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Maze_solver provides a relatively quick computer vision solution to most mazes.

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CV Maze Solver

Maze_solver provides a relatively quick computer vision solution to most mazes.

Maze3

How it works

Maze_solver reads in images of mazes, performs thresholding and thinning, and then converts the remaining "on" pixels to a network. A simple keyboard UI allows the user to update the starting and ending points. The maze is solved using a simple dijkstra algorithm.

Installation

python -m venv venv
pip install -r requirements.in
source venv/bin/activate

Usage

src/maze_solver.py
Key Result
s Move starting point left
f Move starting point right
e Move starting point up
d Move starting point down
j Move ending point left
l Move ending point right
i Move ending point up
k Move ending point down
space Accept start and end points and solve.
escape Exit

Maze3

Todo

The next steps in this project are to

  • Add a CLI to allow user to run on their own mazes
  • Save the name of the file and the starting and ending points in a cache file.
  • Allow the user to use a camera instead of an image.
  • Allow the user to use the mouse to specify starting and ending positions
  • Allow the user to display thinned image
  • Handle color mazes - thresholding and thinning

Contributing

Any contributions you make are greatly appreciated.

  1. Fork the Project
  2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
  3. Commit your Changes (git commit -m 'Add some AmazingFeature')
  4. Push to the Branch (git push origin feature/AmazingFeature)
  5. Open a Pull Request

Written by

John Lee Cooper
[email protected]

Reference

ref

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Maze_solver provides a relatively quick computer vision solution to most mazes.

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