---
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