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/*
Copyright (c) 2010-2016, Mathieu Labbe - IntRoLab - Universite de Sherbrooke
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
* Redistributions of source code must retain the above copyright
notice, this list of conditions and the following disclaimer.
* Redistributions 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.
* Neither the name of the Universite de Sherbrooke nor the
names of its contributors may 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 COPYRIGHT HOLDER 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.
*/
#include <rtabmap/core/DBDriver.h>
#include <rtabmap/core/Rtabmap.h>
#include <rtabmap/core/util3d.h>
#include <rtabmap/core/util3d_filtering.h>
#include <rtabmap/core/util3d_transforms.h>
#include <rtabmap/core/util3d_surface.h>
#include <rtabmap/core/util2d.h>
#include <rtabmap/core/optimizer/OptimizerG2O.h>
#include <rtabmap/core/Graph.h>
#include <rtabmap/utilite/UMath.h>
#include <rtabmap/utilite/UTimer.h>
#include <rtabmap/utilite/UFile.h>
#include <rtabmap/utilite/UStl.h>
#include <pcl/filters/filter.h>
#include <pcl/io/ply_io.h>
#include <pcl/io/obj_io.h>
#include <pcl/common/common.h>
#include <pcl/surface/poisson.h>
#include <stdio.h>
#ifdef RTABMAP_PDAL
#include <rtabmap/core/PDALWriter.h>
#endif
using namespace rtabmap;
void showUsage()
{
printf("\nUsage:\n"
"rtabmap-export [options] database.db\n"
"Options:\n"
" --output \"\" Output name (default: name of the database is used).\n"
" --output_dir \"\" Output directory (default: same directory than the database).\n"
" --ascii Export PLY in ascii format.\n"
" --las Export cloud in LAS instead of PLY (PDAL dependency required).\n"
" --mesh Create a mesh.\n"
" --texture Create a mesh with texture.\n"
" --texture_size # Texture size 1024, 2048, 4096, 8192, 16384 (default 8192).\n"
" --texture_count # Maximum textures generated (default 1). Ignored by --multiband option (adjust --multiband_contrib instead).\n"
" --texture_range # Maximum camera range for texturing a polygon (default 0 meters: no limit).\n"
" --texture_angle # Maximum camera angle for texturing a polygon (default 0 deg: no limit).\n"
" --texture_depth_error # Maximum depth error between reprojected mesh and depth image to texture a face (-1=disabled, 0=edge length is used, default=0).\n"
" --texture_roi_ratios \"# # # #\" Region of interest from images to texture or to color scans. Format is \"left right top bottom\" (e.g. \"0 0 0 0.1\" means 10%% of the image bottom not used).\n"
" --texture_d2c Distance to camera policy.\n"
" --texture_blur # Motion blur threshold (default 0: disabled). Below this threshold, the image is considered blurred. 0 means disabled. 50 can be good default.\n"
" --cam_projection Camera projection on assembled cloud and export node ID on each point (in PointSourceId field).\n"
" --cam_projection_keep_all Keep not colored points from cameras (node ID will be 0 and color will be red).\n"
" --cam_projection_decimation Decimate images before projecting the points.\n"
" --cam_projection_mask \"\" File path for a mask. Format should be 8-bits grayscale. The mask should cover all cameras in case multi-camera is used and have the same resolution.\n"
" --poses Export optimized poses of the robot frame (e.g., base_link).\n"
" --poses_camera Export optimized poses of the camera frame (e.g., optical frame).\n"
" --poses_scan Export optimized poses of the scan frame.\n"
" --poses_format # Format used for exported poses (default is 11):\n"
" 0=Raw 3x4 transformation matrix (r11 r12 r13 tx r21 r22 r23 ty r31 r32 r33 tz)\n"
" 1=RGBD-SLAM (in motion capture coordinate frame)\n"
" 2=KITTI (same as raw but in optical frame)\n"
" 3=TORO\n"
" 4=g2o\n"
" 10=RGBD-SLAM in ROS coordinate frame (stamp x y z qx qy qz qw)\n"
" 11=RGBD-SLAM in ROS coordinate frame + ID (stamp x y z qx qy qz qw id)\n"
" --images Export images with stamp as file name.\n"
" --images_id Export images with node id as file name.\n"
" --ba Do global bundle adjustment before assembling the clouds.\n"
" --gain # Gain compensation value (default 1, set 0 to disable).\n"
" --gain_gray Do gain estimation compensation on gray channel only (default RGB channels).\n"
" --no_blending Disable blending when texturing.\n"
" --no_clean Disable cleaning colorless polygons.\n"
" --min_cluster # When meshing, filter clusters of polygons with size less than this threshold (default 200, -1 means keep only biggest contiguous surface).\n"
" --low_gain # Low brightness gain 0-100 (default 0).\n"
" --high_gain # High brightness gain 0-100 (default 10).\n"
" --multiband Enable multiband texturing (AliceVision dependency required).\n"
" --multiband_downscale # Downscaling reduce the texture quality but speed up the computation time (default 2).\n"
" --multiband_contrib \"# # # # \" Number of contributions per frequency band for the multi-band blending, should be 4 values! (default \"1 5 10 0\").\n"
" --multiband_unwrap # Method to unwrap input mesh: 0=basic (default, >600k faces, fast), 1=ABF (<=300k faces, generate 1 atlas), 2=LSCM (<=600k faces, optimize space).\n"
" --multiband_fillholes Fill Texture holes with plausible values.\n"
" --multiband_padding # Texture edge padding size in pixel (0-100) (default 5).\n"
" --multiband_scorethr # 0 to disable filtering based on threshold to relative best score (0.0-1.0). (default 0.1).\n"
" --multiband_anglethr # 0 to disable angle hard threshold filtering (0.0, 180.0) (default 90.0).\n"
" --multiband_forcevisible Triangle visibility is based on the union of vertices visibility.\n"
" --poisson_depth # Set Poisson depth for mesh reconstruction.\n"
" --poisson_size # Set target polygon size when computing Poisson's depth for mesh reconstruction (default 0.03 m).\n"
" --max_polygons # Maximum polygons when creating a mesh (default 300000, set 0 for no limit).\n"
" --min_range # Minimum range of the created clouds (default 0 m).\n"
" --max_range # Maximum range of the created clouds (default 4 m, 0 m with --scan).\n"
" --decimation # Depth image decimation before creating the clouds (default 4, 1 with --scan).\n"
" --voxel # Voxel size of the created clouds (default 0.01 m, 0 m with --scan).\n"
" --ground_normals_up # Flip ground normals up if close to -z axis (default 0, 0=disabled, value should be >0 and <1, typical 0.9).\n"
" --noise_radius # Noise filtering search radius (default 0, 0=disabled).\n"
" --noise_k # Noise filtering minimum neighbors in search radius (default 5, 0=disabled).\n"
" --prop_radius_factor # Proportional radius filter factor (default 0, 0=disabled). Start tuning from 0.01.\n"
" --prop_radius_scale # Proportional radius filter neighbor scale (default 2).\n"
" --random_samples # Number of output samples using a random filter (default 0, 0=disabled).\n"
" --color_radius # Radius used to colorize polygons (default 0.05 m, 0 m with --scan). Set 0 for nearest color.\n"
" --scan Use laser scan for the point cloud.\n"
" --save_in_db Save resulting assembled point cloud or mesh in the database.\n"
" --xmin # Minimum range on X axis to keep nodes to export.\n"
" --xmax # Maximum range on X axis to keep nodes to export.\n"
" --ymin # Minimum range on Y axis to keep nodes to export.\n"
" --ymax # Maximum range on Y axis to keep nodes to export.\n"
" --zmin # Minimum range on Z axis to keep nodes to export.\n"
" --zmax # Maximum range on Z axis to keep nodes to export.\n"
" --filter_ceiling # Filter points over a custom height (default 0 m, 0=disabled).\n"
" --filter_floor # Filter points below a custom height (default 0 m, 0=disabled).\n"
"\n%s", Parameters::showUsage());
;
exit(1);
}
class ConsoleProgessState : public ProgressState
{
virtual bool callback(const std::string & msg) const
{
if(!msg.empty())
printf("%s\n", msg.c_str());
return true;
}
};
int main(int argc, char * argv[])
{
ULogger::setType(ULogger::kTypeConsole);
ULogger::setLevel(ULogger::kError);
if(argc < 2)
{
showUsage();
}
bool binary = true;
bool las = false;
bool mesh = false;
bool texture = false;
bool ba = false;
bool doGainCompensationRGB = true;
float gainValue = 1;
bool doBlending = true;
bool doClean = true;
int minCluster = 200;
int poissonDepth = 0;
float poissonSize = 0.03;
int maxPolygons = 300000;
int decimation = -1;
float minRange = 0.0f;
float maxRange = -1.0f;
float voxelSize = -1.0f;
float groundNormalsUp = 0.0f;
float noiseRadius = 0.0f;
int noiseMinNeighbors = 5;
float proportionalRadiusFactor = 0.0f;
float proportionalRadiusScale = 2.0f;
int randomSamples = 0;
int textureSize = 8192;
int textureCount = 1;
float textureRange = 0;
float textureAngle = 0;
float textureDepthError = 0;
std::vector<float> textureRoiRatios;
bool distanceToCamPolicy = false;
int laplacianThr = 0;
bool multiband = false;
int multibandDownScale = 2;
std::string multibandNbContrib = "1 5 10 0";
int multibandUnwrap = 0;
bool multibandFillHoles = false;
int multibandPadding = 5;
double multibandBestScoreThr = 0.1;
double multibandAngleHardthr = 90;
bool multibandForceVisible = false;
float colorRadius = -1.0f;
bool cloudFromScan = false;
bool saveInDb = false;
int lowBrightnessGain = 0;
int highBrightnessGain = 10;
bool camProjection = false;
bool camProjectionKeepAll = false;
int cameraProjDecimation = 1;
std::string cameraProjMask;
bool exportPoses = false;
bool exportPosesCamera = false;
bool exportPosesScan = false;
int exportPosesFormat = 11;
bool exportImages = false;
bool exportImagesId = false;
std::string outputName;
std::string outputDir;
cv::Vec3f min, max;
float filter_ceiling = 0.0f;
float filter_floor = 0.0f;
for(int i=1; i<argc; ++i)
{
if(std::strcmp(argv[i], "--help") == 0)
{
showUsage();
}
else if(std::strcmp(argv[i], "--output") == 0)
{
++i;
if(i<argc-1)
{
outputName = argv[i];
}
else
{
showUsage();
}
}
else if(std::strcmp(argv[i], "--output_dir") == 0)
{
++i;
if(i<argc-1)
{
outputDir = argv[i];
}
else
{
showUsage();
}
}
else if(std::strcmp(argv[i], "--bin") == 0)
{
printf("No need to set --bin anymore, ply are now automatically exported in binary by default. Set --ascii to export as text.\n");
}
else if(std::strcmp(argv[i], "--ascii") == 0)
{
binary = false;
}
else if(std::strcmp(argv[i], "--las") == 0)
{
#ifdef RTABMAP_PDAL
las = true;
#else
printf("\"--las\" option cannot be used because RTAB-Map is not built with PDAL support. Will export in PLY...\n");
#endif
}
else if(std::strcmp(argv[i], "--mesh") == 0)
{
mesh = true;
}
else if(std::strcmp(argv[i], "--texture") == 0)
{
texture = true;
}
else if(std::strcmp(argv[i], "--texture_size") == 0)
{
++i;
if(i<argc-1)
{
textureSize = uStr2Int(argv[i]);
UASSERT(textureSize%256==0);
}
else
{
showUsage();
}
}
else if(std::strcmp(argv[i], "--texture_count") == 0)
{
++i;
if(i<argc-1)
{
textureCount = uStr2Int(argv[i]);
}
else
{
showUsage();
}
}
else if(std::strcmp(argv[i], "--texture_range") == 0)
{
++i;
if(i<argc-1)
{
textureRange = uStr2Float(argv[i]);
}
else
{
showUsage();
}
}
else if(std::strcmp(argv[i], "--texture_angle") == 0)
{
++i;
if(i<argc-1)
{
textureAngle = uStr2Float(argv[i])*M_PI/180.0f;
}
else
{
showUsage();
}
}
else if(std::strcmp(argv[i], "--texture_depth_error") == 0)
{
++i;
if(i<argc-1)
{
textureDepthError = uStr2Float(argv[i]);
}
else
{
showUsage();
}
}
else if(std::strcmp(argv[i], "--texture_roi_ratios") == 0)
{
++i;
if(i<argc-1)
{
std::list<std::string> strValues = uSplit(argv[i], ' ');
if(strValues.size() != 4)
{
printf("The number of values must be 4 (roi=\"%s\")\n", argv[i]);
showUsage();
}
else
{
std::vector<float> tmpValues(4);
unsigned int i=0;
for(std::list<std::string>::iterator jter = strValues.begin(); jter!=strValues.end(); ++jter)
{
tmpValues[i] = uStr2Float(*jter);
++i;
}
if(tmpValues[0] >= 0 && tmpValues[0] < 1 && tmpValues[0] < 1.0f-tmpValues[1] &&
tmpValues[1] >= 0 && tmpValues[1] < 1 && tmpValues[1] < 1.0f-tmpValues[0] &&
tmpValues[2] >= 0 && tmpValues[2] < 1 && tmpValues[2] < 1.0f-tmpValues[3] &&
tmpValues[3] >= 0 && tmpValues[3] < 1 && tmpValues[3] < 1.0f-tmpValues[2])
{
textureRoiRatios = tmpValues;
}
else
{
printf("The roi ratios are not valid (roi=\"%s\")\n", argv[i]);
showUsage();
}
}
}
else
{
showUsage();
}
}
else if(std::strcmp(argv[i], "--texture_d2c") == 0)
{
distanceToCamPolicy = true;
}
else if(std::strcmp(argv[i], "--texture_blur") == 0)
{
++i;
if(i<argc-1)
{
laplacianThr = uStr2Int(argv[i]);
}
else
{
showUsage();
}
}
else if(std::strcmp(argv[i], "--cam_projection") == 0)
{
camProjection = true;
}
else if(std::strcmp(argv[i], "--cam_projection_keep_all") == 0)
{
camProjectionKeepAll = true;
}
else if(std::strcmp(argv[i], "--cam_projection_decimation") == 0)
{
++i;
if(i<argc-1)
{
cameraProjDecimation = uStr2Int(argv[i]);
if(cameraProjDecimation<1)
{
printf("--cam_projection_decimation cannot be <1! value=\"%s\"\n", argv[i]);
showUsage();
}
}
else
{
showUsage();
}
}
else if(std::strcmp(argv[i], "--cam_projection_mask") == 0)
{
++i;
if(i<argc-1)
{
cameraProjMask = argv[i];
if(!UFile::exists(cameraProjMask))
{
printf("--cam_projection_mask is set with a file not existing or don't have permissions to open it. Path=\"%s\"\n", argv[i]);
showUsage();
}
}
else
{
showUsage();
}
}
else if(std::strcmp(argv[i], "--poses") == 0)
{
exportPoses = true;
}
else if(std::strcmp(argv[i], "--poses_camera") == 0)
{
exportPosesCamera = true;
}
else if(std::strcmp(argv[i], "--poses_scan") == 0)
{
exportPosesScan = true;
}
else if(std::strcmp(argv[i], "--poses_format") == 0)
{
++i;
if(i<argc-1)
{
exportPosesFormat = uStr2Int(argv[i]);
}
else
{
showUsage();
}
}
else if(std::strcmp(argv[i], "--images") == 0)
{
exportImages = true;
}
else if(std::strcmp(argv[i], "--images_id") == 0)
{
exportImages = true;
exportImagesId = true;
}
else if(std::strcmp(argv[i], "--ba") == 0)
{
ba = true;
}
else if(std::strcmp(argv[i], "--gain_gray") == 0)
{
doGainCompensationRGB = false;
}
else if(std::strcmp(argv[i], "--gain") == 0)
{
++i;
if(i<argc-1)
{
gainValue = uStr2Float(argv[i]);
UASSERT(gainValue>=0.0f);
}
else
{
showUsage();
}
}
else if(std::strcmp(argv[i], "--no_blending") == 0)
{
doBlending = false;
}
else if(std::strcmp(argv[i], "--no_clean") == 0)
{
doClean = false;
}
else if(std::strcmp(argv[i], "--min_cluster") == 0)
{
++i;
if(i<argc-1)
{
minCluster = uStr2Int(argv[i]);
}
else
{
showUsage();
}
}
else if(std::strcmp(argv[i], "--multiband") == 0)
{
#ifdef RTABMAP_ALICE_VISION
multiband = true;
#else
printf("\"--multiband\" option cannot be used because RTAB-Map is not built with AliceVision support. Ignoring multiband...\n");
#endif
}
else if(std::strcmp(argv[i], "--multiband_fillholes") == 0)
{
multibandFillHoles = true;
}
else if(std::strcmp(argv[i], "--multiband_downscale") == 0)
{
++i;
if(i<argc-1)
{
multibandDownScale = uStr2Int(argv[i]);
}
else
{
showUsage();
}
}
else if(std::strcmp(argv[i], "--multiband_contrib") == 0)
{
++i;
if(i<argc-1)
{
if(uSplit(argv[i], ' ').size() != 4)
{
printf("--multiband_contrib has wrong format! value=\"%s\"\n", argv[i]);
showUsage();
}
multibandNbContrib = argv[i];
}
else
{
showUsage();
}
}
else if(std::strcmp(argv[i], "--multiband_unwrap") == 0)
{
++i;
if(i<argc-1)
{
multibandUnwrap = uStr2Int(argv[i]);
}
else
{
showUsage();
}
}
else if(std::strcmp(argv[i], "--multiband_padding") == 0)
{
++i;
if(i<argc-1)
{
multibandPadding = uStr2Int(argv[i]);
}
else
{
showUsage();
}
}
else if(std::strcmp(argv[i], "--multiband_forcevisible") == 0)
{
multibandForceVisible = true;
}
else if(std::strcmp(argv[i], "--multiband_scorethr") == 0)
{
++i;
if(i<argc-1)
{
multibandBestScoreThr = uStr2Float(argv[i]);
}
else
{
showUsage();
}
}
else if(std::strcmp(argv[i], "--multiband_anglethr") == 0)
{
++i;
if(i<argc-1)
{
multibandAngleHardthr = uStr2Float(argv[i]);
}
else
{
showUsage();
}
}
else if(std::strcmp(argv[i], "--poisson_depth") == 0)
{
++i;
if(i<argc-1)
{
poissonDepth = uStr2Int(argv[i]);
}
else
{
showUsage();
}
}
else if(std::strcmp(argv[i], "--poisson_size") == 0)
{
++i;
if(i<argc-1)
{
poissonSize = uStr2Float(argv[i]);
}
else
{
showUsage();
}
}
else if(std::strcmp(argv[i], "--max_polygons") == 0)
{
++i;
if(i<argc-1)
{
maxPolygons = uStr2Int(argv[i]);
}
else
{
showUsage();
}
}
else if(std::strcmp(argv[i], "--min_range") == 0)
{
++i;
if(i<argc-1)
{
minRange = uStr2Float(argv[i]);
}
else
{
showUsage();
}
}
else if(std::strcmp(argv[i], "--max_range") == 0)
{
++i;
if(i<argc-1)
{
maxRange = uStr2Float(argv[i]);
}
else
{
showUsage();
}
}
else if(std::strcmp(argv[i], "--decimation") == 0)
{
++i;
if(i<argc-1)
{
decimation = uStr2Int(argv[i]);
}
else
{
showUsage();
}
}
else if(std::strcmp(argv[i], "--voxel") == 0)
{
++i;
if(i<argc-1)
{
voxelSize = uStr2Float(argv[i]);
}
else
{
showUsage();
}
}
else if(std::strcmp(argv[i], "--ground_normals_up") == 0)
{
++i;
if(i<argc-1)
{
groundNormalsUp = uStr2Float(argv[i]);
}
else
{
showUsage();
}
}
else if(std::strcmp(argv[i], "--noise_radius") == 0)
{
++i;
if(i<argc-1)
{
noiseRadius = uStr2Float(argv[i]);
}
else
{
showUsage();
}
}
else if(std::strcmp(argv[i], "--noise_k") == 0)
{
++i;
if(i<argc-1)
{
noiseMinNeighbors = uStr2Int(argv[i]);
}
else
{
showUsage();
}
}
else if(std::strcmp(argv[i], "--prop_radius_factor") == 0)
{
++i;
if(i<argc-1)
{
proportionalRadiusFactor = uStr2Float(argv[i]);
}
else
{
showUsage();
}
}
else if(std::strcmp(argv[i], "--prop_radius_scale") == 0)
{
++i;
if(i<argc-1)
{
proportionalRadiusScale = uStr2Float(argv[i]);
UASSERT_MSG(proportionalRadiusScale>=1.0f, "--prop_radius_scale should be >= 1.0");
}
else
{
showUsage();
}
}
else if(std::strcmp(argv[i], "--random_samples") == 0)
{
++i;
if(i<argc-1)
{
randomSamples = uStr2Int(argv[i]);
}
else
{
showUsage();
}
}
else if(std::strcmp(argv[i], "--color_radius") == 0)
{
++i;
if(i<argc-1)
{
colorRadius = uStr2Float(argv[i]);
}
else
{
showUsage();
}
}
else if(std::strcmp(argv[i], "--scan") == 0)
{
cloudFromScan = true;
}
else if(std::strcmp(argv[i], "--save_in_db") == 0)
{
saveInDb = true;
}
else if(std::strcmp(argv[i], "--low_gain") == 0)
{
++i;
if(i<argc-1)
{
lowBrightnessGain = uStr2Int(argv[i]);
}
else
{
showUsage();
}
}
else if(std::strcmp(argv[i], "--high_gain") == 0)
{
++i;
if(i<argc-1)
{
highBrightnessGain = uStr2Int(argv[i]);
}
else
{
showUsage();
}
}
else if(std::strcmp(argv[i], "--xmin") == 0)
{
++i;
if(i<argc-1)
{
min[0] = uStr2Float(argv[i]);
}
else
{
showUsage();
}
}
else if(std::strcmp(argv[i], "--xmax") == 0)
{
++i;
if(i<argc-1)
{
max[0] = uStr2Float(argv[i]);
}
else
{
showUsage();
}
}
else if(std::strcmp(argv[i], "--ymin") == 0)
{
++i;
if(i<argc-1)
{
min[1] = uStr2Float(argv[i]);
}
else
{
showUsage();
}
}
else if(std::strcmp(argv[i], "--ymax") == 0)
{
++i;
if(i<argc-1)
{
max[1] = uStr2Float(argv[i]);
}
else
{
showUsage();
}
}
else if(std::strcmp(argv[i], "--zmin") == 0)
{
++i;
if(i<argc-1)
{
min[2] = uStr2Float(argv[i]);
}
else
{
showUsage();
}
}
else if(std::strcmp(argv[i], "--zmax") == 0)
{
++i;
if(i<argc-1)
{
max[2] = uStr2Float(argv[i]);
}
else
{
showUsage();
}
}
else if(std::strcmp(argv[i], "--filter_ceiling") == 0)
{
++i;
if(i<argc-1)
{
filter_ceiling = uStr2Float(argv[i]);
if(filter_floor!=0.0f && filter_ceiling != 0.0f && filter_ceiling<filter_floor)
{
printf("Option --filter_ceiling (%f) should be higher than --filter_floor option (%f)!\n", filter_ceiling, filter_floor);
showUsage();
}
}
else
{
showUsage();
}
}
else if(std::strcmp(argv[i], "--filter_floor") == 0)
{
++i;
if(i<argc-1)
{
filter_floor = uStr2Float(argv[i]);
if(filter_floor!=0.0f && filter_ceiling != 0.0f && filter_ceiling<filter_floor)
{
printf("Option --filter_ceiling (%f) should be higher than --filter_floor option (%f)!\n", filter_ceiling, filter_floor);
showUsage();
}
}
else
{
showUsage();
}
}
}
if(decimation < 1)
{
decimation = cloudFromScan?1:4;
}
if(maxRange < 0)
{
maxRange = cloudFromScan?0:4;
}
if(voxelSize < 0.0f)
{
voxelSize = cloudFromScan?0:0.01f;
}
if(colorRadius < 0.0f)
{
colorRadius = cloudFromScan?0:0.05f;
}
if(saveInDb)
{
if(multiband)
{
printf("Option --multiband is not supported with --save_in_db option, disabling multiband...\n");
multiband = false;
}
if(textureCount>1)
{
printf("Option --texture_count > 1 is not supported with --save_in_db option, setting texture_count to 1...\n");
textureCount = 1;
}
}
ParametersMap params = Parameters::parseArguments(argc, argv, false);
std::string dbPath = argv[argc-1];
if(!UFile::exists(dbPath))
{
UERROR("File \"%s\" doesn't exist!", dbPath.c_str());
return -1;
}
// Get parameters
ParametersMap parameters;
DBDriver * driver = DBDriver::create();
if(driver->openConnection(dbPath))
{
parameters = driver->getLastParameters();
driver->closeConnection(false);
}
else
{
UERROR("Cannot open database %s!", dbPath.c_str());
return -1;
}
delete driver;
driver = 0;
for(ParametersMap::iterator iter=params.begin(); iter!=params.end(); ++iter)
{
printf("Added custom parameter %s=%s\n",iter->first.c_str(), iter->second.c_str());
}
UTimer timer;
printf("Loading database \"%s\"...\n", dbPath.c_str());
// Get the global optimized map
Rtabmap rtabmap;
uInsert(parameters, params);
rtabmap.init(parameters, dbPath);
printf("Loading database \"%s\"... done (%fs).\n", dbPath.c_str(), timer.ticks());
std::map<int, Signature> nodes;
std::map<int, Transform> optimizedPoses;
std::multimap<int, Link> links;
printf("Optimizing the map...\n");
rtabmap.getGraph(optimizedPoses, links, true, true, &nodes, true, true, true, true);
printf("Optimizing the map... done (%fs, poses=%d).\n", timer.ticks(), (int)optimizedPoses.size());
if(optimizedPoses.empty())
{
printf("The optimized graph is empty!? Aborting...\n");
return -1;
}
if(min[0] != max[0] || min[1] != max[1] || min[2] != max[2])
{
cv::Vec3f minP,maxP;
graph::computeMinMax(optimizedPoses, minP, maxP);
printf("Filtering poses (range: x=%f<->%f, y=%f<->%f, z=%f<->%f, map size=%f x %f x %f)...\n",
min[0],max[0],min[1],max[1],min[2],max[2],
maxP[0]-minP[0],maxP[1]-minP[1],maxP[2]-minP[2]);
std::map<int, Transform> posesFiltered;
for(std::map<int, Transform>::const_iterator iter=optimizedPoses.begin(); iter!=optimizedPoses.end(); ++iter)
{
bool ignore = false;
if(min[0] != max[0] && (iter->second.x() < min[0] || iter->second.x() > max[0]))
{
ignore = true;
}
if(min[1] != max[1] && (iter->second.y() < min[1] || iter->second.y() > max[1]))
{
ignore = true;
}
if(min[2] != max[2] && (iter->second.z() < min[2] || iter->second.z() > max[2]))
{
ignore = true;
}
if(!ignore)
{
posesFiltered.insert(*iter);
}
}
graph::computeMinMax(posesFiltered, minP, maxP);
printf("Filtering poses... done! %d/%d remaining (new map size=%f x %f x %f).\n", (int)posesFiltered.size(), (int)optimizedPoses.size(), maxP[0]-minP[0],maxP[1]-minP[1],maxP[2]-minP[2]);
optimizedPoses = posesFiltered;
if(optimizedPoses.empty())
{
return -1;
}
}
std::string outputDirectory = outputDir.empty()?UDirectory::getDir(dbPath):outputDir;
if(!UDirectory::exists(outputDirectory))
{
UDirectory::makeDir(outputDirectory);
}
std::string baseName = outputName.empty()?uSplit(UFile::getName(dbPath), '.').front():outputName;
if(ba)
{
printf("Global bundle adjustment...\n");
OptimizerG2O g2o(parameters);
optimizedPoses = ((Optimizer*)&g2o)->optimizeBA(optimizedPoses.lower_bound(1)->first, optimizedPoses, links, nodes, true);
printf("Global bundle adjustment... done (%fs).\n", timer.ticks());
}
// Construct the cloud
printf("Create and assemble the clouds...\n");
pcl::PointCloud<pcl::PointXYZRGB>::Ptr assembledCloud(new pcl::PointCloud<pcl::PointXYZRGB>);
pcl::PointCloud<pcl::PointXYZI>::Ptr assembledCloudI(new pcl::PointCloud<pcl::PointXYZI>);
std::map<int, rtabmap::Transform> robotPoses;
std::vector<std::map<int, rtabmap::Transform> > cameraPoses;
std::map<int, rtabmap::Transform> scanPoses;
std::map<int, double> cameraStamps;
std::map<int, std::vector<rtabmap::CameraModel> > cameraModels;
std::map<int, cv::Mat> cameraDepths;
int imagesExported = 0;
std::vector<int> rawViewpointIndices;
std::map<int, Transform> rawViewpoints;
for(std::map<int, Transform>::iterator iter=optimizedPoses.lower_bound(1); iter!=optimizedPoses.end(); ++iter)
{
Signature node = nodes.find(iter->first)->second;
// uncompress data
std::vector<CameraModel> models = node.sensorData().cameraModels();
std::vector<StereoCameraModel> stereoModels = node.sensorData().stereoCameraModels();
cv::Mat rgb;
cv::Mat depth;
pcl::IndicesPtr indices(new std::vector<int>);
pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud;
pcl::PointCloud<pcl::PointXYZI>::Ptr cloudI;
if(node.getWeight() != -1)
{
if(cloudFromScan)
{
cv::Mat tmpDepth;
LaserScan scan;
node.sensorData().uncompressData(exportImages?&rgb:0, (texture||exportImages)&&!node.sensorData().depthOrRightCompressed().empty()?&tmpDepth:0, &scan);
if(scan.empty())
{
printf("Node %d doesn't have scan data, empty cloud is created.\n", iter->first);
}
if(decimation>1 || minRange>0.0f || maxRange)
{
scan = util3d::commonFiltering(scan, decimation, minRange, maxRange);
}
if(scan.hasRGB())
{
cloud = util3d::laserScanToPointCloudRGB(scan, scan.localTransform());
if(noiseRadius>0.0f && noiseMinNeighbors>0)
{
indices = util3d::radiusFiltering(cloud, noiseRadius, noiseMinNeighbors);
}
}
else
{
cloudI = util3d::laserScanToPointCloudI(scan, scan.localTransform());
if(noiseRadius>0.0f && noiseMinNeighbors>0)
{
indices = util3d::radiusFiltering(cloudI, noiseRadius, noiseMinNeighbors);
}
}
}
else
{
node.sensorData().uncompressData(&rgb, &depth);
if(depth.empty())
{
printf("Node %d doesn't have depth or stereo data, empty cloud is "
"created (if you want to create point cloud from scan, use --scan option).\n", iter->first);
}
cloud = util3d::cloudRGBFromSensorData(
node.sensorData(),
decimation, // image decimation before creating the clouds
maxRange, // maximum depth of the cloud
minRange,
indices.get());
if(noiseRadius>0.0f && noiseMinNeighbors>0)
{
indices = util3d::radiusFiltering(cloud, indices, noiseRadius, noiseMinNeighbors);
}
}
}
if(exportImages && !rgb.empty())
{
std::string dirSuffix = (depth.type() != CV_16UC1 && depth.type() != CV_32FC1 && !depth.empty())?"left":"rgb";
std::string dir = outputDirectory+"/"+baseName+"_"+dirSuffix;
if(!UDirectory::exists(dir)) {
UDirectory::makeDir(dir);
}
std::string outputPath=dir+"/"+(exportImagesId?uNumber2Str(iter->first):uFormat("%f",node.getStamp()))+".jpg";
cv::imwrite(outputPath, rgb);
++imagesExported;
if(!depth.empty())
{
std::string ext;
cv::Mat depthExported = depth;
if(depth.type() != CV_16UC1 && depth.type() != CV_32FC1)
{
ext = ".jpg";
dir = outputDirectory+"/"+baseName+"_right";
}
else
{
ext = ".png";
dir = outputDirectory+"/"+baseName+"_depth";
if(depth.type() == CV_32FC1)
{
depthExported = rtabmap::util2d::cvtDepthFromFloat(depth);
}
}
if(!UDirectory::exists(dir)) {
UDirectory::makeDir(dir);
}
outputPath=dir+"/"+(exportImagesId?uNumber2Str(iter->first):uFormat("%f",node.getStamp()))+ext;
cv::imwrite(outputPath, depthExported);
}
// save calibration per image (calibration can change over time, e.g. camera has auto focus)
for(size_t i=0; i<models.size(); ++i)
{
CameraModel model = models[i];
std::string modelName = (exportImagesId?uNumber2Str(iter->first):uFormat("%f",node.getStamp()));
if(models.size() > 1) {
modelName += "_" + uNumber2Str((int)i);
}
model.setName(modelName);
std::string dir = outputDirectory+"/"+baseName+"_calib";
if(!UDirectory::exists(dir)) {
UDirectory::makeDir(dir);
}
model.save(dir);
}
for(size_t i=0; i<stereoModels.size(); ++i)
{
StereoCameraModel model = stereoModels[i];
std::string modelName = (exportImagesId?uNumber2Str(iter->first):uFormat("%f",node.getStamp()));
if(stereoModels.size() > 1) {
modelName += "_" + uNumber2Str((int)i);
}
model.setName(modelName, "left", "right");
std::string dir = outputDirectory+"/"+baseName+"_calib";
if(!UDirectory::exists(dir)) {
UDirectory::makeDir(dir);
}
model.save(dir);
}
}
if(voxelSize>0.0f)
{
if(cloud.get() && !cloud->empty())
cloud = rtabmap::util3d::voxelize(cloud, indices, voxelSize);
else if(cloudI.get() && !cloudI->empty())
cloudI = rtabmap::util3d::voxelize(cloudI, indices, voxelSize);
}
if(cloud.get() && !cloud->empty())
cloud = rtabmap::util3d::transformPointCloud(cloud, iter->second);
else if(cloudI.get() && !cloudI->empty())
cloudI = rtabmap::util3d::transformPointCloud(cloudI, iter->second);
if(filter_ceiling != 0.0 || filter_floor != 0.0f)
{
if(cloud.get() && !cloud->empty())
{
cloud = util3d::passThrough(cloud, "z", filter_floor!=0.0f?filter_floor:(float)std::numeric_limits<int>::min(), filter_ceiling!=0.0f?filter_ceiling:(float)std::numeric_limits<int>::max());
}
if(cloudI.get() && !cloudI->empty())
{
cloudI = util3d::passThrough(cloudI, "z", filter_floor!=0.0f?filter_floor:(float)std::numeric_limits<int>::min(), filter_ceiling!=0.0f?filter_ceiling:(float)std::numeric_limits<int>::max());
}
}
if(cloudFromScan)
{
Transform lidarViewpoint = iter->second * node.sensorData().laserScanRaw().localTransform();
rawViewpoints.insert(std::make_pair(iter->first, lidarViewpoint));
}
else if(!node.sensorData().cameraModels().empty() && !node.sensorData().cameraModels()[0].localTransform().isNull())
{
Transform cameraViewpoint = iter->second * node.sensorData().cameraModels()[0].localTransform(); // take the first camera
rawViewpoints.insert(std::make_pair(iter->first, cameraViewpoint));
}
else if(!node.sensorData().stereoCameraModels().empty() && !node.sensorData().stereoCameraModels()[0].localTransform().isNull())
{
Transform cameraViewpoint = iter->second * node.sensorData().stereoCameraModels()[0].localTransform();
rawViewpoints.insert(std::make_pair(iter->first, cameraViewpoint));
}
else
{
rawViewpoints.insert(*iter);
}
if(cloud.get() && !cloud->empty())
{
if(assembledCloud->empty())
{
*assembledCloud = *cloud;
}
else
{
*assembledCloud += *cloud;
}
rawViewpointIndices.resize(assembledCloud->size(), iter->first);
}
else if(cloudI.get() && !cloudI->empty())
{
if(assembledCloudI->empty())
{
*assembledCloudI = *cloudI;
}
else
{
*assembledCloudI += *cloudI;
}
rawViewpointIndices.resize(assembledCloudI->size(), iter->first);
}
if(models.empty())
{
for(size_t i=0; i<node.sensorData().stereoCameraModels().size(); ++i)
{
models.push_back(node.sensorData().stereoCameraModels()[i].left());
}
}
robotPoses.insert(std::make_pair(iter->first, iter->second));
cameraStamps.insert(std::make_pair(iter->first, node.getStamp()));
if(models.empty() && node.getWeight() == -1 && !cameraModels.empty())
{
// For intermediate nodes, use latest models
models = cameraModels.rbegin()->second;
}
if(!models.empty())
{
if(!node.sensorData().imageCompressed().empty())
{
cameraModels.insert(std::make_pair(iter->first, models));
}
if(exportPosesCamera)
{
if(cameraPoses.empty())
{
cameraPoses.resize(models.size());
}
UASSERT_MSG(models.size() == cameraPoses.size(), "Not all nodes have same number of cameras to export camera poses.");
for(size_t i=0; i<models.size(); ++i)
{
cameraPoses[i].insert(std::make_pair(iter->first, iter->second*models[i].localTransform()));
}
}
}
if(!depth.empty() && (depth.type() == CV_16UC1 || depth.type() == CV_32FC1))
{
cameraDepths.insert(std::make_pair(iter->first, depth));
}
if(exportPosesScan && !node.sensorData().laserScanCompressed().empty())
{
scanPoses.insert(std::make_pair(iter->first, iter->second*node.sensorData().laserScanCompressed().localTransform()));
}
}
printf("Create and assemble the clouds... done (%fs, %d points).\n", timer.ticks(), !assembledCloud->empty()?(int)assembledCloud->size():(int)assembledCloudI->size());
if(imagesExported>0)
printf("%d images exported!\n", imagesExported);
ConsoleProgessState progressState;
if(!assembledCloud->empty() || !assembledCloudI->empty())
{
if(saveInDb)
{
driver = DBDriver::create();
UASSERT(driver->openConnection(dbPath, false));
Transform lastlocalizationPose;
driver->loadOptimizedPoses(&lastlocalizationPose);
//optimized poses have changed, reset 2d map
driver->save2DMap(cv::Mat(), 0, 0, 0);
driver->saveOptimizedPoses(optimizedPoses, lastlocalizationPose);
}
else
{
std::string posesExt = (exportPosesFormat==3?"toro":exportPosesFormat==4?"g2o":"txt");
if(exportPoses)
{
std::string outputPath=outputDirectory+"/"+baseName+"_poses." + posesExt;
rtabmap::graph::exportPoses(outputPath, exportPosesFormat, robotPoses, links, cameraStamps);
printf("Poses exported to \"%s\".\n", outputPath.c_str());
}
if(exportPosesCamera)
{
for(size_t i=0; i<cameraPoses.size(); ++i)
{
std::string outputPath;
if(cameraPoses.size()==1)
outputPath = outputDirectory+"/"+baseName+"_camera_poses." + posesExt;
else
outputPath = outputDirectory+"/"+baseName+"_camera_poses_"+uNumber2Str((int)i)+"." + posesExt;
rtabmap::graph::exportPoses(outputPath, exportPosesFormat, cameraPoses[i], std::multimap<int, Link>(), cameraStamps);
printf("Camera poses exported to \"%s\".\n", outputPath.c_str());
}
}
if(exportPosesScan)
{
std::string outputPath=outputDirectory+"/"+baseName+"_scan_poses." + posesExt;
rtabmap::graph::exportPoses(outputPath, exportPosesFormat, scanPoses, std::multimap<int, Link>(), cameraStamps);
printf("Scan poses exported to \"%s\".\n", outputPath.c_str());
}
}
if(proportionalRadiusFactor>0.0f && proportionalRadiusScale>=1.0f)
{
printf("Proportional radius filtering of the assembled cloud... (factor=%f scale=%f, %d points)\n", proportionalRadiusFactor, proportionalRadiusScale, !assembledCloud->empty()?(int)assembledCloud->size():(int)assembledCloudI->size());
pcl::IndicesPtr indices;
if(!assembledCloud->empty())
{
indices = util3d::proportionalRadiusFiltering(assembledCloud, rawViewpointIndices, rawViewpoints, proportionalRadiusFactor, proportionalRadiusScale);
pcl::PointCloud<pcl::PointXYZRGB> tmp;
pcl::copyPointCloud(*assembledCloud, *indices, tmp);
*assembledCloud = tmp;
}
else if(!assembledCloudI->empty())
{
indices = util3d::proportionalRadiusFiltering(assembledCloudI, rawViewpointIndices, rawViewpoints, proportionalRadiusFactor, proportionalRadiusScale);
pcl::PointCloud<pcl::PointXYZI> tmp;
pcl::copyPointCloud(*assembledCloudI, *indices, tmp);
*assembledCloudI = tmp;
}
if(indices.get())
{
std::vector<int> rawCameraIndicesTmp(indices->size());
for (std::size_t i = 0; i < indices->size(); ++i)
rawCameraIndicesTmp[i] = rawViewpointIndices[indices->at(i)];
rawViewpointIndices = rawCameraIndicesTmp;
}
printf("Proportional radius filtering of the assembled cloud.... done! (%fs, %d points)\n", timer.ticks(), !assembledCloud->empty()?(int)assembledCloud->size():(int)assembledCloudI->size());
}
pcl::PointCloud<pcl::PointXYZ>::Ptr rawAssembledCloud(new pcl::PointCloud<pcl::PointXYZ>);
if(!assembledCloud->empty())
pcl::copyPointCloud(*assembledCloud, *rawAssembledCloud); // used to adjust normal orientation
else if(!assembledCloudI->empty())
pcl::copyPointCloud(*assembledCloudI, *rawAssembledCloud); // used to adjust normal orientation
pcl::PointCloud<pcl::PointXYZ>::Ptr cloudWithoutNormals = rawAssembledCloud;
if(voxelSize>0.0f)
{
printf("Voxel grid filtering of the assembled cloud... (voxel=%f, %d points)\n", voxelSize, !assembledCloud->empty()?(int)assembledCloud->size():(int)assembledCloudI->size());
if(!assembledCloud->empty())
{
assembledCloud = util3d::voxelize(assembledCloud, voxelSize);
cloudWithoutNormals.reset(new pcl::PointCloud<pcl::PointXYZ>);
pcl::copyPointCloud(*assembledCloud, *cloudWithoutNormals);
}
else if(!assembledCloudI->empty())
{
assembledCloudI = util3d::voxelize(assembledCloudI, voxelSize);
cloudWithoutNormals.reset(new pcl::PointCloud<pcl::PointXYZ>);
pcl::copyPointCloud(*assembledCloudI, *cloudWithoutNormals);
}
printf("Voxel grid filtering of the assembled cloud.... done! (%fs, %d points)\n", timer.ticks(), !assembledCloud->empty()?(int)assembledCloud->size():(int)assembledCloudI->size());
}
printf("Computing normals of the assembled cloud... (k=20, %d points)\n", !assembledCloud->empty()?(int)assembledCloud->size():(int)assembledCloudI->size());
pcl::PointCloud<pcl::Normal>::Ptr normals = util3d::computeNormals(cloudWithoutNormals, 20, 0);
pcl::PointCloud<pcl::PointXYZRGBNormal>::Ptr cloudToExport(new pcl::PointCloud<pcl::PointXYZRGBNormal>);
pcl::PointCloud<pcl::PointXYZINormal>::Ptr cloudIToExport(new pcl::PointCloud<pcl::PointXYZINormal>);
if(!assembledCloud->empty())
{
UASSERT(assembledCloud->size() == normals->size());
pcl::concatenateFields(*assembledCloud, *normals, *cloudToExport);
printf("Computing normals of the assembled cloud... done! (%fs, %d points)\n", timer.ticks(), (int)assembledCloud->size());
assembledCloud->clear();
// adjust with point of views
printf("Adjust normals to viewpoints of the assembled cloud... (%d points)\n", (int)cloudToExport->size());
util3d::adjustNormalsToViewPoints(
rawViewpoints,
rawAssembledCloud,
rawViewpointIndices,
cloudToExport,
groundNormalsUp);
printf("Adjust normals to viewpoints of the assembled cloud... (%fs, %d points)\n", timer.ticks(), (int)cloudToExport->size());
}
else if(!assembledCloudI->empty())
{
UASSERT(assembledCloudI->size() == normals->size());
pcl::concatenateFields(*assembledCloudI, *normals, *cloudIToExport);
printf("Computing normals of the assembled cloud... done! (%fs, %d points)\n", timer.ticks(), (int)assembledCloudI->size());
assembledCloudI->clear();
// adjust with point of views
printf("Adjust normals to viewpoints of the assembled cloud... (%d points)\n", (int)cloudIToExport->size());
util3d::adjustNormalsToViewPoints(
rawViewpoints,
rawAssembledCloud,
rawViewpointIndices,
cloudIToExport,
groundNormalsUp);
printf("Adjust normals to viewpoints of the assembled cloud... (%fs, %d points)\n", timer.ticks(), (int)cloudIToExport->size());
}
cloudWithoutNormals->clear();
rawAssembledCloud->clear();
if(randomSamples>0)
{
printf("Random samples filtering of the assembled cloud... (samples=%d, %d points)\n", randomSamples, !cloudToExport->empty()?(int)cloudToExport->size():(int)cloudIToExport->size());
if(!cloudToExport->empty())
{
cloudToExport = util3d::randomSampling(cloudToExport, randomSamples);
}
else if(!cloudIToExport->empty())
{
cloudIToExport = util3d::randomSampling(cloudIToExport, randomSamples);
}
printf("Random samples filtering of the assembled cloud.... done! (%fs, %d points)\n", timer.ticks(), !cloudToExport->empty()?(int)cloudToExport->size():(int)cloudIToExport->size());
}
std::vector<int> pointToCamId;
std::vector<float> pointToCamIntensity;
if(camProjection && !robotPoses.empty())
{
printf("Camera projection...\n");
std::map<int, std::vector<rtabmap::CameraModel> > cameraModelsProj;
if(cameraProjDecimation>1)
{
for(std::map<int, std::vector<rtabmap::CameraModel> >::iterator iter=cameraModels.begin();
iter!=cameraModels.end();
++iter)
{
std::vector<rtabmap::CameraModel> models;
for(size_t i=0; i<iter->second.size(); ++i)
{
models.push_back(iter->second[i].scaled(1.0/double(cameraProjDecimation)));
}
cameraModelsProj.insert(std::make_pair(iter->first, models));
}
}
else
{
cameraModelsProj = cameraModels;
}
if(exportImages)
{
printf("Camera projection... projecting cloud to individual cameras (--images option)\n");
// projectCloudToCamera requires PCLPointCloud2
pcl::PCLPointCloud2::Ptr cloud2(new pcl::PCLPointCloud2);
if(!cloudToExport->empty())
{
pcl::toPCLPointCloud2(*cloudToExport, *cloud2);
}
else if(!cloudIToExport->empty())
{
pcl::toPCLPointCloud2(*cloudIToExport, *cloud2);
}
std::string dir = outputDirectory+"/"+baseName+"_depth_from_scan";
if(!UDirectory::exists(dir)) {
UDirectory::makeDir(dir);
}
for(std::map<int, std::vector<rtabmap::CameraModel> >::iterator iter=cameraModelsProj.begin();
iter!=cameraModelsProj.end();
++iter)
{
cv::Mat depth(iter->second.front().imageHeight(), iter->second.front().imageWidth()*iter->second.size(), CV_32FC1);
for(size_t i=0; i<iter->second.size(); ++i)
{
cv::Mat subDepth = util3d::projectCloudToCamera(
iter->second.at(i).imageSize(),
iter->second.at(i).K(),
cloud2,
robotPoses.at(iter->first) * iter->second.at(i).localTransform());
subDepth.copyTo(depth(cv::Range::all(), cv::Range(i*iter->second.front().imageWidth(), (i+1)*iter->second.front().imageWidth())));
}
depth = rtabmap::util2d::cvtDepthFromFloat(depth);
std::string outputPath=dir+"/"+(exportImagesId?uNumber2Str(iter->first):uFormat("%f",cameraStamps.at(iter->first)))+".png";
cv::imwrite(outputPath, depth);
}
}
cv::Mat projMask;
if(!cameraProjMask.empty())
{
projMask = cv::imread(cameraProjMask, cv::IMREAD_GRAYSCALE);
if(cameraProjDecimation>1)
{
cv::Mat out = projMask;
cv::resize(projMask, out, cv::Size(), 1.0f/float(cameraProjDecimation), 1.0f/float(cameraProjDecimation), cv::INTER_NEAREST);
projMask = out;
}
}
printf("Camera projection... projecting cloud to all cameras\n");
pointToCamId.resize(!cloudToExport->empty()?cloudToExport->size():cloudIToExport->size());
std::vector<std::pair< std::pair<int, int>, pcl::PointXY> > pointToPixel;
if(!cloudToExport->empty())
{
pointToPixel = util3d::projectCloudToCameras(
*cloudToExport,
robotPoses,
cameraModelsProj,
textureRange,
textureAngle,
textureRoiRatios,
projMask,
distanceToCamPolicy,
&progressState);
}
else if(!cloudIToExport->empty())
{
pointToPixel = util3d::projectCloudToCameras(
*cloudIToExport,
robotPoses,
cameraModelsProj,
textureRange,
textureAngle,
textureRoiRatios,
projMask,
distanceToCamPolicy,
&progressState);
pointToCamIntensity.resize(pointToPixel.size());
}
printf("Camera projection... coloring the cloud\n");
// color the cloud
UASSERT(pointToPixel.empty() || pointToPixel.size() == pointToCamId.size());
pcl::PointCloud<pcl::PointXYZRGBNormal>::Ptr assembledCloudValidPoints(new pcl::PointCloud<pcl::PointXYZRGBNormal>());
assembledCloudValidPoints->resize(pointToCamId.size());
int imagesDone = 1;
for(std::map<int, rtabmap::Transform>::iterator iter=robotPoses.begin(); iter!=robotPoses.end(); ++iter)
{
int nodeID = iter->first;
cv::Mat image;
if(uContains(nodes,nodeID) && !nodes.at(nodeID).sensorData().imageCompressed().empty())
{
nodes.at(nodeID).sensorData().uncompressDataConst(&image, 0);
}
if(!image.empty())
{
if(cameraProjDecimation>1)
{
image = util2d::decimate(image, cameraProjDecimation);
}
UASSERT(cameraModelsProj.find(nodeID) != cameraModelsProj.end());
int modelsSize = cameraModelsProj.at(nodeID).size();
for(size_t i=0; i<pointToPixel.size(); ++i)
{
int cameraIndex = pointToPixel[i].first.second;
if(nodeID == pointToPixel[i].first.first && cameraIndex>=0)
{
pcl::PointXYZRGBNormal pt;
float intensity = 0;
if(!cloudToExport->empty())
{
pt = cloudToExport->at(i);
}
else if(!cloudIToExport->empty())
{
pt.x = cloudIToExport->at(i).x;
pt.y = cloudIToExport->at(i).y;
pt.z = cloudIToExport->at(i).z;
pt.normal_x = cloudIToExport->at(i).normal_x;
pt.normal_y = cloudIToExport->at(i).normal_y;
pt.normal_z = cloudIToExport->at(i).normal_z;
intensity = cloudIToExport->at(i).intensity;
}
int subImageWidth = image.cols / modelsSize;
cv::Mat subImage = image(cv::Range::all(), cv::Range(cameraIndex*subImageWidth, (cameraIndex+1)*subImageWidth));
int x = pointToPixel[i].second.x * (float)subImage.cols;
int y = pointToPixel[i].second.y * (float)subImage.rows;
UASSERT(x>=0 && x<subImage.cols);
UASSERT(y>=0 && y<subImage.rows);
if(subImage.type()==CV_8UC3)
{
cv::Vec3b bgr = subImage.at<cv::Vec3b>(y, x);
pt.b = bgr[0];
pt.g = bgr[1];
pt.r = bgr[2];
}
else
{
UASSERT(subImage.type()==CV_8UC1);
pt.r = pt.g = pt.b = subImage.at<unsigned char>(pointToPixel[i].second.y * subImage.rows, pointToPixel[i].second.x * subImage.cols);
}
int exportedId = nodeID;
pointToCamId[i] = exportedId;
if(!pointToCamIntensity.empty())
{
pointToCamIntensity[i] = intensity;
}
assembledCloudValidPoints->at(i) = pt;
}
}
}
UINFO("Processed %d/%d images", imagesDone++, (int)robotPoses.size());
}
pcl::IndicesPtr validIndices(new std::vector<int>(pointToPixel.size()));
size_t oi = 0;
for(size_t i=0; i<pointToPixel.size(); ++i)
{
if(pointToPixel[i].first.first <=0)
{
if(camProjectionKeepAll)
{
pcl::PointXYZRGBNormal pt;
float intensity = 0;
if(!cloudToExport->empty())
{
pt = cloudToExport->at(i);
}
else if(!cloudIToExport->empty())
{
pt.x = cloudIToExport->at(i).x;
pt.y = cloudIToExport->at(i).y;
pt.z = cloudIToExport->at(i).z;
pt.normal_x = cloudIToExport->at(i).normal_x;
pt.normal_y = cloudIToExport->at(i).normal_y;
pt.normal_z = cloudIToExport->at(i).normal_z;
intensity = cloudIToExport->at(i).intensity;
}
pointToCamId[i] = 0; // invalid
pt.b = 0;
pt.g = 0;
pt.r = 255;
if(!pointToCamIntensity.empty())
{
pointToCamIntensity[i] = intensity;
}
assembledCloudValidPoints->at(i) = pt; // red
validIndices->at(oi++) = i;
}
}
else
{
validIndices->at(oi++) = i;
}
}
if(oi != validIndices->size())
{
validIndices->resize(oi);
assembledCloudValidPoints = util3d::extractIndices(assembledCloudValidPoints, validIndices, false, false);
std::vector<int> pointToCamIdTmp(validIndices->size());
std::vector<float> pointToCamIntensityTmp(validIndices->size());
for(size_t i=0; i<validIndices->size(); ++i)
{
pointToCamIdTmp[i] = pointToCamId[validIndices->at(i)];
pointToCamIntensityTmp[i] = pointToCamIntensity[validIndices->at(i)];
}
pointToCamId = pointToCamIdTmp;
pointToCamIntensity = pointToCamIntensityTmp;
pointToCamIdTmp.clear();
pointToCamIntensityTmp.clear();
}
cloudToExport = assembledCloudValidPoints;
cloudIToExport->clear();
printf("Camera projection... done! (%fs)\n", timer.ticks());
}
if(!(mesh || texture))
{
if(saveInDb)
{
printf("Saving in db... (%d points)\n", !cloudToExport->empty()?(int)cloudToExport->size():(int)cloudIToExport->size());
if(!cloudToExport->empty())
driver->saveOptimizedMesh(util3d::laserScanFromPointCloud(*cloudToExport, Transform(), false).data());
else if(!cloudIToExport->empty())
driver->saveOptimizedMesh(util3d::laserScanFromPointCloud(*cloudIToExport, Transform(), false).data());
printf("Saving in db... done!\n");
}
else
{
std::string ext = las?"las":"ply";
std::string outputPath=outputDirectory+"/"+baseName+"_cloud."+ext;
printf("Saving %s... (%d points)\n", outputPath.c_str(), !cloudToExport->empty()?(int)cloudToExport->size():(int)cloudIToExport->size());
#ifdef RTABMAP_PDAL
if(las || !pointToCamId.empty() || !pointToCamIntensity.empty())
{
if(!cloudToExport->empty())
{
if(!pointToCamIntensity.empty())
{
savePDALFile(outputPath, *cloudToExport, pointToCamId, binary, pointToCamIntensity);
}
else
{
savePDALFile(outputPath, *cloudToExport, pointToCamId, binary);
}
}
else if(!cloudIToExport->empty())
savePDALFile(outputPath, *cloudIToExport, pointToCamId, binary);
}
else
#endif
{
if(!pointToCamId.empty())
{
if(!pointToCamIntensity.empty())
{
printf("Option --cam_projection is enabled but rtabmap is not built "
"with PDAL support, so camera IDs and lidar intensities won't be exported in the output cloud.\n");
}
else
{
printf("Option --cam_projection is enabled but rtabmap is not built "
"with PDAL support, so camera IDs won't be exported in the output cloud.\n");
}
}
if(!cloudToExport->empty())
pcl::io::savePLYFile(outputPath, *cloudToExport, binary);
else if(!cloudIToExport->empty())
pcl::io::savePLYFile(outputPath, *cloudIToExport, binary);
}
printf("Saving %s... done!\n", outputPath.c_str());
}
}
// Meshing...
if(mesh || texture)
{
if(!cloudIToExport->empty())
{
pcl::copyPointCloud(*cloudIToExport, *cloudToExport);
cloudIToExport->clear();
}
Eigen::Vector4f min,max;
pcl::getMinMax3D(*cloudToExport, min, max);
float mapLength = uMax3(max[0]-min[0], max[1]-min[1], max[2]-min[2]);
int optimizedDepth = 12;
for(int i=6; i<12; ++i)
{
if(mapLength/float(1<<i) < poissonSize)
{
optimizedDepth = i;
break;
}
}
if(poissonDepth>0)
{
optimizedDepth = poissonDepth;
}
// Mesh reconstruction
printf("Mesh reconstruction... depth=%d\n", optimizedDepth);
pcl::PolygonMesh::Ptr mesh(new pcl::PolygonMesh);
pcl::Poisson<pcl::PointXYZRGBNormal> poisson;
poisson.setDepth(optimizedDepth);
poisson.setInputCloud(cloudToExport);
poisson.reconstruct(*mesh);
printf("Mesh reconstruction... done (%fs, %d polygons).\n", timer.ticks(), (int)mesh->polygons.size());
if(mesh->polygons.size())
{
printf("Mesh color transfer (max polygons=%d, color radius=%f, clean=%s)...\n",
maxPolygons,
colorRadius,
doClean?"true":"false");
rtabmap::util3d::denseMeshPostProcessing<pcl::PointXYZRGBNormal>(
mesh,
0.0f,
maxPolygons,
cloudToExport,
colorRadius,
!texture,
doClean,
minCluster);
printf("Mesh color transfer... done (%fs).\n", timer.ticks());
if(!texture)
{
if(saveInDb)
{
printf("Saving mesh in db...\n");
std::vector<std::vector<std::vector<RTABMAP_PCL_INDEX> > > polygons;
polygons.push_back(util3d::convertPolygonsFromPCL(mesh->polygons));
driver->saveOptimizedMesh(
util3d::laserScanFromPointCloud(mesh->cloud, false).data(),
polygons);
printf("Saving mesh in db... done!\n");
}
else
{
std::string outputPath=outputDirectory+"/"+baseName+"_mesh.ply";
printf("Saving %s...\n", outputPath.c_str());
if(binary)
pcl::io::savePLYFileBinary(outputPath, *mesh);
else
pcl::io::savePLYFile(outputPath, *mesh);
printf("Saving %s... done!\n", outputPath.c_str());
}
}
else
{
// Camera filtering for texturing
std::map<int, rtabmap::Transform> robotPosesFiltered;
if(laplacianThr>0)
{
printf("Filtering %ld images from texturing...\n", robotPoses.size());
for(std::map<int, rtabmap::Transform>::iterator iter=robotPoses.begin(); iter!=robotPoses.end(); ++iter)
{
UASSERT(nodes.find(iter->first) != nodes.end());
cv::Mat img;
nodes.find(iter->first)->second.sensorData().uncompressDataConst(&img, 0);
if(!img.empty())
{
cv::Mat imgLaplacian;
cv::Laplacian(img, imgLaplacian, CV_16S);
cv::Mat m, s;
cv::meanStdDev(imgLaplacian, m, s);
double stddev_pxl = s.at<double>(0);
double var = stddev_pxl*stddev_pxl;
if(var < (double)laplacianThr)
{
printf("Camera's image %d is detected as blurry (var=%f < thr=%d), camera is ignored for texturing.\n", iter->first, var, laplacianThr);
}
else
{
robotPosesFiltered.insert(*iter);
}
}
}
printf("Filtered %ld/%ld images from texturing", robotPosesFiltered.size(), robotPoses.size());
}
else
{
robotPosesFiltered = robotPoses;
}
printf("Texturing %d polygons... robotPoses=%d, cameraModels=%d, cameraDepths=%d\n", (int)mesh->polygons.size(), (int)robotPosesFiltered.size(), (int)cameraModels.size(), (int)cameraDepths.size());
std::vector<std::map<int, pcl::PointXY> > vertexToPixels;
pcl::TextureMeshPtr textureMesh = rtabmap::util3d::createTextureMesh(
mesh,
robotPosesFiltered,
cameraModels,
cameraDepths,
textureRange,
textureDepthError,
textureAngle,
multiband?0:50, // Min polygons in camera view to be textured by this camera
textureRoiRatios,
&progressState,
&vertexToPixels,
distanceToCamPolicy);
printf("Texturing... done (%fs).\n", timer.ticks());
// Remove occluded polygons (polygons with no texture)
if(doClean && textureMesh->tex_coordinates.size())
{
printf("Cleanup mesh...\n");
rtabmap::util3d::cleanTextureMesh(*textureMesh, 100); // Min polygons in a cluster to keep them
printf("Cleanup mesh... done (%fs).\n", timer.ticks());
}
if(textureMesh->tex_materials.size())
{
if(multiband)
{
printf("Merging %d texture(s) to single one (multiband enabled)...\n", (int)textureMesh->tex_materials.size());
}
else
{
printf("Merging %d texture(s)... (%d max textures)\n", (int)textureMesh->tex_materials.size(), textureCount);
}
std::map<int, std::map<int, cv::Vec4d> > gains;
std::map<int, std::map<int, cv::Mat> > blendingGains;
std::pair<float, float> contrastValues(0,0);
cv::Mat textures = rtabmap::util3d::mergeTextures(
*textureMesh,
std::map<int, cv::Mat>(),
std::map<int, std::vector<rtabmap::CameraModel> >(),
rtabmap.getMemory(),
0,
textureSize,
multiband?1:textureCount, // to get contrast values based on all images in multiband mode
vertexToPixels,
gainValue>0.0f, gainValue, doGainCompensationRGB,
doBlending, 0,
lowBrightnessGain, highBrightnessGain, // low-high brightness/contrast balance
false, // exposure fusion
0, // state
0, // blank value (0=black)
&gains,
&blendingGains,
&contrastValues);
printf("Merging to %d texture(s)... done (%fs).\n", (int)textureMesh->tex_materials.size(), timer.ticks());
if(saveInDb)
{
printf("Saving texture mesh in db...\n");
driver->saveOptimizedMesh(
util3d::laserScanFromPointCloud(textureMesh->cloud, false).data(),
util3d::convertPolygonsFromPCL(textureMesh->tex_polygons),
textureMesh->tex_coordinates,
textures);
printf("Saving texture mesh in db... done!\n");
}
else
{
// TextureMesh OBJ
bool success = false;
UASSERT(!textures.empty());
for(size_t i=0; i<textureMesh->tex_materials.size(); ++i)
{
textureMesh->tex_materials[i].tex_file += ".jpg";
printf("Saving texture to %s.\n", textureMesh->tex_materials[i].tex_file.c_str());
UASSERT(textures.cols % textures.rows == 0);
success = cv::imwrite(outputDirectory+"/"+textureMesh->tex_materials[i].tex_file, cv::Mat(textures, cv::Range::all(), cv::Range(textures.rows*i, textures.rows*(i+1))));
if(!success)
{
UERROR("Failed saving %s!", textureMesh->tex_materials[i].tex_file.c_str());
}
else
{
printf("Saved %s.\n", textureMesh->tex_materials[i].tex_file.c_str());
}
}
if(success)
{
std::string outputPath=outputDirectory+"/"+baseName+"_mesh.obj";
printf("Saving obj (%d vertices) to %s.\n", (int)textureMesh->cloud.data.size()/textureMesh->cloud.point_step, outputPath.c_str());
success = pcl::io::saveOBJFile(outputPath, *textureMesh) == 0;
if(success)
{
printf("Saved obj to %s!\n", outputPath.c_str());
}
else
{
UERROR("Failed saving obj to %s!", outputPath.c_str());
}
}
}
if(multiband)
{
timer.restart();
std::string outputPath=outputDirectory+"/"+baseName+"_mesh_multiband.obj";
printf("MultiBand texturing (size=%d, downscale=%d, unwrap method=%s, fill holes=%s, padding=%d, best score thr=%f, angle thr=%f, force visible=%s)... \"%s\"\n",
textureSize,
multibandDownScale,
multibandUnwrap==1?"ABF":multibandUnwrap==2?"LSCM":"Basic",
multibandFillHoles?"true":"false",
multibandPadding,
multibandBestScoreThr,
multibandAngleHardthr,
multibandForceVisible?"false":"true",
outputPath.c_str());
if(util3d::multiBandTexturing(outputPath,
textureMesh->cloud,
textureMesh->tex_polygons[0],
robotPosesFiltered,
vertexToPixels,
std::map<int, cv::Mat >(),
std::map<int, std::vector<CameraModel> >(),
rtabmap.getMemory(),
0,
textureSize,
multibandDownScale,
multibandNbContrib,
"jpg",
gains,
blendingGains,
contrastValues,
doGainCompensationRGB,
multibandUnwrap,
multibandFillHoles,
multibandPadding,
multibandBestScoreThr,
multibandAngleHardthr,
multibandForceVisible))
{
printf("MultiBand texturing...done (%fs).\n", timer.ticks());
}
else
{
printf("MultiBand texturing...failed! (%fs)\n", timer.ticks());
}
}
}
}
}
}
}
else
{
printf("Export failed! The cloud is empty.\n");
}
if(driver)
{
driver->closeConnection();
delete driver;
driver = 0;
}
return 0;
}
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