Using other SLAM

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I tried to use deep learning feature detection method to replace ORB,based on ORB-SLAM3 the modification was done and is tested feasible. I tried to compile OpenREALM using the modified ORB-SLAM3. the compilation process was smooth, including Openrealm and OpenREALM_ROS1_Bridge. unfortunately, no results were produced at the end. I think it's the SLAM used in Openrealm that is replaceable, but from compilation experience, it's usually easier to compile successfully using your RepositoriesSLAM libraries (including ORB-SLAM3 https://github.com/laxnpander/ORB_SLAM3 and OpenVSLAM [https://github.com/laxnpander/openvslam]() ). Is there anything I should be concerned of when using other SLAM libraries?

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https://github.com/laxnpander/OpenREALM/blob/91e1e712ffc3d4c8b8b02b3a951d98a8d7817941/modules/realm_vslam/realm_vslam_base/src/orb_slam.cpp#L8-L144 modify to

OrbSlam::OrbSlam(const VisualSlamSettings::Ptr &vslam_set, const CameraSettings::Ptr &cam_set, const ImuSettings::Ptr &imu_set)
: m_prev_keyid(-1),
  m_slam_setting((*vslam_set)["slam_setting"].toDouble()),
  m_resizing((*vslam_set)["resizing"].toDouble()),
  m_timestamp_reference(0),
  m_path_vocabulary((*vslam_set)["path_vocabulary"].toString())
{
  // Read the settings files

  m_slam = new ORB_SLAM::System(m_path_vocabulary, m_slam_setting, ORB_SLAM::System::MONOCULAR,false);

  //namespace ph = std::placeholders;
  //std::function<void(ORB_SLAM2::KeyFrame*)> kf_update = std::bind(&OrbSlam::keyframeUpdateCb, this, ph::_1);
  //_slam->RegisterKeyTransport(kf_update);
}

OrbSlam::~OrbSlam()
{
  m_slam->Shutdown();
  delete m_slam;
}

VisualSlamIF::State OrbSlam::track(Frame::Ptr &frame, const cv::Mat &T_c2w_initial)
{

  if (m_timestamp_reference == 0)
  {
    //Sophus::SE3f Tse1 = m_slam->TrackMonocular(frame->getImageRaw(), m_timestamp_reference, m_imu_queue);
    m_timestamp_reference = frame->getTimestamp();
    return State::LOST;
  }

  // Set image resizing accoring to settings
  // frame->setImageResizeFactor(m_resizing);

  double timestamp = static_cast<double>(frame->getTimestamp() - m_timestamp_reference)/10e3;
  LOG_IF_F(INFO, true, "Time elapsed since first frame: %4.2f [s]", timestamp);

  // ORB SLAM returns a transformation from the world to the camera frame (T_w2c). In case we provide an initial guess
  // of the current pose, we have to invert this before, because in OpenREALM the standard is defined as T_c2w.

  Sophus::SE3f Tse3 = m_slam->TrackMonocular(frame->getImageRaw(),timestamp);

  int TrackingState = m_slam->GetTrackingState();
  LOG_F(INFO,"TrackState is %u",TrackingState);

  if (!Tse3.rotationMatrix().isApprox(Eigen::Matrix3f::Identity()) || !Tse3.translation().isApprox(Eigen::Vector3f::Zero())){

    cv::Mat T_w2c = SE32Mat(Tse3);
    cv::Mat T_c2w = invertPose(T_w2c);
    T_c2w.convertTo(T_c2w, CV_64F);
    T_c2w.pop_back();
    frame->setVisualPose(T_c2w);

    //std::cout << "Soll:\n" << T_c2w << std::endl;
    //std::cout << "Schätz:\n" << T_c2w_initial << std::endl;

    frame->setSparseCloud(getTrackedMapPoints(), true);

    auto keyid = static_cast<int32_t>(m_slam->GetLastKeyFrameId());
    if (m_prev_keyid == -1)
    {
      m_prev_keyid = keyid;
      return State::INITIALIZED;
    }
     else if (m_prev_keyid != keyid)
    {
      m_prev_keyid = keyid;
      m_orb_to_frame_ids.insert({keyid, frame->getFrameId()});
      return State::KEYFRAME_INSERT;
    }
    else
    {
      return State::FRAME_INSERT;
    }

  }
  return State::LOST;
}

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https://github.com/laxnpander/OpenREALM/blob/91e1e712ffc3d4c8b8b02b3a951d98a8d7817941/modules/realm_vslam/realm_vslam_base/src/orb_slam.cpp#L221 modify to

Eigen::Vector3f wp = mappoints[i]->GetWorldPos();

      cv::Mat p = (cv::Mat_<float>(3, 1) << wp(0), wp(1), wp(2));
      points.push_back(p);