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MIDV-260 is a comprehensive dataset designed specifically for the analysis, recognition, and verification of identity documents captured via mobile devices. It was created to address a specific gap in the computer vision community: while there were many datasets for standard Optical Character Recognition (OCR), there was a lack of datasets focusing on the complex, non-ideal conditions of mobile capture.

: Frame-by-frame quadrangle coordinates mapping the precise document boundaries. midv260 full

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MIDV-260 is a deep learning model designed for various computer vision tasks, including object detection, image classification, and segmentation. The model is based on a convolutional neural network (CNN) architecture, which is a type of neural network specifically designed for image and video processing.