Chess Pieces Computer Vision Project

Roboflow

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Classes (13)
bishop
black-bishop
black-king
black-knight
black-pawn
black-queen
black-rook
white-bishop
white-king
white-knight
white-pawn
white-queen
white-rook

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Description

Overview

This is a dataset of Chess board photos and various pieces. All photos were captured from a constant angle, a tripod to the left of the board. The bounding boxes of all pieces are annotated as follows: white-king, white-queen, white-bishop, white-knight, white-rook, white-pawn, black-king, black-queen, black-bishop, black-knight, black-rook, black-pawn. There are 2894 labels across 292 images.

Chess Example

Follow this tutorial to see an example of training an object detection model using this dataset or jump straight to the Colab notebook.

Use Cases

At Roboflow, we built a chess piece object detection model using this dataset.

ChessBoss

You can see a video demo of that here. (We did struggle with pieces that were occluded, i.e. the state of the board at the very beginning of a game has many pieces obscured - let us know how your results fare!)

Using this Dataset

We're releasing the data free on a public license.

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Cite This Project

LICENSE
Public Domain

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

                        @misc{
                            chess-full-cjdca_dataset,
                            title = { Chess Pieces Dataset },
                            type = { Open Source Dataset },
                            author = { Roboflow },
                            howpublished = { \url{ https://universe.roboflow.com/patoutn/chess-full-cjdca } },
                            url = { https://universe.roboflow.com/patoutn/chess-full-cjdca },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2024 },
                            month = { aug },
                            note = { visited on 2024-09-21 },
                            }
                        
                    

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