Patent ID: 11861875
Assignee: TATA CONSULTANCY SERVICES LIMITED
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 0:
1. A processor-implemented method of one or more context-adaptive image transformations comprising:
receiving, via an input/output interface, at least one image to perform one or more context-adaptive image transformations, and one or more preferences of a user to specify one or more content factors and one or more aesthetic factors of a transformed image;
training, via one or more hardware processors, a content learning network based on a predefined set of sample images to extract at least one content factor from the received at least one image;
training, via the one or more hardware processors, an aesthetics learning network based on the predefined set of sample images to extract aesthetic factors from the received at least one image;
training, via the one or more hardware processors, a translation network based on the extracted content factors and aesthetic factors of the predefined set of sample images;
identifying, via the one or more hardware processors, at least one region of interest (RoI) from the received at least one image based on the received one or more preferences of the user;
extracting, via the one or more hardware processors, one or more content factors and one or more aesthetic factors from the at least one identified RoI using the trained content learning network and aesthetics learning network;
deriving, via the one or more hardware processors, at least one context from the extracted one or more content factors and one or more aesthetic factors using the trained translation network;
identifying, via the one or more hardware processors, context-aware workflow from the derived at least one context and the received one or more user preferences;
calculating, via the one or more hardware processors, a similarity metric for the extracted at least one content and aesthetic factor to determine at least one context requirement; and
performing, via the one or more hardware processors, one or more context-adaptive image transformations based on the identified context-aware workflow and calculated similarity metric to get a transformed image, wherein the transformed image preserving the one or more content factors and aesthetics required for the context.