{"id":23661261,"url":"https://github.com/chrisdalvit/sudoku-solver","last_synced_at":"2026-02-07T12:31:40.113Z","repository":{"id":268264782,"uuid":"770336351","full_name":"chrisdalvit/sudoku-solver","owner":"chrisdalvit","description":"Just another real-time Sudoku solver coded in Python using OpenCV and PyTorch. 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Capable of tackling Sudoku puzzles in images and videos, and projecting the solutions back onto the original visuals.\n\n\u003cp align=\"center\"\u003e\n  \u003cimg src=\"./static/solver_demo.gif\" /\u003e\n\u003c/p\u003e\n\n## Setup\nAfter cloning the repository install the dependencies by running\n```\npip install -r requirements.txt\n```\n\nIf you just want to execute ``main.py`` you're good to go, as it comes with a pre-trained neural network for digit classification provided in ``model_file.pt``. \n\nRun the following command to verify that the setup is completed. The solved Sudoku should be displayed in a new window\n```\npython main.py -i ./images/sudoku_photo.jpg\n```\n\nIf you want to retrain the neural network for digit classification you need to download the [dataset](https://www.kaggle.com/datasets/kshitijdhama/printed-digits-dataset?resource=download) from Kaggle. Unzip the downloaded folder, rename it to ``archive`` and paste it into the project directory. Alternatively, you can store the unzipped folder in a directory of your choice and update the path in the ``ASSETS_PATH`` variable within ``classifier/dataset.py``. Now you should be ready to retrain the neural network using the ``classifier.ipynb`` notebook.\n\n## Usage\nFor solving a Sudoku puzzle in an image use \n```\npython main.py -i \u003cPATH_TO_IMAGE\u003e\n```\nThe puzzle with the projected solution should be displayed in an new window.\n\nFor solving a Sudoku puzzle from a videocamera use \n```\npython main.py -v\n```\nThe video stream should be displayed in an new window. Optionally you can pass a device index (integer) to the ``-v`` argument used by OpenCV for camera selection. \n\n## Credits\nThe dataset used in this project was published by Kshitij Dhama on Kaggle.","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fchrisdalvit%2Fsudoku-solver","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fchrisdalvit%2Fsudoku-solver","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fchrisdalvit%2Fsudoku-solver/lists"}