# cvg/Hierarchical-Localization

Visual localization made easy with hloc

Repository: https://github.com/cvg/Hierarchical-Localization
Canonical: https://ross.abutalabs.com/products/hierarchical-localization
Language: Python
License: Apache-2.0
License Family: permissive
Topics: deep-learning, visual-localization, feature-matching, image-retrieval, structure-from-motion, pose-estimation, superglue
Last push: 2025-12-10T10:00:19+00:00

## Health v2 (maintenance only)
Score: 48/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 56, release rhythm 8, longevity 100
- inputs: {"age_days": 2239, "days_push": 266, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 4194, forks 768 (observed 2026-08-28T04:08:38.851591+00:00)

## What it is
hloc is a modular Python toolbox for state-of-the-art 6-DoF visual localization, combining image retrieval and feature matching (SuperPoint, SuperGlue, LightGlue, DISK) with Structure-from-Motion. It lets researchers and engineers build 3D maps, localize query images, and benchmark custom features on indoor and outdoor datasets.

## Use cases
- estimate camera pose from a single image against a 3D map
- run structure-from-motion with SuperPoint and SuperGlue on my own photos
- benchmark my custom local features for visual localization
- localize images captured by a robot or AR device
- reproduce state-of-the-art results on visual localization benchmarks
- build a 3D reconstruction from an image collection

## When to choose
- you need accurate 6-DoF camera pose estimation with deep-learned features
- you want a modular pipeline to swap in different feature extractors and matchers
- you need SfM reconstruction plus localization in one toolbox

## When to avoid
- you need real-time SLAM rather than offline localization against a reference model
- you want a turnkey end-user application rather than a research toolbox
- your project has no GPU and cannot use COLMAP dependencies

## Facets
- artifact type: library
- maturity: active
- function: computer-vision, image-processing, machine-learning, deep-learning
- domain: computer-vision, machine-learning, robotics
- platform: python, windows
- tags: visual-localization, feature-matching, structure-from-motion, pose-estimation, superpoint, superglue, lightglue, image-retrieval, 6dof, colmap, algorithms, gpu, docker, linux, macos

## Member repositories
- cvg/Hierarchical-Localization (main) score 48

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:38.851591+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T18:22:35.106369+00:00, confidence not recorded.
  - readme: https://github.com/cvg/Hierarchical-Localization (fetched 2026-08-28T04:08:38.851591+00:00, sha 4add286c42ec)
- Data as of 2026-08-30T08:39:29.467469+00:00.