depth_row[u];
 
                // Missing points denoted by NaNs
                if (!DepthTraits<T>::valid(depth))
                {
                    *iter_x = *iter_y = *iter_z = bad_point;
                    continue;
                }
                const cv::Vec3f &cvPoint = binned.at<cv::Vec3f>(u,v) * DepthTraits<T>::toMeters(depth);
                // Fill in XYZ
                *iter_x = cvPoint(0);
                *iter_y = cvPoint(1);
                *iter_z = cvPoint(2);
            }
        }
    }
 
} // namespace depth_image_proc
 
// Register as nodelet
#include <pluginlib/class_list_macros.hpp>
PLUGINLIB_EXPORT_CLASS(depth_image_proc::PointCloudXyzRadialNodelet,nodelet::Nodelet);