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#ifndef DEPTH_IMAGE_PROC__CONVERSIONS_HPP_
#define DEPTH_IMAGE_PROC__CONVERSIONS_HPP_

#include <limits>

#include "image_geometry/pinhole_camera_model.hpp"

#include <opencv2/core/mat.hpp>

#include <depth_image_proc/depth_traits.hpp>
#include <sensor_msgs/point_cloud2_iterator.hpp>
#include <sensor_msgs/msg/image.hpp>
#include <sensor_msgs/msg/point_cloud2.hpp>

namespace depth_image_proc
{

// Handles float or uint16 depths
template<typename T>
void convertDepth(
  const sensor_msgs::msg::Image::ConstSharedPtr & depth_msg,
  sensor_msgs::msg::PointCloud2::SharedPtr & cloud_msg,
  const image_geometry::PinholeCameraModel & model,
  double range_max = 0.0)
{
  // Use correct principal point from calibration
  float center_x = model.cx();
  float center_y = model.cy();

  // Combine unit conversion (if necessary) with scaling by focal length for computing (X,Y)
  double unit_scaling = DepthTraits<T>::toMeters(T(1) );
  float constant_x = unit_scaling / model.fx();
  float constant_y = unit_scaling / model.fy();
  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 < static_cast<int>(cloud_msg->height); ++v, depth_row += row_step) {
    for (int u = 0; u < static_cast<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)) {
        if (range_max != 0.0) {
          depth = DepthTraits<T>::fromMeters(range_max);
        } else {
          *iter_x = *iter_y = *iter_z = bad_point;
          continue;
        }
      }

      // Fill in XYZ
      *iter_x = (u - center_x) * depth * constant_x;
      *iter_y = (v - center_y) * depth * constant_y;
      *iter_z = DepthTraits<T>::toMeters(depth);
    }
  }
}

// Handles float or uint16 depths
template<typename T>
void convertDepthRadial(
  const sensor_msgs::msg::Image::ConstSharedPtr & depth_msg,
  sensor_msgs::msg::PointCloud2::SharedPtr & cloud_msg,
  cv::Mat & transform)
{
  // Combine unit conversion (if necessary) with scaling by focal length for computing (X,Y)
  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 < static_cast<int>(cloud_msg->height); ++v, depth_row += row_step) {
    for (int u = 0; u < static_cast<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 = transform.at<cv::Vec3f>(u, v) * DepthTraits<T>::toMeters(depth);
      // Fill in XYZ
      *iter_x = cvPoint(0);
      *iter_y = cvPoint(1);
      *iter_z = cvPoint(2);
    }
  }
}

// Handles float or uint16 depths
template<typename T>
void convertIntensity(
  const sensor_msgs::msg::Image::ConstSharedPtr & intensity_msg,
  sensor_msgs::msg::PointCloud2::SharedPtr & cloud_msg)
{
  sensor_msgs::PointCloud2Iterator<float> iter_i(*cloud_msg, "intensity");
  const T * inten_row = reinterpret_cast<const T *>(&intensity_msg->data[0]);

  const int i_row_step = intensity_msg->step / sizeof(T);
  for (int v = 0; v < static_cast<int>(cloud_msg->height); ++v, inten_row += i_row_step) {
    for (int u = 0; u < static_cast<int>(cloud_msg->width); ++u, ++iter_i) {
      *iter_i = inten_row[u];
    }
  }
}

// Handles RGB8, BGR8, and MONO8
void convertRgb(
  const sensor_msgs::msg::Image::ConstSharedPtr & rgb_msg,
  sensor_msgs::msg::PointCloud2::SharedPtr & cloud_msg,
  int red_offset, int green_offset, int blue_offset, int color_step);

cv::Mat initMatrix(cv::Mat cameraMatrix, cv::Mat distCoeffs, int width, int height, bool radial);

}  // namespace depth_image_proc

#endif  // DEPTH_IMAGE_PROC__CONVERSIONS_HPP_