Roboflow Universe Synthetic Data Go Positions

Go Positions Computer Vision Project

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Images

1000 images

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Synthetic dataset of black and white stones on go boards. Generated using Unity Perception

Use Case

To be able to take a picture of a go game and figure out the position of each stone in order to score the game or analyze with AI. Project inspiration stems from this blog post along with past ideas we've had for this: https://blog.roboflow.com/chess-boards/

Classes

blackStone: Black go stones, 90,501 labels whiteStone: White go stones, 89,963 labels grid: Cross section grid of a go board, 1,000 labels

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.

YOLOv8

This project has a YOLOv8 model checkpoint available for inference with Roboflow Deploy. YOLOv8 is a new state-of-the-art real-time object detection model.

YOLOv5

This project has a YOLOv5 model checkpoint available for inference with Roboflow Deploy. YOLOv5 is a proven and tested, production ready, state-of-the-art real-time object detection model.

Cite This Project

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

@misc{
                            go-positions_dataset,
                            title = { Go Positions Dataset },
                            type = { Open Source Dataset },
                            author = { Synthetic Data },
                            howpublished = { \url{ https://universe.roboflow.com/synthetic-data-3ol2y/go-positions } },
                            url = { https://universe.roboflow.com/synthetic-data-3ol2y/go-positions },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { aug },
                            note = { visited on 2024-04-25 },
                            }