Build-ORB-SLAM

apt-get install -y  git cmake build-essential libgl1-mesa-dev libglew-dev libblas-dev liblapack-dev libopencv-dev python-opencv libeigen3-dev
cd /tmp && git clone https://github.com/stevenlovegrove/Pangolin.git &&   cd Pangolin &&   mkdir build &&   cd build &&   cmake .. &&   make -j; make install
git clone https://github.com/raulmur/ORB_SLAM2.git ORB_SLAM2
cd ORB_SLAM2
chmod +x build.sh

listFiles.py

import datetime
from os import listdir
from os.path import isfile, join
mypath = "/headless/Downloads/dm/"
import time

current = datetime.datetime.now()
onlyfiles = [f for f in listdir(mypath) if isfile(join(mypath, f))]
for f in onlyfiles:
    current += datetime.timedelta(seconds=0.1)
    print(str(current.timestamp()) + " "+ f)

mono_tum.cc

/**
* This file is part of ORB-SLAM2.
*
* Copyright (C) 2014-2016 Raúl Mur-Artal <raulmur at unizar dot es> (University of Zaragoza)
* For more information see <https://github.com/raulmur/ORB_SLAM2>
*
* ORB-SLAM2 is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* ORB-SLAM2 is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with ORB-SLAM2. If not, see <http://www.gnu.org/licenses/>.
*/


#include<iostream>
#include<algorithm>
#include<fstream>
#include<chrono>

#include<opencv2/core/core.hpp>

#include<System.h>

using namespace std;

void LoadImages(const string &strFile, vector<string> &vstrImageFilenames,
                vector<double> &vTimestamps);

int main(int argc, char **argv)
{
    if(argc != 4)
    {
        cerr << endl << "Usage: ./mono_tum path_to_vocabulary path_to_settings path_to_sequence" << endl;
        return 1;
    }

    // Retrieve paths to images
    vector<string> vstrImageFilenames;
    vector<double> vTimestamps;
    string strFile = string(argv[3])+"/rgb.txt";
    LoadImages(strFile, vstrImageFilenames, vTimestamps);

    int nImages = vstrImageFilenames.size();

    // Create SLAM system. It initializes all system threads and gets ready to process frames.
    ORB_SLAM2::System SLAM(argv[1],argv[2],ORB_SLAM2::System::MONOCULAR,true);

    // Vector for tracking time statistics
    vector<float> vTimesTrack;
    vTimesTrack.resize(nImages);

    cout << endl << "-------" << endl;
    cout << "Start processing sequence ..." << endl;
    cout << "Images in the sequence: " << nImages << endl << endl;

    // Main loop
    cv::Mat im;
    for(int ni=0; ni<nImages; ni++)
    {
        // Read image from file
        im = cv::imread(string(argv[3])+"/"+vstrImageFilenames[ni],CV_LOAD_IMAGE_UNCHANGED);
        double tframe = vTimestamps[ni];

        if(im.empty())
        {
            cerr << endl << "Failed to load image at: "
                 << string(argv[3]) << "/" << vstrImageFilenames[ni] << endl;
            return 1;
        }

#ifdef COMPILEDWITHC11
        std::chrono::steady_clock::time_point t1 = std::chrono::steady_clock::now();
#else
        std::chrono::monotonic_clock::time_point t1 = std::chrono::monotonic_clock::now();
#endif

        // Pass the image to the SLAM system
        SLAM.TrackMonocular(im,tframe);

#ifdef COMPILEDWITHC11
        std::chrono::steady_clock::time_point t2 = std::chrono::steady_clock::now();
#else
        std::chrono::monotonic_clock::time_point t2 = std::chrono::monotonic_clock::now();
#endif

        double ttrack= std::chrono::duration_cast<std::chrono::duration<double> >(t2 - t1).count();

        vTimesTrack[ni]=ttrack;

        // Wait to load the next frame
        double T=0;
        if(ni<nImages-1)
            T = vTimestamps[ni+1]-tframe;
        else if(ni>0)
            T = tframe-vTimestamps[ni-1];

        if(ttrack<T)
            usleep((T-ttrack)*1e6);
    }
    std::cout << "recogn stoppped!" << std::endl;
    auto map = SLAM.mpMap;
    const auto & vpMPs = map->GetAllMapPoints();
    ofstream myFileMap("pointCloud.xyz");
    for(size_t i=0, iend=vpMPs.size(); i<iend;i++) {
        if(vpMPs[i]->isBad()) {
            continue;
        }
        auto pos = vpMPs[i]->GetWorldPos();
        myFileMap << pos.at<float>(2) << "\t" <<pos.at<float>(0)<< "\t" << pos.at<float>(1) << std::endl;
    }
    myFileMap.close();
    std::cout << "cloud saved as pointCloud.xyz" << std::endl;
    return 0; //uncomment to create a utilety out of it!
    while(true) {

        std::this_thread::sleep_for(std::chrono::milliseconds(100));
    }
    // Stop all threads
    SLAM.Shutdown();

    // Tracking time statistics
    sort(vTimesTrack.begin(),vTimesTrack.end());
    float totaltime = 0;
    for(int ni=0; ni<nImages; ni++)
    {
        totaltime+=vTimesTrack[ni];
    }
    cout << "-------" << endl << endl;
    cout << "median tracking time: " << vTimesTrack[nImages/2] << endl;
    cout << "mean tracking time: " << totaltime/nImages << endl;

    // Save camera trajectory
    SLAM.SaveKeyFrameTrajectoryTUM("KeyFrameTrajectory.txt");

    return 0;
}

void LoadImages(const string &strFile, vector<string> &vstrImageFilenames, vector<double> &vTimestamps)
{
    ifstream f;
    f.open(strFile.c_str());

    // skip first three lines
    string s0;
    getline(f,s0);
    getline(f,s0);
    getline(f,s0);

    while(!f.eof())
    {
        string s;
        getline(f,s);
        if(!s.empty())
        {
            stringstream ss;
            ss << s;
            double t;
            string sRGB;
            ss >> t;
            vTimestamps.push_back(t);
            ss >> sRGB;
            vstrImageFilenames.push_back(sRGB);
        }
    }
}

System.h

/**
* This file is part of ORB-SLAM2.
*
* Copyright (C) 2014-2016 Raúl Mur-Artal <raulmur at unizar dot es> (University of Zaragoza)
* For more information see <https://github.com/raulmur/ORB_SLAM2>
*
* ORB-SLAM2 is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* ORB-SLAM2 is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with ORB-SLAM2. If not, see <http://www.gnu.org/licenses/>.
*/


#ifndef SYSTEM_H
#define SYSTEM_H

#include<string>
#include<thread>
#include<opencv2/core/core.hpp>

#include "Tracking.h"
#include "FrameDrawer.h"
#include "MapDrawer.h"
#include "Map.h"
#include "LocalMapping.h"
#include "LoopClosing.h"
#include "KeyFrameDatabase.h"
#include "ORBVocabulary.h"
#include "Viewer.h"

namespace ORB_SLAM2
{

class Viewer;
class FrameDrawer;
class Map;
class Tracking;
class LocalMapping;
class LoopClosing;

class System
{
public:
    // Input sensor
    enum eSensor{
        MONOCULAR=0,
        STEREO=1,
        RGBD=2
    };

public:

    // Initialize the SLAM system. It launches the Local Mapping, Loop Closing and Viewer threads.
    System(const string &strVocFile, const string &strSettingsFile, const eSensor sensor, const bool bUseViewer = true);

    // Proccess the given stereo frame. Images must be synchronized and rectified.
    // Input images: RGB (CV_8UC3) or grayscale (CV_8U). RGB is converted to grayscale.
    // Returns the camera pose (empty if tracking fails).
    cv::Mat TrackStereo(const cv::Mat &imLeft, const cv::Mat &imRight, const double &timestamp);

    // Process the given rgbd frame. Depthmap must be registered to the RGB frame.
    // Input image: RGB (CV_8UC3) or grayscale (CV_8U). RGB is converted to grayscale.
    // Input depthmap: Float (CV_32F).
    // Returns the camera pose (empty if tracking fails).
    cv::Mat TrackRGBD(const cv::Mat &im, const cv::Mat &depthmap, const double &timestamp);

    // Proccess the given monocular frame
    // Input images: RGB (CV_8UC3) or grayscale (CV_8U). RGB is converted to grayscale.
    // Returns the camera pose (empty if tracking fails).
    cv::Mat TrackMonocular(const cv::Mat &im, const double &timestamp);

    // This stops local mapping thread (map building) and performs only camera tracking.
    void ActivateLocalizationMode();
    // This resumes local mapping thread and performs SLAM again.
    void DeactivateLocalizationMode();

    // Returns true if there have been a big map change (loop closure, global BA)
    // since last call to this function
    bool MapChanged();

    // Reset the system (clear map)
    void Reset();

    // All threads will be requested to finish.
    // It waits until all threads have finished.
    // This function must be called before saving the trajectory.
    void Shutdown();

    // Save camera trajectory in the TUM RGB-D dataset format.
    // Only for stereo and RGB-D. This method does not work for monocular.
    // Call first Shutdown()
    // See format details at: http://vision.in.tum.de/data/datasets/rgbd-dataset
    void SaveTrajectoryTUM(const string &filename);

    // Save keyframe poses in the TUM RGB-D dataset format.
    // This method works for all sensor input.
    // Call first Shutdown()
    // See format details at: http://vision.in.tum.de/data/datasets/rgbd-dataset
    void SaveKeyFrameTrajectoryTUM(const string &filename);

    // Save camera trajectory in the KITTI dataset format.
    // Only for stereo and RGB-D. This method does not work for monocular.
    // Call first Shutdown()
    // See format details at: http://www.cvlibs.net/datasets/kitti/eval_odometry.php
    void SaveTrajectoryKITTI(const string &filename);

    // TODO: Save/Load functions
    // SaveMap(const string &filename);
    // LoadMap(const string &filename);

    // Information from most recent processed frame
    // You can call this right after TrackMonocular (or stereo or RGBD)
    int GetTrackingState();
    std::vector<MapPoint*> GetTrackedMapPoints();
    std::vector<cv::KeyPoint> GetTrackedKeyPointsUn();

private:

    // Input sensor
    eSensor mSensor;

    // ORB vocabulary used for place recognition and feature matching.
    ORBVocabulary* mpVocabulary;

    // KeyFrame database for place recognition (relocalization and loop detection).
    KeyFrameDatabase* mpKeyFrameDatabase;
public:
    // Map structure that stores the pointers to all KeyFrames and MapPoints.
    Map* mpMap;
private:
    // Tracker. It receives a frame and computes the associated camera pose.
    // It also decides when to insert a new keyframe, create some new MapPoints and
    // performs relocalization if tracking fails.
    Tracking* mpTracker;

    // Local Mapper. It manages the local map and performs local bundle adjustment.
    LocalMapping* mpLocalMapper;

    // Loop Closer. It searches loops with every new keyframe. If there is a loop it performs
    // a pose graph optimization and full bundle adjustment (in a new thread) afterwards.
    LoopClosing* mpLoopCloser;

    // The viewer draws the map and the current camera pose. It uses Pangolin.
    Viewer* mpViewer;

    FrameDrawer* mpFrameDrawer;
    MapDrawer* mpMapDrawer;

    // System threads: Local Mapping, Loop Closing, Viewer.
    // The Tracking thread "lives" in the main execution thread that creates the System object.
    std::thread* mptLocalMapping;
    std::thread* mptLoopClosing;
    std::thread* mptViewer;

    // Reset flag
    std::mutex mMutexReset;
    bool mbReset;

    // Change mode flags
    std::mutex mMutexMode;
    bool mbActivateLocalizationMode;
    bool mbDeactivateLocalizationMode;

    // Tracking state
    int mTrackingState;
    std::vector<MapPoint*> mTrackedMapPoints;
    std::vector<cv::KeyPoint> mTrackedKeyPointsUn;
    std::mutex mMutexState;
};

}// namespace ORB_SLAM

#endif // SYSTEM_H