README.md

metadata

license: cc-by-4.0
tags:
  - image-dataset
  - object-detection
  - tic-tac-toe
task_categories:
  - object-detection

Tic-tac-toe Board Dataset

Overview

• Dataset for occupancy detection of tic-tac-toe boards (top-down view).
• Contents: real images real/images and YOLO-format labels real/labels. Synthetic data can be generated on-demand with the scripts in this repo.
• Classes: 0=empty_cell, 1=white_circle_cell, 2=black_cross_cell

License

• Dataset: CC-BY-4.0
• Real images contain no PII/portraits. Credit per README/model card.
• Source code (generation, training, inference): https://github.com/guren-kaina/AMD_Robotics_Hackathon_2025_ProjectTemplate/tree/main/mission2/code/tic_tac_toe_overlay

Data contents

• Resolution: depends on capture device (boards are typically centered).
• Annotation: YOLO txt (class cx cy w h) normalized coords. Matching .txt lives in real/labels.
• Synthetic data: generated via main.py --num-train/--num-val (noise/contrast changes/distractors included) into data/synth_grid/.
• Parquet export: dataset.parquet (generated by make hf-dataset-stage) with columns: image, label_file, class_id, cx, cy, w, h. One row per bbox; empty label files produce a single row with null class/coords.

Suggested splits

• Real images are limited; mix synthetic:real around 8:2 and hold out val/test separately.

Notes and care

• Optimized for top-down view; for oblique viewpoints or different board designs, re-label and retrain.
• For new token designs or colors, add annotations and retrain.

Usage example

python main.py --real-data real --num-train 1000 --num-val 200 --force-train