| # SimVerse / voi | |
| Text-VOI spatial logic puzzle: choose how to rotate and translate base shapes onto a grid so that their XOR-overlapped union exactly reproduces a target pattern. | |
| - **Records:** 600 levels | |
| - **Modality:** target pattern image + one image per available base shape | |
| - **Output:** `{"placements": [{"shape", "angle", "vertex", "grid"}, ...]}` | |
| ## Loading | |
| ```python | |
| from datasets import load_dataset | |
| ds = load_dataset("SimVer-ano/simverse2026", "voi") | |
| example = ds["test"][0] | |
| system_text = example["prompt"]["system"] | |
| user_text = example["prompt"]["user"] | |
| target_img = example["images_relative_to_config"]["target"] # e.g. "data/voi-000/target.png" | |
| shape_imgs = example["images_relative_to_config"]["shapes"] # e.g. {"S1": "data/voi-000/shapes/S1.png", ...} | |
| gold_placements = example["answer"]["placements"] | |
| ``` | |
| ## Schema | |
| | Field | Type | Description | | |
| |---|---|---| | |
| | `ID` | string | Level id, e.g. `"voi-000"` | | |
| | `__sample_id__` | string | Same as `ID` | | |
| | `prompt.system` / `prompt.user` | string | Exact prompt text | | |
| | `gridSize` | int | Square grid side length | | |
| | `inventory` | dict | `{shape_id: {V1: [x,y], V2: [x,y], ...}}` — each base shape's vertex coordinates | | |
| | `target` | list of polygon dicts | The goal silhouette (XOR of these polygons) | | |
| | `meta` | dict | `difficultyLabel`, `requiredShapeCount`, `distractorShapeCount`, `overlapAllowed` | | |
| | `imageAssets.target` | string | Target pattern image path (level-relative) | | |
| | `imageAssets.shapes` | dict | `{shape_id: image_path}` per available shape | | |
| | `images_relative_to_config` | dict | Same image paths but rewritten to be relative to the config root | | |
| | `answer.placements` | list[{shape, angle, vertex, grid}] | Reference solution | | |
| | `legacy_answer` | string | Pre-v1 plain-text DSL form of the answer | | |
| | `solutionText` | string | The DSL form of the answer (kept because the pixel engine consumes it for the reference mask) | | |
| ## Output format details | |
| Each placement encodes: rotate `shape` clockwise by `angle ∈ {0,90,180,270}` around its local origin, then translate so the post-rotation `vertex` lands at grid coordinate `[gridX, gridY]`. | |
| The benchmark's pixel engine rasterizes the placements and XOR-combines them; a perfect score requires the resulting mask to equal the target pattern's mask. | |
| ## License | |
| MIT — see [LICENSE](../LICENSE) at the repo root. | |