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 of 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 test images and generate labeled test images including primary labeling information and primary confidence scores on primary objects, (ii) allowing a labeler to verify the primary labeling information to generate correction-related class information, (iii) setting a first and a second threshold confidence scores; (b) (i) allowing the labeling network to label unlabeled images and generate labeled images including secondary labeling information and secondary confidence scores on secondary objects, (ii) allowing an object difficulty estimation module to generate object difficulty scores and object difficulty classes, (iii) allowing an image difficulty estimation module to generate image difficulty scores and image difficulty classes; and (c) transmitting the first labeled images to the labeler to generate verified labeled images, and generating the training data.