README.md

metadata

license:
  - cc0-1.0
  - cc-by-4.0
  - cc-by-sa-4.0
task_categories:
  - image-classification
tags:
  - architecture
  - buildings
  - art-history
  - clip-embeddings
  - brutalism
size_categories:
  - 1K<n<10K
pretty_name: Architectural Styles Dataset (Curated and Extended)

Architectural Styles Dataset (Curated and Extended)

Dataset Summary

A curated and extended version of dumitrux's Architectural Styles Dataset. The original dataset covered 25 architectural styles; 630 images were removed by automated filters (duplicates, low-resolution), leaving 9,483 images. A 26th class, Brutalism, was added from 284 manually curated Wikimedia Commons photographs, bringing the total to 9,767 images across 26 classes.

Intended use: training and evaluating image classifiers that predict the architectural style of buildings from exterior photographs.

Supported Tasks

• Image Classification (multi-class-image-classification): predict one of 26 architectural style labels from a building photograph.

Dataset Structure

Data Instances

Each instance is a JPEG or PNG photograph of a building, assigned a single architectural style label. Images vary in resolution (minimum 224 px on the short side) and aspect ratio.

Data Fields

Field	Type	Description
image	Image	Building photograph
label	string	Architectural style class name (one of 26)
split	string	train, val, or test

Classes

26 architectural styles:

Class	Approx. images
Achaemenid architecture	362
American craftsman style	337
American Foursquare architecture	348
Ancient Egyptian architecture	349
Art Deco architecture	548
Art Nouveau architecture	595
Baroque architecture	431
Bauhaus architecture	294
Beaux-Arts architecture	401
Brutalism architecture	284
Byzantine architecture	295
Chicago school architecture	260
Colonial architecture	446
Deconstructivism	290
Edwardian architecture	268
Georgian architecture	348
Gothic architecture	307
Greek Revival architecture	503
International style	387
Novelty architecture	350
Palladian architecture	318
Postmodern architecture	308
Queen Anne architecture	708
Romanesque architecture	285
Russian Revival architecture	318
Tudor Revival architecture	427

Data Splits

Stratified 70/15/15 train/val/test split, fixed seed 42, applied jointly across all 26 classes.

Split	Images
train	6,822
val	1,456
test	1,489
total	9,767

Dataset Creation

Curation Rationale

The original Kaggle dataset contained duplicates and low-resolution images unsuitable for training CLIP-based classifiers (minimum input size 224 px). Brutalism was added because it is a visually distinctive style absent from the original 25 classes, and high-quality labelled images were available from Wikimedia Commons.

Source Data

Original 25 classes:

• Danci, Marian Dumitru/dumitrux. (n.d.). Architectural Styles Dataset [Data set]. Kaggle. https://www.kaggle.com/datasets/dumitrux/architectural-styles-dataset
• Downloaded: 2026-05-05 · Curated: 2026-05-07

Brutalism class:

• Source: Wikimedia Commons, MediaWiki API
• Scraped across 40 country-level categories (e.g. "Brutalist architecture in the United Kingdom") with subcategory recursion up to depth 2
• Scraped & downloaded: 2026-05-08 · Curated: 2026-05-09

Curation Process — Original 25 Classes

• Automated filters: corrupt files; minimum dimension < 224 px; perceptual-hash duplicates (Hamming distance < 5)
• Manual review: stratified random sample of 10 images per class; no further images removed
• Result: 630 images removed from the original 10,113, leaving 9,483 images

Curation Process — Brutalism Class

All 950 downloaded images were reviewed individually. An image was kept only if it showed the exterior of a Brutalist building as the primary subject, was a real photograph (not a render or drawing), had no severe obstructions, and had sufficient resolution and framing for style classification.

Decision	Count	%
Kept	284	29.9 %
Rejected	666	70.1 %

Rejection breakdown:

Reason	Count	% of rejected
other	223	33.5 %
partial_or_detail	157	23.6 %
obstructed	151	22.7 %
low_quality	67	10.1 %
duplicate_building	31	4.7 %
interior_uninformative	22	3.3 %
not_brutalism	13	2.0 %
not_a_photograph	2	0.3 %

"other" covers heavily post-processed images, composites, and signage-dominated shots.

Leakage Remediation

Nearest-neighbour analysis on CLIP ViT-B/32 embeddings identified building-level duplicates split across train and test in the Ancient Egyptian and Novelty classes. Splits were regenerated after remediation; reported F1 for these classes may still be slightly optimistic.

Considerations for Using the Data

Geographic and Temporal Bias

• The original 25 classes are heavily Western and European; the Brutalism extension spans 40 countries but remains biased toward countries with strong Wikimedia Commons representation.
• The dataset is predominantly pre-1980. Parametricism and Metabolism are absent.

Known Limitations

• Manual review of the original 25 classes was sample-based (10 images per class), not exhaustive.
• The Brutalism class (284 images) is smaller than most original classes; performance on this class may be sensitive to distribution shift.
• The model is trained on exterior photographs; performance on interiors, renders, and architectural drawings is undefined.

Sensitive Content

No personally identifiable information. Images are of buildings, not people.

Additional Information

Licensing

• Original 25 classes: CC0 1.0 (Public Domain)
• Brutalism class: mixed free licences (CC0, CC-BY, CC-BY-SA) inherited from Wikimedia Commons contributors. Per-image licence information is recorded in the accompanying brutalism_downloaded.jsonl manifest. Downstream use must comply with the applicable per-image licence.

Citation

If you use the original Kaggle dataset, please cite:

Danci, Marian Dumitru/dumitrux. (n.d.). Architectural Styles Dataset [Data set]. Kaggle.
https://www.kaggle.com/datasets/dumitrux/architectural-styles-dataset