IDSPACE: Synthetic Digital Identity Verification Images from European Locations

IDSPACE is a synthetically generated dataset for evaluating digital identity verification systems. The dataset contains template and scan image files organized by 10 separate locations in European countries. It was created by cactuslab and last updated on Hugging Face in June 2026.

Use Cases

• Benchmarking identity verification systems based on synthetic template and scan images.
• Training models for document authenticity detection based on the described LOC template and scan file pairs.
• Evaluating geographic robustness of verification algorithms using data from multiple European locations.

Strengths

• Dataset is entirely synthetic, which likely eliminates privacy concerns associated with real personal data.
• Data is organized by 10 distinct geographic locations, suggesting potential for location-specific analysis.
• Last update timestamp (2026-06-02 17:47:42) is provided.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count and total dataset size are unknown, which may limit suitability assessment.
• Description metadata is limited; actual data quality and structure require manual inspection after download.

Provenance

Source

cactuslab on Hugging Face

Collection Method

Synthetically generated.

Freshness

Last updated 2026-06-02 17:47:42; freshness should be verified.

Geography

Multiple locations in European countries.