Python rubik's cube solver

Overview

py-rubik_solver

Python solver for a rubik's cube

This program makes a 3D representation of a rubiks cube and solves it step by step.

solving the cube image

Usage

To use this program you need to execute the following commands

  • For 3D visualizations:

    python visualizer.py

  • For statistics:

    python stats.py

Requirements

To use this program you need to install python 3.8.10 or later (although it will probably work on python 3.7) You will also need a recent version of numpy and vpython 7 or later, those can be installed with:

pip install numpy vpython

Implementation

This project is separated in different files, each implementing a different functionality. The content and functionality of each of these files is the following:

configs.py

This file contains general configuration parameters mostly related to the visual representation of the cube:

  • The default colors
  • The number of fps
  • The time taken to reproduce each move
  • Time to wait between moves
  • Speed factor

cube.py

This file contains the Cube class, which implements a data structure for storing the pieces of the cube and some functions for rotating the faces of the cube. It also implements the possibility to shuffle the cube on creation and the possibility of recording a list of moves made in the cube, this is used for generating a solution.

The main functions implemented in this class are:

  • move(move, n=1, record=True): where move should be a string representing the face to move and n is the number of 90 degree rotations to perform (2 is half turn and 3 or -1 is a turn to the other side). The codes used for the move are:

    • "U", "F", "R", "B", "L", "D" for individual faces.
    • "UD", "FB", "RL" for the middle faces.
    • "UU", "FF", "RR" for rotations of the whole cube along this axis.
  • rotate(axis, n=1): this has the same effect as using move with "UU", "FF", "RR" but these moves are never recorded.

  • is_solved(): checks whether the cube equals the solved cube. Keep in mind that this function will return False even if the cube is solved but faces a different way.

  • copy(): creates a deep_copy of the cube. The copy is completely independent of the original cube.

cube_3d.py

This file implements the Cube3D class, which directly inherits from the Cube class. This class overrides the __init__ and move functions to first create all the cubes necessary to represent the rubiks cube in 3D and then animate them each time any face is moved.

cube_solver.py

This file implements the CubeSolver class, which acts as an abstract class for all the other solving algorithms. It only takes care of taking some measures for statistics.

simple_solver.py

This is the first solving algorithm implemented, it's the usual beginer algorithm for anyone learning how to solve the rubiks cube. It's implemented on a really naive way, and it's far from optimal in terms of the number of steps of the solution. It was just a proof of concept and my goal is to implement a better, more efficient version of this class in the future.

In my personal computer this algorithm takes 1.78 ms on average to compute a solution, and the solutions have 205.6 steps on average. Again these results are far from good, but this was just a proof of concept.

The process of the algorithm is separated in different steps, which are:

  • solve_first_cross: solves the cross on the UP face
  • solve_first_corners: solves the corners on the UP face
  • solve_second_row: solves the second "crown" or the second row
  • solve_second_cross: creates a cross on the DOWN face
  • orientate_2nd_cross: positions correctly the pieces inside the cross on the DOWN face
  • solve_second_corners: positions correctly the corners in the DOWN face
  • orientate_2nd_corners: rotates correctly the corners in the DOWN face
  • reorient_cube: rotates the whole cube so that the UP face is facing up and the FRONT face if facing front

stats.py

This file is used to compute some statistics of the cube solutions. At this point this file is used to compute:

  • The average time taken to generate a solution
  • The average number of steps of the generated solutions
  • Some data of the solving process

Keep in mind the data computed will probably change in the future.

util.py

In this file we store different lists and dictionaries used in the project such as a solved cube structure, a list of the directions, a function for generating random moves, ...

visualizer.py

This file is used to launch a 3D representation of the solving process of the cube. It also contains a function to check the progress of the solving algorithm.

Notes

In the future I'm planing to make more solving algorithms as well as an implementation for a physical robot that solves a given cube.

Use this code as you wish, just let me know if you do, I'll love to hear what you are up to!

If you have any doubts/comments/suggestions/anything please let my know via email at [email protected] or at the email in my profile.

Owner
Pablo QB
I'm a student of the double degree on Computer Engineering and Mathematics at UAM university. Here I upload some of my personal proyects just for fun.
Pablo QB
Isearch (OSINT) 🔎 Face recognition reverse image search on Instagram profile feed photos.

isearch is an OSINT tool on Instagram. Offers a face recognition reverse image search on Instagram profile feed photos.

Malek salem 20 Oct 25, 2022
STEFANN: Scene Text Editor using Font Adaptive Neural Network

STEFANN: Scene Text Editor using Font Adaptive Neural Network @ The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2020.

Prasun Roy 208 Dec 11, 2022
Implementation of EAST scene text detector in Keras

EAST: An Efficient and Accurate Scene Text Detector This is a Keras implementation of EAST based on a Tensorflow implementation made by argman. The or

Jan Zdenek 208 Nov 15, 2022
Table recognition inside douments using neural networks

TableTrainNet A simple project for training and testing table recognition in documents. This project was developed to make a neural network which reco

Giovanni Cavallin 93 Jul 24, 2022
A general list of resources to image text localization and recognition 场景文本位置感知与识别的论文资源与实现合集 シーンテキストの位置認識と識別のための論文リソースの要約

Scene Text Localization & Recognition Resources Read this institute-wise: English, 简体中文. Read this year-wise: English, 简体中文. Tags: [STL] (Scene Text L

Karl Lok (Zhaokai Luo) 901 Dec 11, 2022
Text to QR-CODE

QR CODE GENERATO USING PYTHON Author : RAFIK BOUDALIA. Installation Use the package manager pip to install foobar. pip install pyqrcode Usage from tki

Rafik Boudalia 2 Oct 13, 2021
Automatically fishes for you while you are afk :)

Dank-memer-afk-script A simple and quick way to make easy money in Dank Memer! How to use Open a discord channel which has the Dank Memer bot enabled.

Pranav Doshi 9 Nov 11, 2022
Deskew is a command line tool for deskewing scanned text documents. It uses Hough transform to detect "text lines" in the image. As an output, you get an image rotated so that the lines are horizontal.

Deskew by Marek Mauder https://galfar.vevb.net/deskew https://github.com/galfar/deskew v1.30 2019-06-07 Overview Deskew is a command line tool for des

Marek Mauder 127 Dec 03, 2022
Programa que viabiliza a OCR (Optical Character Reading - leitura óptica de caracteres) de um PDF.

Este programa tem o intuito de ser um modificador de arquivos PDF. Os arquivos PDFs podem ser 3: PDFs verdadeiros - em que podem ser selecionados o ti

Daniel Soares Saldanha 2 Oct 11, 2021
Repository of conference publications and source code for first-/ second-authored papers published at NeurIPS, ICML, and ICLR.

Repository of conference publications and source code for first-/ second-authored papers published at NeurIPS, ICML, and ICLR.

Daniel Jarrett 26 Jun 17, 2021
The code for “Oriented RepPoints for Aerail Object Detection”

Oriented RepPoints for Aerial Object Detection The code for the implementation of “Oriented RepPoints”, Under review. (arXiv preprint) Introduction Or

WentongLi 207 Dec 24, 2022
computer vision, image processing and machine learning on the web browser or node.

Image processing and Machine learning labs   computer vision, image processing and machine learning on the web browser or node note Fast Fourier Trans

ryohei tanaka 487 Nov 11, 2022
A dataset handling library for computer vision datasets in LOST-fromat

A dataset handling library for computer vision datasets in LOST-fromat

8 Dec 15, 2022
Line based ATR Engine based on OCRopy

OCR Engine based on OCRopy and Kraken using python3. It is designed to both be easy to use from the command line but also be modular to be integrated

948 Dec 23, 2022
Generate text images for training deep learning ocr model

New version release:https://github.com/oh-my-ocr/text_renderer Text Renderer Generate text images for training deep learning OCR model (e.g. CRNN). Su

Qing 1.2k Jan 04, 2023
Image processing using OpenCv

Image processing using OpenCv Write a program that opens the webcam, and the user selects one of the following on the video: ✅ If the user presses the

M.Najafi 4 Feb 18, 2022
Read Japanese manga inside browser with selectable text.

mokuro Read Japanese manga with selectable text inside a browser. See demo: https://kha-white.github.io/manga-demo mokuro_demo.mp4 Demo contains excer

Maciej Budyś 170 Dec 27, 2022
Code for generating synthetic text images as described in "Synthetic Data for Text Localisation in Natural Images", Ankush Gupta, Andrea Vedaldi, Andrew Zisserman, CVPR 2016.

SynthText Code for generating synthetic text images as described in "Synthetic Data for Text Localisation in Natural Images", Ankush Gupta, Andrea Ved

Ankush Gupta 1.8k Dec 28, 2022
This is a GUI for scrapping PDFs with the help of optical character recognition making easier than ever to scrape PDFs.

pdf-scraper-with-ocr With this tool I am aiming to facilitate the work of those who need to scrape PDFs either by hand or using tools that doesn't imp

Jacobo José Guijarro Villalba 75 Oct 21, 2022
Code for the ACL2021 paper "Combining Static Word Embedding and Contextual Representations for Bilingual Lexicon Induction"

CSCBLI Code for our ACL Findings 2021 paper, "Combining Static Word Embedding and Contextual Representations for Bilingual Lexicon Induction". Require

Jinpeng Zhang 12 Oct 08, 2022