sudoku-solver

Hi, my name is Rémi LUX. I end my final year of Computer Vision Degree in Grenoble INP - Phelma, and I'm now engineer at Niryo. Welcome to my project
My algorithm is able to detect and to directly solve sudokus in VR

What is it doing ?

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 :

Preprocess image to enhance high frequencies
Find lines thanks to Hough Space
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 ?

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/folder/

You can see the options by typing python3 sudoku_solver_main.py -h

You will need some libraries before running it

Numpy
OpenCV
Keras
Tensorflow

To Install : pip install <library_name>

Easy way

Take your own picture/video of your process target and use the command
python3 sudoku_solver_main.py -i path/to/your/file
You also want to add -s to save the output result In both cases, the result will be display on your monitor during processing

If you want to use your webcam, you can chose the profile n°2 by adding -p 2 to your command. Nevertheless, the algorithm is too long to give a real-time pleasant experience (mainly cause of the Hough Transform)

Advanced way

The user can use his own Keras model to identify digits. For that use the parameter -mp path/to/your/model

Evolution, TODO list, Q&A, ...

Evolution of the Algorithm

Version	Source	Algorithm Output
1.5	Video
1.3
1.2
1.1
1.0

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

VERSION LIST

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 | 01/054/19
v1.0 : First version | 28/04/19