/*
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/OdometryF2M.h>
#include "rtabmap/core/Rtabmap.h"
#include "rtabmap/core/CameraStereo.h"
#include "rtabmap/core/CameraThread.h"
#include "rtabmap/core/Graph.h"
#include "rtabmap/core/OdometryInfo.h"
#include "rtabmap/core/OdometryEvent.h"
#include "rtabmap/core/Memory.h"
#include "rtabmap/core/util3d_registration.h"
#include "rtabmap/utilite/UConversion.h"
#include "rtabmap/utilite/UDirectory.h"
#include "rtabmap/utilite/UFile.h"
#include "rtabmap/utilite/UMath.h"
#include "rtabmap/utilite/UStl.h"
#include "rtabmap/utilite/UProcessInfo.h"
#include <pcl/common/common.h>
#include <stdio.h>
#include <signal.h>

using namespace rtabmap;

void showUsage()
{
	printf("\nUsage:\n"
			"rtabmap-kitti_dataset [options] path\n"
			"  path               Folder of the sequence (e.g., \"~/KITTI/dataset/sequences/07\")\n"
			"                        containing least calib.txt, times.txt, image_0 and image_1 folders.\n"
			"                        Optional image_2, image_3 and velodyne folders.\n"
			"  --output           Output directory. By default, results are saved in \"path\".\n"
			"  --output_name      Output database name (default \"rtabmap\").\n"
			"  --gt \"path\"        Ground truth path (e.g., ~/KITTI/devkit/cpp/data/odometry/poses/07.txt)\n"
			"  --quiet            Don't show log messages and iteration updates.\n"
			"  --color            Use color images for stereo (image_2 and image_3 folders).\n"
			"  --height           Add car's height to camera local transform (1.67m).\n"
			"  --disp             Generate full disparity.\n"
			"  --exposure_comp    Do exposure compensation between left and right images.\n"
			"  --scan             Include velodyne scan in node's data.\n"
			"  --scan_step #      Scan downsample step (default=1).\n"
			"  --scan_voxel #.#   Scan voxel size (default 0.5 m).\n"
			"  --scan_k           Scan normal K (default 0).\n"
			"  --scan_radius      Scan normal radius (default 0).\n\n"
			"%s\n"
			"Example:\n\n"
			"   $ rtabmap-kitti_dataset \\\n"
			"       --Rtabmap/PublishRAMUsage true\\\n"
			"       --Rtabmap/DetectionRate 2\\\n"
			"       --Rtabmap/CreateIntermediateNodes true\\\n"
			"       --RGBD/LinearUpdate 0\\\n"
			"       --GFTT/QualityLevel 0.01\\\n"
			"       --GFTT/MinDistance 7\\\n"
			"       --OdomF2M/MaxSize 3000\\\n"
			"       --Mem/STMSize 30\\\n"
			"       --Kp/MaxFeatures 750\\\n"
			"       --Vis/MaxFeatures 1500\\\n"
			"       --gt \"~/KITTI/devkit/cpp/data/odometry/poses/07.txt\"\\\n"
			"       ~/KITTI/dataset/sequences/07\n\n", rtabmap::Parameters::showUsage());
	exit(1);
}

// catch ctrl-c
bool g_forever = true;
void sighandler(int sig)
{
	printf("\nSignal %d caught...\n", sig);
	g_forever = false;
}

int main(int argc, char * argv[])
{
	signal(SIGABRT, &sighandler);
	signal(SIGTERM, &sighandler);
	signal(SIGINT, &sighandler);

	ULogger::setType(ULogger::kTypeConsole);
	ULogger::setLevel(ULogger::kWarning);

	ParametersMap parameters;
	std::string path;
	std::string output;
	std::string outputName = "rtabmap";
	std::string seq;
	bool color = false;
	bool height = false;
	bool scan = false;
	bool disp = false;
	bool exposureCompensation = false;
	int scanStep = 1;
	float scanVoxel = 0.5f;
	int scanNormalK = 0;
	float scanNormalRadius = 0.0f;
	std::string gtPath;
	bool quiet = false;
	if(argc < 2)
	{
		showUsage();
	}
	else
	{
		for(int i=1; i<argc; ++i)
		{
			if(std::strcmp(argv[i], "--output") == 0)
			{
				output = argv[++i];
			}
			else if(std::strcmp(argv[i], "--output_name") == 0)
			{
				outputName = argv[++i];
			}
			else if(std::strcmp(argv[i], "--quiet") == 0)
			{
				quiet = true;
			}
			else if(std::strcmp(argv[i], "--scan_step") == 0)
			{
				scanStep = atoi(argv[++i]);
				if(scanStep <= 0)
				{
					printf("scan_step should be > 0\n");
					showUsage();
				}
			}
			else if(std::strcmp(argv[i], "--scan_voxel") == 0)
			{
				scanVoxel = atof(argv[++i]);
				if(scanVoxel < 0.0f)
				{
					printf("scan_voxel should be >= 0.0\n");
					showUsage();
				}
			}
			else if(std::strcmp(argv[i], "--scan_k") == 0)
			{
				scanNormalK = atoi(argv[++i]);
				if(scanNormalK < 0)
				{
					printf("scanNormalK should be >= 0\n");
					showUsage();
				}
			}
			else if(std::strcmp(argv[i], "--scan_radius") == 0)
			{
				scanNormalRadius = atof(argv[++i]);
				if(scanNormalRadius < 0.0f)
				{
					printf("scanNormalRadius should be >= 0\n");
					showUsage();
				}
			}
			else if(std::strcmp(argv[i], "--gt") == 0)
			{
				gtPath = argv[++i];
			}
			else if(std::strcmp(argv[i], "--color") == 0)
			{
				color = true;
			}
			else if(std::strcmp(argv[i], "--height") == 0)
			{
				height = true;
			}
			else if(std::strcmp(argv[i], "--scan") == 0)
			{
				scan = true;
			}
			else if(std::strcmp(argv[i], "--disp") == 0)
			{
				disp = true;
			}
			else if(std::strcmp(argv[i], "--exposure_comp") == 0)
			{
				exposureCompensation = true;
			}
		}
		parameters = Parameters::parseArguments(argc, argv);
		path = argv[argc-1];
		path = uReplaceChar(path, '~', UDirectory::homeDir());
		path = uReplaceChar(path, '\\', '/');
		if(output.empty())
		{
			output = path;
		}
		else
		{
			output = uReplaceChar(output, '~', UDirectory::homeDir());
			UDirectory::makeDir(output);
		}
		parameters.insert(ParametersPair(Parameters::kRtabmapWorkingDirectory(), output));
		parameters.insert(ParametersPair(Parameters::kRtabmapPublishRAMUsage(), "true"));
	}

	seq = uSplit(path, '/').back();
	if(seq.empty() || !(uStr2Int(seq)>=0 && uStr2Int(seq)<=21))
	{
		UWARN("Sequence number \"%s\" should be between 0 and 21 (official KITTI datasets).", seq.c_str());
		seq.clear();
	}
	std::string pathLeftImages  = path+(color?"/image_2":"/image_0");
	std::string pathRightImages = path+(color?"/image_3":"/image_1");
	std::string pathCalib = path+"/calib.txt";
	std::string pathTimes = path+"/times.txt";
	std::string pathScan;

	printf("Paths:\n"
			"   Sequence number:  %s\n"
			"   Sequence path:    %s\n"
			"   Output:           %s\n"
			"   Output name:      %s\n"
			"   left images:      %s\n"
			"   right images:     %s\n"
			"   calib.txt:        %s\n"
			"   times.txt:        %s\n",
			seq.c_str(),
			path.c_str(),
			output.c_str(),
			outputName.c_str(),
			pathLeftImages.c_str(),
			pathRightImages.c_str(),
			pathCalib.c_str(),
			pathTimes.c_str());
	if(!gtPath.empty())
	{
		gtPath = uReplaceChar(gtPath, '~', UDirectory::homeDir());
		gtPath = uReplaceChar(gtPath, '\\', '/');
		if(!UFile::exists(gtPath))
		{
			UWARN("Ground truth file path doesn't exist: \"%s\", benchmark values won't be computed.", gtPath.c_str());
			gtPath.clear();
		}
		else
		{
			printf("   Ground Truth:      %s\n", gtPath.c_str());
		}
	}
	printf("   Exposure Compensation: %s\n", exposureCompensation?"true":"false");
	printf("   Disparity:         %s\n", disp?"true":"false");
	if(scan)
	{
		pathScan = path+"/velodyne";
		printf("   Scan:               %s\n", pathScan.c_str());
		printf("   Scan step:          %d\n", scanStep);
		printf("   Scan voxel:         %fm\n", scanVoxel);
		printf("   Scan normal k:      %d\n", scanNormalK);
		printf("   Scan normal radius: %f\n", scanNormalRadius);
	}

	// convert calib.txt to rtabmap format (yaml)
	FILE * pFile = 0;
	pFile = fopen(pathCalib.c_str(),"r");
	if(!pFile)
	{
		UERROR("Cannot open calibration file \"%s\"", pathCalib.c_str());
		return -1;
	}
	cv::Mat_<double> P0(3,4);
	cv::Mat_<double> P1(3,4);
	cv::Mat_<double> P2(3,4);
	cv::Mat_<double> P3(3,4);
	if(fscanf (pFile, "%*s %lf %lf %lf %lf %lf %lf %lf %lf %lf %lf %lf %lf",
			&P0(0, 0), &P0(0, 1), &P0(0, 2), &P0(0, 3),
			&P0(1, 0), &P0(1, 1), &P0(1, 2), &P0(1, 3),
			&P0(2, 0), &P0(2, 1), &P0(2, 2), &P0(2, 3)) != 12)
	{
		UERROR("Failed to parse calibration file \"%s\"", pathCalib.c_str());
		return -1;
	}
	if(fscanf (pFile, "%*s %lf %lf %lf %lf %lf %lf %lf %lf %lf %lf %lf %lf",
			&P1(0, 0), &P1(0, 1), &P1(0, 2), &P1(0, 3),
			&P1(1, 0), &P1(1, 1), &P1(1, 2), &P1(1, 3),
			&P1(2, 0), &P1(2, 1), &P1(2, 2), &P1(2, 3)) != 12)
	{
		UERROR("Failed to parse calibration file \"%s\"", pathCalib.c_str());
		return -1;
	}
	if(fscanf (pFile, "%*s %lf %lf %lf %lf %lf %lf %lf %lf %lf %lf %lf %lf",
			&P2(0, 0), &P2(0, 1), &P2(0, 2), &P2(0, 3),
			&P2(1, 0), &P2(1, 1), &P2(1, 2), &P2(1, 3),
			&P2(2, 0), &P2(2, 1), &P2(2, 2), &P2(2, 3)) != 12)
	{
		UERROR("Failed to parse calibration file \"%s\"", pathCalib.c_str());
		return -1;
	}
	if(fscanf (pFile, "%*s %lf %lf %lf %lf %lf %lf %lf %lf %lf %lf %lf %lf",
			&P3(0, 0), &P3(0, 1), &P3(0, 2), &P3(0, 3),
			&P3(1, 0), &P3(1, 1), &P3(1, 2), &P3(1, 3),
			&P3(2, 0), &P3(2, 1), &P3(2, 2), &P3(2, 3)) != 12)
	{
		UERROR("Failed to parse calibration file \"%s\"", pathCalib.c_str());
		return -1;
	}
	fclose (pFile);
	// get image size
	UDirectory dir(pathLeftImages);
	std::string firstImage = dir.getNextFileName();
	cv::Mat image = cv::imread(dir.getNextFilePath());
	if(image.empty())
	{
		UERROR("Failed to read first image of \"%s\"", firstImage.c_str());
		return -1;
	}

	StereoCameraModel model(outputName+"_calib",
			image.size(), P0.colRange(0,3), cv::Mat(), cv::Mat(), P0,
			image.size(), P1.colRange(0,3), cv::Mat(), cv::Mat(), P1,
			cv::Mat(), cv::Mat(), cv::Mat(), cv::Mat());
	if(!model.save(output, true))
	{
		UERROR("Could not save calibration!");
		return -1;
	}
	printf("Saved calibration \"%s\" to \"%s\"\n", (outputName+"_calib").c_str(), output.c_str());

	if(!parameters.empty())
	{
		printf("Parameters:\n");
		for(ParametersMap::iterator iter=parameters.begin(); iter!=parameters.end(); ++iter)
		{
			printf("   %s=%s\n", iter->first.c_str(), iter->second.c_str());
		}
	}

	printf("RTAB-Map version: %s\n", RTABMAP_VERSION);

	if(quiet)
	{
		ULogger::setLevel(ULogger::kError);
	}

	// We use CameraThread only to use postUpdate() method
	Transform opticalRotation(0,0,1,0, -1,0,0,color?-0.06:0, 0,-1,0,height?1.67:0.0);
	CameraThread cameraThread(new
		CameraStereoImages(
				pathLeftImages,
				pathRightImages,
				false, // assume that images are already rectified
				0.0f,
				opticalRotation), parameters);
	((CameraStereoImages*)cameraThread.camera())->setTimestamps(false, pathTimes, false);
	if(exposureCompensation)
	{
		cameraThread.setStereoExposureCompensation(true);
	}
	if(disp)
	{
		cameraThread.setStereoToDepth(true);
	}
	if(!gtPath.empty())
	{
		((CameraStereoImages*)cameraThread.camera())->setGroundTruthPath(gtPath, 2);
	}
	if(!pathScan.empty())
	{
		((CameraStereoImages*)cameraThread.camera())->setScanPath(
						pathScan,
						130000,
						scanStep,
						scanVoxel,
						scanNormalK,
						scanNormalRadius,
						Transform(-0.27f, 0.0f, 0.08+(height?1.67f:0.0f), 0.0f, 0.0f, 0.0f),
						true);
	}

	float detectionRate = Parameters::defaultRtabmapDetectionRate();
	bool intermediateNodes = Parameters::defaultRtabmapCreateIntermediateNodes();
	int odomStrategy = Parameters::defaultOdomStrategy();
	Parameters::parse(parameters, Parameters::kOdomStrategy(), odomStrategy);
	Parameters::parse(parameters, Parameters::kRtabmapDetectionRate(), detectionRate);
	Parameters::parse(parameters, Parameters::kRtabmapCreateIntermediateNodes(), intermediateNodes);

	// assuming source is 10 Hz
	int mapUpdate = 10 / detectionRate;
	if(mapUpdate < 1)
	{
		mapUpdate = 1;
	}

	std::string databasePath = output+"/"+outputName+".db";
	UFile::erase(databasePath);
	if(cameraThread.camera()->init(output, outputName+"_calib"))
	{
		int totalImages = (int)((CameraStereoImages*)cameraThread.camera())->filenames().size();

		printf("Processing %d images...\n", totalImages);

		ParametersMap odomParameters = parameters;
		odomParameters.erase(Parameters::kRtabmapPublishRAMUsage()); // as odometry is in the same process than rtabmap, don't get RAM usage in odometry.
		Odometry * odom = Odometry::create(odomParameters);
		Rtabmap rtabmap;
		rtabmap.init(parameters, databasePath);

		UTimer totalTime;
		UTimer timer;
		CameraInfo cameraInfo;
		SensorData data = cameraThread.camera()->takeImage(&cameraInfo);
		int iteration = 0;

		/////////////////////////////
		// Processing dataset begin
		/////////////////////////////
		cv::Mat covariance;
		int odomKeyFrames = 0;
		while(data.isValid() && g_forever)
		{
			cameraThread.postUpdate(&data, &cameraInfo);
			cameraInfo.timeTotal = timer.ticks();


			OdometryInfo odomInfo;
			Transform pose = odom->process(data, &odomInfo);
			float speed = 0.0f;
			if(odomInfo.interval>0.0)
				speed = odomInfo.transform.x()/odomInfo.interval*3.6;
			if(odomInfo.keyFrameAdded)
			{
				++odomKeyFrames;
			}

			if(odomStrategy == 2)
			{
				//special case for FOVIS, set covariance 1 if 9999 is detected
				if(!odomInfo.reg.covariance.empty() && odomInfo.reg.covariance.at<double>(0,0) >= 9999)
				{
					odomInfo.reg.covariance = cv::Mat::eye(6,6,CV_64FC1);
				}
			}

			bool processData = true;
			if(iteration % mapUpdate != 0)
			{
				// set negative id so rtabmap will detect it as an intermediate node
				data.setId(-1);
				data.setFeatures(std::vector<cv::KeyPoint>(), std::vector<cv::Point3f>(), cv::Mat());// remove features
				processData = intermediateNodes;
			}
			if(covariance.empty() || odomInfo.reg.covariance.at<double>(0,0) > covariance.at<double>(0,0))
			{
				covariance = odomInfo.reg.covariance;
			}

			timer.restart();
			if(processData)
			{
				std::map<std::string, float> externalStats;
				// save camera statistics to database
				externalStats.insert(std::make_pair("Camera/BilateralFiltering/ms", cameraInfo.timeBilateralFiltering*1000.0f));
				externalStats.insert(std::make_pair("Camera/Capture/ms", cameraInfo.timeCapture*1000.0f));
				externalStats.insert(std::make_pair("Camera/Disparity/ms", cameraInfo.timeDisparity*1000.0f));
				externalStats.insert(std::make_pair("Camera/ImageDecimation/ms", cameraInfo.timeImageDecimation*1000.0f));
				externalStats.insert(std::make_pair("Camera/Mirroring/ms", cameraInfo.timeMirroring*1000.0f));
				externalStats.insert(std::make_pair("Camera/ExposureCompensation/ms", cameraInfo.timeStereoExposureCompensation*1000.0f));
				externalStats.insert(std::make_pair("Camera/ScanFromDepth/ms", cameraInfo.timeScanFromDepth*1000.0f));
				externalStats.insert(std::make_pair("Camera/TotalTime/ms", cameraInfo.timeTotal*1000.0f));
				externalStats.insert(std::make_pair("Camera/UndistortDepth/ms", cameraInfo.timeUndistortDepth*1000.0f));
				// save odometry statistics to database
				externalStats.insert(std::make_pair("Odometry/LocalBundle/ms", odomInfo.localBundleTime*1000.0f));
				externalStats.insert(std::make_pair("Odometry/LocalBundleConstraints/", odomInfo.localBundleConstraints));
				externalStats.insert(std::make_pair("Odometry/LocalBundleOutliers/", odomInfo.localBundleOutliers));
				externalStats.insert(std::make_pair("Odometry/TotalTime/ms", odomInfo.timeEstimation*1000.0f));
				externalStats.insert(std::make_pair("Odometry/Registration/ms", odomInfo.reg.totalTime*1000.0f));
				externalStats.insert(std::make_pair("Odometry/Speed/kph", speed));
				externalStats.insert(std::make_pair("Odometry/Inliers/", odomInfo.reg.inliers));
				externalStats.insert(std::make_pair("Odometry/Features/", odomInfo.features));
				externalStats.insert(std::make_pair("Odometry/DistanceTravelled/m", odomInfo.distanceTravelled));
				externalStats.insert(std::make_pair("Odometry/KeyFrameAdded/", odomInfo.keyFrameAdded));
				externalStats.insert(std::make_pair("Odometry/LocalKeyFrames/", odomInfo.localKeyFrames));
				externalStats.insert(std::make_pair("Odometry/LocalMapSize/", odomInfo.localMapSize));
				externalStats.insert(std::make_pair("Odometry/LocalScanMapSize/", odomInfo.localScanMapSize));

				OdometryEvent e(SensorData(), Transform(), odomInfo);
				rtabmap.process(data, pose, covariance, e.velocity(), externalStats);
				covariance = cv::Mat();
			}

			++iteration;
			if(!quiet || iteration == totalImages)
			{
				double slamTime = timer.ticks();

				float rmse = -1;
				if(rtabmap.getStatistics().data().find(Statistics::kGtTranslational_rmse()) != rtabmap.getStatistics().data().end())
				{
					rmse = rtabmap.getStatistics().data().at(Statistics::kGtTranslational_rmse());
				}

				if(data.keypoints().size() == 0 && data.laserScanRaw().size())
				{
					if(rmse >= 0.0f)
					{
						//printf("Iteration %d/%d: speed=%dkm/h camera=%dms, odom(quality=%f, kfs=%d)=%dms, slam=%dms, rmse=%fm, noise stddev=%fm %frad",
						//		iteration, totalImages, int(speed), int(cameraInfo.timeTotal*1000.0f), odomInfo.reg.icpInliersRatio, odomKeyFrames, int(odomInfo.timeEstimation*1000.0f), int(slamTime*1000.0f), rmse, sqrt(odomInfo.reg.covariance.at<double>(0,0)), sqrt(odomInfo.reg.covariance.at<double>(3,3)));
						printf("Iteration %d/%d: speed=%dkm/h camera=%dms, odom(quality=%f, kfs=%d)=%dms, slam=%dms, rmse=%fm",
								iteration, totalImages, int(speed), int(cameraInfo.timeTotal*1000.0f), odomInfo.reg.icpInliersRatio, odomKeyFrames, int(odomInfo.timeEstimation*1000.0f), int(slamTime*1000.0f), rmse);
					}
					else
					{
						printf("Iteration %d/%d: speed=%dkm/h camera=%dms, odom(quality=%f, kfs=%d)=%dms, slam=%dms",
								iteration, totalImages, int(speed), int(cameraInfo.timeTotal*1000.0f), odomInfo.reg.icpInliersRatio, odomKeyFrames, int(odomInfo.timeEstimation*1000.0f), int(slamTime*1000.0f));
					}
				}
				else
				{
					if(rmse >= 0.0f)
					{
						//printf("Iteration %d/%d: speed=%dkm/h camera=%dms, odom(quality=%d/%d, kfs=%d)=%dms, slam=%dms, rmse=%fm, noise stddev=%fm %frad",
						//		iteration, totalImages, int(speed), int(cameraInfo.timeTotal*1000.0f), odomInfo.reg.inliers, odomInfo.features, odomKeyFrames, int(odomInfo.timeEstimation*1000.0f), int(slamTime*1000.0f), rmse, sqrt(odomInfo.reg.covariance.at<double>(0,0)), sqrt(odomInfo.reg.covariance.at<double>(3,3)));
						printf("Iteration %d/%d: speed=%dkm/h camera=%dms, odom(quality=%d/%d, kfs=%d)=%dms, slam=%dms, rmse=%fm",
								iteration, totalImages, int(speed), int(cameraInfo.timeTotal*1000.0f), odomInfo.reg.inliers, odomInfo.features, odomKeyFrames, int(odomInfo.timeEstimation*1000.0f), int(slamTime*1000.0f), rmse);
					}
					else
					{
						printf("Iteration %d/%d: speed=%dkm/h camera=%dms, odom(quality=%d/%d, kfs=%d)=%dms, slam=%dms",
								iteration, totalImages, int(speed), int(cameraInfo.timeTotal*1000.0f), odomInfo.reg.inliers, odomInfo.features, odomKeyFrames, int(odomInfo.timeEstimation*1000.0f), int(slamTime*1000.0f));
					}
				}
				if(processData && rtabmap.getLoopClosureId()>0)
				{
					printf(" *");
				}
				printf("\n");
			}
			else if(iteration % (totalImages/10) == 0)
			{
				printf(".");
				fflush(stdout);
			}

			cameraInfo = CameraInfo();
			timer.restart();
			data = cameraThread.camera()->takeImage(&cameraInfo);
		}
		delete odom;
		printf("Total time=%fs\n", totalTime.ticks());
		/////////////////////////////
		// Processing dataset end
		/////////////////////////////

		// Save trajectory
		printf("Saving trajectory ...\n");
		std::map<int, Transform> poses;
		std::multimap<int, Link> links;
		rtabmap.getGraph(poses, links, true, true);
		std::string pathTrajectory = output+"/"+outputName+"_poses.txt";
		if(poses.size() && graph::exportPoses(pathTrajectory, 2, poses, links))
		{
			printf("Saving %s... done!\n", pathTrajectory.c_str());
		}
		else
		{
			printf("Saving %s... failed!\n", pathTrajectory.c_str());
		}

		if(!gtPath.empty())
		{
			// Log ground truth statistics
			std::map<int, Transform> groundTruth;

			for(std::map<int, Transform>::const_iterator iter=poses.begin(); iter!=poses.end(); ++iter)
			{
				Transform o, gtPose;
				int m,w;
				std::string l;
				double s;
				std::vector<float> v;
				GPS gps;
				rtabmap.getMemory()->getNodeInfo(iter->first, o, m, w, l, s, gtPose, v, gps, true);
				if(!gtPose.isNull())
				{
					groundTruth.insert(std::make_pair(iter->first, gtPose));
				}
			}

			// compute KITTI statistics
			float t_err = 0.0f;
			float r_err = 0.0f;
			graph::calcKittiSequenceErrors(uValues(groundTruth), uValues(poses), t_err, r_err);
			printf("Ground truth comparison:\n");
			printf("   KITTI t_err = %f %%\n", t_err);
			printf("   KITTI r_err = %f deg/m\n", r_err);

			// compute RMSE statistics
			float translational_rmse = 0.0f;
			float translational_mean = 0.0f;
			float translational_median = 0.0f;
			float translational_std = 0.0f;
			float translational_min = 0.0f;
			float translational_max = 0.0f;
			float rotational_rmse = 0.0f;
			float rotational_mean = 0.0f;
			float rotational_median = 0.0f;
			float rotational_std = 0.0f;
			float rotational_min = 0.0f;
			float rotational_max = 0.0f;
			graph::calcRMSE(
					groundTruth,
					poses,
					translational_rmse,
					translational_mean,
					translational_median,
					translational_std,
					translational_min,
					translational_max,
					rotational_rmse,
					rotational_mean,
					rotational_median,
					rotational_std,
					rotational_min,
					rotational_max);

			printf("   translational_rmse=   %f m\n", translational_rmse);
			printf("   rotational_rmse=      %f deg\n", rotational_rmse);

			pFile = 0;
			std::string pathErrors = output+"/"+outputName+"_rmse.txt";
			pFile = fopen(pathErrors.c_str(),"w");
			if(!pFile)
			{
				UERROR("could not save RMSE results to \"%s\"", pathErrors.c_str());
			}
			fprintf(pFile, "Ground truth comparison:\n");
			fprintf(pFile, "  KITTI t_err =         %f %%\n", t_err);
			fprintf(pFile, "  KITTI r_err =         %f deg/m\n", r_err);
			fprintf(pFile, "  translational_rmse=   %f\n", translational_rmse);
			fprintf(pFile, "  translational_mean=   %f\n", translational_mean);
			fprintf(pFile, "  translational_median= %f\n", translational_median);
			fprintf(pFile, "  translational_std=    %f\n", translational_std);
			fprintf(pFile, "  translational_min=    %f\n", translational_min);
			fprintf(pFile, "  translational_max=    %f\n", translational_max);
			fprintf(pFile, "  rotational_rmse=      %f\n", rotational_rmse);
			fprintf(pFile, "  rotational_mean=      %f\n", rotational_mean);
			fprintf(pFile, "  rotational_median=    %f\n", rotational_median);
			fprintf(pFile, "  rotational_std=       %f\n", rotational_std);
			fprintf(pFile, "  rotational_min=       %f\n", rotational_min);
			fprintf(pFile, "  rotational_max=       %f\n", rotational_max);
			fclose(pFile);
		}
	}
	else
	{
		UERROR("Camera init failed!");
	}

	printf("Saving rtabmap database (with all statistics) to \"%s\"\n", (output+"/"+outputName+".db").c_str());
	printf("Do:\n"
			" $ rtabmap-databaseViewer %s\n\n", (output+"/"+outputName+".db").c_str());

	return 0;
}
