OpenCV/opencv_contrib/modules/structured_light/samples/pointcloud.cpp

/*M///////////////////////////////////////////////////////////////////////////////////////
 //
 //  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
 //
 //  By downloading, copying, installing or using the software you agree to this license.
 //  If you do not agree to this license, do not download, install,
 //  copy or use the software.
 //
 //
 //                           License Agreement
 //                For Open Source Computer Vision Library
 //
 // Copyright (C) 2015, OpenCV Foundation, all rights reserved.
 // Third party copyrights are property of their respective owners.
 //
 // Redistribution and use in source and binary forms, with or without modification,
 // are permitted provided that the following conditions are met:
 //
 //   * Redistribution's of source code must retain the above copyright notice,
 //     this list of conditions and the following disclaimer.
 //
 //   * Redistribution's in binary form must reproduce the above copyright notice,
 //     this list of conditions and the following disclaimer in the documentation
 //     and/or other materials provided with the distribution.
 //
 //   * The name of the copyright holders may not be used to endorse or promote products
 //     derived from this software without specific prior written permission.
 //
 // This software is provided by the copyright holders and contributors "as is" and
 // any express or implied warranties, including, but not limited to, the implied
 // warranties of merchantability and fitness for a particular purpose are disclaimed.
 // In no event shall the Intel Corporation or contributors be liable for any direct,
 // indirect, incidental, special, exemplary, or consequential damages
 // (including, but not limited to, procurement of substitute goods or services;
 // loss of use, data, or profits; or business interruption) however caused
 // and on any theory of liability, whether in contract, strict liability,
 // or tort (including negligence or otherwise) arising in any way out of
 // the use of this software, even if advised of the possibility of such damage.
 //
 //M*/

#include <iostream>
#include <opencv2/core.hpp>
#include <opencv2/highgui.hpp>
#include <opencv2/calib3d.hpp>
#include <opencv2/imgproc.hpp>
#include <opencv2/structured_light.hpp>
#include <opencv2/opencv_modules.hpp>

// (if you did not build the opencv_viz module, you will only see the disparity images)
#ifdef HAVE_OPENCV_VIZ
#include <opencv2/viz.hpp>
#endif

using namespace std;
using namespace cv;

static const char* keys =
{ "{@images_list | | Image list where the captured pattern images are saved}"
    "{@calib_param_path     | | Calibration_parameters            }"
    "{@proj_width      | | The projector width used to acquire the pattern          }"
    "{@proj_height     | | The projector height used to acquire the pattern}"
    "{@white_thresh     | | The white threshold height (optional)}"
    "{@black_thresh     | | The black threshold (optional)}" };

static void help()
{
  cout << "\nThis example shows how to use the \"Structured Light module\" to decode a previously acquired gray code pattern, generating a pointcloud"
        "\nCall:\n"
        "./example_structured_light_pointcloud <images_list> <calib_param_path> <proj_width> <proj_height> <white_thresh> <black_thresh>\n"
        << endl;
}

static bool readStringList( const string& filename, vector<string>& l )
{
  l.resize( 0 );
  FileStorage fs( filename, FileStorage::READ );
  if( !fs.isOpened() )
  {
    cerr << "failed to open " << filename << endl;
    return false;
  }
  FileNode n = fs.getFirstTopLevelNode();
  if( n.type() != FileNode::SEQ )
  {
    cerr << "cam 1 images are not a sequence! FAIL" << endl;
    return false;
  }

  FileNodeIterator it = n.begin(), it_end = n.end();
  for( ; it != it_end; ++it )
  {
    l.push_back( ( string ) *it );
  }

  n = fs["cam2"];
  if( n.type() != FileNode::SEQ )
  {
    cerr << "cam 2 images are not a sequence! FAIL" << endl;
    return false;
  }

  it = n.begin(), it_end = n.end();
  for( ; it != it_end; ++it )
  {
    l.push_back( ( string ) *it );
  }

  if( l.size() % 2 != 0 )
  {
    cout << "Error: the image list contains odd (non-even) number of elements\n";
    return false;
  }
  return true;
}

int main( int argc, char** argv )
{
  structured_light::GrayCodePattern::Params params;
  CommandLineParser parser( argc, argv, keys );
  String images_file = parser.get<String>( 0 );
  String calib_file = parser.get<String>( 1 );

  params.width = parser.get<int>( 2 );
  params.height = parser.get<int>( 3 );

  if( images_file.empty() || calib_file.empty() || params.width < 1 || params.height < 1 || argc < 5 || argc > 7 )
  {
    help();
    return -1;
  }

  // Set up GraycodePattern with params
  Ptr<structured_light::GrayCodePattern> graycode = structured_light::GrayCodePattern::create( params );
  size_t white_thresh = 0;
  size_t black_thresh = 0;

  if( argc == 7 )
  {
    // If passed, setting the white and black threshold, otherwise using default values
    white_thresh = parser.get<unsigned>( 4 );
    black_thresh = parser.get<unsigned>( 5 );

    graycode->setWhiteThreshold( white_thresh );
    graycode->setBlackThreshold( black_thresh );
  }

  vector<string> imagelist;
  bool ok = readStringList( images_file, imagelist );
  if( !ok || imagelist.empty() )
  {
    cout << "can not open " << images_file << " or the string list is empty" << endl;
    help();
    return -1;
  }

  FileStorage fs( calib_file, FileStorage::READ );
  if( !fs.isOpened() )
  {
    cout << "Failed to open Calibration Data File." << endl;
    help();
    return -1;
  }

  // Loading calibration parameters
  Mat cam1intrinsics, cam1distCoeffs, cam2intrinsics, cam2distCoeffs, R, T;
  fs["cam1_intrinsics"] >> cam1intrinsics;
  fs["cam2_intrinsics"] >> cam2intrinsics;
  fs["cam1_distorsion"] >> cam1distCoeffs;
  fs["cam2_distorsion"] >> cam2distCoeffs;
  fs["R"] >> R;
  fs["T"] >> T;

  cout << "cam1intrinsics" << endl << cam1intrinsics << endl;
  cout << "cam1distCoeffs" << endl << cam1distCoeffs << endl;
  cout << "cam2intrinsics" << endl << cam2intrinsics << endl;
  cout << "cam2distCoeffs" << endl << cam2distCoeffs << endl;
  cout << "T" << endl << T << endl << "R" << endl << R << endl;

  if( (!R.data) || (!T.data) || (!cam1intrinsics.data) || (!cam2intrinsics.data) || (!cam1distCoeffs.data) || (!cam2distCoeffs.data) )
  {
    cout << "Failed to load cameras calibration parameters" << endl;
    help();
    return -1;
  }

  size_t numberOfPatternImages = graycode->getNumberOfPatternImages();
  vector<vector<Mat> > captured_pattern;
  captured_pattern.resize( 2 );
  captured_pattern[0].resize( numberOfPatternImages );
  captured_pattern[1].resize( numberOfPatternImages );

  Mat color = imread( imagelist[numberOfPatternImages], IMREAD_COLOR );
  Size imagesSize = color.size();

  // Stereo rectify
  cout << "Rectifying images..." << endl;
  Mat R1, R2, P1, P2, Q;
  Rect validRoi[2];
  stereoRectify( cam1intrinsics, cam1distCoeffs, cam2intrinsics, cam2distCoeffs, imagesSize, R, T, R1, R2, P1, P2, Q, 0,
                -1, imagesSize, &validRoi[0], &validRoi[1] );

  Mat map1x, map1y, map2x, map2y;
  initUndistortRectifyMap( cam1intrinsics, cam1distCoeffs, R1, P1, imagesSize, CV_32FC1, map1x, map1y );
  initUndistortRectifyMap( cam2intrinsics, cam2distCoeffs, R2, P2, imagesSize, CV_32FC1, map2x, map2y );

  // Loading pattern images
  for( size_t i = 0; i < numberOfPatternImages; i++ )
  {
    captured_pattern[0][i] = imread( imagelist[i], IMREAD_GRAYSCALE );
    captured_pattern[1][i] = imread( imagelist[i + numberOfPatternImages + 2], IMREAD_GRAYSCALE );

    if( (!captured_pattern[0][i].data) || (!captured_pattern[1][i].data) )
    {
      cout << "Empty images" << endl;
      help();
      return -1;
    }

    remap( captured_pattern[1][i], captured_pattern[1][i], map1x, map1y, INTER_NEAREST, BORDER_CONSTANT, Scalar() );
    remap( captured_pattern[0][i], captured_pattern[0][i], map2x, map2y, INTER_NEAREST, BORDER_CONSTANT, Scalar() );

  }
  cout << "done" << endl;

  vector<Mat> blackImages;
  vector<Mat> whiteImages;

  blackImages.resize( 2 );
  whiteImages.resize( 2 );

  // Loading images (all white + all black) needed for shadows computation
  cvtColor( color, whiteImages[0], COLOR_RGB2GRAY );

  whiteImages[1] = imread( imagelist[2 * numberOfPatternImages + 2], IMREAD_GRAYSCALE );
  blackImages[0] = imread( imagelist[numberOfPatternImages + 1], IMREAD_GRAYSCALE );
  blackImages[1] = imread( imagelist[2 * numberOfPatternImages + 2 + 1], IMREAD_GRAYSCALE );

  remap( color, color, map2x, map2y, INTER_NEAREST, BORDER_CONSTANT, Scalar() );

  remap( whiteImages[0], whiteImages[0], map2x, map2y, INTER_NEAREST, BORDER_CONSTANT, Scalar() );
  remap( whiteImages[1], whiteImages[1], map1x, map1y, INTER_NEAREST, BORDER_CONSTANT, Scalar() );

  remap( blackImages[0], blackImages[0], map2x, map2y, INTER_NEAREST, BORDER_CONSTANT, Scalar() );
  remap( blackImages[1], blackImages[1], map1x, map1y, INTER_NEAREST, BORDER_CONSTANT, Scalar() );

  cout << endl << "Decoding pattern ..." << endl;
  Mat disparityMap;
  bool decoded = graycode->decode( captured_pattern, disparityMap, blackImages, whiteImages,
                                  structured_light::DECODE_3D_UNDERWORLD );
  if( decoded )
  {
    cout << endl << "pattern decoded" << endl;

    // To better visualize the result, apply a colormap to the computed disparity
    double min;
    double max;
    minMaxIdx(disparityMap, &min, &max);
    Mat cm_disp, scaledDisparityMap;
    cout << "disp min " << min << endl << "disp max " << max << endl;
    convertScaleAbs( disparityMap, scaledDisparityMap, 255 / ( max - min ) );
    applyColorMap( scaledDisparityMap, cm_disp, COLORMAP_JET );

    // Show the result
    resize( cm_disp, cm_disp, Size( 640, 480 ), 0, 0, INTER_LINEAR_EXACT );
    imshow( "cm disparity m", cm_disp );

    // Compute the point cloud
    Mat pointcloud;
    disparityMap.convertTo( disparityMap, CV_32FC1 );
    reprojectImageTo3D( disparityMap, pointcloud, Q, true, -1 );

    // Compute a mask to remove background
    Mat dst, thresholded_disp;
    threshold( scaledDisparityMap, thresholded_disp, 0, 255, THRESH_OTSU + THRESH_BINARY );
    resize( thresholded_disp, dst, Size( 640, 480 ), 0, 0, INTER_LINEAR_EXACT );
    imshow( "threshold disp otsu", dst );

#ifdef HAVE_OPENCV_VIZ
    // Apply the mask to the point cloud
    Mat pointcloud_tresh, color_tresh;
    pointcloud.copyTo( pointcloud_tresh, thresholded_disp );
    color.copyTo( color_tresh, thresholded_disp );

    // Show the point cloud on viz
    viz::Viz3d myWindow( "Point cloud with color" );
    myWindow.setBackgroundMeshLab();
    myWindow.showWidget( "coosys", viz::WCoordinateSystem() );
    myWindow.showWidget( "pointcloud", viz::WCloud( pointcloud_tresh, color_tresh ) );
    myWindow.showWidget( "text2d", viz::WText( "Point cloud", Point(20, 20), 20, viz::Color::green() ) );
    myWindow.spin();
#endif // HAVE_OPENCV_VIZ

  }

  waitKey();
  return 0;
}