# mikepound/mazesolving

A variety of algorithms to solve mazes from an input image

Repository: https://github.com/mikepound/mazesolving
Canonical: https://ross.abutalabs.com/products/mazesolving
Language: Python
License: Unlicense
License Family: permissive
Last push: 2022-10-25T06:21:07+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3489, "days_push": 1408, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1747, forks 399 (observed 2026-08-28T04:05:30.787530+00:00)

## What it is
A collection of Python algorithms that solve mazes from input images, created as a companion to a Computerphile video. It supports multiple pathfinding approaches including breadth-first search, Dijkstra, and A* on black-and-white maze images.

## Use cases
- solve a maze from a png image
- compare pathfinding algorithms like bfs dijkstra and a-star
- learn how maze solving algorithms work
- find the shortest path through a maze image
- educational demo of graph search on images
- process large maze images with low memory usage

## When to choose
- you want to learn or teach classic pathfinding algorithms with visual maze examples
- you need a simple script to solve black-and-white maze images
- you want reference code from a well-known educational video

## When to avoid
- you need a production-grade or actively maintained maze solver
- your mazes have large open white areas or non-standard formats
- you need high performance on very large mazes with limited RAM

## Facets
- artifact type: library
- maturity: maintenance
- function: image-processing, search-engine, developer-tools
- domain: computer-vision, education, developer-tools
- platform: python, cross-platform
- tags: maze-solving, pathfinding, computerphile, graph-algorithms, breadth-first-search, dijkstra, a-star, algorithms

## Member repositories
- mikepound/mazesolving (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:30.787530+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 2026-08-30T03:29:03.150853+00:00, confidence not recorded.
  - readme: https://github.com/mikepound/mazesolving (fetched 2026-08-28T04:05:30.787530+00:00, sha 2a606f536612)
- Data as of 2026-08-30T08:39:29.467469+00:00.