| --- |
| pretty_name: Shared-Class Sketch |
| task_categories: |
| - image-classification |
| tags: |
| - synthetic |
| - sketch |
| - compositionality |
| - hierarchical-representation |
| size_categories: |
| - 10K<n<100K |
| --- |
| |
| # Shared-Class Sketch |
|
|
| Shared-Class Sketch is a deterministic synthetic corpus for testing whether a |
| model can represent sketch categories through reusable primitives and parts. |
| Every image is a 128 x 128 binary raster with white strokes on a black |
| background. No real sketch raster or stroke is copied into the dataset. |
|
|
| ## Classes and structural variation |
|
|
| The ten semantic classes are `bicycle`, `truck`, `binoculars`, `face`, |
| `windmill`, `birthday_cake`, `butterfly`, `chandelier`, `flower`, and `guitar`. |
| Each class contains five balanced structural families: |
|
|
| - bicycle: diamond, open frame, beam, step-through, and compact; |
| - truck: box truck, pickup, dump truck, tanker, and flatbed; |
| - binoculars: porro prism, roof prism, compact, field glass, and opera glasses; |
| - face: round smile, oval neutral, square jaw, long surprised, and wide grin; |
| - windmill: four sail, six sail, Dutch, farm wheel, and pinwheel; |
| - birthday cake: tiered round, layer cake, single candle, many candles, and |
| cupcake; |
| - butterfly: rounded four-wing, angular swallowtail, monarch spotted, |
| side-swept, and compact moth; |
| - chandelier: three-arm, five-arm, pendant, tiered crystal, and candle wheel; |
| - flower: five-petal, many-petal daisy, tulip, bell flower, and sunflower; |
| - guitar: classical, dreadnought, electric cutaway, triangular, and double |
| cutaway. |
|
|
| Structural-family names, primitive counts, geometry profiles, and drawing-style |
| profiles are audit metadata. The intended model supervision consists only of |
| the semantic class and object center; these audit fields are not intended as |
| training targets. |
|
|
| ## Splits |
|
|
| | Split | Images | Purpose | |
| |---|---:|---| |
| | train | 20,480 | Single-object model training | |
| | val | 2,560 | Single-object checkpoint selection | |
| | heldout | 2,560 | Unseen elongated plus loose-overdrawn factor combination | |
| | composition | 4,320 | Forty-five unseen unordered two-class pairs, 96 images per pair | |
|
|
| Archetype identifiers are disjoint across all splits. Training contains the |
| elongated geometry factor and the loose-overdrawn style factor separately, but |
| never their joint combination. The composition split contains no paired scene |
| used for optimization. |
|
|
| ## Files |
|
|
| - `train/`, `val/`, and `heldout/` contain class-named image folders. |
| - `composition/` contains one folder for each unordered class pair. |
| - `metadata/*.jsonl` contains class and object-center records used by the HDD |
| experiment. |
| - `records.jsonl` contains complete audit provenance for every image. |
| - `manifest.json` contains counts, checksums, source-disjointness, topology |
| coverage, foreground/border audits, and binary-image uniqueness statistics. |
| - `generation_config.json` is the strict deterministic generation recipe. |
| - The PDF previews separately visualize training topology diversity, the |
| held-out factor combination, and unseen two-object compositions. |
|
|
| Image-folder loaders can infer the single-object class labels directly from the |
| directory names. The experiment-specific JSONL metadata is only needed when |
| object-center supervision is desired. |
|
|
| ## Integrity and provenance |
|
|
| All 29,920 stored rasters are binary and every split is duplicate-free under a |
| SHA-256 hash of the raster bytes. The generation configuration SHA-256 is |
| `9a46c478594748c3a7c84ce971bf3ef4d79914cebfa4581a34fba6c5eab1f24c`; |
| the complete records file SHA-256 is |
| `2626c48df7a5d1fd31388bee106764b516de68216424d9e466eda1cfaf75a8c4`. |
|
|
| Aggregate style and abstraction statistics were calibrated against the ten |
| corresponding SlowSketch categories. SlowSketch remains an external held-out |
| reference: no SlowSketch sample path, raster, or stroke initializes a synthetic |
| sample. |
|
|
| ## Generation |
|
|
| From the Hierarchical Detector-Decoder repository root: |
|
|
| ```bash |
| PYTHONPATH=.:src python scripts/create_shared_class_sketch_dataset.py \ |
| --config_json configs/shared_class_sketch_dataset_10class.json |
| ``` |
|
|
| The generator is deterministic and refuses to overwrite an existing output |
| directory unless overwrite is explicitly enabled. |
|
|
