Chess-I Object Detection Dataset and Pre-Trained Model by ChessI

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Explore Dataset

Here are a few use cases for this project:

Chess Game Analysis: Chess-I could be used to digitize physical games of chess and convert them into a digital format for later review, analysis or sharing. The model could also offer real-time insights about the position of the chess pieces.
Online Chess Platforms: The model could be implemented by online chess platforms to allow users to play physical games that are mirrored online. Players would simply use their own chess set at home, and the platform would utilize Chess-I to recognize the different chess pieces and their positions on the board, creating an immersive online-offline hybrid gaming experience.
Chess Tutoring and Learning Applications: Chess-I could be used in learning or tutoring applications to provide feedback on chess strategies, possible moves and their consequences. This would allow learners to play a physical game of chess while accessing informational assistance, improving their game.
Automated Chess Robots: In robotics, Chess-I could be used to power an automated chess-playing robot. The robot would use the vision model to identify the pieces on the board and decide on the next move, effectively playing a game of chess against a human opponent.
Broadcasting Physical Chess Matches: In sports broadcasting, Chess-I could be used to create real-time digital visualizations of important matches, making it easier for viewers to follow the game. This would be particularly useful in professional chess tournaments.

Trained Model API

This project has a trained model available that you can try in your browser and use to get predictions via our Hosted Inference API and other deployment methods.

Cite This Project

If you use this dataset in a research paper, please cite it using the following BibTeX:

@misc{
                            chess-i_dataset,
                            title = { Chess-I Dataset },
                            type = { Open Source Dataset },
                            author = { ChessI },
                            howpublished = { \url{ https://universe.roboflow.com/chessi/chess-i } },
                            url = { https://universe.roboflow.com/chessi/chess-i },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { feb },
                            note = { visited on 2024-06-12 },
                            }