Method for generating training data to be used for training deep learning network capable of analyzing images and auto labeling device using the same

Abstract

A method for generating training data for a deep learning network is provided. The method includes steps of: an auto labeling device (a) (i) allowing a labeling network to label acquired test images and generate primary bounding boxes, primary class information, and primary confidence scores, (ii) allowing a labeler to verify labeled primary objects and generate correction-related class information, and (iii) setting first and second threshold confidence scores; (b) (i) allowing the labeling network to label acquired unlabeled images and generate secondary bounding boxes, secondary class information, and secondary confidence scores, (ii) allowing an object difficulty estimation module to generate object difficulty scores and determine object difficulty classes, and (iii) allowing an image difficulty estimation module to determine image difficulty classes; and (c) allowing the labeler to verify the first labeled images and generating the training data comprised of second labeled images and the verified first labeled images.