openni_ii_normal_estimation.cpp

/*
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 *  Copyright (c) 2011, Willow Garage, Inc.
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#include <pcl/common/time.h>
#include <pcl/console/parse.h>
#include <pcl/features/integral_image_normal.h>
#include <pcl/io/openni_camera/openni_driver.h>
#include <pcl/io/openni_grabber.h>
#include <pcl/visualization/cloud_viewer.h>
#include <pcl/point_cloud.h>
#include <pcl/point_types.h>

#include <mutex>
#include <thread>

using namespace std::chrono_literals;

// clang-format off
#define FPS_CALC(_WHAT_)                                                               \
  do {                                                                                 \
    static unsigned count = 0;                                                         \
    static double last = pcl::getTime();                                               \
    double now = pcl::getTime();                                                       \
    ++count;                                                                           \
    if (now - last >= 1.0) {                                                           \
      std::cout << "Average framerate(" << _WHAT_ << "): "                             \
                << double(count) / double(now - last) << " Hz" << std::endl;           \
      count = 0;                                                                       \
      last = now;                                                                      \
    }                                                                                  \
  } while (false)
// clang-format on

template <typename PointType>
class OpenNIIntegralImageNormalEstimation {
public:
  using Cloud = pcl::PointCloud<PointType>;
  using CloudPtr = typename Cloud::Ptr;
  using CloudConstPtr = typename Cloud::ConstPtr;

  OpenNIIntegralImageNormalEstimation(const std::string& device_id = "")
  : viewer("PCL OpenNI NormalEstimation Viewer"), device_id_(device_id)
  {
    ne_.setNormalEstimationMethod(
        pcl::IntegralImageNormalEstimation<PointType, pcl::Normal>::COVARIANCE_MATRIX);
    ne_.setNormalSmoothingSize(11.0);
    new_cloud_ = false;
    viewer.registerKeyboardCallback(
        &OpenNIIntegralImageNormalEstimation::keyboard_callback, *this);
  }

  void
  cloud_cb(const CloudConstPtr& cloud)
  {
    std::lock_guard<std::mutex> lock(mtx_);
    // lock while we set our cloud;

    normals_.reset(new pcl::PointCloud<pcl::Normal>);

    ne_.setInputCloud(cloud);
    ne_.compute(*normals_);
    cloud_ = cloud;

    new_cloud_ = true;
  }

  void
  viz_cb(pcl::visualization::PCLVisualizer& viz)
  {
    mtx_.lock();
    if (!cloud_ || !normals_) {
      mtx_.unlock();
      return;
    }

    CloudConstPtr temp_cloud;
    pcl::PointCloud<pcl::Normal>::Ptr temp_normals;
    temp_cloud.swap(cloud_); // here we set cloud_ to null, so that
    temp_normals.swap(normals_);
    mtx_.unlock();

    if (!viz.updatePointCloud(temp_cloud, "OpenNICloud")) {
      viz.addPointCloud(temp_cloud, "OpenNICloud");
      viz.resetCameraViewpoint("OpenNICloud");
    }
    // Render the data
    if (new_cloud_) {
      viz.removePointCloud("normalcloud");
      viz.addPointCloudNormals<PointType, pcl::Normal>(
          temp_cloud, temp_normals, 100, 0.05f, "normalcloud");
      new_cloud_ = false;
    }
  }

  void
  keyboard_callback(const pcl::visualization::KeyboardEvent& event, void*)
  {
    std::lock_guard<std::mutex> lock(mtx_);
    switch (event.getKeyCode()) {
    case '1':
      ne_.setNormalEstimationMethod(
          pcl::IntegralImageNormalEstimation<PointType,
                                             pcl::Normal>::COVARIANCE_MATRIX);
      std::cout << "switched to COVARIANCE_MATRIX method\n";
      break;
    case '2':
      ne_.setNormalEstimationMethod(
          pcl::IntegralImageNormalEstimation<PointType,
                                             pcl::Normal>::AVERAGE_3D_GRADIENT);
      std::cout << "switched to AVERAGE_3D_GRADIENT method\n";
      break;
    case '3':
      ne_.setNormalEstimationMethod(
          pcl::IntegralImageNormalEstimation<PointType,
                                             pcl::Normal>::AVERAGE_DEPTH_CHANGE);
      std::cout << "switched to AVERAGE_DEPTH_CHANGE method\n";
      break;
    case '4':
      ne_.setNormalEstimationMethod(
          pcl::IntegralImageNormalEstimation<PointType,
                                             pcl::Normal>::SIMPLE_3D_GRADIENT);
      std::cout << "switched to SIMPLE_3D_GRADIENT method\n";
      break;
    }
  }

  void
  run()
  {
    pcl::OpenNIGrabber interface(device_id_);

    std::function<void(const CloudConstPtr&)> f = [this](const CloudConstPtr& cloud) {
      cloud_cb(cloud);
    };
    boost::signals2::connection c = interface.registerCallback(f);

    viewer.runOnVisualizationThread(
        [this](pcl::visualization::PCLVisualizer& viz) { viz_cb(viz); }, "viz_cb");

    interface.start();

    while (!viewer.wasStopped()) {
      std::this_thread::sleep_for(1s);
    }

    interface.stop();
  }

  pcl::IntegralImageNormalEstimation<PointType, pcl::Normal> ne_;
  pcl::visualization::CloudViewer viewer;
  std::string device_id_;
  std::mutex mtx_;
  // Data
  pcl::PointCloud<pcl::Normal>::Ptr normals_;
  CloudConstPtr cloud_;
  bool new_cloud_;
};

void
usage(char** argv)
{
  std::cout << "usage: " << argv[0] << " [-device_id X (default: \"#1\")]\n\n";

  openni_wrapper::OpenNIDriver& driver = openni_wrapper::OpenNIDriver::getInstance();
  if (driver.getNumberDevices() > 0) {
    for (unsigned deviceIdx = 0; deviceIdx < driver.getNumberDevices(); ++deviceIdx) {
      // clang-format off
      std::cout << "Device: " << deviceIdx + 1 
                << ", vendor: " << driver.getVendorName (deviceIdx) 
                << ", product: " << driver.getProductName (deviceIdx)
                << ", connected: " << driver.getBus (deviceIdx) << " @ " << driver.getAddress (deviceIdx) << ", serial number: \'" << driver.getSerialNumber (deviceIdx) << "\'" 
                << std::endl;
      // clang-format on
    }

    std::cout << "\ndevice_id may be:" << std::endl
              << "    #1, #2, ... for the first second etc device in the list or"
              << std::endl

              << "    bus@address for the device connected to a specific "
                 "usb-bus/address combination (works only in Linux) or"

              << "    <serial-number> (only in Linux and for devices which provide "
                 "serial numbers)";
  }
  else
    std::cout << "No devices connected." << std::endl;
}

int
main(int argc, char** argv)
{
  /////////////////////////////////////////////////////////////////////
  if (pcl::console::find_argument(argc, argv, "-h") != -1 ||
      pcl::console::find_argument(argc, argv, "--help") != -1) {
    usage(argv);
    return 1;
  }

  std::string device_id = "";
  if (pcl::console::parse_argument(argc, argv, "-device_id", device_id) == -1 &&
      argc > 1 && argv[1][0] != '-')
    device_id = argv[1];
  /////////////////////////////////////////////////////////////////////

  // clang-format off
  std::cout << "Press following keys to switch to the different integral image normal estimation methods:\n";
  std::cout << "<1> COVARIANCE_MATRIX method\n";
  std::cout << "<2> AVERAGE_3D_GRADIENT method\n";
  std::cout << "<3> AVERAGE_DEPTH_CHANGE method\n";
  std::cout << "<4> SIMPLE_3D_GRADIENT method\n";
  std::cout << "<Q,q> quit\n\n";
  // clang-format on

  pcl::OpenNIGrabber grabber(device_id);
  if (grabber.providesCallback<pcl::OpenNIGrabber::sig_cb_openni_point_cloud_rgba>()) {
    PCL_INFO("PointXYZRGBA mode enabled.\n");
    OpenNIIntegralImageNormalEstimation<pcl::PointXYZRGBA> v(device_id);
    v.run();
  }
  else {
    PCL_INFO("PointXYZ mode enabled.\n");
    OpenNIIntegralImageNormalEstimation<pcl::PointXYZ> v(device_id);
    v.run();
  }

  return 0;
}