Training a Machine Learning Model to Read Illegible Barcodes

Illegible barcodes can hinder use of barcodes in many contexts. This document describes a machine learning (ML) model trained to read illegible barcodes. The training dataset used to train the ML model comprises illegible barcodes (e.g., having low contrast, small size, wear-and-tear) and corresponding groundtruth. The ML model is trained to generate a legible version of the barcode. During training, the model output is compared with the groundtruth and the difference is fed to a loss function to adjust the weights of the model. In field use, a user can capture a photo of an illegible barcode and access the trained ML model to obtain a legible version. The described ML model can improve barcode scanning in industrial settings, data centers, and other contexts where barcodes are used.