Skip to content

mkdirer/AiPO_project

 
 

Repository files navigation

Authors

  • Dominik Dziuba - general idea and implementation of the algorithm
  • Przemysław Rodzik - GUI, implementation of Dijkstra pathfinding algorithm
  • Łukasz Wajda - GUI
  • Mateusz Niepokój - test image generation
  • Mariusz Biegański - creating windows and linux release
  • Szymon Pawelec - documentation

How to run

Go to our Release page and select the most suitable option for your system. You can find them under this link. Both the releases are created for python version 3.11 as well as the script itself has been tested with that version in mind. Older versions might also work but that has not been tested.

Linux

Download *.tar.gz from Releases and run e.g. for newest linux 64 bit release

tar -xzf aipo_project_linux_64_v.1.0.0.tar.gz 
./aipo_project/main

Windows

Download *.zip from Releases for your platform and unzip the folder, open aipo_project_windows folder, find main.exe and double click it to start the application.

Python

If all else fails on a python-supported platform you can also simply download the interpreter and then the source code for the project. Run the following line to install necessary dependencies:

pip install -r requirements.txt

In the folder you have unpacked the source code in. And then simply launch the program like so:

python main.py

It is necessary that during the installation of the python interpreter, the tcl/tk additional package is also installed.

How to use

  1. Select an image
  2. Change Minimum Pixel Weight(Optional)
  3. Change Step Value(Optional)
  4. Chose Path Color(Optional)
  5. Change Custom Error(Optional)
  6. Change Filter Size (Optional)
  7. Change Path Width(Optional)
  8. Select to points on the image you selected
  9. Click Find Path and wait, the path will appear on the image, additionally you will get a popup window with path cost and average cost per pixel

About

A desktop app with GUI to find the shortest path between selected points on a map using tkinter, numpy, cv2, heapq, numba, and PIL

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Python 100.0%