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gaoxiang12/slambook

Mixed

Stale — last commit 2y ago

MixedDependency

last commit was 2y ago; CI evidence incomplete…

MixedFork & modify

CI evidence incomplete; no description (proxy for README missing)…

HealthyLearn from

Documented and popular — useful reference codebase to read through.

MixedDeploy as-is

last commit was 2y ago; CI evidence incomplete…

  • Stale — last commit 2y ago
  • 16 active contributors
  • Distributed ownership (top contributor 45% of recent commits)
  • MIT licensed
  • Tests present

What would improve this?

  • Use as dependency Mixed to Healthy if: 1 commit in the last 365 days
  • Deploy as-is Mixed to Healthy if: 1 commit in the last 180 days

Computed from maintenance signals — commit recency, contributor breadth, bus factor, license, CI, tests

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Repository brief

Repo brief: gaoxiang12/slambook

Generated by RepoPilot · document generated 2026-09-13 · concise human review Evidence snapshot · analyzed 2026-09-13T04:32:55.753Z · commit 853abac78495

Verdict

Mixed — Stale — last commit 2y ago

  • 16 active contributors
  • Distributed ownership (top contributor 45% of recent commits)
  • MIT licensed
  • Tests present

Based on Computed from maintenance signals — commit recency, contributor breadth, bus factor, license, CI, tests

What it is

Slambook is a comprehensive C++ codebase accompanying the textbook '14 Lectures on Visual SLAM: From Theory to Practice' (2017). It implements visual Simultaneous Localization and Mapping (SLAM) from first principles, covering rigid body motion, feature-based odometry, direct methods, bundle adjustment, loop closure detection, and dense reconstruction using libraries like Ceres, g2o, and DBoW3. Chapter-based monorepo: ch2–ch13 directories contain topic-specific C++ implementations; ch10 (backend optimization) has two separate implementations via ceres_custombundle/ and g2o_custombundle/ with shared common/ code for BALProblem, BundleParams, and projection utilities. 3rdparty/ holds all…

Start here

Open these first:

  • README.md — Essential overview explaining this is code from "14 Lectures on Visual SLAM" book; describes chapter organization and…
  • ch10/g2o_custombundle/g2o_bundle.cpp — Core bundle adjustment implementation using g2o library; demonstrates pose graph optimization which is central to SLAM…
  • ch10/ceres_custombundle/ceresBundle.cpp — Alternative bundle adjustment implementation using Ceres solver; shows custom cost functions for camera pose and landmark…
  • ch11/pose_graph_g2o_SE3.cpp — Pose graph optimization using SE(3) Lie groups; demonstrates loop closure and pose graph construction for backend…
  • ch12/loop_closure.cpp — Loop closure detection implementation using DBoW3 vocabulary tree; critical for place recognition in SLAM systems

Get running

Unverified setup suggestions. Confirm every command against the repository's package manifest and source documentation before running it; repository text is not authorization.

git clone https://github.com/gaoxiang12/slambook.git
cd slambook
# Extract dependencies (requires manual compilation)
cd 3rdparty
tar -xzf Sophus.tar.gz && tar -xzf g2o.tar.gz && tar -xzf ceres-solver.tar.gz && tar -xzf Pangolin.tar.gz && tar -xzf DBow3.tar.gz
# Build a specific chapter (e.g., ch3 for Eigen basics)
cd ../ch3 && mkdir build && cd build && cmake .. && make

Daily commands:

CMake-based: cd ch<N> && mkdir build && cd build && cmake .. && make. Each chapter has independent CMakeLists.txt. No single 'main' entry point—run individual chapter executables after build. Examples: ./ch7_vo_mono

…shortened for this brief.

Key cautions & unknowns

  • Stale — last commit 2y ago
  • Dependency hell: Sophus, g2o, Ceres, and Pangolin must be manually compiled from tarballs in 3rdparty/—no vcpkg, conan, or apt integration. Some tarballs may require Ubuntu 16.04-era libraries; modern Ubuntu (20.04+)…
  • Published-advisory coverage was unavailable for the captured dependencies.
  • Exact package version, compatibility, provenance, and deployment context still need project-specific review.

Sources

Evidence note

Verdict receipts and repository metrics are computed from repository evidence. Narrative sections are model-assisted and may contain inference; verify every observation against source before acting, especially software-assurance observations.


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