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https://github.com/yashindane/webcube
Rubik's cube assistant on Flask webapp
https://github.com/yashindane/webcube
flask image-processing machine-learning
Last synced: 1 day ago
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Rubik's cube assistant on Flask webapp
- Host: GitHub
- URL: https://github.com/yashindane/webcube
- Owner: YashIndane
- License: apache-2.0
- Created: 2021-06-01T10:31:38.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2024-03-10T16:13:30.000Z (8 months ago)
- Last Synced: 2024-03-10T17:27:19.344Z (8 months ago)
- Topics: flask, image-processing, machine-learning
- Language: Python
- Homepage: https://www.linkedin.com/posts/yash-indane-aa6534179_machinelearning-flask-python-activity-6805902901546901507-dN6M
- Size: 146 KB
- Stars: 56
- Watchers: 3
- Forks: 17
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
  
# webcube
Rubik's cube assistant on Flask webapp. This webapp accepts the six faces of your cube and gives you the voice instructions as a response.
Demo -> [Link](https://www.linkedin.com/posts/yash-indane-aa6534179_machinelearning-flask-python-activity-6805902901546901507-dN6M)
## Requirements
This webapp requires a lot of extra modules and packages to be downloaded, It is recommanded to follow this order :
```
$ yum install python3 -y
$ yum install gcc-c++ -y
$ yum install python3-devel -y
$ pip3 install flask
$ pip3 install Pillow
$ pip3 install numpy
$ pip3 install joblib
$ pip3 install scikit-learn
$ pip3 install scikit-build
$ pip3 install opencv-python
$ yum install opencv opencv-devel opencv-python -y
$ pip3 install kociemba
```
## Usage
Navigate to `http://:/input`.
This webapp runs on port no. `85` by default, but can be changed in the `app.py` file. To use take edge to edge and centred pics of the cube.
Start with `Red` face with the `White` face down, and take pictures in the order `Red -> Green -> Orange -> Blue -> Yellow -> White`. After this click `get solution`. While listening to the instructions
face the `Red` centred face with the `White` centred face down.
## Running the container
```
$ sudo docker run -dit -p :85 --name yashindane/webcube:v1
```
## Running the container using podman
```
$ sudo podman run -dit -p :85 --name docker.io/yashindane/webcube:v1
```
## Arm64v8 machines
```
$ sudo docker run --platform linux/arm64/v8 -dit -p :85 --name yashindane/webcube:linux-arm64v8
```
Code for arm64v8 version -> [link](https://github.com/YashIndane/webcube-arm64v8)
## Working
The six images of six faces have there respective `data_uri`, which are submitted by a form when you click `get solution`. This `data_uri` are converted to images and saved.
Next the function `order` from `order_image.py` renames and creates new images (format example face_0.png to face_5.png), according to images that have central tile colour matching in the order `yellow -> green -> red -> white -> blue -> orange`. Naming images in this order is required for the cube to be solved. A cubestring is formed after predicting the tile colours and getting there respective notations.
```py
colour_mappings = {
"red": "F",
"green": "R",
"blue": "L",
"yellow": "U",
"white": "D",
"orange": "B"
}
```
The cubestring is passed to the `kociemba.solve()` function, which return a string containing instructions for solving the cube.
Kociemba is a Python/C implementation of Herbert Kociemba's Two-Phase algorithm for solving Rubik's Cube.
Read full documentation of Kociemba here -> [Link](https://pypi.org/project/kociemba/)
the instructions are decoded to human voice instructions. This instructions are then written to the `output.js` file, which outputs this instructions as voice.
## Building docker image
build docker image by ->
`$ docker build -t /:`
I have also uploded already build image for this webapp on Docker Hub -> [Link](https://hub.docker.com/repository/docker/yashindane/webcube)
## deploying the image in Kubernetes
create a deployment by ->
`$ kubectl create deployment --image /: `
Scale the deployment if necessary and create a service by ->
`$ kubectl expose deployment --port=85 --name= --type=LoadBalancer`
## Prerequisite browser settings
### 1. Remove chrome managed by your organisation (Optional)
Visit this link -> [link](https://www.youtube.com/watch?v=DaLaWChdyug)
### 2. Edit chrome flags for camera access
Navigate to `chrome://flags/#unsafely-treat-insecure-origin-as-secure` on chrome browser and add `http://:` inside `Insecure origins treated as secure box` and click enable and reload the chrome page.
After usage just remove the entry and click disable.