SimVerse / cube1
Cube reconstruction (six-face map): given a blank cross net of a cube and a top-down image of the bottom-face imprints stamped along a roll path, reconstruct the patternId and rotation of every outer face.
- Records: 502 levels
- Modality: blank cross net image + top-down path-imprint image
- Output:
{"faces": {"TOP": {patternId, rotation}, "BOTTOM": ..., ..., "RIGHT": ...}}
Loading
from datasets import load_dataset
ds = load_dataset("SimVer-ano/simverse2026", "cube1")
example = ds["test"][0]
system_text = example["prompt"]["system"]
user_text = example["prompt"]["user"]
# Image paths (relative to this config's root)
blank_net = example["image_paths"]["blank_net_image"] # e.g. "images/blank_nets/open.png"
path_seq = example["image_paths"]["path_sequence_image"] # e.g. "images/path_sequences/C001_path_sequence.png"
gold_faces = example["answer"]["faces"] # {TOP: {...}, BOTTOM: {...}, ...}
The image paths in image_paths are already relative to this config's root, so you can resolve them as-is.
Schema
| Field | Type | Description |
|---|---|---|
sample_id |
string | Level id, e.g. "C001" |
__sample_id__ |
string | Same as sample_id |
prompt.system / prompt.user |
string | Exact prompt text |
net_layout |
string | Net layout name (e.g. "standard_cross") |
roll_sequence |
list[string] | Sequence of rolls, each "N"/"S"/"E"/"W" |
observed_path_faces |
list of face observations | Per-step bottom-face imprints visible in the path image |
image_paths.blank_net_image |
string | Blank cross net image path |
image_paths.path_sequence_image |
string | Top-down path imprint image path |
metadata |
dict | difficulty, move_count, tier, tier_label, etc. |
net_faces |
list of face dicts | Net cells with their initial patterns and rotations |
bottom_faces |
list of stamped face dicts | The imprints with their (x, y) positions |
slot_sequence / required_slots / required_count |
various | Which faces the engine ranks for partial-credit scoring |
true_solution_faces |
dict | Ground-truth full face map (used for scoring) |
answer.faces |
dict | Reference (patternId, rotation) per face |
legacy_answer |
dict | Pre-v1 bare face map (kept for back-compat) |
Companion file
catalog.json mirrors the original levels/index.json — a fat JSON containing every level's full data inline. The frontend demo at https://github.com/SimVer-ano/simverse2026 reads this file. It is regenerable from data/*.json via python cube1/regenerate_catalog.py in the repo.
"?" sentinel rule
Each face's patternId is either a string from the per-level allowed-patternId list, or the literal "?" meaning "cannot be uniquely determined". When patternId == "?", rotation is forced to 0. The validator scores ? against ? as correct; ? against a concrete pattern (or vice versa) as wrong.
License
MIT — see LICENSE at the repo root.