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
Page to PAGE Layout Analysis Tool

P2PaLA Page to PAGE Layout Analysis (P2PaLA) is a toolkit for Document Layout Analysis based on Neural Networks. 💥 Try our new DEMO for online baseli

Lorenzo Quirós Díaz 180 Nov 24, 2022
TextBoxes: A Fast Text Detector with a Single Deep Neural Network https://github.com/MhLiao/TextBoxes 基于SSD改进的文本检测算法,textBoxes_note记录了之前整理的笔记。

TextBoxes: A Fast Text Detector with a Single Deep Neural Network Introduction This paper presents an end-to-end trainable fast scene text detector, n

zhangjing1 24 Apr 28, 2022
Fast image augmentation library and easy to use wrapper around other libraries. Documentation: https://albumentations.ai/docs/ Paper about library: https://www.mdpi.com/2078-2489/11/2/125

Albumentations Albumentations is a Python library for image augmentation. Image augmentation is used in deep learning and computer vision tasks to inc

11.4k Jan 02, 2023
Creating a virtual tv using opencv in python3.

Virtual-TV Creating a virtual tv using opencv in python3. In order to run the code follow the below given steps: Make sure the desired videos which ar

Vamsi 1 Jan 01, 2022
Source Code for AAAI 2022 paper "Graph Convolutional Networks with Dual Message Passing for Subgraph Isomorphism Counting and Matching"

Graph Convolutional Networks with Dual Message Passing for Subgraph Isomorphism Counting and Matching This repository is an official implementation of

HKUST-KnowComp 13 Sep 08, 2022
Sign Language Recognition service utilizing a deep learning model with Long Short-Term Memory to perform sign language recognition.

Sign Language Recognition Service This is a Sign Language Recognition service utilizing a deep learning model with Long Short-Term Memory to perform s

Martin Lønne 1 Jan 08, 2022
Tracking the latest progress in Scene Text Detection and Recognition: Must-read papers well organized

SceneTextPapers Tracking the latest progress in Scene Text Detection and Recognition: must-read papers well organized Information about this repositor

Shangbang Long 763 Jan 01, 2023
A community-supported supercharged version of paperless: scan, index and archive all your physical documents

Paperless-ngx Paperless-ngx is a document management system that transforms your physical documents into a searchable online archive so you can keep,

5.2k Jan 04, 2023
Code for CVPR 2022 paper "Bailando: 3D dance generation via Actor-Critic GPT with Choreographic Memory"

Bailando Code for CVPR 2022 (oral) paper "Bailando: 3D dance generation via Actor-Critic GPT with Choreographic Memory" [Paper] | [Project Page] | [Vi

Li Siyao 237 Dec 29, 2022
This is the official PyTorch implementation of the paper "TransFG: A Transformer Architecture for Fine-grained Recognition" (Ju He, Jie-Neng Chen, Shuai Liu, Adam Kortylewski, Cheng Yang, Yutong Bai, Changhu Wang, Alan Yuille).

TransFG: A Transformer Architecture for Fine-grained Recognition Official PyTorch code for the paper: TransFG: A Transformer Architecture for Fine-gra

Ju He 307 Jan 03, 2023
Let's explore how we can extract text from forms

Form Segmentation Let's explore how we can extract text from any forms / scanned pages. Objectives The goal is to find an algorithm that can extract t

Philip Doxakis 42 Jun 05, 2022
graph learning code for ogb

The final code for OGB Installation Requirements: ogb=1.3.1 torch=1.7.0 torch-geometric=1.7.0 torch-scatter=2.0.6 torch-sparse=0.6.9 Baseline models T

PierreHao 20 Nov 10, 2022
keras复现场景文本检测网络CPTN: 《Detecting Text in Natural Image with Connectionist Text Proposal Network》;欢迎试用,关注,并反馈问题...

keras-ctpn [TOC] 说明 预测 训练 例子 4.1 ICDAR2015 4.1.1 带侧边细化 4.1.2 不带带侧边细化 4.1.3 做数据增广-水平翻转 4.2 ICDAR2017 4.3 其它数据集 toDoList 总结 说明 本工程是keras实现的CPTN: Detecti

mick.yi 107 Jan 09, 2023
A simple component to display annotated text in Streamlit apps.

Annotated Text Component for Streamlit A simple component to display annotated text in Streamlit apps. For example: Installation First install Streaml

Thiago Teixeira 312 Dec 30, 2022
Document Image Dewarping

Document image dewarping using text-lines and line Segments Abstract Conventional text-line based document dewarping methods have problems when handli

Taeho Kil 268 Dec 23, 2022
~1000 book pages + OpenCV + python = page regions identified as paragraphs, lines, images, captions, etc.

cosc428-structor I had an open-ended Computer Vision assignment to complete, and an out-of-copyright book that I wanted to turn into an ebook. Convent

Chad Oliver 45 Dec 06, 2022
Lightning Fast Language Prediction 🚀

whatthelang Lightning Fast Language Prediction 🚀 Dependencies The dependencies can be installed using the requirements.txt file: $ pip install -r req

Indix 152 Oct 16, 2022
Polaris is a Face recognition attendance system .

Support Me 🚀 About Polaris 📄 Polaris is a system based on facial recognition with a futuristic GUI design, Can easily find people informations store

XN3UR0N 215 Dec 26, 2022
An Agnostic Computer Vision Framework - Pluggable to any Training Library: Fastai, Pytorch-Lightning with more to come

An Agnostic Object Detection Framework IceVision is the first agnostic computer vision framework to offer a curated collection with hundreds of high-q

airctic 790 Jan 05, 2023