This repository is an educational tutorial implementation of a stereo visual SLAM (Simultaneous Localization and Mapping) system, based on the classic feature-point method (ORB/GFTT) with optical flow tracking, PnP pose estimation, and local bundle adjustment using g2o. It is structured as a modular C++ library (libmyslam.so) with components for frontend, backend, map management, camera model, dataset reading, and Pangolin-based 3D visualization. The primary entry point is a CLI application that processes KITTI stereo sequences to estimate camera trajectory and sparse 3D map points. While the code demonstrates solid software engineering practices such as threading, singletons, and factory methods, it is not production-ready: it lacks loop closure, map persistence, and comprehensive testing. The repository serves as a hands-on companion to the 'Visual SLAM: From Theory to Practice' textbook, with documentation and chapter-wise code examples. External dependencies include OpenCV, Eigen, Sophus, g2o, Pangolin, and Glog, with version-specific requirements that may cause compatibility issues on modern systems.