By clicking "Access repository", you agree to use this dataset responsibly and in accordance with the following terms: (1) You will not claim ownership or authorship of the original images. (2) You will not redistribute the dataset without proper attribution to the curator and the source (Pexels). (3) You acknowledge that all images are sourced from Pexels under the Pexels License, which permits free commercial use without attribution. (4) You will use the dataset in compliance with applicable laws and ethical standards, and will not use it for any unlawful or harmful purpose.

World Architectural Buildings Dataset for Multi‑Class Image Classification

Multi‑Class Image Classification dataset of world architectural buildings with finalized curation.

Classes

Class	Count	Description
barn	1,680	Traditional wooden barn architecture — residential and storage buildings
bridge	1,680	Various bridge architectures (suspension, arch, truss)
castle	1,680	Medieval and modern castle structures
mosque	1,680	Islamic mosque architecture (domes, minarets)
skyscraper	1,680	Tall commercial and residential, city skyline buildings
stadium	1,680	Sports arenas, stadiums, amphitheaters
temple	1,680	Religious temple structures (Buddhist, Hindu, Asian)
windmill	1,680	Windmill structures (traditional, tower, Dutch)
Total	13,440	All datasets are finalized for curation

Data Collection & Processing

Source

All images sourced from Pexels.com — free stock photos licensed under the Pexels License (free for commercial use, no attribution required).

Collection Pipeline

Images were collected using a multi-mode scraping cascade:

Pexels API Key — primary source, direct API access with keyword-based queries per architectural class
BrightData SDK — supplementary collection for underrepresented subcategories
Selenium — fallback for specific queries requiring browser automation

Search Keywords

Class	Keywords
🏚️ Barn	old wooden barn, barn homes, barn architecture, red barn
🌉 Bridge	bridge, bridge architecture, bridge landscape, bridge building, bridge at night
🏰 Castle	castle architecture, medieval castle, castle building, european castle
🕌 Mosque	islamic mosque, mosque architecture, mosque exterior, beautiful mosque
🏙️ Skyscraper	skyscraper architecture, skyscraper building, tall building, city skyline, skyscraper at night
🏟️ Stadium	stadium design, football stadium, arena stadium, stadium at night, stadium architecture
🛕 Temple	temple building, temple architecture, buddhist temple, ancient temple, temple at night
🎡 Windmill	windmill architecture, traditional windmill, tower mill, windmill exterior, dutch windmill

Compression & Format

Max resolution: 720px on the longest side, min 200px on the shortest side
Max file size: 200 KB per image
Format: JPEG, adaptive quality compression (start: 85, step: −5, min: 40) until file ≤ 200 KB

Quality Filters

Images were filtered based on the following criteria:

Filter	Threshold	Purpose
Minimum resolution	150 × 150 px	Remove thumbnails and icons
Aspect ratio	0.28 – 3.5	Remove extreme panoramas and strips
Color standard deviation	≥ 10.0	Remove near-monochrome images
Minimum file size	5 KB	Remove corrupt/stub files
Maximum file size	4,096 KB	Remove uncompressed originals
File extension filter	Skip .svg, .gif, .webm, .mp4, .ico	Ensure JPEG-only dataset
URL pattern filter	Skip logos, avatars, icons, AI art, illustrations, people, badges, buttons, emojis, text overlays	Remove non-photographic content

Deduplication

Method	Threshold	Description
pHash (perceptual hash, 16×16)	Distance ≤ 8	Remove near-duplicate images (visual similarity)
SHA256	Exact match	Remove byte-identical duplicates
Human Curation	Full review	Final visual annotation and selection by domain experts

Resolution Distribution

Dimension	Range
Width	256 – 889 px
Height	160 – 1140 px

How to Load

from datasets import load_dataset

dataset = load_dataset("0xgr3y/arch-building-dataset", data_dir="dataset")

Dataset Structure

dataset/
├── barn/         barn_00000.jpg – barn_01679.jpg
├── bridge/       bridge_00000.jpg – bridge_01679.jpg
├── castle/       castle_00000.jpg – castle_01679.jpg
├── mosque/       mosque_00000.jpg – mosque_01679.jpg
├── skyscraper/   skyscraper_00000.jpg – skyscraper_01679.jpg
├── stadium/      stadium_00000.jpg – stadium_01679.jpg
├── temple/       temple_00000.jpg – temple_01679.jpg
└── windmill/     windmill_00000.jpg – windmill_01679.jpg

Naming convention: {class}_{5-digit-sequence}.jpg (sequential, zero-padded)
File format: JPEG (all images)
Total files: 13,440

Dataset Splits

The recommended split is 80% / 10% / 10% using split-folders with seed=42:

Split	Images	Per Class
Train	10,752	1,344
Validation	1,344	168
Test	1,344	168
Total	13,440	1,680

Ethical Considerations

No personally identifiable information (PII): All images are photographs of architectural buildings — no faces, names, or personal data are included.
Human content filtered: URL pattern filters explicitly exclude images tagged with people, portraits, or human-focused content during collection.
Commercial-free licensing: All images sourced from Pexels under the Pexels License (free for commercial use, no attribution required).
Building-only scope: This dataset is strictly limited to architectural structures. It does not include content that could be used for surveillance, profiling, or any harmful purpose.
Responsible use: Users agree not to claim ownership of original images, redistribute without attribution, or use the dataset for unlawful purposes.

Model: 0xgr3y/Arch-Building-Image-Classification (DenseNet121 + GeM Pooling + SWA)
Live on HuggingFace: 0xgr3y/arch-building-classifier (Gradio Space)
GitHub: arcxteam/arch-building-classifier (notebook.ipynb, training, method, scraping, technical)

Citation

@misc{saugani2026_arch_building_dataset,
  title={World Architectural Buildings Dataset for Multi‑Class Image Classification},
  author={Saugani},
  year={2026},
  publisher={Hugging Face},
  url={https://huggingface.co/datasets/0xgr3y/arch-building-dataset}
}