: Running an existing optical character recognition (OCR) tool against the dataset to see how well it performs in difficult lighting.
: A modern iteration designed to test the latest biometric and security features on newer smartphone cameras. midv260 full
: Includes low-light, glare, and hand-held motion blur. Why "Full" Access Matters for Developers : Running an existing optical character recognition (OCR)
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. Why "Full" Access Matters for Developers Since the
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.
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.
Understanding MIDV-260: The Identity Document Dataset for Mobile AI