Garment fabrication using machine learning

Patent metadata

Field	Value
Publication number	US-12499631-B2
Application number	US-202318229510-A
Country	US
Kind code	B2
Filing date	Aug 2, 2023
Priority date	Aug 2, 2023
Publication date	Dec 16, 2025
Grant date	Dec 16, 2025

Abstract

Methods and systems are disclosed for generating a physical garment using a machine learning model. The methods and systems receive a plurality of parameters of an optimization problem, the plurality of parameters describing a fashion item, and form a prompt based on values of the plurality of parameters. The prompt is processed by a generative machine learning model to output an image comprising an artificial fashion item corresponding to the values of the plurality of parameters. An augmented reality experience is generated in which a real-world object is overlaid with a virtual object that depicts the artificial fashion item. Feedback associated with the augmented reality experience is used to condition fabrication of a real-world fashion item that resembles the artificial fashion item.

First claim

What is claimed is:

1 . A method comprising:
receiving a plurality of parameters of an optimization problem, the plurality of parameters describing a fashion item; forming a prompt based on values of the plurality of parameters; processing the prompt by a generative machine learning model to output an image depicting a first artificial fashion item corresponding to the values of the plurality of parameters; generating multiple augmented reality experiences, including an augmented reality experience, each comprising a respective virtual object that represents a respective artificial fashion item that has been generated using different values for the plurality of parameters; generating the augmented reality experience in which a real-world object is overlaid with a virtual object that depicts the first artificial fashion item; collecting feedback for the multiple augmented reality experiences; and using first feedback, of the collected feedback, associated with the augmented reality experience to condition fabrication of a real-world fashion item that resembles the first artificial fashion item, the using of the first feedback comprising identifying an individual artificial fashion item that corresponds to a respective one of the multiple augmented reality experiences for which the collected feedback for the multiple augmented reality experiences satisfies one or more fabrication criteria, the real-world fashion item being fabricated using the individual artificial fashion item that has been identified.

2 . The method of claim 1 , further comprising:
generating a solution to the optimization problem that optimizes the plurality of parameters, wherein the prompt is formed using the values of the plurality of parameters that have been optimized.

3 . The method of claim 1 , wherein the prompt comprises a textual prompt.

4 . The method of claim 1 , wherein the generative machine learning model comprises a diffusion model.

5 . The method of claim 1 , wherein the plurality of parameters comprises at least one of a fashion item style, fashion item type, or fashion item theme.

6 . The method of claim 5 , wherein:
the fashion item style comprises at least one of an upper body garment, a lower body garment, or a whole body garment; the fashion item type describes physical attributes of the fashion item style; and the fashion item theme comprises one or more graphical elements for a fashion item corresponding to the fashion item style that is of the fashion item type.

7 . The method of claim 1 , further comprising:
accessing a prompt template that includes placeholders for the plurality of parameters, wherein the prompt is formed by populating the prompt template with the values for the received plurality of parameters.

8 . The method of claim 1 , further comprising:
processing the image of the first artificial fashion item by a virtual object machine learning model to generate a three-dimensional model of the first artificial fashion item, wherein the augmented reality experience is generated using the three-dimensional model of the first artificial fashion item.

9 . The method of claim 1 , further comprising:
updating a solution to the optimization problem to generate new values for the plurality of parameters of the optimization problem based on the first feedback.

10 . The method of claim 9 , further comprising:
forming a new prompt comprising the new values for the plurality of parameters; processing the new prompt by the generative machine learning model to output a new image comprising a new artificial fashion item; generating a new augmented reality experience in which another real-world object is overlaid with a new virtual object that depicts the new artificial fashion item; and using new feedback associated with the new augmented reality experience to condition fabrication of the real-world fashion item.

11 . The method of claim 1 , further comprising:
determining whether the first feedback satisfies one or more fabrication criteria.

12 . The method of claim 11 , further comprising:
in response to determining that the first feedback satisfies the one or more fabrication criteria, providing the image comprising the first artificial fashion item to a fashion item manufacturer for fabricating the real-world fashion item.

13 . The method of claim 11 , wherein the first feedback represents engagement with the augmented reality experience comprising at least one of a quantity of users who requested access to the augmented reality experience within a threshold interval, a quantity of users who shared the augmented reality experience with other users, a rating of the augmented reality experience, or a quantity of users who stored images generated using the augmented reality experience.

14 . The method of claim 13 , wherein the one or more fabrication criteria comprises at least one of a threshold quantity of users requesting access to the augmented reality experience, a threshold quantity of users sharing the augmented reality experience, a threshold rating for the augmented reality experience, or a threshold quantity of users who stored images generated using the augmented reality experience.

15 . The method of claim 11 , further comprising:
in response to determining that the first feedback fails to satisfy the one or more fabrication criteria, generating a new solution to the optimization problem to generate new values for the plurality of parameters of the optimization problem.

16 . The method of claim 1 , further comprising:
generating a random seed; and generating the values for the plurality of parameters based on the random seed.

17 . The method of claim 1 , further comprising:
receiving an image depicting a particular fashion item; and deriving the values of the plurality of parameters based on the received image that depicts the particular fashion item.

18 . A system comprising:
at least one processor; and at least one memory component having instructions stored thereon that, when executed by the at least one processor, cause the at least one processor to perform operations comprising: receiving a plurality of parameters of an optimization problem, the plurality of parameters describing a fashion item; forming a prompt based on values of the plurality of parameters; processing the prompt by a generative machine learning model to output an image depicting a first artificial fashion item corresponding to the values of the plurality of parameters; generating multiple augmented reality experiences, including an augmented reality experience, each comprising a respective virtual object that represents a respective artificial fashion item that has been generated using different values for the plurality of parameters; generating the augmented reality experience in which a real-world object is overlaid with a virtual object that depicts the first artificial fashion item; collecting feedback for the multiple augmented reality experiences; and using first feedback, of the collected feedback, associated with the augmented reality experience to condition fabrication of a real-world fashion item that resembles the first artificial fashion item, the using of the first feedback comprising identifying an individual artificial fashion item that corresponds to a respective one of the multiple augmented reality experiences for which the collected feedback for the multiple augmented reality experiences satisfies one or more fabrication criteria, the real-world fashion item being fabricated usi

Assignees

• Snap Inc

Inventors

• Assouline Avihay
• Berger Itamar

Classifications

• G06N3/006

  based on simulated virtual individual or collective life forms, e.g. social simulations or particle swarm optimisation [PSO] · CPC title

• G06N20/00

  Machine learning · CPC title

• G06Q30/0621

  by configuring or customising goods or services · CPC title

• G06Q30/0201

  Market modelling; Market analysis; Collecting market data · CPC title

• G06N3/02

  Neural networks · CPC title