Datasets:

Xuban
/

rock-paper-scissors-room

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End of preview. Expand in Data Studio

Rock Paper Scissors (labelled by the room)

This repository is empty for now. It gets filled at coffee time on 7 October 2026 with the labels the room makes in Label Studio during the LibreYOLO hands-on at Mondragon Unibertsitatea. It holds only what people labelled that morning.

The dataset is built by make_dataset.py from the Label Studio export, in the same LibreYOLO format as Xuban/rock-paper-scissors-roboflow: YOLO text labels, class ids 0 rock, 1 paper, 2 scissors, and data.yaml files with no path: line.

data.yaml        the room's photos and the Roboflow photos the room labelled, with the room's labels
data_B.yaml      the same photos, but the Roboflow ones keep Roboflow's labels
data_C.yaml      only the room's own photos
images/room      photos taken in the room (labels/room)
images/rf        Roboflow photos labelled by the room (labels/rf)
images/rf_orig   the same Roboflow photos with Roboflow's labels (labels/rf_orig)
images/val       the 100 validation photos (labels/val)

The validation set is the fixed set of 100 photos with Roboflow's labels, the same as in the Roboflow repository, so scores can be compared. The workshop's Colab notebook downloads this repository with snapshot_download("Xuban/rock-paper-scissors-room", repo_type="dataset").

The photos come from the Roboflow Universe project Rock Paper Scissors (CC BY 4.0). Credit: rock-paper-scissors-2, Roboflow Universe.

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