orb slam 2 代码解析2

orb slam 2 代码解析2

接上文，我们分析system的函数和起实现，我们会一个一个函数去分析实现,我们仍旧会精简其中不重要的部分，例如打印信息，错误处理等 如果需要了解详细代码实现，请看源代码。

System::System(const string &strVocFile, const string &strSettingsFile, const eSensor sensor,
               const bool bUseViewer):mSensor(sensor), mpViewer(static_cast<Viewer*>(NULL)), mbReset(false),mbActivateLocalizationMode(false),
        mbDeactivateLocalizationMode(false)
{

    cv::FileStorage fsSettings(strSettingsFile.c_str(), cv::FileStorage::READ); //读取配置文件，省略读取失败处理

    mpVocabulary = new ORBVocabulary(); // 读取词袋模型，省略读取错误处理
    bool bVocLoad = mpVocabulary->loadFromTextFile(strVocFile);

    mpKeyFrameDatabase = new KeyFrameDatabase(*mpVocabulary); //关键帧数据

    mpMap = new Map(); //创建地图

    //Create Drawers. These are used by the Viewer
    mpFrameDrawer = new FrameDrawer(mpMap); // 创建绘制地图类
    mpMapDrawer = new MapDrawer(mpMap, strSettingsFile); //地图绘制类，根据设置文件

    mpTracker = new Tracking(this, mpVocabulary, mpFrameDrawer, mpMapDrawer,
                             mpMap, mpKeyFrameDatabase, strSettingsFile, mSensor); //跟踪类及其线程创建 主线程执行

    mpLocalMapper = new LocalMapping(mpMap, mSensor==MONOCULAR); //局部地图构建类
    mptLocalMapping = new thread(&ORB_SLAM2::LocalMapping::Run,mpLocalMapper); //开启执行线程
    
    //初始化回环检测线程并执行

    mpLoopCloser = new LoopClosing(mpMap, mpKeyFrameDatabase, mpVocabulary, mSensor!=MONOCULAR);
    mptLoopClosing = new thread(&ORB_SLAM2::LoopClosing::Run, mpLoopCloser);

    //初始化交互展示线程并运行
    if(bUseViewer)
    {
        mpViewer = new Viewer(this, mpFrameDrawer,mpMapDrawer,mpTracker,strSettingsFile);
        mptViewer = new thread(&Viewer::Run, mpViewer);
        mpTracker->SetViewer(mpViewer); //给Tracker设置viewer目前看并没有用处，viewer主要用于显示map相关内容
    }
    //设置各个线程的数据指针
    mpTracker->SetLocalMapper(mpLocalMapper);
    mpTracker->SetLoopClosing(mpLoopCloser);
    mpLocalMapper->SetTracker(mpTracker);
    mpLocalMapper->SetLoopCloser(mpLoopCloser);

    mpLoopCloser->SetTracker(mpTracker);
    mpLoopCloser->SetLocalMapper(mpLocalMapper);
}

通过分析，可以看到，system作为整个库的管理类，承担的职责是完成整体的创建和管理工作，此类并不涉及具体算法实现。

下面是三个函数

    // 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); 
    //英文注释写的简明易懂，就留着吧

这三个函数适用于不同硬件，我们首先看下单目的实现代码

cv::Mat System::TrackMonocular(const cv::Mat &im, const double &timestamp)
{

    // Check mode change
    {
        unique_lock<mutex> lock(mMutexMode); //资源锁，等待资源就绪
        if(mbActivateLocalizationMode)
        {
            mpLocalMapper->RequestStop();

            // Wait until Local Mapping has effectively stopped
            while(!mpLocalMapper->isStopped())
            {
                usleep(1000);
            }

            mpTracker->InformOnlyTracking(true);
            mbActivateLocalizationMode = false;
        }
        if(mbDeactivateLocalizationMode)
        {
            mpTracker->InformOnlyTracking(false);
            mpLocalMapper->Release();
            mbDeactivateLocalizationMode = false;
        }
    }

    cv::Mat Tcw = mpTracker->GrabImageMonocular(im,timestamp); //主要实现跟踪函数，我们需要着重分析的函数实现

    unique_lock<mutex> lock2(mMutexState);
    mTrackingState = mpTracker->mState;
    mTrackedMapPoints = mpTracker->mCurrentFrame.mvpMapPoints;
    mTrackedKeyPointsUn = mpTracker->mCurrentFrame.mvKeysUn;

    return Tcw;
}

经过前两篇，我们能看到orbslam主流程，后续在第三篇我们将进入主要实现分析