add ai sudoku | issue #796

[Tusharb331]

Pull Request for PyVerse 💡

Requesting to submit a pull request to the PyVerse repository.

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Issue Title

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[Code Addition Request]: AI SUDOKU SOLVER using cv2 and Tensorflow |#796

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Info about the Related Issue

What's the goal of the project?
The goal of the project is to add an AI-powered Sudoku Solver that extracts and solves Sudoku puzzles from images using KNN or CNN-based recognition.

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Name

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Tushar Bansal

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GitHub ID

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tusharb331

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Email ID

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[email protected]

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Identify Yourself

Mention in which program you are contributing (e.g., WoB, GSSOC, SSOC, SWOC).
GSSOC-EXT, hacktoberfest

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Closes

Enter the issue number that will be closed through this PR.
Closes: #796 ['Feature Addition']

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Describe the Add-ons or Changes You've Made

Give a clear description of what you have added or modified.

• This PR adds the AI_Sudoku project, which involves a GUI-based Smart Sudoku Solver using Python.

• It attempts to extract and solve Sudoku puzzles from images using KNN or CNN-based recognition.

• I have described my changes.

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Type of Change

Select the type of change:

• Bug fix (non-breaking change which fixes an issue)
• New feature (non-breaking change which adds functionality)
• Code style update (formatting, local variables)
• Breaking change (fix or feature that would cause existing functionality to not work as expected)
• This change requires a documentation update

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Proposed Changes

• Added the entire AI_Sudoku project folder, including scripts for image preprocessing, recognition, and GUI.

• Included a README file that provides detailed installation instructions, usage guide, and working explanation.

• Added screenshots demonstrating various stages of the application, from image preprocessing to solution generation.

• Updated the requirements.txt to include necessary dependencies like cv2, tensorflow, and matplotlib.

• I have described my changes.

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Additional Info

• The KNN and CNN models are trained on the MNIST dataset for digit recognition.

• Image preprocessing steps include Gaussian blurring, adaptive thresholding, and perspective warping.

• Users can select images of Sudoku puzzles, and the application will process, recognize, and solve the puzzles.

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Screenshots

Please refer to the screenshots folder under AI_Sudoku for screenshots.

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How Has This Been Tested?

Describe how your changes have been tested.
The solution was tested on various Sudoku images with different complexities, validating the output for accuracy and checking the robustness of the image preprocessing and recognition modules.

• I have described my testing process.

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Checklist

Please confirm the following:

• My code follows the guidelines of this project.
• I have performed a self-review of my own code.
• I have commented my code, particularly wherever it was hard to understand.
• I have made corresponding changes to the documentation.
• My changes generate no new warnings.
• I have added things that prove my fix is effective or that my feature works.
• Any dependent changes have been merged and published in downstream modules.

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