METHOD FOR IMAGE REVAMPING

Abstract

ABSTRACT A method (100) for image revamping, the method (100) comprising the steps of receiving an input image representing an initial visual structure, receiving a textual description specifying transformation details for the input image, processing the input image and textual description with a machine learning model configured to generate a transformed output image, generating, by the machine learning model, a transformed image based on the input image and textual description and outputting the transformed image for display. <>

Specification

Description:FIELD OF THE DISCLOSURE
[0001] This invention generally relates to a field of image processing and, in particular, relates to a method for image revamping using text and image input.
BACKGROUND

[0002] The subject matter discussed in the background section should not be assumed to be prior art merely as a result of its mention in the background section. Similarly, a problem mentioned in the background section or associated with the subject matter of the background section should not be assumed to have been previously recognized in the prior art. The subject matter in the background section merely represents different approaches, which in and of themselves may also correspond to implementations of the claimed technology.
[0003] Image editing and enhancement are essential in a variety of fields, including graphic design, marketing, and photography. Conventional image-editing tools typically require extensive manual adjustments and advanced skills, limiting accessibility for users without specialized expertis , Claims:1. A method (100) for image revamping, the method (100) comprising the steps of:
receiving an input image representing an initial visual structure;
receiving a textual description specifying transformation details for the input image;
processing the input image and textual description with a machine learning model configured to generate a transformed output image;
generating, by the machine learning model, a transformed image based on the input image and textual description;
outputting the transformed image for display.

2. The method (100) of claim 1, wherein the textual description includes instructions for modifying specific visual features within the input image.

3. The method (100) of claim 1, wherein the input image and textual description are processed jointly to create an augmented input for the machine learning model.

4. The method (100) of claim 1, further comprising applying post-processing filters to the transformed image based on additional user instructions.

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