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sudoku-solver

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Smart solution to solve sudoku in VR

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# sudoku-solver
Hi, my name is Rémi LUX. Currently engineer at Niryo, I code this sudoku solver during
my free time.
My algorithm is able to detect and to directly solve sudokus in VR as shown on the video
below

## The Application

The Application is based on [KivyMD][KivyMD repo]. It currently has 2 screens :
- One for Live Solving which allows you to chose between full solving and hint mode
- One which Solve image from gallery

| Live Solving | Gallery Solving  |
:-------------------------:|:-------------------------:
![Live Solving](https://raw.githubusercontent.com/remi2257/sudoku-solver/master/readme_images/live_solver_screen.png) | ![Gallery Solving](https://raw.githubusercontent.com/remi2257/sudoku-solver/master/readme_images/galery_solver_screen.png)

## How is it working ?
For a single image process, my algorithm is using working as following :
### Grids  Extraction
Firstly, the algorithm have to find where the grids are !  
The pipeline is :
1. Preprocess image to enhance high frequencies
2. Find lines thanks to Hough Space
3. Analyse lines to know which can correspond to a grid

### Digits Identification & Grids Solving
Once grids are extracted, for each grid we do :

* Detect shape which can be digits
* Use my CNN do identify digits
* Create a numeric grid in a table & solve it

### Grids Reconstruction
* Create a virtual image to fill the initial image
* Add the 2 images together to create the final result

### Video Case
When user chose to use video as input, the algorithm will
act quite differently :
- For grids extraction, we use position of last grids to deduce
if 2 grids in 2 pictures are actually the same
- For grids solving, we wait to have meet the same extracted numeric
grid twice, to be confident on digits extraction
- It do not resolve a grid if it a grid is detected as same
as an already solved grid

## How to use ?

### Dependencies
You will need some libraries before running it  
- Numpy
- OpenCV 
- Tensorflow
- KivyMD >= 1.11.1 (as this version isn't publish on Pypi yet, 
you should install it form the [KivyMD repo])

### Run the program
The best way to use my algorithm is to firstly clone the git
repo where you want to.
Then, open a terminal & go in the repository  
`cd /path/to/the/repo/`

Then, simply use the command

`python3 kivy_md.py`

## Evolution, TODO list, Q&A, ...
### Evolution of the Algorithm
#### Application
| Version | Visu  |
:-------------------------:|:-------------------------:
2.0 | ![Application](https://raw.githubusercontent.com/remi2257/sudoku-solver/master/readme_images/live_solver_screen.png)

#### Python Script
| Version | Source | Algorithm Output |
:-------------------------:|:-------------------------:|:-------------------------:
1.5 | Video | <img src="https://user-images.githubusercontent.com/39727257/57652501-0213a500-75d0-11e9-9f14-2a3bada71923.gif" width="400"/>
1.3 | <img src="https://user-images.githubusercontent.com/39727257/57191967-b146e100-6f2b-11e9-993d-3f6e8dc8e246.jpg" width="400"/> | <img src="https://user-images.githubusercontent.com/39727257/57191964-aa1fd300-6f2b-11e9-8a3e-9403b851b2dd.jpg" width="400"/>
1.2 | <img src="https://user-images.githubusercontent.com/39727257/57106087-d5889f00-6d2c-11e9-805f-350233fed9bc.jpg" width="400"/> | <img src="https://user-images.githubusercontent.com/39727257/57106093-d91c2600-6d2c-11e9-95da-c739bb21131e.jpg" width="400"/>
1.1 | <img src="https://user-images.githubusercontent.com/39727257/57035511-89692c00-6c52-11e9-852f-34acd3ed28e4.jpg" width="400"/> | <img src="https://user-images.githubusercontent.com/39727257/57035569-abfb4500-6c52-11e9-9dd2-c7ca6e954a3f.jpg" width="400"/>
1.0 | <img src="https://user-images.githubusercontent.com/39727257/56866566-da6eeb00-69da-11e9-80bf-0f5eb124dce4.jpg" width="400"/> | <img src="https://user-images.githubusercontent.com/39727257/56866569-ec508e00-69da-11e9-9949-baaf827d3f6e.jpg" width="400"/>

### Where can I find weights for the CNN :( ?
I trained mine personally with on a dataset of 10k numeric digits
with data augmentation. It gave me a precision of 99.5+ %

### TODO LIST

- [ ] Create App
- [ ] Adapt App for phone !

### VERSION LIST

- v2.0 : Creating the first App' version | 13/09/20
    - Clean old code
    - Use of Kivy

- v1.7 : Multiple performance improvement | 17/12/19
    - New training method
    - Improve Reconstruction
- v1.6 : Multiple performance improvement | 19/05/19
    - Optimize method for solving
    - Optimize method for grid detection
    - Improve Robustness
    It is now able do deal with Real-Time
- v1.5 : Stabilizing video resolution | 12/05/19
    - Multiple checking if the grid is well detect
    - Jump solving step if seems to be already solved !
- v1.4 : Video Handling | 08/05/19
- v1.3 : More flexible / New training, better CNN ! | 05/05/19
- v1.2 : Multiple grids baby ! | 02/05/19
- v1.1 : Use probabilistic Hough & detect grid better | 01/05/19
- v1.0 : First version | 28/04/19

[KivyMD repo]: https://github.com/kivymd/KivyMD

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