FIELD: generating images.
SUBSTANCE: initial training of the neural network and text marking of elements in the image is done by loading a dataset from several images of one element, whereas connections with the ontology are built; images are fed to the input of the CLIP neural network for marking, where parallel analysis of the image and text description is carried out, due to which a feature vector is created; the downloaded images are analysed by segmenting the image in several iterations, by highlighting large objects; a mask with a segmented image is formed; classification of selected objects is carried out using a neural network; in parallel with the identification of objects, image tagging is carried out; at the final stage, images are generated based on an existing library of images, and each image is equipped with a set of tags that determine the possibility of its use in a specific composition.
EFFECT: improvement of quality of image generation.
1 cl, 6 dwg
