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End of preview. Expand
in Data Studio
Tic-tac-toe Board Dataset
Overview
- Dataset for occupancy detection of tic-tac-toe boards (top-down view).
- Contents: real images
real/imagesand YOLO-format labelsreal/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
.txtlives inreal/labels. - Synthetic data: generated via
main.py --num-train/--num-val(noise/contrast changes/distractors included) intodata/synth_grid/. - Parquet export:
dataset.parquet(generated bymake 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
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