3dpcp/.svn/pristine/b0/b03ec22d7cba6c3b4bdd91895a682bc62d2efba7.svn-base

/**
 *
 * Copyright (C) Jacobs University Bremen
 *
 * @author Vaibhav Kumar Mehta
 * @file calc_normals.cc
 */

#include <iostream>
#include <string>
#include <fstream>
#include <errno.h>

#include <boost/program_options.hpp>

#include <slam6d/io_types.h>
#include <slam6d/globals.icc>
#include <slam6d/scan.h>
#include "slam6d/fbr/panorama.h"
#include <scanserver/clientInterface.h>

#include <normals/normals.h>


#ifdef _MSC_VER
#define strcasecmp _stricmp
#define strncasecmp _strnicmp
#else
#include <strings.h>
#endif

namespace po = boost::program_options;
using namespace std;

enum normal_method {AKNN, ADAPTIVE_AKNN, PANORAMA, PANORAMA_FAST};

/*
 * validates normal calculation method specification
 */
void validate(boost::any& v, const std::vector<std::string>& values,
              normal_method*, int) {
  if (values.size() == 0)
    throw std::runtime_error("Invalid model specification");
  string arg = values.at(0);
  if(strcasecmp(arg.c_str(), "AKNN") == 0) v = AKNN;
  else if(strcasecmp(arg.c_str(), "ADAPTIVE_AKNN") == 0) v = ADAPTIVE_AKNN;
  else if(strcasecmp(arg.c_str(), "PANORAMA") == 0) v = PANORAMA;
  else if(strcasecmp(arg.c_str(), "PANORAMA_FAST") == 0) v = PANORAMA_FAST;
  else throw std::runtime_error(std::string("normal calculation method ") + arg + std::string(" is unknown"));
}

/// validate IO types
void validate(boost::any& v, const std::vector<std::string>& values,
              IOType*, int) {
  if (values.size() == 0)
    throw std::runtime_error("Invalid model specification");
  string arg = values.at(0);
  try {
    v = formatname_to_io_type(arg.c_str());
  } catch (...) { // runtime_error
    throw std::runtime_error("Format " + arg + " unknown.");
  }
}

/// Parse commandline options
void parse_options(int argc, char **argv, int &start, int &end, bool &scanserver, int &max_dist, int &min_dist, string &dir,
                   IOType &iotype, int &k1, int &k2, normal_method &ntype,int &width,int &height)
{
  /// ----------------------------------
  /// set up program commandline options
  /// ----------------------------------
  po::options_description cmd_options("Usage: calculateNormals <options> where options are (default values in brackets)");
  cmd_options.add_options()
      ("help,?", "Display this help message")
      ("start,s", po::value<int>(&start)->default_value(0), "Start at scan number <arg>")
      ("end,e", po::value<int>(&end)->default_value(-1), "Stop at scan number <arg>")
      ("scanserver,S", po::value<bool>(&scanserver)->default_value(false), "Use the scanserver as an input method")
      ("format,f", po::value<IOType>(&iotype)->default_value(UOS),
       "using shared library <arg> for input. (chose format from [uos|uosr|uos_map|"
       "uos_rgb|uos_frames|uos_map_frames|old|rts|rts_map|ifp|"
       "riegl_txt|riegl_rgb|riegl_bin|zahn|ply])")
      ("max,M", po::value<int>(&max_dist)->default_value(-1),"neglegt all data points with a distance larger than <arg> 'units")
      ("min,m", po::value<int>(&min_dist)->default_value(-1),"neglegt all data points with a distance smaller than <arg> 'units")
      ("normal,g", po::value<normal_method>(&ntype)->default_value(AKNN), "normal calculation method "
       "(AKNN, ADAPTIVE_AKNN, PANORAMA, PANORAMA_FAST)")
      ("K1,k", po::value<int>(&k1)->default_value(20), "<arg> value of K value used in the nearest neighbor search of ANN or" 								     "kmin for k-adaptation")
      ("K2,K", po::value<int>(&k2)->default_value(20), "<arg> value of Kmax for k-adaptation")
      ("width,w", po::value<int>(&width)->default_value(1280),"width of panorama image")
      ("height,h", po::value<int>(&height)->default_value(960),"height of panorama image")
      ;

  po::options_description hidden("Hidden options");
  hidden.add_options()
      ("input-dir", po::value<string>(&dir), "input dir");

  po::positional_options_description pd;
  pd.add("input-dir", 1);

  po::options_description all;
  all.add(cmd_options).add(hidden);

  po::variables_map vmap;
  po::store(po::command_line_parser(argc, argv).options(all).positional(pd).run(), vmap);
  po::notify(vmap);

  if (vmap.count("help")) {
    cout << cmd_options << endl << endl;
    cout << "SAMPLE COMMAND FOR CALCULATING NORMALS" << endl;
    cout << " bin/normals -s 0 -e 0 -f UOS -g AKNN -k 20 dat/" <<endl;
    cout << endl << endl;
    cout << "SAMPLE COMMAND FOR VIEWING CALCULATING NORMALS IN RGB SPACE" << endl;
    cout << " bin/show -c -f UOS_RGB dat/normals/" << endl;
    exit(-1);
  }

  // read scan path
  if (dir[dir.length()-1] != '/') dir = dir + "/";

}

/// Write a pose file with the specofied name
void writePoseFiles(string dir, const double* rPos, const double* rPosTheta,int scanNumber)
{
  string poseFileName = dir + "/scan" + to_string(scanNumber, 3) + ".pose";
  ofstream posout(poseFileName.c_str());

  posout << rPos[0] << " "
         << rPos[1] << " "
         << rPos[2] << endl
         << deg(rPosTheta[0]) << " "
         << deg(rPosTheta[1]) << " "
         << deg(rPosTheta[2]) << endl;
  posout.clear();
  posout.close();
}

/// write scan files for all segments
void writeScanFiles(string dir, vector<Point> &points, vector<Point> &normals, int scanNumber)
{
  string ofilename = dir + "/scan" + to_string(scanNumber, 3) + ".3d";
  ofstream normptsout(ofilename.c_str());

  for (size_t i=0; i<points.size(); ++i)
  {
    int r,g,b;
    r = (int)(normals[i].x * (127.5) + 127.5);
    g = (int)(normals[i].y * (127.5) + 127.5);
    b = (int)(fabs(normals[i].z) * (255.0));
    normptsout <<points[i].x<<" "<<points[i].y<<" "<<points[i].z<<" "<<r<<" "<<g<<" "<<b<<" "<<endl;
  }
  normptsout.clear();
  normptsout.close();
}

/// =============================================
/// Main
/// =============================================
int main(int argc, char** argv)
{
  int start, end;
  bool scanserver;
  int max_dist, min_dist;
  string dir;
  IOType iotype;
  int k1, k2;
  normal_method ntype;
  int width, height;

  parse_options(argc, argv, start, end, scanserver, max_dist, min_dist,
                dir, iotype, k1, k2, ntype, width, height);

  /// ----------------------------------
  /// Prepare and read scans
  /// ----------------------------------
  if (scanserver) {
    try {
      ClientInterface::create();
    } catch(std::runtime_error& e) {
      cerr << "ClientInterface could not be created: " << e.what() << endl;
      cerr << "Start the scanserver first." << endl;
      exit(-1);
    }
  }

  /// Make directory for saving the scan segments
  string normdir = dir + "normals";

#ifdef _MSC_VER
  int success = mkdir(normdir.c_str());
#else
  int success = mkdir(normdir.c_str(), S_IRWXU|S_IRWXG|S_IRWXO);
#endif
  if(success == 0) {
    cout << "Writing segments to " << normdir << endl;
  } else if(errno == EEXIST) {
    cout << "WARN: Directory " << normdir << " exists already. Contents will be overwriten" << endl;
  } else {
    cerr << "Creating directory " << normdir << " failed" << endl;
    exit(1);
  }

  /// Read the scans
  Scan::openDirectory(scanserver, dir, iotype, start, end);
  if(Scan::allScans.size() == 0) {
    cerr << "No scans found. Did you use the correct format?" << endl;
    exit(-1);
  }

  cv::Mat img;

  /// --------------------------------------------
  /// Initialize and perform segmentation
  /// --------------------------------------------
  std::vector<Scan*>::iterator it = Scan::allScans.begin();
  int scanNumber = 0;

  for( ; it != Scan::allScans.end(); ++it) {
    Scan* scan = *it;

    // apply optional filtering
    scan->setRangeFilter(max_dist, min_dist);

    const double* rPos = scan->get_rPos();
    const double* rPosTheta = scan->get_rPosTheta();

    /// read scan into points
    DataXYZ xyz(scan->get("xyz"));
    vector<Point> points;
    points.reserve(xyz.size());
    vector<Point> normals;
    normals.reserve(xyz.size());

    for(unsigned int j = 0; j < xyz.size(); j++) {
      points.push_back(Point(xyz[j][0], xyz[j][1], xyz[j][2]));
    }

    if(ntype == AKNN)
      calculateNormalsApxKNN(normals,points, k1, rPos);
    else if(ntype == ADAPTIVE_AKNN)
      calculateNormalsAdaptiveApxKNN(normals,points, k1, k2, rPos);
    else
    {
      // create panorama
      fbr::panorama fPanorama(width, height, fbr::EQUIRECTANGULAR, 1, 0, fbr::EXTENDED);
      fPanorama.createPanorama(scan2mat(scan));

      // the range image has to be converted from float to uchar
      img = fPanorama.getRangeImage();
      img = float2uchar(img, 0, 0.0);

      if(ntype == PANORAMA)
        calculateNormalsPANORAMA(normals,points,fPanorama.getExtendedMap(), rPos);
      else if(ntype == PANORAMA_FAST)
        cout << "PANORAMA_FAST is not working yet" << endl;
      //   calculateNormalsFAST(normals,points,img,fPanorama.getExtendedMap());
    }

    // pose file (repeated for the number of segments
    writePoseFiles(normdir, rPos, rPosTheta, scanNumber);
    // scan files for all segments
    writeScanFiles(normdir, points,normals,scanNumber);

    scanNumber++;
  }

  // shutdown everything
  if (scanserver)
    ClientInterface::destroy();

  Scan::closeDirectory();

  cout << "Normal program end" << endl;

  return 0;
}