Visual Chessboard Analysis: CNN-based FEN Code Generation

[Varunshiyam]

Is your feature request related to a problem? Please describe.

Recording and analyzing chessboard positions is a common yet challenging task for chess players, analysts, and software developers. Manual conversion of board configurations into FEN (Forsyth-Edwards Notation) strings is time-consuming and prone to human error, limiting the efficient use of chess engines, digital recording, and automated analysis tools.

This project aims to automate FEN generation from chessboard images by leveraging deep learning, specifically CNNs. The model predicts chess piece positions and converts them into standardized FEN notation, facilitating seamless integration with chess software and engines for analysis, gameplay, and training purposes.

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Describe the solution you'd like

The Chess FEN Position Prediction project is designed to convert images of chessboard positions into FEN codes through an end-to-end pipeline of image processing, model training, and FEN generation.

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**Kindly Assign me this Issue Under: **

• Gssoc 🌸
• hacktoberfest ☘️
• Level - 2 ✨

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Screen Shots of Notebook

[github-actions]

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[github-actions]

Hello @Varunshiyam! Your issue #725 has been closed. Thank you for your contribution!

[github-actions]

Hello @Varunshiyam! Your issue #725 has been closed. Thank you for your contribution!