G-G-Games/diecamera-crops

dieCamera — per-die crops

One cropped image per physical die, labelled with its type and face value. This is the deliberately-simple training set for dieCamera's offline value reader — the app that watches a dice tray and posts the roll into a virtual tabletop (source).

For the full frames these crops were cut from (and the multi-die detector-training data), see the companion repo G-G-Games/diecamera-frames.

Schema

Standard 🤗 imagefolder layout — load_dataset("G-G-Games/diecamera-crops") needs no config.

data/<file>.jpg        one die, cropped to its bounding box + a small margin
data/metadata.jsonl    one row per crop

column	type	meaning
file_name	string	the crop image
source	string	rig (our webcam) or roboflow:<fork> (a third-party image, see below)
type	string	die type — d4, d6, d8, d10, d12, d20
value	int	the up-face value read (d10 may be 0)
date	string	capture date (rig), or publish date when the source has none
added_at	string	the day this crop first entered the dataset — filter added_at > last_run to train only on what's new
holdout	bool	true = reserved for evaluation; filter these out when training

Training tip. Exclude eval frames and (optionally) skip what you've already trained on: ds.filter(lambda r: not r["holdout"]). added_at lets an incremental finetune pick up only rows added since its last run, instead of reprocessing the whole set.

Every die here has a trusted face value: rig dice are human-confirmed or placed to a prompt; roboflow dice are the ones a human reviewed and confirmed by hand.

Licence — read this before commercial use

This dataset is mixed-licence, and the source column tells you which applies per row:

source	licence
rig	CC BY-NC 4.0 © G-G-Games — free personal use; commercial needs a licence
roboflow:<fork>	CC BY 4.0 © the fork's original author (commercial OK, attribution required)

The labels on every row are G-G-Games' own work (CC BY-NC 4.0). Full terms: LICENSE-NC.md.

Roboflow attribution (CC BY 4.0)

Crops with a roboflow: source derive from these Roboflow Universe datasets, used with modifications (cropped; our own top-face type/value labels added):

source	original author → dataset
roboflow:200_dataset	vkr-55xr7 → https://universe.roboflow.com/vkr-55xr7/200_dataset
roboflow:d4-turbo-rad-v4	turbo-rad → https://universe.roboflow.com/turbo-rad/d4-bmzdm

See ATTRIBUTIONS.md for the full provenance record.