passport-photo-specs

Canonical passport, visa, and ID document photo specifications, validated against 15+ official government sources. 100 countries, 248 document formats. MIT licensed.

The same dataset that powers idphotosnap.com — a free browser-only passport and visa photo maker. Published here so anyone can build on top of it.

What's in it

Each record is one document format (a country - document pair). Fields:

field	type	description
country_id	string	ISO-style short code (us, uk, schengen, india, etc.)
country_name	string	Human-readable country name
country_flag	string	Emoji flag
document_id	string	Unique document identifier within the country
document_name	string	e.g. "US Visa & Passport", "Indian Voter ID"
slug	string	URL-safe slug used by IDPhotoSnap
width_mm / height_mm	int	Physical dimensions in millimeters
width_px / height_px	int	Pixel dimensions at the listed DPI
dpi	int	Dots per inch (usually 300)
background_description	string	"Plain white", "Cream or light grey", etc.
background_color_hex	string	Reference hex color (#ffffff = white)
background_color_label	string	Short label for UI
requirements	list[string]	Human-readable spec bullets (face coverage, expression, glasses rule, recency, etc.)
source_url	string	Citation URL to the official government source

Coverage

• All 26 Schengen states (separate generic Schengen entry + per-country)
• Anglosphere: US, UK, Canada, Australia, New Zealand, Ireland
• South Asia: India (passport, visa, voter ID, driving licence, PAN), Pakistan, Bangladesh, Sri Lanka, Nepal
• East / Southeast Asia: China (visa, passport), Japan (passport, MyNumber), South Korea, Taiwan, Indonesia, Vietnam, Philippines, Thailand, Malaysia, Singapore (incl. work passes)
• Middle East & North Africa: UAE, Saudi Arabia, Egypt, Israel, Turkey, Morocco
• Sub-Saharan Africa: Nigeria, Kenya, South Africa, Ghana, Egypt
• Latin America: Brazil, Mexico, Argentina, Chile, Colombia, Peru
• Others: Russia, Ukraine, plus visa-photo pair pages for major origin -> destination routes

The full country list is in the dataset itself.

Sources

Specs are validated against the issuing authority for each country:

• US State Department / USCIS
• UK Home Office (HMPO, UKVI)
• German Bundesdruckerei
• Italian Polizia di Stato
• French ANTS
• Spanish MAE
• Canadian IRCC
• Australian DFAT
• Indian PSK + Sarathi + Parivahan
• Chinese MFA COVA
• Japanese MOFA
• Schengen Annex 11 / ICAO 9303
• EU EES
• NZ DIA
• Brazilian Polícia Federal
• Mexican SRE

Each record carries an inline source_url to the relevant government page.

Usage

from datasets import load_dataset

ds = load_dataset("whiterocket/passport-photo-specs", split="train")
# Filter to Schengen-compliant visa formats
schengen = ds.filter(lambda r: r["width_mm"] == 35 and r["height_mm"] == 45)

License

MIT. Free for commercial use, no attribution required (but appreciated).

Citation

This dataset is also archived on Zenodo with a versioned DOI:

whitetirocket. (2026). passport-photo-specs: Open Dataset of Passport, Visa, and ID Photo Specifications for 100+ Countries. Zenodo. https://doi.org/10.5281/zenodo.20409880

@dataset{passport_photo_specs_2026,
  author       = {whitetirocket},
  title        = {{passport-photo-specs: Open Dataset of Passport,
                   Visa, and ID Photo Specifications for 100+ Countries}},
  year         = 2026,
  publisher    = {Zenodo},
  doi          = {10.5281/zenodo.20409880},
  url          = {https://doi.org/10.5281/zenodo.20409880}
}

Related distributions

• GitHub (canonical source): https://github.com/whitetirocket/passport-photo-specs
• npm package: npm install passport-photo-specs
• PyPI package: pip install passport-photo-specs
• Hosted reference site: https://idphotosnap.com

Use cases

• Government compliance tooling. Validate a user's uploaded photo against the destination country's spec before they submit to the portal.
• Biometric photo validators. Cross-check spec dimensions against ICAO 9303 reference data.
• Travel and immigration software. Surface correct dimensions and background colors per route.
• AI / ML training data. Use as ground truth for face-detection and crop systems that need to output compliant photos. The 2026 US State Department rule (no AI retouching) makes this distinction load-bearing.
• Academic research. Compare biometric photo standards across jurisdictions; the open dataset removes the per-country research burden.