Datasets:

AETHORIA-AI
/

complexity-atlas-image-edits

license: other
task_categories:
  - image-to-image
language:
  - en
tags:
  - image-editing
  - instruction-guided-editing
  - restoration
  - webdataset
  - tr-hash
pretty_name: Complexity Atlas Image Edits
size_categories:
  - 100K<n<1M
configs:
  - config_name: default
    data_files:
      - split: train
        path: train/*.tar
      - split: validation
        path: validation/*.tar
      - split: test
        path: test/*.tar

Complexity Atlas Image Edits

Complexity Atlas Image Edits is an aligned instruction-guided image editing dataset derived from the normalized public-domain Complexity Atlas image bank. It contains 336,245 explicit source/instruction/target triplets at 256 x 256.

Dataset structure

Each WebDataset record contains:

<edit_id>.source.webp
<edit_id>.target.webp
<edit_id>.txt
<edit_id>.json

source.webp is a deterministic degraded image;
target.webp is the unchanged normalized public-domain artwork;
txt is an original imperative restoration instruction;
json records transformation parameters, hashes, provenance, source URL, upstream revision, source license, and split identity.

Scale

Property	Value
Editing pairs	336,245
Train	329,510
Validation	3,428
Test	3,307
WebDataset shards	136
Stored bytes	11,302,287,360
Edit families	13
Exact instruction variants	126
Maximum exact instruction share	1.56%

Editing families

The first release covers color restoration, deblurring, underexposure and overexposure correction, contrast and saturation restoration, detail recovery, compression restoration, warm and cool cast correction, orientation correction, surface-damage restoration, and missing-region restoration.

These are verifiable restoration operations. The release does not claim to contain semantic object insertion, removal, identity changes, or unconstrained creative edits.

Construction and split integrity

One deterministic edit is selected per source artwork. The original target's split is preserved, so an artwork cannot cross train, validation, and test. The complete audit reports:

zero source-identity leakage;
zero rejected records;
complete source/instruction/target/metadata membership;
a non-trivial pixel change for every source;
unique edit identifiers;
exact instruction repetition below 5%.

See audit_report.json, build_manifest.json, and files_manifest.json for machine-readable evidence.

Provenance and licensing

The normalized target images originate from Mitsua/art-museums-pd-440k at pinned revision fba945da78b36262eb9272067197cc28d06cffbf. Every retained record is marked CC0 and retains its source URL and upstream metadata.

Generated source images are deterministic mechanical transformations of those targets. This repository does not impose a new blanket copyright restriction on the public-domain image assets. The builder code is available separately under Apache-2.0. Users remain responsible for reviewing the per-record provenance for their intended jurisdiction and use.

Builder

The reproducible builder and tests are available at:

https://github.com/Complexity-ML/complexity-atlas-images