Creation of a painting dataset for use in artificial intelligence tasks

Abstract

This article describes the creation of a custom thematic dataset for generating descriptions of artistic works (paintings). An algorithm for forming a dataset using deep learning models is proposed. Initially, an analysis of scientific publications was conducted to identify key features important for the perception of works of art. Then, relevant datasets with descriptions in various languages were extracted from various sources, including the collections of major museums. After preliminary processing and filtering of irrelevant features, the data were combined into a single dataset. All text data were translated into Russian. 7 key features and 21 fields were selected for each painting image with corresponding descriptive information. As a result, a new dataset consisting of 10,000 images of paintings and annotations to them was formed.