I recently wanted to learn a bit about computer vision. Initially, I wanted to build something which could solve a jigsaw puzzle, but figured I should start with something (much) simpler, so I've built this instead.
This is a visual Sudoku solver which runs in the browser. It works by using OpenCV to identify and process the Sudoku grid, passing this to a simple ML model to identify the digits, and then solving the puzzle with a backtracking algorithm. The ML model was trained on the TMNIST data set using a model built with Keras, also a completely new area to me.
It's far from perfect, and doesn't like non perfectly lit or overly warped puzzles, but the main goal here was learning, which I did, a lot.
As this was primarily a learning project, I've tried to document my approach as much as possible, which can be found in this Python notebook:
https://github.com/Taiters/sudoku-solver/blob/main/notebooks...
I used Python while exploring OpenCV and training the models etc, and eventually ported this over to web (OpenCV.js + Tensorflow.js) to get something I could actually share with people.
Feel free to have a dig around the source or play around with the solver!