| license: cc-by-4.0 | |
| pretty_name: FactorAtlas | |
| size_categories: | |
| - 10K<n<100K | |
| tags: | |
| - image | |
| - synthetic-data | |
| - vision-language | |
| - benchmark | |
| # FactorAtlas | |
| FactorAtlas is the dataset accompanying [*Seeing Is Not Addressing: Auditing | |
| Linguistic Access to Frozen Visual Geometry*](https://github.com/LABA-SNU/seeing-is-not-addressing). | |
| It contains 23,040 controlled synthetic images spanning 8 shapes, 12 hues, 10 | |
| surface patterns, 12 rendering contexts, and 2 renderer seeds. | |
| ## Use with the reference code | |
| Clone the [reference implementation](https://github.com/LABA-SNU/seeing-is-not-addressing), | |
| install its dependencies, then run from the repository root: | |
| ```bash | |
| pip install -r requirements.txt | |
| bash scripts/run_factoratlas.sh | |
| ``` | |
| The runner downloads FactorAtlas into `data/factoratlas`, caches frozen model | |
| features, and writes the complete audit report locally. | |
| ## Files | |
| - `metadata.json` — one record per image with factor labels and rendering keys | |
| - `data/factoratlas-*.tar` — 24 image shards containing 224×224 PNGs | |
| - `data/SHA256SUMS` — SHA-256 checksums for the shards | |