Chess Extended Computer Vision Project
Updated 3 years ago
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Here are a few use cases for this project:
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Chess Automation: This model can be used in the development of automated chess systems. By identifying pieces and their locations, the system can help in tracking moves and assist in virtualizing real-world chess games.
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Chess Training Tools: The model can be used to create chess training applications. It can help beginners learn different pieces and their movements by identifying and explaining each piece as they play.
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Real-time Game Analysis: It can be used for on-going game analysis during live tournaments. The positions of the pieces can help derive the current state of the game and assess potential future moves or strategies.
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Online Chess Platforms: Integration of this model can enable physical chess board situations to be uploaded to online platforms. This will allow the continuation of games or analysis in digital form for remote or later gameplay.
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Historical Game Reconstruction: The model can be used to recreate famous historical games. By identifying the pieces in photos of historical matches, these games can be digitally recreated for future learning and analysis.
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Cite This Project
If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
chess-extended_dataset,
title = { Chess Extended Dataset },
type = { Open Source Dataset },
author = { Raisa Riabinina },
howpublished = { \url{ https://universe.roboflow.com/raisa-riabinina/chess-extended } },
url = { https://universe.roboflow.com/raisa-riabinina/chess-extended },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2021 },
month = { dec },
note = { visited on 2024-10-08 },
}