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Understanding MIDV-260: The Identity Document Dataset for Mobile AI

: Feeding high-quality, diverse data into machine learning models to teach them how to "see" a passport or driver's license. midv260 full

: Running an existing optical character recognition (OCR) tool against the dataset to see how well it performs in difficult lighting. Midv-260 //top\\ The "260" in its name refers

For those in the tech industry, MIDV-260 remains a foundational benchmark for building the secure, fast ID scanning features we use every day in banking and travel apps. Midv-260 //top\\ Variety : 20 distinct identity document types

The "260" in its name refers to the specific count and variety of document samples, providing 130 images for each of the 20 document types. These are captured under "realistic" conditions—meaning they include the common challenges mobile apps face, such as varying lighting, shadows, and perspective distortions. Key Technical Specifications : 2,600 frames. Variety : 20 distinct identity document types.

When researchers look for the "MIDV-260 full" dataset, they are typically seeking the complete set of annotated frames and ground truth data. Access to the full dataset allows for:

Since the release of MIDV-260, the collection has expanded. The dataset is part of a larger family of research tools, including: : An expanded version featuring 500 document types.