: Running an existing optical character recognition (OCR) tool against the dataset to see how well it performs in difficult lighting.
Understanding MIDV-260: The Identity Document Dataset for Mobile AI midv260 full
: Feeding high-quality, diverse data into machine learning models to teach them how to "see" a passport or driver's license. : Running an existing optical character recognition (OCR)
: Includes low-light, glare, and hand-held motion blur. Why "Full" Access Matters for Developers Why "Full" Access Matters for Developers : Comparing
: Comparing the efficiency of new mobile algorithms against established standards in the field of document analysis. The Evolution: Beyond 260
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.
MIDV-260 is a specialized public dataset designed to improve how mobile devices recognize and process identity documents (IDs). It contains 2,600 individual images derived from video clips of 20 different document types, such as passports and ID cards from various countries.