  Scene text recognition has made significant progress in recent years and has
become an important part of the work-flow. The widespread use of mobile devices
opens up wide possibilities for using OCR technologies in everyday life.
However, lack of training data for new research in this area remains relevant.
In this article, we present a new dataset consisting of real shots on
smartphones and demonstrate the effectiveness of profile normalization in this
task. In addition, the influence of various augmentations during the training
of models for analyzing document images on smartphones is studied in detail.
Our dataset is publicly available.
