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本博客以单目的形式学习代码。 以下为ORB-SLAM2源码的Examples文件夹下的Monocular的mono_tum.cc源代码及注释：

/** * 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> #include<unistd.h> using namespace std;   void LoadImages(const string &strFile, vector<string> &vstrImageFilenames,                 vector<double> &vTimestamps);  int main(int argc, char **argv)// 这是主函数 { 
             if(argc != 4)     { 
                 cerr << endl << "Usage: ./mono_tum path_to_vocabulary path_to_setting 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);
// 此处重点讲解system函数，在这段代码下面第二章
    // 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);
    }

    // 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;
}

/** * @brief 导入图片 * * @param[in] strFile 读入的文件名称 * @param[in&out] vstrImageFilenames 彩色图片名称 * @param[in&out] vTimestamps 记录时间戳 */
void LoadImages(const string &strFile, vector<string> &vstrImageFilenames, vector<double> &vTimestamps)
{ 
        
    ifstream f;
    f.open(strFile.c_str());

    // skip first three lines
    // 前三行是注释，跳过
    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);
        }
    }
}

control+system进入include文件夹下的system.h文件 代码注释如下：

control+system进入src文件夹下的system.cc文件 代码注释如下：

//系统的构造函数，将会启动其他的线程
System::System(const string &strVocFile,					//词典文件路径
			   const string &strSettingsFile,				//配置文件路径
			   const eSensor sensor,						//传感器类型
               const bool bUseViewer):						//是否使用可视化界面
					 mSensor(sensor), 							//初始化传感器类型
					 mpViewer(static_cast<Viewer*>(NULL)),		//空。。。对象指针？ TODO 
					 mbReset(false),							//无复位标志
					 mbActivateLocalizationMode(false),			//没有这个模式转换标志
        			 mbDeactivateLocalizationMode(false)		//没有这个模式转换标志
{ 
        
    // Output welcome message
    cout << endl <<
    "ORB-SLAM2 Copyright (C) 2014-2016 Raul Mur-Artal, University of Zaragoza." << endl <<
    "This program comes with ABSOLUTELY NO WARRANTY;" << endl  <<
    "This is free software, and you are welcome to redistribute it" << endl <<
    "under certain conditions. See LICENSE.txt." << endl << endl;

    // 输出当前传感器类型
    cout << "Input sensor was set to: ";

    if(mSensor==MONOCULAR)
        cout << "Monocular" << endl;
    else if(mSensor==STEREO)
        cout << "Stereo" << endl;
    else if(mSensor==RGBD)
        cout << "RGB-D" << endl;

    //Check settings file
    cv::FileStorage fsSettings(strSettingsFile.c_str(), 	//将配置文件名转换成为字符串
    						   cv::FileStorage::READ);		//只读
    //如果打开失败，就输出调试信息
    if(!fsSettings.isOpened())
    { 
        
       cerr << "Failed to open settings file at: " << strSettingsFile << endl;
       //然后退出
       exit(-1);
    }
        //Load ORB Vocabulary
    cout << endl << "Loading ORB Vocabulary. This could take a while..." << endl;

    //建立一个新的ORB字典
    mpVocabulary = new ORBVocabulary();
    //获取字典加载状态
    bool bVocLoad = mpVocabulary->loadFromTextFile(strVocFile);
    //如果加载失败，就输出调试信息
    if(!bVocLoad)
    { 
        
        cerr << "Wrong path to vocabulary. " << endl;
        cerr << "Falied to open at: " << strVocFile << endl;
        //然后退出
        exit(-1);
    }
    //否则则说明加载成功
    cout << "Vocabulary loaded!" << endl << endl;

    //Create KeyFrame Database
    mpKeyFrameDatabase = new KeyFrameDatabase(*mpVocabulary);

    //Create the Map
    mpMap = new Map();

    //Create Drawers. These are used by the Viewer
    //这里的帧绘制器和地图绘制器将会被可视化的Viewer所使用
    mpFrameDrawer = new FrameDrawer(mpMap);
    mpMapDrawer = new MapDrawer(mpMap, strSettingsFile);

    //在本主进程中初始化追踪线程
    //Initialize the Tracking thread
    //(it will live in the main thread of execution, the one that called this constructor)
    mpTracker = new Tracking(this,						//现在还不是很明白为什么这里还需要一个this指针 TODO 
    						 mpVocabulary,				//字典
    						 mpFrameDrawer, 			//帧绘制器
    						 mpMapDrawer,				//地图绘制器
                             mpMap, 					//地图
                             mpKeyFrameDatabase, 		//关键帧地图
                             strSettingsFile, 			//设置文件路径
                             mSensor);					//传感器类型iomanip

下一章，重点讲上面这个Tracking函数，这是整个orb-slam2最重要的地方，包括ORBextractor函数提取特征点，下面第三章重点讲解。

control+Tracking进入src文件夹下的Tracking.cc文件 代码注释如下：